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Predictive, preventive, and personalized medicine in breast cancer: targeting the PI3K pathway

Abstract

Breast cancer (BC) is a multifaceted disease characterized by distinct molecular subtypes and varying responses to treatment. In BC, the phosphatidylinositol 3-kinase (PI3K) pathway has emerged as a crucial contributor to the development, advancement, and resistance to treatment. This review article explores the implications of the PI3K pathway in predictive, preventive, and personalized medicine for BC. It emphasizes the identification of predictive biomarkers, such as PIK3CA mutations, and the utility of molecular profiling in guiding treatment decisions. The review also discusses the potential of targeting the PI3K pathway for preventive strategies and the customization of therapy based on tumor stage, molecular subtypes, and genetic alterations. Overcoming resistance to PI3K inhibitors and exploring combination therapies are addressed as important considerations. While this field holds promise in improving patient outcomes, further research and clinical trials are needed to validate these approaches and translate them into clinical practice.

Graphical Abstract

Introduction

Breast cancer stands as the prevailing form of cancer among women worldwide, exhibiting the highest incidence rate compared to other types of cancer [1, 2]. This complex and diverse disease is characterized by uncontrolled proliferation and growth of abnormal cells in breast tissue. There are diverse subtypes of BC, each with diverse clinical and molecular features and requiring individualized approaches for diagnosis and treatment [3, 4]. Despite advances in oncology, BC remains a global health challenge, requiring further research and innovative therapies [5].

The PI3K pathway has emerged as a key player in BC development [6, 7]. The PI3K pathway governs a wide range of cellular processes through its signaling mechanism, such as cell growth [8, 9], survival [10, 11], metabolism [8, 12] and motility [13]. Dysregulation of the PI3K pathway is linked with several aspects of BC development and progression [14, 15]. Malactivation of this pathway occurs through various mechanisms, including genetic alterations and somatic mutations [16, 17], gene amplification [18], and loss of negative regulators [19]. Such alterations sustain and reinforce the signaling of the PI3K pathway, resulting in amplified cell proliferation, enhanced cell survival, and the emergence of therapy resistance.

The Downstream activation of the PI3K signaling pathway occurs through multiple receptor tyrosine kinases, among which the epidermal growth factor receptor (EGFR) [20], insulin-like growth factor receptor (IGFR) [21], and human epidermal growth factor receptor 2 (HER2) [22] are included. Upon binding with ligands, these receptors initiate the activation of PI3K, triggering the conversion of phosphatidylinositol 4,5-bisphosphate (PIP2) into phosphatidylinositol 3,4,5-trisphosphate (PIP3) [23]. Acting as a secondary messenger, PIP3 recruits proteins harboring pleckstrin homology domains (PH), such as AKT and PDK1, to the plasma membrane [24]. AKT activation promotes cell survival and proliferation through phosphorylation of downstream targets such as mTOR (mammalian target of rapamycin) [11, 25], BAD [26, 27], and FOXO transcription factors [28, 29].

The significance of PI3K signaling in BC extends to crucial implications in diagnosis, prognosis, and treatment. Targeting this pathway shows promise in overcoming resistance and enhancing outcomes. Nevertheless, resistance mechanisms pose limitations to the clinical effectiveness of inhibitors targeting PI3K, AKT, and mTOR. This comprehensive review emphasizes the pivotal role of the PI3K pathway in BC, delving into its dysregulation, impact on disease progression, and development of therapy resistance. It discusses current strategies, challenges in clinical translation, and advancements in prediction, prevention, and personalized medicine. The article emphasizes the significance of tailored therapies and predictive biomarkers to improve BC patients' outcomes and quality of life.

PI3K isoforms and classes

In mammals, PI3Ks can be categorized into three classes. Class I PI3K can be further subdivided into subclasses IA and IB based on their regulation. Class IA PI3Ks comprise the catalytic subunits p110 and the regulatory subunit p85. The genes PIK3CA, PIK3CB, and PIK3CD encode the catalytic isoforms p110α, p110β, and p110δ, respectively. These isoforms can be associated with various regulatory isoforms, including p85α, p85β, and p55γ, collectively called p85-type regulatory subunits. The genes PIK3R1, PIK3R2, and PIK3R3 encode these regulatory subunits. On the other hand, class IB PI3Ks interact with the catalytic subunit p110γ, encoded by PIK3CG, and the regulatory isoforms p101 (encoded by PIK3R5) or p87 (also known as p84 or p87PIKAP, encoded by PIK3R6). The expression of p110α and p110β is widespread, while p110δ and p110γ are mainly found in leukocytes (Fig. 1) [30].

Fig. 1
figure 1

PI3Ks are classified based on their substrate specificities and structures. Class IA and IB PI3Ks phosphorylate PtdIns(4,5)P2, while class III PI3Ks phosphorylate PtdIns. Class II PI3Ks may also preferentially phosphorylate PtdIns. Class IA PI3Ks consist of p110 catalytic subunits and p85 regulatory subunits, with specific domains such as p85-BD, RBD, helical, and catalytic domains. Class IB PI3Ks comprise p110γ catalytic subunits and p101 or p87 regulatory subunits. Class II PI3Ks, including PI3K-C2α, PI3K-C2β, and PI3K-C2γ, have monomeric structures. The only class III PI3K is VPS34, which forms a heterodimer with VPS15 and possesses helical and catalytic domains. Various domains, such as P domains and C2 domains, are also indicated in their structures

Predictive medicine approach to breast cancer

A predictive medicine approach to BC involves identifying and using biomarkers to predict response to specific treatments. For BC, predictive biomarkers help determine the efficacy of PI3K inhibitors. Understanding the predictive biomarkers of PI3K inhibitors is critical for selecting the most appropriate therapy and improving patient outcomes.

Predictive biomarkers for PI3K inhibitors in breast cancer

Predictive biomarkers are vital in guiding treatment decisions and predicting response to specific BC treatments [31]. Several biomarkers associated with PI3K inhibitors have been identified that may help predict the efficacy of these inhibitors in breast cancer patients [32, 33]. In particular, the PI3K/AKT/mTOR signaling pathway has been extensively studied due to its dysregulation and availability of targeted inhibitors in BC, particularly PIK3CA mutation and PTEN loss [34, 35].

PIK3CA mutations, activation of downstream targets and PI3K isoform-specific biomarkers

The PIK3CA gene, which encodes the p110α catalytic subunit of PI3K [36, 37], is frequently mutated in BC [38, 39]. Studies have shown that patients with PIK3CA mutations tend to have increased activation of PI3K pathway and may have increased sensitivity to PI3K inhibitors [38]. Identifying PIK3CA mutations through testing can assist in determining the potential effectiveness of PI3K inhibitor therapy for patients.

Several biomarkers tested in tumor tissue samples provide additional information on PI3K pathway activation and response to PI3K inhibitors. These include markers such as phosphorylated AKT (pAKT) [40], and phosphorylated S6 (pS6) [41] that indicate activation of the PI3K pathway.

PI3K inhibitors can target different isoforms of the PI3K enzyme [42]. A biomarker that indicates the presence or activation of a particular isoform will help select the most appropriate PI3K inhibitor for a particular patient. For example, PIK3CA mutations are more commonly linked with sensitivity to PI3Kα inhibitors.

Liquid biopsy, which analyzes circulating tumor DNA (ctDNA) or circulating tumor cells (CTCs) in blood [43, 44], provides a non-invasive approach to assess PIK3CA mutations and monitor treatment response [45, 46]. Detection of PIK3CA mutations in ctDNA or CTCs may help select patients for PI3K inhibitor therapy.

Next-generation sequencing, such as genomic profiling, enables comprehensive analysis of the genetic landscape of breast cancer [47]. This approach allows us to identify additional genetic alterations that may affect response to PI3K inhibitors, including alterations in other genes involved in PI3K signaling and genes associated with therapy resistance.

It is important to note that although these biomarkers are associated with response to PI3K inhibitors, they do not conclusively predict individual patient outcome. Further validation with clinical trials and real-world data is needed to optimize patient selection for PI3K inhibitor therapy. Ongoing research aims to identify additional biomarkers and develop more accurate predictive models for personalized BC treatment.

PTEN loss

The PTEN gene, short for phosphatase and tensin homolog, is pivotal in suppressing tumors. It aids in regulating the PI3K/AKT pathway, which is crucial for maintaining cellular functionality and preventing abnormal cell proliferation [48]. This pathway is complicated in the control of some cellular processes such as cell growth [49, 50], survival [51] and metabolism [52]. The PTEN gene acts as a negative PI3K/AKT pathway regulator, inhibiting its activation and maintaining cellular homeostasis [53, 54].

Loss of PTEN expression or PTEN gene mutation, another biomarker, is linked with enhanced activation of the PI3K pathway and potential susceptibility to PI3K inhibitors [55]. Moreover, as PIK3CA mutations are more common in ER+ BC [56], hormone receptor status, particularly estrogen receptor (ER) positivity, is associated with the potential efficacy of PI3K inhibitors in this subtype.

Loss of PTEN function due to genetic mutation or epigenetic silencing disrupts the PI3K/AKT pathway, leading to increased activation and tumor formation [57]. The dysregulation of PTEN can result in uncontrolled cell proliferation and survival, key factors in the development and progression of cancer. Specifically, BC patients who have experienced loss of PTEN function tend to exhibit a greater potential for therapeutic benefits from PI3K inhibitors [58]. By specifically targeting the overactive HER PI3K/AKT pathway, these inhibitors could restore the balance of cellular processes and potentially inhibit cancer cell proliferation and metastasis.

AKT1

AKT1 (v-AKT Murine Thymoma Viral Oncogene Homolog 1) has emerged as a prospective predictive biomarker in breast cancer, offering valuable insights into disease prognosis and treatment response. Beyond its role as a signaling molecule, AKT1 functions as a genomic marker, facilitating the tailoring of treatment strategies for individual patients [31]. The identification of specific genetic alterations within the AKT1 gene, particularly within the pleckstrin homology domain (PH), has been substantiated in breast cancer cases. These somatic mutations lead to the constitutive activation of AKT1 and disrupt the normal regulatory mechanisms governing its activation [59, 60].

Notably, the prevalence of AKT1 mutations is notably higher in specific breast cancer subtypes, particularly HR+ and HER2− tumors [60]. Serving as a predictive biomarker, AKT1 mutations exert an influence on disease prognosis. Studies indicate that breast cancer patients harboring AKT1 mutations may exhibit distinct clinical features and outcomes. These mutations correlate with specific clinicopathological features such as tumor size, grade, and lymph node metastasis, thereby providing additional information for stratifying patients based on their risk profiles [61, 62].

Moreover, investigations into AKT1 mutations aim to predict responses to targeted therapies within the PI3K/AKT/mTOR signaling pathway, where AKT1 assumes a central role [31, 59]. Understanding AKT1 mutation status enables the identification of patients who may benefit from targeted inhibitors of the PI3K pathway [63, 64]. This personalized treatment approach aligns with the principles of precision medicine, allowing the selection of potentially effective treatments based on specific genetic changes in a patient's tumor.

Clinical studies evaluating the efficacy of AKT inhibitors in breast cancer patients with AKT1 mutations underscore the role of AKT1 as a predictive biomarker. These studies seek to assess the safety and efficacy of targeted therapies that directly inhibit the aberrant signaling caused by AKT1 mutations. If successful, these inhibitors hold promise as a treatment option for certain breast cancer patients with AKT1-mutated tumors.

PIK3R1

Phosphoinositide 3-kinase regulatory subunit 1 (PIK3R1) serves as the regulatory subunit of the PI3K, a pivotal player in cell signaling pathways governing growth, survival, and metabolism. PIK3R1 plays a crucial role in modulating the activity of the catalytic subunit of PI3K, thereby exerting influence over downstream signaling events [65].

In the realm of breast cancer, PIK3R1 has emerged as a prospective predictive biomarker, offering valuable insights into disease prognosis and treatment responsiveness. Genetic alterations in PIK3R1, encompassing both somatic mutations and copy number variations, have been discerned in breast cancer. These alterations have the potential to induce dysregulation within the PI3K signaling pathway, contributing to unbridled cellular proliferation and enhanced survival capabilities [65].

Of significance is the association of PIK3R1 mutations with specific breast cancer subtypes, suggesting potential implications for disease stratification [66]. As a predictive biomarker, PIK3R1 mutations have been linked to diverse clinical outcomes in breast cancer patients [65]. Investigations have delved into the correlation between PIK3R1 status and various clinicopathological features, including tumor grade, hormone receptor status, and HER2 amplification.

An understanding of the specific molecular characteristics of tumors, particularly the presence of PIK3R1 mutations, holds promise for refining prognostic assessments and tailoring treatment strategies. Furthermore, PIK3R1 status assumes importance in predicting responses to targeted therapy [67]. The PI3K signaling pathway, in which PIK3R1 is a critical component, stands out as a crucial therapeutic target in breast cancer [68]. Clinical trials involving PI3K inhibitors have been conducted, and the presence of PIK3R1 mutations may exert an influence on treatment responsiveness.

Identification of breast cancer patients with PIK3R1 mutations presents an opportunity to select individuals poised to derive greater benefit from PI3K pathway inhibitors, aligning with the principles of precision medicine. The study of PIK3R1 as a predictive biomarker extends beyond its individual role. Through a comprehensive analysis encompassing multiple genomic changes within the PI3K pathway, including not only PIK3R1 mutations but also mutations in PIK3CA and PTEN, a more nuanced understanding of the molecular landscape of breast cancer emerges. This integrated approach enhances the ability to predict patient outcomes and make well-informed therapeutic decisions.

INPP4B

Inositol polyphosphate 4-phosphatase type II (INPP4B) is a phosphoinositide phosphatase that plays a pivotal role in the regulation of intracellular signaling pathways, particularly the phosphoinositide 3-kinase (PI3K) pathway. Functionally, INPP4B acts as a tumor suppressor by exerting negative regulation on PI3K signaling, a signaling cascade crucial for controlling cell proliferation, survival, and metabolism. In breast cancer, INPP4B has emerged as a potential predictive biomarker, offering valuable insights into disease prognosis and treatment response [69, 70].

Genetic alterations in INPP4B, including mutations and changes in expression levels, have been identified in breast cancer. Particularly noteworthy is the common occurrence of the loss of INPP4B expression in breast tumors, resulting in heightened activity of the PI3K signaling pathway. This dysregulation contributes significantly to the uncontrolled cellular proliferation and survival characteristic of cancer [69].

As a predictive biomarker, the status of INPP4B is associated with clinical outcomes in breast cancer patients. Rigorous studies have explored the correlation between INPP4B expression levels and various clinicopathological features, such as tumor grade, hormone receptor status, and HER2 amplification. The loss of INPP4B expression has been consistently linked to a more aggressive tumor phenotype and poor prognosis, underscoring its potential as a robust prognostic indicator [71].

Moreover, the predictive utility of INPP4B extends to its role in determining the response to specific therapeutic interventions. Preclinical investigations have suggested that breast cancer cells exhibiting reduced INPP4B expression may display heightened sensitivity to selective inhibitors of the PI3K pathway, presenting a promising avenue for targeted therapeutic strategies [72].

The comprehensive research on INPP4B as a predictive biomarker also encompasses understanding its role within the broader molecular landscape of breast cancer [71]. Integrative analyses, including the evaluation of INPP4B alongside other genetic alterations within the PI3K pathway, are poised to contribute to a more nuanced and holistic understanding of the disease's molecular underpinnings. This integrated approach holds significant potential for refining prognostic assessments and tailoring treatment strategies in breast cancer patients.

Pre-clinical models for evaluating PI3k inhibitors in breast cancer

Pre-clinical models play a crucial role in evaluating the efficacy of PI3K inhibitors in BC before advancing to clinical trials. Here are some commonly used pre-clinical models for studying PI3K inhibitors in BC.

Cell lines

Cell lines have emerged as essential preclinical models for evaluating the efficacy of PI3K inhibitors in BC research (Fig. 2A) [73, 74]. These models have several advantages (Table 1), including ease of establishment, controlled culture conditions, and high-throughput screening capabilities. The researchers used cell lines to gain valuable insight into the molecular mechanisms of changes in PI3K signaling that commonly occur in BC.

Fig. 2
figure 2

A Combined inhibition of Poly (ADP-ribose) polymerase (PARP) by Talazoparib (TAL) and phosphatidylinositol 3-kinase (PI3K) by LY294002 synergistically inhibited the proliferation of BRCA1 mutant HCC1937 triple-negative breast cancer (TNBC) cells. This figure illustrates the enhanced anti-proliferative effects of the combination treatment compared to each drug alone. The combined inhibition induced multiple cellular responses, including apoptosis, G0/G1 arrest, oxidative stress, and increased DNA damage. The synergistic effect suggests that the dual targeting strategy holds promise as a therapeutic approach for TNBC with BRCA1 mutations. B LAR (Luminal Androgen Receptor) subtype patient-derived xenografts (PDXs) of triple-negative breast cancer (TNBC) exhibited a significant enrichment of PIK3CA and AKT1 mutations, along with higher levels of luminal-androgen-like gene expression and increased activation of the PI3K pathway proteins, when compared to other TNBC subtypes. Immunohistochemistry analysis revealed strong expression of luminal cytokeratin CK18 and androgen receptor (AR) in three LAR PDX models. In vivo experiments using these PDX models, which harbored genomic alterations of PIK3CA and AKT1 and were resistant to the AR antagonist enzalutamide, demonstrated that mTOR and PI3K inhibitors displayed notable antitumor activity

Table 1 Advantages and disadvantages of using cell lines as preclinical models

The establishment and characterization of BC cell lines is a critical step in preclinical research [75]. Methods to establish these cell lines from patient tumor samples or cell line repositories have been refined over the years [76, 77]. In addition, extensive molecular characterization, including identification of alterations in the PI3K signaling pathway, such as mutations in the PIK3CA gene [78, 79], ensures that the cell lines used in our experiments accurately represent the genetic landscape of BC.

Cell line studies can gain insight into the mechanism of response to PI3K inhibitors [80]. Researchers can manipulate gene expression in these models using techniques such as RNA interference (RNAi) [81], and CRISPR-Cas9 [82, 83], enabling targeted studies of the role of specific genes and signaling pathways. Conducting these studies will enhance our understanding of the molecular mechanisms underlying drug response and resistance, ultimately facilitating the advancement of novel therapeutic approaches and driving progress in the field of medicine.

Cell lines also serve as valuable tools for studying combinations of PI3K inhibitors and other agents [84, 85]. Evaluating drug combinations, such as chemotherapeutic agents and targeted therapies, allows researchers to identify potential synergies and optimize therapeutic approaches. These studies provide important insights into potential combination strategies to improve the efficacy of PI3K inhibitors in BC treatment.

Despite their advantages, it is important to recognize the limitations of cell line models (Table 1). They lack the in vivo tumor microenvironment, interaction with the immune system, and three-dimensional structural complexity observed in patient tumors. Therefore, it is important to evaluate the results of cell line studies using more clinically relevant models. Patient-derived xenografts or transgenic mouse models prior to being placed in clinical trials.

Patient-derived xenografts (PDX)

Patient-derived xenografts (PDX) have proven to be a valuable preclinical model for evaluating the efficacy of PI3K inhibitors in BC research (Fig. 2B) [86]. In these models, the patient's own BC tissue is directly transplanted into immunodeficient mice, preserving the heterogeneity and complexity of the original tumor microenvironment.

PDX models provide a more clinically relevant representation of human breast tumors compared to traditional cell line models [87]. PDX models have several advantages (Table 2), such as using the patient's own tissue ensures that the molecular and genetic features of the tumor are preserved, including the presence of alterations in the PI3K signaling pathway that are common in BC patients. This will allow researchers to assess the effects of PI3K inhibitors on tumors that closely resemble the patient's original tumors, increasing the translatability of the results. One of the key advantages of PDX models is their ability to recapitulate the tumor microenvironment [88]. Breast tumors reside in a complex ecosystem composed of stromal cells [89], immune cells [90], and blood vessels [91]. The PDX model retains these elements, allowing the study of tumor-stromal interactions and the effects of PI3K inhibitors on the tumor microenvironment. Assessing the effectiveness of PI3K inhibitors holds significant relevance, given the crucial involvement of the PI3K signaling pathway in mediating communication between tumor cells and their microenvironment. This understanding helps shed light on the interplay between these factors and enables informed evaluation of PI3K inhibitors' efficacy.

Table 2 Advantages and disadvantages of using patient-derived xenografts as preclinical models

The PDX model also provides a platform to study the mechanisms of tumor response and resistance to PI3K inhibitors [92, 93]. Longitudinal studies can be performed by treating PDX mice with PI3K inhibitor and monitoring tumor growth and molecular changes over time. This enables the discovery of potential predictive biomarkers for response and resistance, which can inform patient stratification and create personalized therapeutic strategies.

It is important to recognize the limitations of PDX models (Table 2), such as the reliance on immunodeficient mice and the time required to establish and disseminate these models. Furthermore, transplant success rates vary with tumor type and individual patient characteristics. Nevertheless, the PDX model remains a valuable tool for the preclinical evaluation of PI3K inhibitors in BC and provides a more clinically relevant predictive model system.

Genetically engineered mouse models (GEMMs)

The genetically engineered mouse model (GEMM) has proven to be a valuable preclinical model for evaluating the efficacy of PI3K inhibitors in BC research. These models involve genetically engineering mice to introduce specific mutations in genes associated with BC, such as the PIK3CA gene, which encodes the PI3K catalytic subunit (Fig. 3) [94].

Fig. 3
figure 3

The figure illustrates different types of genetically engineered mouse models (GEMMs) for studying PI3K-driven breast cancer. The color scheme represents different genetic alterations in the mouse tissues. Wildtype tissues are depicted in white, knockout tissues are shown in gray, and tissues expressing a transgene or knock-in gene are represented in blue. A Conventional knockout mice exhibit inactivation of tumor suppressor genes (TSGs) in all tissues. B Conditional knockout models can be created by flanking critical exons of TSGs with loxP sequences. This allows tissue-specific inactivation of the TSG through Cre site-specific recombinase action, achieved by utilizing a tissue-specific promoter to control Cre expression. C Hypomorphic mouse models can be generated by inserting a neomycin cassette into intronic regions, leading to transcriptional interference and reduced expression of the targeted TSG. D Constitutive transgenic models involve the insertion of a transgene into the host genome under the control of a tissue-specific promoter (TSP), enabling tissue-specific expression of the gene of interest (GOI). E Conditional transgenic systems utilize loxP sites to flank a transcriptional termination sequence (represented by a STOP sign). Recombination by Cre recombinase removes the STOP sequence, allowing tissue-specific expression of the GOI. F Doxycycline-inducible 'tet-on' systems rely on the tissue-specific expression of a transactivator (rtTA) that binds to the Tet operator (TetO) and activates expression of the GOI only in the presence of doxycycline (dox). These various GEMMs provide valuable tools to study the role of PI3K signaling in breast cancer by enabling the investigation of tissue-specific effects and the regulation of gene expression

GEMM offers several advantages for the study of PI3K inhibitors in BC (Table 3). By introducing specific genetic alterations, GEMM can closely mimic the molecular properties of human BC, such as activation of the PI3K pathway [94]. This will allow researchers to study the effects of PI3K inhibitors on tumorigenesis, progression and response to therapy in vivo. One of the main strengths of GEMM is its ability to represent the complex nature of BC development and progression. These models mimic the stepwise progression from preinvasive lesions to invasive breast tumors and provide insight into the earliest events of tumorigenesis and the effects of PI3K inhibitors at various stages. GEMM can also be used to assess tumor growth dynamics, metastasis, and interactions between tumors and the surrounding microenvironment [95, 96].

Table 3 Advantages and disadvantages of using genetically engineered mouse models as preclinical models

GEMM allows assessment of both the therapeutic efficacy and potential toxicity of PI3K inhibitors [97]. Researchers can monitor tumor response to treatment by measuring tumor volume, assessing histopathological changes, and analyzing molecular changes in tumor tissue. In addition, GEMM provides an opportunity to study possible side effects of PI3K inhibitors on normal tissues and organs and helps identify potential off-target side effects.

Furthermore, GEMM enables mechanistic studies to understand the molecular mechanisms underlying response and resistance to PI3K inhibitors [98]. By manipulating gene expression within specific cell types or specific tumor subtypes, researchers can uncover the role of individual genes or pathways in mediating drug sensitivity or resistance [99, 100]. This information can guide the development of combination therapies and the identification of predictive biomarkers for patient stratification.

Despite its advantages, GEMM also has limitations (Table 3). Creating and maintaining them can be time-consuming and expensive. The genetic alterations introduced into GEMM may not fully reflect the mutational landscape found in human BC. Therefore, it is critical to integrate insights from GEMM with other preclinical models and clinical data to understand the effects of PI3K inhibitors in BC fully.

3D organoids

3D organoids have emerged as promising preclinical models for evaluating the efficacy of PI3K inhibitors in BC research [101]. These models are derived from patient-derived cells and self-assemble into three-dimensional structures that mimic the architecture and cellular heterogeneity of the original tumor [102].

There are various advantages of the 3D organoids model (Table 4). One of the major advantages of 3D organoids is their ability to recreate complex tumor microenvironments in a controlled laboratory environment [103]. 3D organoids provide a more physiologically relevant model for assessing the effects of PI3K inhibitors. 3D organoids also preserve patient tumours' genetic and molecular characteristics, such as altered PI3K signaling. This will allow researchers to study the effects of PI3K inhibitors on tumor growth, survival and response to therapy in settings that mimic patient tumors. By using the patient's own cells, 3D organoids offer a personalized approach to drug screening, allowing assessment of individual patient response to PI3K inhibitors.

Table 4 Advantages and disadvantages of using 3d organoids as preclinical models

Furthermore, 3D organoids show structural and functional similarities to the original tumor, enabling the study of important aspects such as invasion and metastasis [104]. These models allow researchers to assess the effects of PI3K inhibitors on the development of tumor invasion and metastatic potential. By incorporating features such as extracellular matrix components, blood vessels, and lymphatics, 3D organoids enable a more comprehensive understanding of the effects of PI3K inhibitors on tumor behavior.

Another advantage of 3D organoids is the potential for high-throughput drug screening [105, 106]. The ability to generate multiple organoids simultaneously allows researchers to quickly and inexpensively test a wide range of PI3K inhibitors and combination therapies. This screening approach provides valuable insight into the efficacy of PI3K inhibitors and helps identify potential drug candidates for further development.

Additionally, 3D organoids offer the potential for long-term culture and monitoring of therapeutic response [107]. Researchers can track changes in organoid growth, morphology, and molecular profile over time, allowing them to assess both short-term and long-term effects of PI3K inhibitors. This longitudinal approach helps identify potential resistance mechanisms and paves the way for developing strategies to overcome drug resistance.

Although 3D organoids have many advantages, they also have some limitations (Table 4). Compared to in vivo models, they may not fully capture the complexity of the tumor microenvironment. The lack of immune cells within the organoids and the limited vasculature may limit the assessment of immune responses and drug penetration. However, efforts are being made to integrate immune cells and vasculature into organoid models to address these limitations.

Co-culture models

Co-culture models have emerged as valuable preclinical models for evaluating the efficacy of PI3K inhibitors in BC research. These models utilize co-cultivation of diverse cell types, such as tumor cells and stromal cells, in close proximity to replicate the intricate interactions observed within the tumor microenvironment [108].

Co-culture models have several advantages (Table 5). One of the major advantages of co-culture models is their ability to capture the complexity and heterogeneity of the tumor microenvironment [109]. Breast tumors consist of malignant cells and diverse stromal cell types, including fibroblasts, endothelial cells, and immune cells [110]. The utilization of co-culture models enables the investigation of interactions between tumor and stromal cells, which hold significant importance in both tumor progression and response to therapeutic interventions [111]. These models provide a more physiologically relevant environment for evaluating the effects of PI3K inhibitors.

Table 5 Advantages and disadvantages of using co-culture models as preclinical models

Co-culture models also facilitate the study of drug resistance mechanisms with PI3K inhibitors [112]. It is known that the tumor microenvironment may contribute to drug resistance by providing cancer cells with a protective niche. By co-culturing tumor cells with stromal cells, researchers can study the effects of PI3K inhibitors on the development of drug resistance and identify possible molecular mechanisms involved. This information is important for developing strategies to overcome resistance and improve the efficacy of PI3K inhibitors in BC therapy.

Despite its advantages, the co-culture model has limitations (Table 5). They lack the spatial organization and three-dimensional structure observed in patient tumors and may not fully capture the complexity of the tumor microenvironment in vivo. Furthermore, choosing the appropriate stromal cell types and their ratios in the co-culture system is critical to ensure the relevance and accuracy of the model.

Preventive medicine strategies for breast cancer

Preventive medicine strategies targeting the PI3K pathway in BC may help reduce risks associated with its dysregulated activation.

PI3K pathway activation

Activation of the PI3K signaling pathway in BC poses a major challenge in prevention and treatment [113, 114], but several preventative medical strategies targeting this pathway show promise [34, 115].

One approach involves the use of PI3K inhibitors [116, 117]. These small-molecule inhibitors specifically block the activity of PI3K, Akt, or mTOR, disrupt downstream signaling cascades, and inhibit tumor growth. Clinical trials have demonstrated the effectiveness of PI3K inhibitor as a treatment for advanced BC [118]. Expanding its use as a prophylactic agent in high-risk individuals or as adjuvant therapy after BC treatment may reduce the risk of cancer recurrence and improve patient outcomes.

Lifestyle changes offer an additional preventive approach. Research indicates that adopting a healthy lifestyle can impact the activation of the PI3K signaling pathway, thereby lowering the risk of BC. Engaging in regular physical activity is associated with a decreased likelihood of developing BC and can positively influence insulin sensitivity [119], and reduce chronic inflammation [120], Both maintaining a healthy weight and consuming a balanced diet rich in fruits, vegetables, and whole grains contribute to reducing the risk of BC. These lifestyle choices potentially affect PI3K signaling, emphasizing their significance in promoting BC prevention [121, 122]. Hormone receptor modulators represent another preventive medicine strategy targeting the PI3K pathway. Endocrine therapies such as selective estrogen receptor modulators (SERMs) and aromatase inhibitors are commonly used for HR+ BC [123, 124]. These agents indirectly affect the PI3K pathway by interfering with estrogen signaling that interacts with the PI3K pathway. Implementing hormone receptor modulators as a preventive intervention in individuals at high risk can substantially decrease the likelihood of developing ER+ BC.

Combination therapies targeting multiple pathways are also expected to prevent PI3K pathway activation in BC. For instance, the synergistic effects and enhanced therapeutic outcomes can be achieved by combining PI3K inhibitors with agents that target other signaling pathways like HER2 inhibitors. The concurrent targeting of both PI3K and HER2 signaling pathways has shown effectiveness in treating HER2-positive BC, highlighting the potential of combination therapy in preventing BC associated with PI3K pathway dysregulation [125].

Pre-clinical evidence for the preventive effect of PI3K inhibitors

Preclinical evidence proposes that PI3K inhibitors are a promising strategy for preventing BC or arresting disease progression [33, 126]. These inhibitors target the PI3K signaling pathway. The PI3K signaling pathway is a key signaling pathway involved in cell proliferation [127, 128], survival [129, 130], and metabolism [131], which is often dysregulated in BC.

A key finding from preclinical studies is that PI3K inhibitors effectively block the PI3K signaling pathway that is frequently activated in BC [34, 132]. By interfering with this signaling pathway, these inhibitors interfere with cell proliferation and survival, resulting in the suppression of BC growth [117]. Moreover, laboratory models have demonstrated the ability of PI3K inhibitors to suppress the proliferation of BC cells. These inhibitors induce cell cycle arrest, impede cell division, and stimulate apoptosis, thereby preventing tumor progression [133, 134].

Metastasis, the spread of cancer cells to distant organs, is a major challenge in BC treatment. However, preclinical evidence suggests that PI3K inhibitors may help prevent metastasis by targeting key processes involved in cancer cell migration [135], invasion [136], and angiogenesis [137]. By interfering with the PI3K signaling pathway, these inhibitors may impede the metastatic cascade and reduce the likelihood of cancer spreading to other organs.

PI3K inhibitors have also shown the ability to improve the efficacy of other BC treatments. Combining PI3K inhibitors with standard therapies such as chemotherapy [138], and hormone therapy [139], has shown synergistic effects in preclinical studies. This combined approach improves tumor regression and overall survival. This means that PI3K inhibitors may be used as adjunctive therapy to enhance the efficacy of existing treatments and reduce the risk of cancer recurrence.

In addition, preclinical studies have focused on identifying genomic biomarkers that can predict response to PI3K inhibitors [140]. By profiling BC's genomic and molecular features, specific mutations or alterations in genes associated with the PI3K pathway have been identified [141]. These biomarkers may aid in patient stratification and individualized treatment decisions, ensuring that individuals most likely to benefit from PI3K inhibitors are selected. Although preclinical evidence is encouraging, further studies through human clinical trials are important to validate these results. The efficacy, safety and long-term benefits of PI3K inhibitors in BC prevention have yet to be confirmed.

Mechanisms underlying the preventive effect of PI3K inhibitors in breast cancer

PI3K inhibitors have shown hopeful results as potential preventive agents for BC [142]. To understand the mechanisms underlying the preventive effect, it is important to address the role of the PI3K signaling pathway in BC development and progression.

The PI3K signaling pathway is a key signaling pathway involved in cell growth, survival and metabolism. It is often dysregulated in various cancers, including BC, leading to uncontrolled cell and tumor growth. PI3Ks are crucial in phosphorylating phosphatidylinositol lipids within cell membranes, generating PIP3. Subsequently, PIP3 activates downstream signaling effectors including AKT, mTOR, and other signaling molecules implicated in cell proliferation and survival.

Inhibition of PI3K/AKT/mTOR signaling

PI3K inhibitors exert their prophylactic effects by potently blocking PI3K activity, thereby inhibiting the conversion of phosphatidylinositol lipids into PIP3 [143]. This inhibition is vital in decreasing the activation of downstream effectors such as AKT and mTOR [115].

The PI3K/AKT/mTOR signaling pathway helps promote cell survival, growth and angiogenesis [11]. By suppressing this signaling cascade, PI3K inhibitors interfere with key cellular processes such as proliferation and survival that are required for the development and progression of BC.

By inhibiting PI3K, the formation of PIP3, a crucial activator of AKT, is prevented. As a result, reduced AKT activity restricts the activation of downstream targets involved in cell proliferation and survival [144]. Furthermore, inhibition of mTOR, another downstream effector of PI3K, interferes with regulation of protein synthesis and cell cycle progression [145]. By targeting both AKT and mTOR, PI3K inhibitors comprehensively block multiple signaling pathways that drive tumor growth and BC progression.

Overall, inhibition of the PI3K/AKT/mTOR signaling pathway by PI3K inhibitors disrupts a complex network of cellular processes that contribute to BC development. This markedly reduces cell proliferation, promotes apoptosis, inhibits angiogenesis, and ultimately prevents BC tumor formation and progression.

Cell cycle arrest and apoptosis induction

An essential mechanism contributing to the protective impact of PI3K inhibitors in BC involves their capability to induce cell cycle arrest [146], and promote apoptosis [147], in BC cells. Dysregulation of the PI3K signaling pathway often disrupts the fine-tuned control of cell cycle progression, allowing cancer cells to evade cell cycle checkpoints and proliferate uncontrollably.

PI3K inhibitors play a central role in restoring proper cell cycle control by targeting key proteins involved in cell cycle progression. By inhibiting the activity of CDKs, central cell cycle regulators, these inhibitors halt cell cycle progression and prevent uncontrolled proliferation of BC cells [148]. PI3K inhibitors suppress tumor growth and prevent BC development by restoring cell cycle checkpoints [149]. In addition, PI3K inhibitors exert a preventive effect by promoting apoptosis, a natural mechanism that eliminates damaged or abnormal cells. Dysregulation of the PI3K signaling pathway often confers anti-apoptotic properties on cancer cells, enabling cancer cell survival and resistance to cell death signals. PI3K inhibitors counter this effect by interfering with anti-apoptotic proteins and promoting the activation of pro-apoptotic signaling pathways [150]. These inhibitors can directly inhibit proteins such as Bcl-2 that inhibit apoptosis, thus shifting the balance towards apoptosis induction in BC cells.

Inhibition of angiogenesis

Angiogenesis, the process of forming new blood vessels, is crucial in tumor growth and metastasis. The PI3K signaling pathway assumes a central role in promoting angiogenesis by stimulating the production of pro-angiogenic factors, particularly vascular endothelial growth factor (VEGF) (Fig. 4) [50, 151].

Fig. 4
figure 4

Schematic representation of the PI3K/AKT/mTOR pathway in angiogenesis. Activation of the pathway can occur through multiple mechanisms, including RAS mutation, increased expression of growth factor receptors (e.g., EGFR), or loss of PTEN. Once activated, the pathway leads to the secretion of vascular endothelial growth factor (VEGF), a potent inducer of angiogenesis. Additionally, the PI3K/AKT pathway regulates the expression of other angiogenic factors, such as nitric oxide and angiopoietins

PI3K inhibitors offer a promising approach to prevent angiogenesis in BC [152]. These inhibitors target the dysregulated PI3K signaling pathway and effectively attenuate angiogenesis by inhibiting the expression and secretion of pro-angiogenic factors. In particular, inhibition of PI3K signaling reduces the production of VEGF, a potent inducer of angiogenesis [151]. By inhibiting VEGF and other pro-angiogenic factors, PI3K inhibitors disrupt the delicate balance between stimulators and inhibitors of angiogenesis, thereby inhibiting the formation of new blood vessels required for tumor growth and progression. This decreased angiogenesis limits the blood supply to tumors, deprives them of vital nutrients and oxygen, and ultimately inhibits tumor growth.

Moreover, inhibition of PI3K signaling in endothelial cells lining the inner walls of blood vessels directly affects the cells' ability to form new blood vessels in response to pro-angiogenic signals [153]. PI3K inhibitors disrupt key signaling pathways involved in endothelial cell migration, proliferation, and tubule formation, thereby contributing to the suppression of angiogenesis.

Targeting the PI3K signaling pathway and inhibiting angiogenesis, PI3K inhibitors provide a valuable strategy for preventing the development and progression of BC. By inhibiting pro-angiogenic factors like VEGF, these inhibitors effectively disrupt the formation of new blood vessels, compromising tumor nutrition and impeding tumor growth and metastatic capabilities.

Modulation of hormone receptor signaling

Hormone receptor-positive BC is characterized by the presence of estrogen or progesterone receptors on cancer cells, which respond to hormone stimulation and promote tumor growth [154]. The PI3K signaling pathway has been shown to interact with hormone receptor signaling pathways, leading to hormone resistance and contributing to tumor progression in hormone receptor-positive BC [155].

A key mechanism underlying the preventive effects of PI3K inhibitors is disruption of the crosstalk between PI3K signaling and hormone receptor signaling. By targeting the dysregulated PI3K pathway, these inhibitors effectively interfere with communication between the PI3K pathway and hormone receptor signaling, allowing HR+ BC cells to respond to antiestrogenic drugs such as tamoxifen [155].

The PI3K pathway activates downstream effectors such as AKT that directly phosphorylate hormone receptors and alter their activity [143]. This phosphorylation increases hormone receptor activity and may promote resistance to endocrine therapy. PI3K inhibitors counteract this effect by inhibiting AKT activation and downstream signaling, thereby attenuating hormone receptor phosphorylation and activation.

In addition, PI3K inhibitors may modulate other components of hormone receptor signaling pathways. For example, these inhibitors may affect the expression and function of co-regulatory proteins that interact with hormone receptors, thereby affecting hormone receptor activity and response to endocrine therapy.

Combining PI3K inhibitors with endocrine therapy synergistically prevents HR+ BC by targeting multiple signaling pathways, addressing complexity, and improving patient outcomes.

Immune modulation

In addition to their direct effects on cancer cells, PI3K inhibitors have shown remarkable immunomodulatory properties by influencing the tumor microenvironment (TME) and enhancing anti-tumor immune responses [156]. The PI3K signaling pathway is vital in suppressing immune cell function and promoting an immunosuppressive environment within tumors [157].

PI3K inhibitors counteract these immunosuppressive effects by promoting immune cell activity and promoting immunostimulatory TME. One of the key mechanisms by which PI3K inhibitors exert immunomodulation is by enhancing the function of immune cells such as T cells and natural killer (NK) cells [158]. Activation of the PI3K signaling pathway in immune cells can impair the cytotoxic capacity of immune cells and weaken anti-tumor responses. By inhibiting PI3K, these inhibitors restore immune cell function and enhance the ability to recognize and eliminate cancer cells.

Furthermore, PI3K inhibitors modulate the TME and promote an immunostimulatory environment by hindering the recruitment and activation of immunosuppressive cells like regulatory T cells (Treg) [159]. Furthermore, PI3K inhibitors can reduce the production of immunosuppressive factors such as cytokines and chemokines while promoting the secretion of immunostimulatory factors [160].

The immunomodulation exerted by PI3K inhibitors helps prevent tumor formation and progression. By enhancing immune cell activity and promoting an immune-stimulating TME, these inhibitors facilitate the immune system's recognition and elimination of cancer cells, thereby hindering tumor growth and metastasis.

Interplay between metabolism and PI3K inhibitors

The intricate interplay between metabolism and PI3K inhibitors in breast cancer underscores the nuanced nature of targeted therapy. Metabolically, breast cancer cells prominently exhibit the Warburg effect, marked by heightened glucose uptake and glycolysis to sustain rapid cellular proliferation [161, 162]. Altered lipid metabolism and increased reliance on specific amino acids further accentuate the metabolic demands associated with abnormal growth.

PI3K inhibitors specifically intervene in this metabolic milieu by targeting the dysregulated PI3K signaling pathway, a common feature in breast cancer progression [163]. Mutations in the PIK3CA gene contribute to the hyperactivation of PI3K signaling, underscoring the therapeutic significance of PI3K inhibitors [164, 165]. Designed to selectively target isoforms such as p110α, PI3K inhibitors disrupt downstream signaling events involving molecules like AKT and mTOR. This targeted intervention disrupts the orchestrated processes that maintain cancer cell viability and uncontrolled growth [163].

This precision in targeting aligns with the metabolic vulnerabilities of breast cancer cells, presenting a strategic approach to disrupt signaling cascades intricately linked to cellular metabolism [166]. Clinical trials evaluating PI3K inhibitors, such as alpelisib and taselisib, have demonstrated their potential in breast cancer treatment. These studies explore the synergistic effects of PI3K inhibitors in combination therapy, often integrating them with endocrine therapy, HER2-targeted therapy, or chemotherapy to maximize therapeutic efficacy [34, 167].

Patient stratification based on molecular profiling becomes paramount to optimize the prophylactic efficacy of PI3K inhibitors [168]. Identifying PIK3CA mutations enables a personalized approach, ensuring that individuals most likely to benefit from PI3K inhibitor therapy are precisely targeted [169, 170]. This tailored strategy not only optimizes treatment outcomes but also minimizes potential side effects [171, 172].

Despite these advancements, challenges persist, including the emergence of resistance to PI3K inhibitors and the intricate regulatory mechanisms within the PI3K signaling pathway [173]. Ongoing research efforts aim to unravel this complexity, refining preventive strategies and providing insights to further advance breast cancer treatments [6, 174]. The dynamic interactions between metabolism and PI3K inhibitors offer a promising avenue for the development of more effective and personalized therapies in the context of breast cancer [175].

Personalized medicine approaches for breast cancer

Personalized medicine approaches in BC focus on identifying factors that influence treatment response, particularly in relation to the PI3K pathway. Several key factors play a role in determining the efficacy of PI3K inhibitors and can guide personalized treatment decisions:

Tumor stage

Breast cancer stage is an important factor in selecting the most suitable treatment strategy [176]. This includes various aspects such as tumor size, nearby lymph node involvement, and distant metastases. These factors guide treatment decisions and help determine each patient's best course of action.

In early-stage BC where the tumor is localized and has not spread beyond the breast or nearby lymph nodes, may benefit from the use of PI3K inhibitors as part of adjuvant therapy [177]. Adjuvant therapy refers to additional treatment administered after initial procedures like surgery or radiation to reduce the risk of cancer recurrence [178]. The goal is to target BC's dysregulated PI3K signaling pathways by including PI3K inhibitors in adjuvant therapy regimens. This targeted approach prevents cancer cells from growing and reduces the risk of recurrence.

In patients with advanced or metastatic BC whose cancer has spread to other parts of the body, PI3K inhibitors are often part of systemic treatment [85, 179]. Systemic treatment aims to manage cancer growth and metastasis throughout the body effectively. In this regard, PI3K inhibitors target the aberrant HER/PI3K signaling pathway, significantly influencing cancer cell proliferation and survival [180]. Blocking this signaling pathway has the potential to slow or halt disease progression, alleviate symptoms, and improve overall survival.

It should be noted that treatment decisions are made individually, considering factors such as the patient's general health status, genetic profile, specific BC subtype, and other relevant clinical factors. Therefore, the use of PI3K inhibitors may vary depending on the patient's unique characteristics and the stage of BC. Close collaboration between the patient and the medical team is essential to determine the most appropriate treatment plan for optimal results.

Molecular subtypes

Breast cancer has several molecular subtypes, including but not limited to HR+ BC [181, 182], HER2+ BC [183, 184], and triple-negative breast cancer (TNBC) [185, 186]. Classifying BC into molecular subtypes is essential as it provides important insights into tumor biology and helps in adjusting therapeutic approaches accordingly [187, 188].

One of the most important applications of molecular subtyping in the treatment of BC is the selection of targeted therapies [189]. PI3K inhibitors have exhibited effectiveness when combined with other targeted therapies against specific molecular subtypes. Notably, cases of HR+ BC with mutations in the PIK3CA gene, responsible for encoding the PI3K enzyme, have displayed distinct responses to PI3K inhibitors [190]. HR+ BC refers to tumors that express estrogen and/or progesterone receptors. This subtype often benefits from endocrine therapies such as hormone receptor blockers and aromatase inhibitors that interfere with hormone signaling pathways. However, in HR+ BC cases with PIK3CA mutations, dysregulated PI3K signaling may contribute to resistance to endocrine therapy [191]. Adding a PI3K inhibitor to the treatment regimen can overcome this resistance and improve treatment outcomes.

It is crucial to acknowledge that PI3K inhibitors and other targeted therapies are often tailored to specific molecular subtypes of BC due to variations in efficacy and applicability. Identifying PIK3CA mutations through molecular profiling or genetic testing can aid in selecting patients who are more likely to benefit from PI3K inhibitors as part of their treatment.

Genetic alterations

Genetic changes within the PI3K signaling pathway, particularly PIK3CA gene mutations, significantly influence the response to therapy in BC [192, 193]. Such alterations can affect the activation or dysregulation of PI3K signaling pathways, which play a vital role in cell growth, survival and proliferation.

BC patients with PIK3CA mutations show increased sensitivity to PI3K inhibitors, making them potential candidates for targeted therapy [194]. Genetic testing plays an important role in identifying patients who are likely to respond positively to PI3K inhibitor therapy. Analyzing the tumor's genetic profile, particularly PIK3CA mutations, will allow healthcare providers to individualize treatment decisions and select the most appropriate treatment option [195]. Identifying patients with PIK3CA mutations will enable targeted therapeutic approaches that specifically administer PI3K inhibitors to block signaling defects in the PI3K pathway [195]. This targeted therapy aims to block the activity of the PI3K enzyme, whose activity is increased by genetic alterations, thereby inhibiting the growth and survival of cancer cells.

Genetic testing is typically performed using various methods such as DNA sequencing technology to detect specific mutations within the PIK3CA gene [196]. It is essential to recognize that PIK3CA mutations are absent in all BC patients. Hence, genetic testing is crucial in identifying specific subsets of patients who are most likely to derive significant benefits from PI3K inhibitor therapy.

Incorporating genetic testing into the clinical setting will enable healthcare providers to optimize treatment decisions and deliver precision medicine to BC patients. This approach maximizes the likelihood of a positive treatment response while minimizing unnecessary treatment exposure for individuals unlikely to benefit from PI3K inhibitors.

Biomarker analysis

A comprehensive analysis of biomarkers, including genomic profiling, is of great value in understanding BC treatment outcomes [47, 197]. In addition to PIK3CA mutations, alterations in other genes within PI3K pathway, such as PTEN [198, 199], serve as important biomarkers for patient stratification and prediction of response to PI3K inhibitors.

Genomic profiling allows us to study the genetic makeup of tumors in detail and identify specific alterations and abnormalities within the PI3K signaling pathway. Besides PIK3CA mutations, biomarker analyses include assessing PTEN, a tumor suppressor gene, and AKT, a downstream effector of PI3K signaling [200]. These biomarkers may provide important insights into the dysregulation of PI3K signaling pathways and influence therapeutic decisions. Integrating biomarker analysis, including genomic profiling, into clinical trial design enables a more individualized and customized therapeutic approach. By identifying patients with specific biomarker profiles, such as changes in PIK3CA, PTEN and AKT, researchers can select participants who are likely to respond positively to PI3K inhibitor treatment [201]. This approach will improve the efficacy and efficiency of clinical trials and provide a better understanding of treatment response within specific patient subgroups.

Furthermore, biomarker analysis helps in patient stratification and offers the potential for personalized treatment approaches [202, 203]. By considering each patient's unique biomarker profile, healthcare providers can optimize treatment decisions and select the most appropriate therapeutic agents, such as PI3K inhibitors that target specific molecular alterations within tumors.

Host factors

Host factors, including individual patient characteristics, greatly influence response to BC therapy [204]. Factors such as age [205], general health status [206], and genetic diversity can significantly influence various aspects of treatment, such as drug metabolism, drug interactions, and tolerability [207]. Recognizing these host factors and incorporating them into treatment decisions allows for a more individualized and customized treatment approach that addresses each patient's unique needs.

Age plays an important role in considering treatment. Older patients may have differences in drug metabolism and tolerability compared to younger individuals [208, 209]. Additionally, additional comorbidities and age-related factors may necessitate treatment plan adjustment. Conversely, younger patients may have other fertility-sparing concerns and long-term side-effect considerations that need to be addressed [210].

The patient's overall health status, including organ function, performance status, and presence of comorbidities, is important in determining treatment options and dose adjustments. Associated medical conditions may affect a patient's ability to tolerate a particular therapy or influence treatment outcome [211]. For example, patients with hepatic or renal impairment may require dose adjustments or alternative therapeutic approaches to ensure optimal efficacy and safety. Genetic differences between individuals can significantly impact therapeutic response and drug metabolism. Polymorphisms in genes involved in drug pathways can affect drug efficacy and toxicity. Genetic testing can help identify specific mutations that may affect metabolism or response to certain treatments, and aid in individualized treatment decisions [212].

Considering these host factors allows healthcare providers to tailor treatment to individual patient needs. Tailoring treatment to address age-related considerations, general health conditions and genetic variability to ensure optimal treatment outcomes while minimizing potential risks and side effects. Incorporating these factors into treatment decisions promotes a patient-centred approach that considers each individual's unique characteristics and circumstances.

Challenges in developing PI3K inhibitors for breast cancer

In BC, PI3K inhibitors exhibit a distinct toxicity and side effect profile. The management strategies for mitigating the toxicity of PI3K inhibitors are discussed below.

Toxicity

Although toxicity has been a major obstacle in developing PI3K inhibitors for the treatment of BC [180], the PI3K signaling pathway plays a vital role in multiple cellular processes related to cell proliferation, survival, and metabolism, and may be therapeutically useful.

A targeted approach is needed to address the toxicity challenge, especially in BC therapy [183, 213]. The goal is to develop PI3K inhibitors with a better therapeutic window that allows selective targeting of cancer cells with minimal toxicity to normal breast tissue. To achieve this, researchers are investigating strategies to increase the selectivity of PI3K inhibitors for BC cells. This includes the development of inhibitors that specifically target isoforms of PI3K that are often dysregulated in BC, such as PI3Kα [214, 215], and PI3Kβ [216]. Targeting these isoforms can reduce off-target side effects and minimize toxicity to normal cells.

Additionally, researchers are exploring new drug delivery systems to improve the accumulation and retention of PI3K inhibitors in BC cells [217]. Targeted delivery mechanisms such as nanoparticle-based systems [218, 219] and antibody–drug conjugates [220, 221] can be used to increase the concentration of inhibitors within tumor cells while sparing healthy breast tissue. This approach helps to reduce the potential for toxicity further.

Isoform-specificity

Isoform specificity poses a major challenge in the development of PI3K inhibitors for the treatment BC [222]. PI3K is composed of four distinct isoforms (α, β, γ, δ), each with unique roles in cellular processes [223]. Various subtypes of BC may depend on specific isoforms of PI3K in their proliferation and survival. Therefore, the development of inhibitors that selectively target relevant isoforms involved in BC while sparing other isoforms is an important goal.

Breast cancer subtypes, including HR+, HER2+, and TNBC, show different dependencies on PI3K isoforms. For example, HR+ BC often show dysregulated activation of the PI3Kα isoform [224], which is associated with resistance to hormone therapy [191]. In contrast, activation of both PI3Kα and PI3Kβ isoforms is common in HER2+ BC [225].

To address this challenge, researchers are focusing on developing isoform-specific PI3K inhibitors that selectively target isoforms involved in BC subtypes [226]. Understanding the specific isoform dependencies of different BC subtypes has allowed scientists to develop isoform-targeted inhibitors that promote cancer growth while sparing less relevant isoforms [227].

Two approaches are being pursued to selectively inhibit PI3K isoforms. The first approach involves rational design of inhibitors with structural modifications that exploit the inherent differences between isoforms. This enables the development of isoform-specific inhibitors, reducing off-target effects and toxicity. The second strategy involves computational methods and virtual screening to identify isoform-specific PI3K inhibitors. Researchers can screen chemical libraries for compounds with high affinity and selectivity using computer models and molecular docking, optimizing isoform specificity and potency. Additionally, combination therapies targeting multiple isoforms simultaneously or sequentially are being explored to improve efficacy while considering the complex heterogeneity and overlapping functions of PI3K isoforms in BC.

Isoform-specific inhibitors

Recent advances in drug discovery have led to the development of isoform-specific PI3K inhibitors, offering promising opportunities for treating BC (Fig. 5). By targeting isoforms specifically linked to certain BC subtypes, these inhibitors have the potential to enhance treatment effectiveness while reducing adverse effects [228, 229].

Fig. 5
figure 5

The figure illustrates the molecular contexts that determine the applications of isoform-selective PI3K inhibitors. It represents different molecular alterations and their effects on PtdIns(3,4,5)P3 production through specific PI3K isoforms. A Upregulation or mutation of receptor tyrosine kinases (RTKs), oncogenic RAS mutations, or activating p110α mutations result in increased PtdIns(3,4,5)P3 production through p110α, which can be further amplified by mutation or loss of PTEN. In these contexts, the use of p110α-selective inhibitors is effective. B In the absence of other oncogenic alterations, loss or mutation of PTEN increases PtdIns(3,4,5)P3 production through p110β, potentially due to RAC1- or CDC42-mediated p110β activation or the basal activity of this isoform. In this context, the use of p110β-selective inhibitors is effective. C Upregulation or mutation of B cell receptors (BCRs), cytokine receptors, or other immune cell surface markers leads to increased PtdIns(3,4,5)P3 production through p110δ. In this context, the use of p110δ-selective inhibitors is effective. These different molecular alterations and their specific effects on PI3K isoforms highlight the rationale for using isoform-selective PI3K inhibitors based on the molecular context of the disease. This knowledge can guide the development and application of targeted therapies for various contexts associated with PI3K pathway dysregulation

The subtypes exhibit different characteristics and treatment responses, necessitating customized therapeutic approaches. For instance, dysregulated PI3Kα isoform signaling is often observed in HR+ BC. By developing isoform-specific inhibitors that selectively target PI3Kα, aberrant signaling pathways promoting proliferation and survival in HR+ BC cells can be more effectively inhibited while minimizing toxicity to normal cells [230, 231].

Furthermore, in TNBC, PI3Kγ isoforms were found to play central roles in tumor growth and progression. The development of isoform-specific inhibitors that selectively target these isoforms would provide a targeted approach to disrupt PI3K signaling, particularly in TNBC cells [232], potentially overcoming resistance mechanisms and reducing this malignancy. It may improve treatment response in high-grade BC subtypes. Advances in structural biology, computational modeling, and medicinal chemistry techniques have enabled researchers to rationally design isoform-specific PI3K inhibitors. By exploiting each isoform's unique structural features and binding pockets, it becomes possible to design inhibitors that selectively bind and inhibit target isoforms while sparing other isoforms. This approach increases inhibitor selectivity, reduces off-target effects, and improves therapeutic index.

Biomarkers and patient stratification

The Reliable biomarkers are crucial in BC therapy with PI3K inhibitors. They aid in patient stratification, identifying those who will likely respond well to treatment. Biomarkers enable personalized approaches, improving the chances of successful outcomes [140, 233]. Additionally, the discovery of predictive biomarkers will aid in monitoring therapeutic response and early detection of resistance among BC patients. This enables more precise and timely interventions to optimize treatment outcomes.

Identifying biomarkers associated with susceptibility to PI3K inhibitors, such as mutations in the PIK3CA gene, can optimize treatment outcomes in BC. PIK3CA mutations are prevalent in BC and serve as a useful biomarker for guiding treatment decisions [234], especially in HR+ and HER2 negative subtypes [235]. PIK3CA mutations increase sensitivity to PI3K inhibitors, helping identify patients for targeted therapy. Other gene alterations in the PI3K pathway, like PTEN and AKT, can also serve as biomarkers for response prediction. Loss of PTEN function or AKT activation may cause resistance to PI3K inhibitors [236].

Advances in genomic profiling techniques such as next-generation sequencing and gene expression profiling have enabled the identification of additional biomarkers associated with PI3K inhibitor response in BC. By analyzing the molecular properties of tumors, specific genomic alterations, gene expression patterns, or activation signatures can be identified as potential predictive biomarkers [237, 238]. These biomarkers help classify patients into responders and non-responders, allowing for more individualized therapeutic approaches and improved clinical outcomes.

Additionally, biomarkers may play a role in monitoring treatment response and detecting early signs of resistance. Continuous monitoring of biomarkers during treatment can provide insight into the efficacy of PI3K inhibitors and detect potential resistance mechanisms that may emerge. Alterations in biomarker profiles can indicate response to therapy, disease progression, or the development of resistance, allowing timely adjustments in therapeutic strategies and exploration of alternative therapeutic options.

Preclinical and clinical trial design

Improving preclinical models and optimizing clinical study designs are essential to gain valuable insight into the toxicity and side effect profiles of PI3K inhibitors in BC. These efforts will contribute to the development of more effective drugs and help identify strategies to reduce toxicity associated with PI3K inhibitors.

Preclinical models, like cell cultures and animal models, assess PI3K inhibitor efficacy and safety before human trials [85]. Enhancing breast cancer-specific preclinical models improves accuracy in predicting response. PDX models transplant BC tissue into mice, enabling evaluation in a clinically relevant context. PDX models uncover molecular subtypes and genetic alterations that influence PI3K inhibitor sensitivity or resistance, aiding targeted therapy development.

In addition to preclinical models, it is important to optimize clinical trial designs to assess the safety and efficacy of PI3K inhibitors in BC patients [42, 116]. Well-controlled clinical trial design, including appropriate patient stratification, outcome measures, and monitoring protocols, is essential to obtain reliable data on drug toxicity profiles. This includes considering factors such as BC subtype, hormone receptor status, and the presence of certain genetic alterations (such as PIK3CA mutations) to guide patient selection and assessment of treatment response. Clinical trials rigorously assess and monitor the toxicity of PI3K inhibitors in BC patients. Comprehensive evaluation and reporting of adverse events enable identifying common toxicities and the development of mitigation strategies. This enhances patient tolerability and treatment adherence. Integrating biomarker analysis in clinical trials enhances patient selection, treatment response prediction, and toxicity identification. Molecular profiling identifies drug susceptibility, resistance, and toxicity biomarkers, enabling personalized therapies. This optimizes outcomes by targeting patient subsets likely to benefit from PI3K inhibitors.

Resistance mechanisms to PI3K inhibitors

Resistance to PI3K inhibitors can arise through various mechanisms, limiting their long-term effectiveness in cancer treatment. Some common resistance mechanisms include:

Activation of alternative signaling pathways

Cancer cells show remarkable adaptability to PI3K inhibition, which can activate alternative signaling pathways and circumvent the silencing effects of PI3K inhibitors. A key mechanism in these cells is the activation of parallel signaling pathways such as the MAPK pathway (mitogen-activated protein kinase) and the mTOR pathway. Cancer cells can evade the blocking of PI3K signaling by using these signalling pathways, thus ensuring cancer cell survival and uncontrolled proliferation (Fig. 6) [9].

Fig. 6
figure 6

Insulin-Mediated Feedback Loops Following PI3K/mTOR Inhibition: This figure illustrates the complex feedback loops that occur following treatment with PI3K and mTOR inhibitors in cancer cells. When PI3K is inhibited, the liver breaks down stored glycogen, releasing glucose into the bloodstream, resulting in hyperglycemia. The pancreas detects elevated glucose levels, triggering a substantial insulin release, leading to hyperinsulinemia. Hyperinsulinemia partially reactivates the insulin receptor, thereby reinstating the activity of insulin receptor substrate (IRS) and growth factor receptor-bound protein 2 (GRB2). This reactivation leads to an increase in both PI3K and MAPK pathway activation, limiting the therapeutic effects of PI3K inhibitors. Similarly, mTOR1 inhibitors, such as rapamycin, downregulate S6 kinase 1 (S6K1) and eukaryotic translation initiation factor 4E-binding protein 1 (4E-BP1), which blocks downstream translation. The de-repression of 4E-BP1 leads to the enhanced availability of IRS1, acting as an intermediary between the insulin receptor and the PI3K complex. This recruitment of PI3K to the active receptor enhances both MAPK and downstream PI3K signaling, thereby reducing the overall sensitivity to mTOR inhibition. Downregulation of mTOR activity through AKT inhibition or direct mTOR inhibition blocks 4E-BP1-mediated phosphatase and tensin homolog (PTEN) translation. This results in the accumulation of phosphatidylinositol 3,4,5-trisphosphate (PIP3), leading to sustained activation of AKT

The MAPK signaling pathway is pivotal in governing fundamental cellular processes, including cell proliferation and division [239, 240]. In response to PI3K inhibition, cancer cells may activate the MAPK pathway as an alternative way to sustain proliferation. Through this activation, cancer cells can evade the effects of PI3K inhibitors, facilitating their survival and proliferation despite the presence of these targeted therapies.

The mTOR pathway, a critical regulator of cell proliferation and protein synthesis, acts as a compensatory pathway when PI3K is inhibited. Cancer cells can upregulate mTOR pathway activity, even in the presence of PI3K inhibitors. This allows them to sustain growth and proliferation despite the blockade of PI3K signaling [241].

By activating these parallel signaling pathways, cancer cells evade the target's inhibition of PI3K, thereby conferring resistance to PI3K inhibitors. This adaptive response highlights the complex nature of cancer and the challenges in developing effective therapeutic strategies against dysregulated PI3K signaling.

Mutations in the PI3K pathway

Mutations in the PI3K signaling pathway pose a significant challenge to the efficacy of PI3K inhibitors in cancer therapy, particularly secondary to key components such as the PIK3CA gene and other essential components of the signaling pathway [194]. Mutations can impair the efficacy of PI3K inhibitors. These mutations can cause structural or functional alterations in PI3K or its downstream targets, thereby reducing the efficacy of inhibitors that block signaling pathways. As a result, cancer cells harboring such mutations retain the ability to maintain dysregulated activation of the PI3K pathway, ultimately resulting in resistance to PI3K-targeted therapy [242].

Specifically, mutations in the PIK3CA gene, responsible for encoding the PI3K catalytic subunit, can lead to the continuous activation of PI3K signaling, rendering it unaffected by inhibitors [243]. These mutations often involve changes in key domains of the protein, such as the kinase domain, resulting in increased enzymatic activity and maintenance of downstream signaling. Furthermore, mutations in other components of the PI3K signaling pathway, including PTEN, impair negative feedback regulation and enhance activation of signaling pathways, leading to resistance [244].

Upregulation of compensatory pathways

The adaptability of cancer cells to PI3K inhibition is demonstrated by their ability to upregulate compensatory pathways such as the MAPK and mTOR pathways [126]. These alternative pathways act as countermeasures against PI3K blockade, allowing cancer cells to maintain proliferation despite inhibitory effects.

Compensatory upregulation of the MAPK signaling pathway is common in cancer cells in the presence of PI3K inhibitors [245]. The MAPK signaling pathway plays a pivotal role in governing cellular processes including cell growth, proliferation, and survival. Cancer cells can exploit this pathway by amplifying its activity, bypassing the inhibitory effects of PI3K inhibitors and promoting unchecked cancer cell proliferation. This activation ensures that critical cellular functions required for survival and proliferation are maintained even in the presence of PI3K inhibitors.

Similarly, cancer cells use upregulation strategies involving the mTOR signaling pathway as compensatory mechanisms. The mTOR pathway is a key regulator of protein synthesis, cell growth and proliferation [246]. PI3K inhibition causes cancer cells to increase the activity of mTOR pathway to compensate for loss of PI3K signaling. This upregulation provides an alternative way to sustain PI3K proliferation and overcome the inhibitory effects of PI3K inhibitors. By activating these compensatory pathways, cancer cells establish mechanisms to overcome blockade of PI3K signaling and ensure survival and proliferation. Upregulation of the MAPK and mTOR signaling pathways allows cancer cells to compensate for PI3K loss of function and maintain proliferative potential despite treatment with PI3K inhibitors.

Loss of negative regulators

Loss of PTEN, a key negative regulator of PI3K signaling [247], plays an important role in conferring resistance to PI3K inhibitors [248]. PTEN normally functions as a tumor suppressor by inhibiting PI3K signaling [249]. However, when PTEN is lost or inactivated by genetic alterations or other mechanisms, the PI3K pathway is overactivated. This loss of PTEN function results in dysregulation of the PI3K signaling pathway, resulting in increased cell proliferation and survival signals.

When cancer cells lose functional PTEN, they become less susceptible to the inhibitory effects of PI3K inhibitors [58]. In the absence of PTEN, the PI3K pathway is persistently misactivated, evading the intended therapeutic effects of PI3K inhibitors. As a result, cancer cells lacking functional PTEN may continue to proliferate uncontrolled and evade the inhibitory effects of PI3K inhibitors.

Loss or inactivation of PTEN can occur through various mechanisms, including genetic mutations [250], epigenetic modifications [251], and altered protein stability [252]. These alterations disrupt normal PTEN function and cause imbalances within the PI3K signaling pathway.

Understanding the importance of PTEN loss in the emergence of resistance to PI3K inhibitors is critical for the development of effective therapeutic strategies. Therapeutic approaches targeting restoration of PTEN function and alternative vulnerabilities in PTEN-deficient cancer cells may overcome resistance and improve outcomes of PI3K-targeted therapies.

Opportunities in developing PI3K inhibitors for breast cancer

Developing PI3K inhibitors for BC presents promising opportunities to enhance treatment strategies and improve patient outcomes. These opportunities include:

Overcoming resistance to PI3K inhibitors

The development of resistance to PI3K inhibitors is a major challenge in BC therapy. Strategies to overcome resistance to PI3K inhibitors are described below.

Dual inhibition

A dual inhibition strategy has emerged as a powerful approach to improve the efficacy of PI3K-targeted therapy by blocking compensatory signals and overcoming resistance [253]. These strategies simultaneously target multiple components of the PI3K pathway to achieve comprehensive and synergistic blockade, ultimately improving therapeutic outcomes.

The PI3K signaling pathway consists of several key components, including PI3K itself, downstream effectors such as AKT and mTOR [145]. Cancer cells often evolve compensatory mechanisms by activating alternative signaling pathways when a single component of the PI3K signaling pathway is attacked. To circumvent this resistance, dual-inhibition approaches aim to simultaneously target multiple components of the PI3K signaling pathway. One strategy involves combined inhibition of PI3K and its downstream effector mTOR. This dual-inhibition approach effectively suppresses two key nodes in the signaling pathway, resulting in broader blockade. Simultaneous targeting of PI3K and mTOR prevents compensatory signaling through mTOR activation, enhances therapeutic efficacy, and overcomes resistance to PI3K inhibitors [33, 115].

A dual inhibition strategy targeting both PI3K and AKT maybe effective in disrupting the signaling cascade and preventing compensatory activation of AKT, leading to potent inhibition of downstream events. Combining PI3K inhibitors with agents targeting alternative pathways, such as the MAPK pathway, may further enhances therapeutic response by preventing compensatory activation of MAPK signaling and suppressing pro-survival signals. This comprehensive approach will hold promise for overcoming resistance mechanisms and improving outcomes in PI3K-associated cancers.

Novel agents targeting resistance mechanisms

The development of new drugs that specifically target and overcome known resistance mechanisms is an important tool for improving cancer outcomes [254]. Identifying and targeting specific resistance mechanisms that emerge during therapy. By doing so, these new drugs have the potential to be transformative in order to increase the efficacy of targeted therapies [255].

Resistance mechanisms occur through various processes such as genetic alterations, epigenetic modifications, and activation of compensatory pathways. Understanding the specific mechanisms of resistance allows researchers to design drugs that directly target and counteract these mechanisms [255].

For example, in the context of therapies targeting the PI3K signaling pathway, new drugs may be developed that selectively block secondary mutations that impair the efficacy of PI3K inhibitors. These agents can be designed to specifically target and inhibit variants of PIK3CA and other key components of the PI3K signaling pathway, thereby increasing the sensitivity of cancer cells to PI3K inhibitors.

Additionally, drugs can be designed to restore the function of, or mimic the action of, negative regulators that are lost or inactivated during therapy. For example, if PTEN is lost, new drugs can be developed to restore PTEN expression or enhance its tumor suppressor activity. These agents can sensitize cancer cells to PI3K inhibitors and overcome resistance by restoring balance in the PI3K signaling pathway.

Another strategy involves developing drugs that specifically target and inhibit compensatory pathways that are activated in response to treatment. For example, drugs can be designed to selectively block the MAPK [256], or mTOR [257, 258] signaling pathways, which are often upregulated in response to PI3K inhibition. By inhibiting these compensatory pathways, these novel agents may prevent their activation and enhance the efficacy of therapies targeting the PI3K pathway.

Additionally, novel drugs can be developed that target specific signaling nodes or molecular targets important for resistance development. A thorough understanding of the mechanisms underlying resistance will allow researchers to identify points of weakness within signaling pathways and design drugs that selectively inhibit these targets, thereby reducing resistance.

Biomarker-guided therapy

Biomarker-based therapy has shown promise to optimise outcomes for cancer patients receiving PI3K inhibitors [259]. By identifying predictive biomarkers that can stratify patients based on their likelihood of responding to PI3K inhibitors, individualized treatment strategies can be tailored to individual profiles, resulting in improved treatment efficacy.

An important aspect of biomarker-based therapy is the identification of specific biomarkers that can reliably predict a patient's response to PI3K inhibitors. These biomarkers can be genetic, molecular, or cellular traits associated with sensitivity or resistance to PI3K inhibition. Researchers can identify and validate these biomarkers by analyzing tumor samples or performing non-invasive tests such as liquid biopsies. For example, genetic alterations in the PIK3CA gene [260, 261], which encodes the PI3K catalytic subunit, have been identified as potential predictive biomarkers. Patients with certain PIK3CA mutations may show an increased response to PI3K inhibitors. Therefore, biomarker-based therapy could identify these mutations through genetic testing and select patients with PIK3CA mutations as good candidates for PI3K inhibitor therapy.

In addition to genetic biomarkers, other molecular markers or changes in signaling pathways may also serve as predictive biomarkers. For example, altered expression or activity of PTEN, which negatively regulates PI3K signaling [262], could influence responses to PI3K inhibitors. Biomarker-based therapy can assess PTEN status through immunohistochemistry or molecular testing to identify patients who may benefit from PI3K inhibitor therapy.

Biomarker-based therapies play a crucial role in tailoring PI3K inhibitor treatments. Identifying biomarkers associated with compensatory pathway activation, such as MAPK and mTOR, can guide combination therapies. Positive biomarker profiles indicate patients likely to respond to PI3K inhibitors, while negative profiles suggest alternative treatment options or combination therapies targeting alternative pathways. This individualized approach optimizes therapeutic response and minimizes side effects, advancing precision oncology in PI3K-associated cancers.

Adaptive treatment approaches

Adaptive therapeutic approaches have emerged as dynamic strategies to optimize therapeutic efficacy and overcome resistance in cancer patients [263]. By continuously monitoring treatment response and adjusting treatment based on real-time patient-specific data, these approaches can enable personalized and dynamic adjustments to improve outcomes [264].

Central to the adaptive treatment approach is regular monitoring of treatment response using various techniques such as imaging [265], and liquid biopsy [266]. These monitoring methods provide real-time insight into a patient's tumor dynamics, allowing physicians to assess the efficacy of ongoing therapy.

Treatment strategies can be adjusted to optimize treatment efficacy based on the data collected. For example, if initial treatment with a PI3K inhibitor produces a suboptimal response or demonstrates the emergence of resistance, an adaptive approach allows for timely changes. This may include switching to an alternative PI3K inhibitor with a different binding profile or choosing a combination therapy targeting compensatory pathways identified through real-time monitoring.

Adaptive approaches also include changing treatment schedules and dosages [267]. By fine-tuning treatment regimens based on patient response and tolerability, efficacy can be maximized while minimizing toxicity [268]. For example, doses may be adjusted or treatment interrupted to manage side effects or improve drug delivery. Additionally, adaptive treatment approaches integrate the use of predictive models and algorithms to guide decision making. Combining patient-specific data such as molecular profiling, treatment history and clinical parameters with computational analysis, these models can generate individualized treatment response predictions and identify potential resistance mechanisms. Such predictive modeling enables proactive decision-making, allowing physicians to anticipate and counteract resistance before it becomes clinically apparent.

Adopting adaptive therapeutic approaches in PI3K-associated cancers requires collaboration among clinicians, researchers, and data analysts. Establishing a robust data infrastructure and clinical guidelines enables real-time collection and analysis of patient-specific data, facilitating treatment adjustments based on individual needs. This dynamic approach improves outcomes by allowing timely intervention, early resistance detection, and optimized treatment strategies.

Combination therapy

Combining PI3K inhibitors with other targeted agents enables a synergistic approach to simultaneously target multiple signaling pathways and address potential resistance mechanisms. Several targeted agents have shown promise in combination with his PI3K inhibitors in the treatment of breast cancer [84].

HER2-targeted therapies

In HER2 BC, PI3K signaling is often co-activated with HER2 signaling, which contributes to resistance and poor response to HER2-targeted therapy [269]. To meet this challenge, combinations of PI3K inhibitors and HER2-targeting agents, such as trastuzumab [270, 271], and lapatinib [272, 273], have emerged as promising therapies.

The combination of HER2-targeted therapy and PI3K inhibition in HER2+ BC aims to suppress proliferative signals from HER2 and inhibit the PI3K signaling pathway. This approach enhances anti-tumor activity and improves patient outcomes by overcoming resistance mechanisms and interfering with compensatory signaling.

In addition, this combined strategy offers the potential for synergistic effects, as the PI3K signaling pathway can regulate multiple cellular processes such as cell cycle progression, survival and metabolism that influence tumor growth and therapeutic response [274]. By blocking both pathways, combination therapy aims to achieve a more comprehensive inhibition of tumor cell signaling and proliferation. Pre-clinical trials have shown encouraging results that the combination of PI3K inhibitors and HER2-targeted agents improves objective response rates and progression-free survival in patients with HER2+ BC [275]. These results support the concept of dual pathway inhibition as a powerful strategy to overcome resistance and improve patient outcomes.

Overall, the combination of PI3K inhibitors and HER2-targeted therapy represents a rational and targeted therapeutic approach for HER2+ BC, addressing co-activation of PI3K signaling pathways, overcoming resistance mechanisms, and exerting antitumor efficacy offers the possibility of strengthening. This ultimately provides new opportunities to improve therapeutic efficacy in this specific subtype of breast cancer.

CDK4/6 inhibitors

CDK4/6 inhibitors, including Palbociclib [276, 277], ribociclib [278, 279], and abemaciclib [280, 281], have demonstrated notable effectiveness in HR+ BC. These inhibitors work by targeting CDK4/6, inducing cell cycle arrest and suppressing tumor cell proliferation.

A combination of CDK4/6 inhibitors and PI3K inhibitors has proven to be a promising therapeutic strategy. Preclinical and clinical studies have provided evidence of synergy when these two inhibitors are used together [282]. The combination of PI3K inhibitors and CDK4/6 inhibitors in HR+ breast cancer is driven by their complementary mechanisms. PI3K inhibitors suppress cell survival and proliferation by targeting the PI3K signaling pathway, while CDK4/6 inhibitors directly block cell cycle progression at the G1/S phase transition by inhibiting Rb phosphorylation.

Combining these inhibitors may enhance inhibition of tumor growth. This combination synergistically disrupts both the cell cycle and PI3K signaling pathways, resulting in a more comprehensive inhibition of tumor cell proliferation. This approach addresses potential resistance mechanisms associated with single-pathway targeting and has broad-spectrum effects on tumor growth control [283].

Clinical trials investigating the combination of CDK4/6 inhibitors and PI3K inhibitors in HR+ BC have demonstrated promising results, including longer progression-free survival, improved objective response rate, and longer duration of response compared to monotherapy. This combination therapy offers potential advantages in terms of minimizing treatment resistance and optimizing patient outcomes by targeting multiple key pathways involved in tumor growth and survival, overcoming resistance mechanisms that may arise during monotherapy.

Endocrine therapies

Endocrine therapies such as aromatase inhibitors [284, 285], and selective estrogen receptor modulators are important treatments for HR+ BC. However, the interplay between PI3K signaling and estrogen receptor signaling may lead to resistance to endocrine therapy. In order to overcome resistance mechanisms and improve treatment response in HR+ BC, the combination of PI3K inhibitors and endocrine therapy has been explored as a potential approach [117].

The PI3K signaling pathway interacts with estrogen receptor signaling to promote cell proliferation and survival [286]. Dysregulation of PI3K signaling may contribute to endocrine resistance by evading or interfering with the effects of endocrine therapy [17]. Combining PI3K inhibitors with endocrine therapy can simultaneously target both signalling pathways, resulting in more comprehensive tumour growth inhibition. PI3K inhibitors block the PI3K signaling pathway, whereas endocrine therapy interferes with estrogen receptor signaling and globally impedes cancer cell survival and proliferation [17].

Preclinical and clinical studies have demonstrated promising results with the combination of PI3K inhibitors and endocrine therapy in HR+ BC. This approach leads to increased tumor growth suppression, improved response rates, and longer progression-free survival compared to endocrine therapy alone [287]. By targeting multiple signaling pathways, this combination strategy overcomes acquired resistance and prevents the emergence of resistance, addressing the complexity of HR+ BC and offering potential for optimized treatment outcomes.

mTOR inhibitors

The mTOR is closely related to the PI3K signaling pathway and is central in regulating cell growth and proliferation [288]. The PI3K and mTOR pathways share some points of interaction and co-regulation. Dysregulation of these pathways can lead to increased cell survival, increased cell proliferation, and resistance to therapy [114]. Targeting both pathways simultaneously can achieve a more comprehensive inhibition of tumor growth. The combination of PI3K and mTOR inhibitors represents a dual blockade approach that effectively suppresses signaling cascades in promoting cancer cell growth. This combination inhibits PI3K-mediated activation of mTOR and downstream effectors, thereby synergizing tumor cells [289].

The combination of PI3K inhibitors and mTOR inhibitors has demonstrated encouraging outcomes in cancer treatment. Compared to monotherapy, this synergistic approach enhances progression-free survival, objective response rate, and overall survival. This strategy effectively tackles resistance mechanisms by concurrently targeting the PI3K and mTOR pathways, offering a compelling therapeutic option for patients with this specific type of BC.

MEK inhibitors

Activation of the MAPK, particularly by the downstream kinase MEK, may serve as a compensatory mechanism in response to PI3K inhibition [290]. The PI3K and MAPK signaling pathways are interrelated and often activated in cancer cells [291]. When PI3K signaling is inhibited, cancer cells activate MAPK signaling as an alternative survival mechanism, promoting cell proliferation and therapy resistance.

The combination of PI3K and MEK inhibitors represents a dual inhibitory strategy that simultaneously targets the PI3K and MAPK pathways [292, 293]. By blocking both pathways, this combined approach aims to achieve broader inhibition of tumor cell proliferation and survival.

Preclinical studies have shown that the combination of PI3K inhibitors and MEK inhibitors may provide synergistic effects and increase anti-tumor activity compared to monotherapy. This synergistic effect results from the complementary actions of these inhibitors, jointly repressing key signaling nodes in both signaling pathways and impeding compensatory signaling [294].

This combination strategy may overcome resistance mechanisms that may arise during treatment with PI3K inhibitors by simultaneously targeting the PI3K and MAPK signaling pathways. This interferes with compensatory activation of the MAPK pathway, which may contribute to treatment resistance, and improves overall therapeutic response.

Clinical trials

Several trials have been completed, and some are currently underway to investigate the targeting of the PI3K pathway in breast cancer (Table 6). The ongoing trials are discussed below. The clinical trial (NCT03962647) is a neoadjuvant study investigating the feasibility and tolerability of a 2-week ketogenic diet combined with letrozole in patients with operable early-stage ER+ breast cancer. The primary objective is to assess the viability and tolerability of the dietary intervention alongside endocrine therapy before surgery. Secondary goals include evaluating the combined impact on inhibiting cancer cell growth, measuring insulin/PI3K pathway activation, assessing changes in weight and body composition, and determining the efficacy of inducing a ketogenic state in synergy with endocrine therapy. Participants undergo baseline measurements, initiate a 2-week ketogenic diet with meal replacement shakes, and receive letrozole. Post-intervention, metabolic parameters are re-evaluated, and patients proceed to surgical intervention. The study represents a crucial step in understanding the potential benefits of combining dietary modification and endocrine therapy in ER+ breast cancer treatment [295].

Table 6 Clinical trials for targeting the PI3k signalling in breast cancer

The ongoing SABINA study (NCT05810870) is a Phase II clinical trial designed to assess the safety and efficacy of MEN1611, both as a monotherapy and in combination with eribulin, in patients with unresectable, HR/HER2-negative, PIK3CA/PTEN-altered locally advanced or metastatic breast cancer (MpBC). The trial initiates with a run-in period to evaluate the safety and tolerability of the combination, aiming to establish the dosing schedule based on toxicity profiles identified in a preliminary study. The primary objective is to evaluate the efficacy of the eribulin and MEN1611 combination, measured by clinical benefit rate (CBR) in patients with unresectable MpBC (cohort A). Simultaneously, the study assesses MEN1611's efficacy as monotherapy through objective response rate (ORR) after 6 weeks (cohort B). The study plans to enroll 28 patients, with Cohort A potentially expanding based on a toxicity review. Cohort B is contingent on positive results in Cohort A, utilizing Simon's two-stage minimax design to guide further expansion based on treatment response in a staged manner. This study represents a significant step in understanding the therapeutic potential of MEN1611 in MpBC [296].

Another Phase I/II clinical trial (NCT04345913) investigates the safety, toxicity profile, and efficacy of combining copanlisib hydrochloride and eribulin mesylate for treating metastatic triple-negative breast cancer. Following a prior dose-escalation study, the primary objectives are to determine safety parameters and compare progression-free survival (PFS) between patients treated with eribulin monotherapy and those receiving the combination. Secondary objectives include evaluating objective response rate (ORR), clinical benefit rate (CBR), and safety in both arms, along with documenting antitumor activity. The study aims to assess outcomes based on PIK3CA/PTEN pathway alterations and employs biomarkers to evaluate targeted inhibition by copanlisib and eribulin. Patient randomization into two groups involves different administration schedules, and both groups undergo imaging, biopsies, and blood sample collections at specified intervals. Follow-up occurs every 3 months post-treatment for up to 36 months. Overall, this study is crucial for understanding the potential therapeutic benefits of copanlisib and eribulin in the context of metastatic triple-negative breast cancer [297].

The ongoing Phase II clinical trial (NCT03765983) investigates the investigational intervention GDC-0084 in combination with the FDA-approved targeted therapy trastuzumab for the treatment of HER2-positive breast cancer, specifically focusing on patients with brain metastases. GDC-0084, though not FDA-approved, exhibits the capability to inhibit PI3 kinase, disrupting a crucial pathway in cancer cell growth. In contrast, trastuzumab, an established HER2-targeted therapy, disrupts proliferative signals and enhances immune recognition of cancer cells. The study aims to unravel the potential synergistic effects of combining GDC-0084 with trastuzumab, shedding light on the responses of HER2-positive breast cancers. The trial represents a critical milestone in understanding the therapeutic benefits of this combination in the challenging context of HER2-positive breast cancer with brain metastases [298].

Conclusion

In summary, advances in predictive, preventive and personalized medicine and our understanding of the challenges and opportunities in developing PI3K inhibitors for BC have paved the way for significant progress in this field. By focusing on predictive biomarkers, preclinical models, and genomic approaches, researchers have made significant progress in identifying biomarkers that can help predict response to PI3K inhibitors in BC patients. These predictive biomarkers provide valuable insight into patient stratification and individualized treatment decisions.

Moreover, preventive medicine strategies for PI3K activation in BC have shown promise. Preclinical evidence supports the protective effect of PI3K inhibitors, raising hopes for BC risk reduction in high-risk populations. Understanding the mechanisms underlying these preventive effects may open up the possibility of developing new preventive interventions.

Personalized medicine approaches have revolutionized BC treatment by addressing multiple factors that influence treatment response, including tumor stage, molecular subtype, and patient-specific characteristics. Clinical evidence has demonstrated the efficacy of PI3K inhibitors in specific patient subgroups, allowing targeted therapy to be tailored to individual patients. Overcoming resistance to PI3K inhibitors remains a challenge, but continued efforts to identify mechanisms of resistance and develop combination therapies promise better outcomes.

Finally, PI3K inhibitor development for BC needs to address its toxicity and side effect profile. Rigorous evaluation and monitoring of adverse events are critical to optimize patient compliance and adherence to treatment. Additionally, combining PI3K inhibitors with other targeted agents, such as his HER2-targeted therapy and CDK4/6 inhibitors, offers the opportunity to improve therapeutic efficacy and overcome resistance mechanisms.

Overall, a thorough understanding of the challenges and opportunities in developing PI3K inhibitors for BC, as well as integrating predictive, preventive, and personalized medicine approaches, has the potential to transform patient care. Harnessing the power of predictive biomarkers, preventive strategies, individual treatment options, and combination therapies to maximize treatment efficacy, improve patient outcomes, and ultimately advance the therapeutic field of BC.

Future directions

In the field of predictive medicine, future research should focus on identifying and validating predictive biomarkers for PI3K inhibitors in BC. This requires the study of specific genetic alterations, protein expression patterns and molecular signatures that can accurately predict treatment response. Furthermore, developing and refining preclinical models of PI3K inhibitors in BC will improve their predictive value and enable better transition to clinical trials. Incorporating patient-derived models, organoids, and 3D culture systems can provide a more clinically relevant understanding of drug efficacy and resistance mechanisms. Genomic approaches such as next-generation sequencing and multi-omics analysis should be used to comprehensively identify potential biomarkers of response to PI3K inhibitors. Integrating genomic data with clinical outcomes will improve our understanding of patient stratification and serve as the basis for personalized treatment decisions.

In the field of preventive medicine, prospective clinical trials are needed to evaluate the preventive efficacy of PI3K inhibitors in high-risk populations, such as those with a family history of BC or precancerous lesions. Long-term follow-up will provide insight into prophylactic interventions' sustained benefits and safety profile. Further research into the underlying mechanisms of the preventive effects of PI3K inhibitors is important. Elucidating how PI3K activation contributes to BC development and progression will help identify new targets and avenues for prevention strategies. Combinatorial approaches targeting both PI3K and other relevant signaling pathways involved in BC development should be explored to improve preventive efficacy. Understanding the interactions between different signaling networks will facilitate the development of more comprehensive preventative measures.

In the field of personalized medicine, refinement of patient selection criteria based on tumor stage, molecular subtype and other factors will optimize the use of PI3K inhibitors in BC treatment. Prospective studies should validate the clinical utility of these selection criteria and investigate additional factors influencing treatment response, such as the TME and host genetic variation. Examining the efficacy of PI3K inhibitors in specific patient subgroups, such as those with different genetic mutations or resistance mechanisms, will guide individualized therapeutic strategies. Prospective clinical trials using stratified patient cohorts are needed to identify patients who will benefit most from PI3K inhibitors. Overcoming resistance to PI3K inhibitors is an important research area. Combination therapies targeting resistance mechanisms such as MAPK signaling or alternative signaling pathways should be considered. Developing new drugs and rational combinations based on understanding resistance mechanisms will help improve treatment outcomes.

Comprehensive assessment and treatment of the toxicity and side effect profiles associated with these inhibitors should be a priority when addressing the challenges and opportunities in the development of PI3K inhibitors for BC. Identifying strategies that reduce toxicity and optimize patient compliance improve treatment adherence and quality of life. Further elucidation of the mechanisms of resistance to PI3K inhibitors is needed. This includes understanding adaptive feedback loops, genetic alterations, and other molecular events that produce resistance. Combination therapies that target specific resistance mechanisms or use synergistic drug combinations show promise in overcoming resistance. Further research is needed into combination therapy approaches using PI3K inhibitors and other targeted agents, such as HER2-targeted therapies and immune checkpoint inhibitors. Rational design of combination therapies based on mechanistic insights and preclinical evidence will improve therapeutic efficacy and expand treatment options.

In summary, future directions in the field of PI3K inhibitors for BC include improving predictive medicine approaches, developing prevention strategies, advancing personalized medicine approaches, and addressing drug development challenges and opportunities. These efforts will streamline treatment selection, improve preventive interventions, improve patient outcomes, and bring us closer to the realization of precision medicine in breast cancer.

Availability of data and materials

Not applicable.

Abbreviations

BC:

Breast cancer

PI3K:

Phosphatidylinositol-3-kinase

EGFR:

Epidermal growth factor receptor

IGFR:

Insulin-like growth factor receptor

HER2:

Human epidermal growth factor receptor 2

PIP2:

Phosphatidylinositol 4,5-bisphosphate

PIP3:

Phosphatidylinositol 3,4,5-trisphosphate

pAKT:

Phosphorylated AKT

AKT1:

V-AKT Murine Thymoma Viral Oncogene Homolog 1

PIK3R1:

Phosphoinositide 3-kinase regulatory subunit 1

INPP4B:

Inositol polyphosphate 4-phosphatase type II

ctDNA:

Circulating tumor DNA

CTCs:

Circulating tumor cells

ER:

Estrogen receptor

PDX:

Patient-derived xenografts

GEMM:

Genetically engineered mouse model

mTOR:

Mammalian target of rapamycin

VEGF:

Vascular endothelial growth factor

NK:

Natural killer

Treg:

Regulatory T cells

HR+:

Hormone receptor-positive

TNBC:

Triple-negative breast cancer

MAPK:

Mitogen-activated protein kinase

References

  1. Xu S, Liu Y, Zhang T, Zheng J, Lin W, Cai J, Zou J, Chen Y, Xie Y, Chen YY, Li Z. The global, regional, and national burden and trends of breast cancer from 1990 to 2019: results from the global burden of disease study 2019. Front Oncol. 2021;1:689562.

    Article  Google Scholar 

  2. DeSantis CE, Bray F, Ferlay J, Lortet-Tieulent J, Anderson BO, Jemal A. International variation in female breast cancer incidence and mortality rates. Cancer Epidemiol Biomark Prev. 2015;24:1495–506.

    Article  Google Scholar 

  3. Aalhate M, Mahajan S, Singh H, Guru SK, Singh PK. Nanomedicine in therapeutic warfront against estrogen receptor–positive breast cancer. Drug Deliv Transl Res. 2023;13:1621–53.

    Article  PubMed  Google Scholar 

  4. Guo L, Kong D, Liu J, Zhan L, Luo L, Zheng W, Zheng Q, Chen C, Sun S. Breast cancer heterogeneity and its implication in personalized precision therapy. Exp Hematol Oncol. 2023;12:3.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Ganesan K, Du B, Chen J. Effects and mechanisms of dietary bioactive compounds on breast cancer prevention. Pharmacol Res. 2022;178: 105974.

    Article  CAS  PubMed  Google Scholar 

  6. Alves CL, Ditzel HJ. Drugging the PI3K/AKT/mTOR pathway in ER+ breast cancer. Int J Mol Sci. 2023;24:4522.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Chen H, Gu Z, An H, Chen C, Chen J, Cui R, Chen S, Chen W, Chen X, Chen X, et al. Precise nanomedicine for intelligent therapy of cancer. Sci China Chem. 2018;61:1503–52.

    Article  CAS  Google Scholar 

  8. Jiang N, Dai Q, Su X, Fu J, Feng X, Peng J. Role of PI3K/AKT pathway in cancer: the framework of malignant behavior. Mol Biol Rep. 2020;47:4587–629.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Wright SCE, Vasilevski N, Serra V, Rodon J, Eichhorn PJA. Mechanisms of resistance to PI3K inhibitors in cancer: adaptive responses, drug tolerance and cellular plasticity. Cancers. 2021;13:1538.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Khezri MR, Jafari R, Yousefi K, Zolbanin NM. The PI3K/AKT signaling pathway in cancer: molecular mechanisms and possible therapeutic interventions. Exp Mol Pathol. 2022;127: 104787.

    Article  CAS  PubMed  Google Scholar 

  11. Peng Y, Wang Y, Zhou C, Mei W, Zeng C. PI3K/Akt/mTOR pathway and its role in cancer therapeutics: are we making headway? Front Oncol. 2022;12: 819128.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Davis WJ, Lehmann PZ, Li W. Nuclear PI3K signaling in cell growth and tumorigenesis. Front Cell Dev Biol. 2015;3:24.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Zhang T, Li P, Guo W, Liu Q, Qiao W, Deng M. NCAPH promotes proliferation as well as motility of breast cancer cells by activating the PI3K/AKT pathway. Physiol Int. 2022. https://doi.org/10.1556/2060.2022.00028.

    Article  PubMed  Google Scholar 

  14. Donnella HJ, Webber JT, Levin RS, Camarda R, Momcilovic O, Bayani N, Shah KN, Korkola JE, Shokat KM, Goga A. Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer. Nat Chem Biol. 2018;14:768–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Castaneda CA, Cortes-Funes H, Gomez HL, Ciruelos EM. The phosphatidyl inositol 3-kinase/AKT signaling pathway in breast cancer. Cancer Metastasis Rev. 2010;29:751–9.

    Article  CAS  PubMed  Google Scholar 

  16. Vitale SR, Martorana F, Stella S, Motta G, Inzerilli N, Massimino M, Tirrò E, Manzella L, Vigneri P. PI3K inhibition in breast cancer: Identifying and overcoming different flavors of resistance. Crit Rev Oncol Hematol. 2021;162: 103334.

    Article  PubMed  Google Scholar 

  17. Miricescu D, Totan A, Stanescu-Spinu I-I, Badoiu SC, Stefani C, Greabu M. PI3K/AKT/mTOR signaling pathway in breast cancer: from molecular landscape to clinical aspects. Int J Mol Sci. 2020;22:173.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Firoozinia M, Jahromi MZ, Moghadamtousi SZ, Nikzad S, Kadir HA. PIK3CA gene amplification and PI3K p110α protein expression in breast carcinoma. Int J Med Sci. 2014;11:620.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Yang L, Zhao S, Zhu T, Zhang J. GPRC5A is a negative regulator of the pro-survival PI3K/Akt signaling pathway in triple-negative breast cancer. Front Oncol. 2021;10: 624493.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Meng X, Hu B, Hossain MM, Chen G, Sun Y, Zhang X. ADAM17-siRNA inhibits MCF-7 breast cancer through EGFR-PI3K-AKT activation. Int J Oncol. 2016;49:682–90.

    Article  CAS  PubMed  Google Scholar 

  21. Drury S, Detre S, Leary A, Salter J, Reis-Filho J, Barbashina V, Marchio C, Lopez-Knowles E, Ghazoui Z, Habben K. Changes in breast cancer biomarkers in the IGF1R/PI3K pathway in recurrent breast cancer after tamoxifen treatment. Endocrine Related Cancer. 2011;18:565.

    Article  CAS  PubMed  Google Scholar 

  22. Fu X, Osborne CK, Schiff R. Biology and therapeutic potential of PI3K signaling in ER+/HER2-negative breast cancer. The Breast. 2013;22:S12–8.

    Article  PubMed  Google Scholar 

  23. Katan M, Cockcroft S. Phosphatidylinositol(4,5)bisphosphate: diverse functions at the plasma membrane. Essays Biochem. 2020;64:513–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Antal CE, Newton AC. Spatiotemporal dynamics of phosphorylation in lipid second messenger signaling. Mol Cell Proteomics. 2013;12:3498–508.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Fath MK, Ebrahimi M, Nourbakhsh E, Hazara AZ, Mirzaei A, Shafieyari S, Salehi A, Hoseinzadeh M, Payandeh Z, Barati G. PI3K/Akt/mTOR signaling pathway in cancer stem cells. Pathol Res Pract. 2022;237: 154010.

    Article  Google Scholar 

  26. Kizilboga T, Baskale EA, Yildiz J, Akcay IM, Zemheri E, Can ND, Ozden C, Demir S, Ezberci F, Dinler-Doganay G. Bag-1 stimulates Bad phosphorylation through activation of Akt and Raf kinases to mediate cell survival in breast cancer. BMC Cancer. 2019;19:1–13.

    Article  Google Scholar 

  27. Liu R, Chen Y, Liu G, Li C, Song Y, Cao Z, Li W, Hu J, Lu C, Liu Y. PI3K/AKT pathway as a key link modulates the multidrug resistance of cancers. Cell Death Dis. 2020;11:797.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Jiramongkol Y. Lam EW-F: FOXO transcription factor family in cancer and metastasis. Cancer Metastasis Rev. 2020;39:681–709.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Zeng CX, Fu SB, Feng WS, Zhao JY, Li FX, Gao P. TCF19 enhances cell proliferation in hepatocellular carcinoma by activating the ATK/FOXO1 signaling pathway. Neoplasma. 2019;66:46.

    Article  CAS  PubMed  Google Scholar 

  30. Thorpe LM, Yuzugullu H, Zhao JJ. PI3K in cancer: divergent roles of isoforms, modes of activation and therapeutic targeting. Nat Rev Cancer. 2015;15:7–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Tarighati E, Keivan H, Mahani H. A review of prognostic and predictive biomarkers in breast cancer. Clin Exp Med. 2023;23:1–16.

    CAS  PubMed  Google Scholar 

  32. O’Brien C, Wallin JJ, Sampath D, GuhaThakurta D, Savage H, Punnoose EA, Guan J, Berry L, Prior WW, Amler LC. Predictive biomarkers of sensitivity to the phosphatidylinositol 3′ kinase inhibitor GDC-0941 in breast cancer preclinical modelsPI3K inhibitor biomarkers in breast cancer models. Clin Cancer Res. 2010;16:3670–83.

    Article  CAS  PubMed  Google Scholar 

  33. Lee JJ, Loh K, Yap Y-S. PI3K/Akt/mTOR inhibitors in breast cancer. Cancer Biol Med. 2015;12:342.

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Li H, Prever L, Hirsch E, Gulluni F. Targeting PI3K/AKT/mTOR signaling pathway in breast cancer. Cancers. 2021;13:3517.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Huemer F, Bartsch R, Gnant M. The PI3K/AKT/MTOR signaling pathway: the role of PI3K and AKT inhibitors in breast cancer. Curr Breast Cancer Rep. 2014;6:59–70.

    Article  CAS  Google Scholar 

  36. Jenkins ML, Ranga-Prasad H, Parson MA, Harris NJ, Rathinaswamy MK, Burke JE. Oncogenic mutations of PIK3CA lead to increased membrane recruitment driven by reorientation of the ABD, p85 and C-terminus. Nat Commun. 2023;14:1–14.

    Article  Google Scholar 

  37. Hao Y, He B, Wu L, Li Y, Wang C, Wang T, Sun L, Zhang Y, Zhan Y, Zhao Y. Nuclear translocation of p85β promotes tumorigenesis of PIK3CA helical domain mutant cancer. Nat Commun. 1974;2022:13.

    Google Scholar 

  38. Fusco N, Malapelle U, Fassan M, Marchiò C, Buglioni S, Zupo S, Criscitiello C, Vigneri P, Dei Tos AP, Maiorano E, Viale G. PIK3CA mutations as a molecular target for hormone receptor-positive, HER2-negative metastatic breast cancer. Front Oncol. 2021;11: 644737.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Narayan P, Prowell TM, Gao JJ, Fernandes LL, Li E, Jiang X, Qiu J, Fan J, Song P, Yu J. FDA approval summary: alpelisib plus fulvestrant for patients with HR-positive, HER2-negative, PIK3CA-mutated, advanced or metastatic breast cancer. Clin Cancer Res. 2021;27:1842–9.

    Article  CAS  PubMed  Google Scholar 

  40. Sonnenblick A, Venet D, Brohée S, Pondé N, Sotiriou C. pAKT pathway activation is associated with PIK3CA mutations and good prognosis in luminal breast cancer in contrast to p-mTOR pathway activation. NPJ Breast Cancer. 2019;5:7.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Polo ML, Riggio M, May M, Rodríguez MJ, Perrone MC, Stallings-Mann M, Kaen D, Frost M, Goetz M, Boughey J. Activation of PI3K/Akt/mTOR signaling in the tumor stroma drives endocrine therapy-dependent breast tumor regression. Oncotarget. 2015;6:22081.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Mishra R, Patel H, Alanazi S, Kilroy MK, Garrett JT. PI3K inhibitors in cancer: clinical implications and adverse effects. Int J Mol Sci. 2021;22:3464.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Cescon DW, Bratman SV, Chan SM, Siu LL. Circulating tumor DNA and liquid biopsy in oncology. Nat Cancer. 2020;1:276–90.

    Article  CAS  PubMed  Google Scholar 

  44. Tellez-Gabriel M, Knutsen E, Perander M. Current status of circulating tumor cells, circulating tumor DNA, and exosomes in breast cancer liquid biopsies. Int J Mol Sci. 2020;21:9457.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Tzanikou E, Markou A, Politaki E, Koutsopoulos A, Psyrri A, Mavroudis D, Georgoulias V, Lianidou E. PIK 3 CA hotspot mutations in circulating tumor cells and paired circulating tumor DNA in breast cancer: a direct comparison study. Mol Oncol. 2019;13:2515–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Koo KM, Mainwaring PN. The role of circulating tumor DNA testing in breast cancer liquid biopsies: getting ready for prime time. Fut Med. 2020. https://doi.org/10.2217/bmt-2020-0003.

    Article  Google Scholar 

  47. Curtis C. Genomic profiling of breast cancers. Curr Opin Obstet Gynecol. 2015;27:34.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Yadollahi-Farsani M, Amini-Farsani Z, Moayedi F, Khazaei N, Yaghoobi H. MiR-548k suppresses apoptosis in breast cancer cells by affecting PTEN/PI3K/AKT signaling pathway. IUBMB Life. 2023;75:97–116.

    Article  CAS  PubMed  Google Scholar 

  49. Wang L-L, Hao S, Zhang S, Guo L-J, Hu C-Y, Zhang G, Gao B, Zhao J-J, Jiang Y, Tian W-G. PTEN/PI3K/AKT protein expression is related to clinicopathological features and prognosis in breast cancer with axillary lymph node metastases. Hum Pathol. 2017;61:49–57.

    Article  CAS  PubMed  Google Scholar 

  50. Dastmalchi N, Hosseinpourfeizi MA, Khojasteh SMB, Baradaran B, Safaralizadeh R. Tumor suppressive activity of miR-424-5p in breast cancer cells through targeting PD-L1 and modulating PTEN/PI3K/AKT/mTOR signaling pathway. Life Sci. 2020;259: 118239.

    Article  CAS  PubMed  Google Scholar 

  51. Zhang J, Li L, Peng Y, Chen Y, Lv X, Li S, Qin X, Yang H, Wu C, Liu Y. Surface chemistry induces mitochondria-mediated apoptosis of breast cancer cells via PTEN/PI3K/AKT signaling pathway. Biochimica et Biophysica Acta BBA Mol Cell Res. 2018;1865:172–85.

    Article  CAS  Google Scholar 

  52. Carnero A, Blanco-Aparicio C, Renner O, Link W, Leal JF. The PTEN/PI3K/AKT signalling pathway in cancer, therapeutic implications. Curr Cancer Drug Targets. 2008;8:187–98.

    Article  CAS  PubMed  Google Scholar 

  53. Tsai C-Y, Wu JC, Fang C, Chang AY. PTEN, a negative regulator of PI3K/Akt signaling, sustains brain stem cardiovascular regulation during mevinphos intoxication. Neuropharmacology. 2017;123:175–85.

    Article  CAS  PubMed  Google Scholar 

  54. Yan Y, Huang H. Interplay among PI3K/AKT, PTEN/FOXO and AR signaling in prostate cancer. Prostate Cancer. 2019;1210:319–31.

    Article  CAS  Google Scholar 

  55. Gao X, Qin T, Mao J, Zhang J, Fan S, Lu Y, Sun Z, Zhang Q, Song B, Li L. PTENP1/miR-20a/PTEN axis contributes to breast cancer progression by regulating PTEN via PI3K/AKT pathway. J Exp Clin Cancer Res. 2019;38:256.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Shariati M, Evans KW, Zheng X, Bristow CA, Ng PK-S, Rizvi YQ, Tapia C, Yang F, Carugo A, Heffernan TP. Combined inhibition of DDR1 and CDK4/6 induces synergistic effects in ER-positive, HER2-negative breast cancer with PIK3CA/AKT1 mutations. Oncogene. 2021;40:4425–39.

    Article  CAS  PubMed  Google Scholar 

  57. Tserga A, Chatziandreou I, Michalopoulos NV, Patsouris E, Saetta AA. Mutation of genes of the PI3K/AKT pathway in breast cancer supports their potential importance as biomarker for breast cancer aggressiveness. Virchows Arch. 2016;469:35–43.

    Article  CAS  PubMed  Google Scholar 

  58. Dillon LM, Miller TW. Therapeutic targeting of cancers with loss of PTEN function. Curr Drug Targets. 2014;15:65–79.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Smyth LM, Zhou Q, Nguyen B, Yu C, Lepisto EM, Arnedos M, Hasset MJ, Lenoue-Newton ML, Blauvelt N, Dogan S, et al. Characteristics and outcome of AKT1E17K-mutant breast cancer defined through AACR Project GENIE, a clinicogenomic registry. Cancer Discov. 2020;10:526–35.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Rudolph M, Anzeneder T, Schulz A, Beckmann G, Byrne AT, Jeffers M, Pena C, Politz O, Köchert K, Vonk R, Reischl J. AKT1E17K mutation profiling in breast cancer: prevalence, concurrent oncogenic alterations, and blood-based detection. BMC Cancer. 2016;16:622.

    Article  PubMed  PubMed Central  Google Scholar 

  61. Chen Y, Huang L, Dong Y, Tao C, Zhang R, Shao H, Shen H. Effect of AKT1 (p. E17K) hotspot mutation on malignant tumorigenesis and prognosis. Front Cell Dev Biol. 2020;8: 573599.

    Article  PubMed  PubMed Central  Google Scholar 

  62. Shimoi T, Hashimoto J, Sudo K, Shimomura A, Noguchi E, Shimizu C, Yunokawa M, Yonemori K, Yoshida H, Yoshida M, et al. Hotspot mutation profiles of AKT1 in Asian women with breast and endometrial cancers. BMC Cancer. 2021;21:1131.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Hyman DM, Smyth LM, Donoghue MT, Westin SN, Bedard PL, Dean EJ, Bando H, El-Khoueiry AB, Pérez-Fidalgo JA, Mita A. AKT inhibition in solid tumors with AKT1 mutations. J Clin Oncol. 2017;35:2251.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Holmes D. PI3K pathway inhibitors approach junction. Nat Rev Drug Discovery. 2011;10:563.

    Article  CAS  PubMed  Google Scholar 

  65. Cizkova M, Vacher S, Meseure D, Trassard M, Susini A, Mlcuchova D, Callens C, Rouleau E, Spyratos F, Lidereau R, Bièche I. PIK3R1 underexpression is an independent prognostic marker in breast cancer. BMC Cancer. 2013;13:545.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Chen L, Yang L, Yao L, Kuang X-Y, Zuo W-J, Li S, Qiao F, Liu Y-R, Cao Z-G, Zhou S-L. Characterization of PIK3CA and PIK3R1 somatic mutations in Chinese breast cancer patients. Nat Commun. 2018;9:1357.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Turturro SB, Najor MS, Yung T, Portt L, Malarkey CS, Abukhdeir AM, Cobleigh MA. Somatic loss of PIK3R1 may sensitize breast cancer to inhibitors of the MAPK pathway. Breast Cancer Res Treat. 2019;177:325–33.

    Article  CAS  PubMed  Google Scholar 

  68. Nunnery SE, Mayer IA. Targeting the PI3K/AKT/mTOR pathway in hormone-positive breast cancer. Drugs. 2020;80:1685–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Liu H, Paddock MN, Wang H, Murphy CJ, Geck RC, Navarro AJ, Wulf GM, Elemento O, Haucke V, Cantley LC, Toker A. The INPP4B tumor suppressor modulates EGFR trafficking and promotes triple-negative breast cancer. Cancer Discov. 2020;10:1226–39.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Rodgers SJ, Ooms LM, Oorschot VM, Schittenhelm RB, Nguyen EV, Hamila SA, Rynkiewicz N, Gurung R, Eramo MJ, Sriratana A. INPP4B promotes PI3Kα-dependent late endosome formation and Wnt/β-catenin signaling in breast cancer. Nat Commun. 2021;12:3140.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Sueta A, Yamamoto Y, Yamamoto-Ibusuki M, Hayashi M, Takeshita T, Yamamoto S, Iwase H. An integrative analysis of PIK3CA mutation, PTEN, and INPP4B expression in terms of trastuzumab efficacy in HER2-positive breast cancer. PLoS ONE. 2014;9: e116054.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Kwon MJ. Predictive biomarkers for molecularly targeted therapies and immunotherapies in breast cancer. Arch Pharmacal Res. 2022;45:597–617.

    Article  CAS  Google Scholar 

  73. Ku AT, Young AI, Ibrahim AA, Bu W, Jiang W, Lin M, Williams LC, McCue BL, Miles G, Nagi C. Short-term PI3K inhibition prevents breast cancer in preclinical models. Cancer Prev Res. 2023;16:65–73.

    Article  CAS  Google Scholar 

  74. O’Brien NA, McDermott MSJ, Conklin D, Luo T, Ayala R, Salgar S, Chau K, DiTomaso E, Babbar N, Su F, et al. Targeting activated PI3K/mTOR signaling overcomes acquired resistance to CDK4/6-based therapies in preclinical models of hormone receptor-positive breast cancer. Breast Cancer Res. 2020;22:89.

    Article  PubMed  PubMed Central  Google Scholar 

  75. Keydar I, Chen L, Karby S, Weiss FR, Delarea J, Radu M, Chaitcik S, Brenner HJ. Establishment and characterization of a cell line of human breast carcinoma origin. Eur J Cancer. 1965;1979(15):659–70.

    Google Scholar 

  76. Zhuang Y, Grainger JM, Vedell PT, Yu J, Moyer AM, Gao H, Fan XY, Qin S, Liu D, Kalari KR, et al. Establishment and characterization of immortalized human breast cancer cell lines from breast cancer patient-derived xenografts (PDX). NPJ Breast Cancer. 2021;7:79.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Miao X, Hu J, Chai C, Tang H, Zhao Z, Luo W, Zhou W, Xu H. Establishment and characterization of a new intrahepatic cholangiocarcinoma cell line derived from a Chinese patient. Cancer Cell Int. 2022;22:418.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Kumar R, Agrawal U, Deo S, Mathur S, Gogia A, Tanwar P. Comprehensive mutation profiling of PIK3CA gene in Indian breast cancer patients. Eur J Cancer. 2022;175:S33.

    Article  CAS  Google Scholar 

  79. Reinhardt K, Stückrath K, Hartung C, Kaufhold S, Uleer C, Hanf V, Lantzsch T, Peschel S, John J, Pöhler M. PIK3CA-mutations in breast cancer. Breast Cancer Res Treat. 2022;196(3):483–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Piombino C, Cortesi L. Insights into the possible molecular mechanisms of resistance to PARP inhibitors. Cancers. 2022;14:2804.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Kara G, Calin GA, Ozpolat B. RNAi-based therapeutics and tumor targeted delivery in cancer. Adv Drug Deliv Rev. 2022;182: 114113.

    Article  CAS  PubMed  Google Scholar 

  82. Selvakumar SC, Preethi KA, Ross K, Tusubira D, Khan MWA, Mani P, Rao TN, Sekar D. CRISPR/Cas9 and next generation sequencing in the personalized treatment of cancer. Mol Cancer. 2022;21:83.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Vaghari-Tabari M, Hassanpour P, Sadeghsoltani F, Malakoti F, Alemi F, Qujeq D, Asemi Z, Yousefi B. CRISPR/Cas9 gene editing: a new approach for overcoming drug resistance in cancer. Cell Mol Biol Lett. 2022;27:1–29.

    Article  Google Scholar 

  84. Eskiler GG, Ozturk M. Therapeutic potential of the PI3K inhibitor LY294002 and PARP inhibitor Talazoparib combination in BRCA-deficient triple negative breast cancer cells. Cell Signal. 2022;91: 110229.

    Article  Google Scholar 

  85. Fuso P, Muratore M, D’Angelo T, Paris I, Carbognin L, Tiberi G, Pavese F, Duranti S, Orlandi A, Tortora G, et al. PI3K inhibitors in advanced breast cancer: the past, the present, new challenges and future perspectives. Cancers. 2022;14:2161.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Coussy F, Lavigne M, De Koning L, El Botty R, Nemati F, Naguez A, Bataillon G, Ouine B, Dahmani A, Montaudon E. Response to mTOR and PI3K inhibitors in enzalutamide-resistant luminal androgen receptor triple-negative breast cancer patient-derived xenografts. Theranostics. 2020;10:1531.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Holen I, Speirs V, Morrissey B, Blyth K. In vivo models in breast cancer research: progress, challenges and future directions. Dis Model Mech. 2017;10:359–71.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Yoshida GJ. Applications of patient-derived tumor xenograft models and tumor organoids. J Hematol Oncol. 2020;13:4.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Zou Y, Ye F, Kong Y, Hu X, Deng X, Xie J, Song C, Ou X, Wu S, Wu L. The single-cell landscape of intratumoral heterogeneity and the immunosuppressive microenvironment in liver and brain metastases of breast cancer. Adv Sci. 2023;10:2203699.

    Article  CAS  Google Scholar 

  90. Zhao N, Rosen JM. Breast cancer heterogeneity through the lens of single-cell analysis and spatial pathologies. Semin Cancer Biol. 2022;82:3–10.

    Article  CAS  PubMed  Google Scholar 

  91. Sharma MC, Jain D. Important role of annexin A2 (ANXA2) in new blood vessel development in vivo and human triple negative breast cancer (TNBC) growth. Exp Mol Pathol. 2020;116: 104523.

    Article  CAS  PubMed  Google Scholar 

  92. Mundt F, Rajput S, Li S, Ruggles KV, Mooradian AD, Mertins P, Gillette MA, Krug K, Guo Z, Hoog J. Mass spectrometry-based proteomics reveals potential roles of NEK9 and MAP2K4 in resistance to PI3K inhibition in triple-negative breast cancersproteomic profiling of PI3K inhibitor resistance. Can Res. 2018;78:2732–46.

    Article  CAS  Google Scholar 

  93. Guo Z, Primeau T, Luo J, Zhang C, Sun H, Hoog J, Gao F, Huang S, Edwards DP, Davies SR. Proteomic resistance biomarkers for PI3K inhibitor in triple negative breast cancer patient-derived xenograft models. Cancers. 2020;12:3857.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Klarenbeek S, van Miltenburg MH, Jonkers J. Genetically engineered mouse models of PI3K signaling in breast cancer. Mol Oncol. 2013;7:146–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Walrath JC, Hawes JJ, Van Dyke T, Reilly KM. Genetically engineered mouse models in cancer research. Adv Cancer Res. 2010;106:113–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Bos PD, Nguyen DX, Massagué J. Modeling metastasis in the mouse. Curr Opin Pharmacol. 2010;10:571–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Singh M, Murriel CL, Johnson L. Genetically engineered mouse models: closing the gap between preclinical data and trial outcomes translating preclinical trials into prediction. Can Res. 2012;72:2695–700.

    Article  CAS  Google Scholar 

  98. Creedon H, Balderstone LA, Muir M, Balla J, Gomez-Cuadrado L, Tracey N, Loane J, Klinowska T, Muller WJ, Brunton VG. Use of a genetically engineered mouse model as a preclinical tool for HER2 breast cancer. Dis Model Mech. 2016;9:131–40.

    CAS  PubMed  PubMed Central  Google Scholar 

  99. Chang JC, Wooten EC, Tsimelzon A, Hilsenbeck SG, Gutierrez MC, Elledge R, Mohsin S, Osborne CK, Chamness GC, Allred DC, O’Connell P. Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. The Lancet. 2003;362:362–9.

    Article  CAS  Google Scholar 

  100. van t’Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AAM, Mao M, Peterse HL, van der Kooy K, Marton MJ, Witteveen AT, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415:530–6.

    Article  PubMed  Google Scholar 

  101. Guillen KP, Fujita M, Butterfield AJ, Scherer SD, Bailey MH, Chu Z, DeRose YS, Zhao L, Cortes-Sanchez E, Yang C-H, et al. A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology. Nat Cancer. 2022;3:232–50.

    Article  PubMed  PubMed Central  Google Scholar 

  102. Yuki K, Cheng N, Nakano M, Kuo CJ. Organoid models of tumor immunology. Trends Immunol. 2020;41:652–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Li W, Zhou Z, Zhou X, Khoo BL, Gunawan R, Chin YR, Zhang L, Yi C, Guan X, Yang M. 3D biomimetic models to reconstitute tumor microenvironment in vitro: spheroids, organoids, and tumor-on-a-Chip. Adv Healthc Mater. 2023;12:2202609.

    Article  CAS  Google Scholar 

  104. Gunti S, Hoke AT, Vu KP, London NR Jr. Organoid and spheroid tumor models: techniques and applications. Cancers. 2021;13:874.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  105. Phan N, Hong JJ, Tofig B, Mapua M, Elashoff D, Moatamed NA, Huang J, Memarzadeh S, Damoiseaux R, Soragni A. A simple high-throughput approach identifies actionable drug sensitivities in patient-derived tumor organoids. Commun Biol. 2019;2:78.

    Article  PubMed  PubMed Central  Google Scholar 

  106. Li L, Zhou Q, Voss TC, Quick KL, LaBarbera DV. High-throughput imaging: focusing in on drug discovery in 3D. Methods. 2016;96:97–102.

    Article  CAS  PubMed  Google Scholar 

  107. Dekkers JF, van Vliet EJ, Sachs N, Rosenbluth JM, Kopper O, Rebel HG, Wehrens EJ, Piani C, Visvader JE, Verissimo CS. Long-term culture, genetic manipulation and xenotransplantation of human normal and breast cancer organoids. Nat Protoc. 2021;16:1936–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Heneweer M, Muusse M, Dingemans M, de Jong PC, van den Berg M, Sanderson JT. Co-culture of primary human mammary fibroblasts and MCF-7 cells as an in vitro breast cancer model. Toxicol Sci. 2005;83:257–63.

    Article  CAS  PubMed  Google Scholar 

  109. De Ninno A, Bertani FR, Gerardino A, Schiavoni G, Musella M, Galassi C, Mattei F, Sistigu A, Businaro L. Microfluidic co-culture models for dissecting the immune response in in vitro tumor microenvironments. J Vis Exp. 2021. https://doi.org/10.3791/61895.

    Article  PubMed  Google Scholar 

  110. Campbell LL, Polyak K. Breast tumor heterogeneity: cancer stem cells or clonal evolution? Cell Cycle. 2007;6:2332–8.

    Article  CAS  PubMed  Google Scholar 

  111. Arrigoni C, De Luca P, Gilardi M, Previdi S, Broggini M, Moretti M. Direct but not indirect co-culture with osteogenically differentiated human bone marrow stromal cells increases RANKL/OPG ratio in human breast cancer cells generating bone metastases. Mol Cancer. 2014;13:1–6.

    Article  CAS  Google Scholar 

  112. Usman MW, Gao J, Zheng T, Rui C, Li T, Bian X, Cheng H, Liu P, Luo F. Macrophages confer resistance to PI3K inhibitor GDC-0941 in breast cancer through the activation of NF-κB signaling. Cell Death Dis. 2018;9:809.

    Article  PubMed  PubMed Central  Google Scholar 

  113. Tokunaga E, Kimura Y, Mashino K, Oki E, Kataoka A, Ohno S, Morita M, Kakeji Y, Baba H, Maehara Y. Activation of PI3K/Akt signaling and hormone resistance in breast cancer. Breast Cancer. 2006;13:137–44.

    Article  PubMed  Google Scholar 

  114. Jin X, Wang D, Lei M, Guo Y, Cui Y, Chen F, Sun W, Chen X. TPI1 activates the PI3K/AKT/mTOR signaling pathway to induce breast cancer progression by stabilizing CDCA5. J Transl Med. 2022;20:1–20.

    Article  Google Scholar 

  115. Zhu K, Wu Y, He P, Fan Y, Zhong X, Zheng H, Luo T. PI3K/AKT/mTOR-targeted therapy for breast cancer. Cells. 2022;11:2508.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Ellis H, Ma CX. PI3K inhibitors in breast cancer therapy. Curr Oncol Rep. 2019;21:1–9.

    Article  Google Scholar 

  117. Verret B, Cortes J, Bachelot T, Andre F, Arnedos M. Efficacy of PI3K inhibitors in advanced breast cancer. Ann Oncol. 2019;30:x12–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Alzahrani AS. PI3K/Akt/mTOR inhibitors in cancer: at the bench and bedside. Semin Cancer Biol. 2019;59:125–32.

    Article  CAS  PubMed  Google Scholar 

  119. Bruning PF, Bonfrèr JM, van Noord PA, Hart AA, de Jong-Bakker M, Nooijen WJ. Insulin resistance and breast-cancer risk. Int J Cancer. 1992;52:511–6.

    Article  CAS  PubMed  Google Scholar 

  120. Rogers LQ, Fogleman A, Trammell R, Hopkins-Price P, Vicari S, Rao K, Edson B, Verhulst S, Courneya KS, Hoelzer K. Effects of a physical activity behavior change intervention on inflammation and related health outcomes in breast cancer survivors: pilot randomized trial. Integr Cancer Ther. 2013;12:323–35.

    Article  CAS  PubMed  Google Scholar 

  121. Cava E, Marzullo P, Farinelli D, Gennari A, Saggia C, Riso S, Prodam F. Breast cancer diet “BCD”: a review of healthy dietary patterns to prevent breast cancer recurrence and reduce mortality. Nutrients. 2022;14:476.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  122. Rakhmanovna PO. Nutrition and diet in breast cancer. Texas Journal of Medical Science. 2022;7:27–30.

    Google Scholar 

  123. Das S, Kulkarni S, Singh Y, Kumar P, Thareja S. Selective estrogen receptor modulators (SERMs) for the treatment of ER+ breast cancer: an overview. J Mol Struct. 2022;1270: 133853.

    Article  CAS  Google Scholar 

  124. Das A, Lavanya KJ, Kaur K, Jaitak V. Effectiveness of selective estrogen receptor modulators in breast cancer therapy: an update. Curr Med Chem. 2023;30:3287.

    Article  CAS  PubMed  Google Scholar 

  125. Serra V, Scaltriti M, Prudkin L, Eichhorn PJA, Ibrahim YH, Chandarlapaty S, Markman B, Rodriguez O, Guzman M, Rodriguez S, et al. PI3K inhibition results in enhanced HER signaling and acquired ERK dependency in HER2-overexpressing breast cancer. Oncogene. 2011;30:2547–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  126. Zhang Z, Richmond A, Yan C. Immunomodulatory properties of PI3K/AKT/mTOR and MAPK/MEK/ERK inhibition augment response to immune checkpoint blockade in melanoma and triple-negative breast cancer. Int J Mol Sci. 2022;23:7353.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. Zhang L, Ruan X, Gu M, Mueck A. E2+ norethisterone promotes the PI3K–AKT pathway via PGRMC1 to induce breast cancer cell proliferation. Climacteric. 2022;25:467–75.

    Article  CAS  PubMed  Google Scholar 

  128. Li L, Wei D, Zhang J, Deng R, Tang J, Su D. miR-641 inhibited cell proliferation and induced apoptosis by targeting NUCKS1/PI3K/AKT signaling pathway in breast cancer. Comput Math Methods Med. 2022;2022:1–18.

    Google Scholar 

  129. Wu D, Jia H, Zhang Z, Li S. Capsaicin suppresses breast cancer cell viability by regulating the CDK8/PI3K/Akt/Wnt/β-catenin signaling pathway. Mol Med Rep. 2020;22:4868–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Fultang N, Illendula A, Chen B, Wu C, Jonnalagadda S, Baird N, Klase Z, Peethambaran B. Strictinin, a novel ROR1-inhibitor, represses triple negative breast cancer survival and migration via modulation of PI3K/AKT/GSK3ß activity. PLoS ONE. 2019;14: e0217789.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Hoxhaj G, Manning BD. The PI3K–AKT network at the interface of oncogenic signalling and cancer metabolism. Nat Rev Cancer. 2020;20:74–88.

    Article  CAS  PubMed  Google Scholar 

  132. Khan MA, Jain VK, Rizwanullah M, Ahmad J, Jain K. PI3K/AKT/mTOR pathway inhibitors in triple-negative breast cancer: a review on drug discovery and future challenges. Drug Discov Today. 2019;24:2181–91.

    Article  CAS  PubMed  Google Scholar 

  133. Gallagher EJ, Fierz Y, Vijayakumar A, Haddad N, Yakar S, LeRoith D. Inhibiting PI3K reduces mammary tumor growth and induces hyperglycemia in a mouse model of insulin resistance and hyperinsulinemia. Oncogene. 2012;31:3213–22.

    Article  CAS  PubMed  Google Scholar 

  134. Vanhaesebroeck B, Perry MW, Brown JR, André F, Okkenhaug K. PI3K inhibitors are finally coming of age. Nat Rev Drug Discov. 2021;20:741–69.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. De P, Aske JC, Williams C, Dey N, Leyland-Jones B. PI3Kα/δ inhibitor, copanlisib is highly effective in ER-positive breast cancer. Can Res. 2019;79:3438–3438.

    Article  Google Scholar 

  136. Xu S, Sun X, Luo L, Yang Y, Guo Q, Tang S, Jiang Z, Li Y, Han J, Gan W. XS-2, a novel potent dual PI3K/mTOR inhibitor, exhibits high in vitro and in vivo anti-breast cancer activity and low toxicity with the potential to inhibit the invasion and migration of triple-negative breast cancer. Biomed Pharmacother. 2022;155: 113537.

    Article  CAS  PubMed  Google Scholar 

  137. Sharma V, Sharma AK, Punj V, Priya P. Recent nanotechnological interventions targeting PI3K/Akt/mTOR pathway: a focus on breast cancer. Semin Cancer Biol. 2019;59:133–46.

    Article  CAS  PubMed  Google Scholar 

  138. Kaboli PJ, Imani S, Jomhori M, Ling K-H. Chemoresistance in breast cancer: PI3K/Akt pathway inhibitors vs the current chemotherapy. Am J Cancer Res. 2021;11:5155.

    CAS  PubMed  PubMed Central  Google Scholar 

  139. Araki K, Miyoshi Y. Mechanism of resistance to endocrine therapy in breast cancer: the important role of PI3K/Akt/mTOR in estrogen receptor-positive, HER2-negative breast cancer. Breast Cancer. 2018;25:392–401.

    Article  PubMed  Google Scholar 

  140. Gonzalez-Angulo A, Blumenschein G Jr. Defining biomarkers to predict sensitivity to PI3K/Akt/mTOR pathway inhibitors in breast cancer. Cancer Treat Rev. 2013;39:313–20.

    Article  CAS  PubMed  Google Scholar 

  141. VanLandingham NK, Nazarenko A, Grandis JR, Johnson DE. The mutational profiles and corresponding therapeutic implications of PI3K mutations in cancer. Adv Biol Regulat. 2022;87: 100934.

    Article  Google Scholar 

  142. Qin H, Liu L, Sun S, Zhang D, Sheng J, Li B, Yang W. The impact of PI3K inhibitors on breast cancer cell and its tumor microenvironment. PeerJ. 2018;6: e5092.

    Article  PubMed  PubMed Central  Google Scholar 

  143. Vasan N, Toska E, Scaltriti M. Overview of the relevance of PI3K pathway in HR-positive breast cancer. Ann Oncol. 2019;30:x3–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  144. McNamara CR, Degterev A. Small-molecule inhibitors of the PI3K signaling network. Future Med Chem. 2011;3:549–65.

    Article  CAS  PubMed  Google Scholar 

  145. Zuo Y, Zhang C-Z, Ren Q, Chen Y, Li X, Yang J-R, Li H-X, Tang W-T, Hing-Man H, Sun C. Activation of mitochondrial-associated apoptosis signaling pathway and inhibition of PI3K/Akt/mTOR signaling pathway by voacamine suppress breast cancer progression. Phytomedicine. 2022;99: 154015.

    Article  CAS  PubMed  Google Scholar 

  146. Abdallah ME, El-Readi MZ, Althubiti MA, Almaimani RA, Ismail AM, Idris S, Refaat B, Almalki WH, Babakr AT, Mukhtar MH. Tamoxifen and the PI3K inhibitor: LY294002 synergistically induce apoptosis and cell cycle arrest in breast cancer MCF-7 cells. Molecules. 2020;25:3355.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. Brachmann SM, Hofmann I, Schnell C, Fritsch C, Wee S, Lane H, Wang S, Garcia-Echeverria C, Maira S-M. Specific apoptosis induction by the dual PI3K/mTor inhibitor NVP-BEZ235 in HER2 amplified and PIK3CA mutant breast cancer cells. Proc Natl Acad Sci. 2009;106:22299–304.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  148. Clark AS, Makhlin I, DeMichele A. Setting the pick: can PI3K inhibitors circumvent CDK4/6 inhibitor resistance? PI3K Inhibitors+/− CDK 4/6 inhibitors in breast cancer. Clin Cancer Res. 2021;27:371–3.

    Article  CAS  PubMed  Google Scholar 

  149. Berrak Ö, Akkoç Y, Arısan ED, Çoker-Gürkan A, Obakan-Yerlikaya P, Palavan-Ünsal N. The inhibition of PI3K and NFκB promoted curcumin-induced cell cycle arrest at G2/M via altering polyamine metabolism in Bcl-2 overexpressing MCF-7 breast cancer cells. Biomed Pharmacother. 2016;77:150–60.

    Article  CAS  PubMed  Google Scholar 

  150. Crawford A, Nahta R. Targeting Bcl-2 in herceptin-resistant breast cancer cell lines. Curr Pharmacogenom. 2011;9:184–90.

    CAS  Google Scholar 

  151. Tao Q, Qi Y, Gu J, Yu D, Lu Y, Liu J, Liang X. Breast cancer cells-derived Von Willebrand Factor promotes VEGF-A-related angiogenesis through PI3K/Akt-miR-205-5p signaling pathway. Toxicol Appl Pharmacol. 2022;440: 115927.

    Article  CAS  PubMed  Google Scholar 

  152. Safdari Y, Khalili M, Ebrahimzadeh MA, Yazdani Y, Farajnia S. Natural inhibitors of PI3K/AKT signaling in breast cancer: Emphasis on newly-discovered molecular mechanisms of action. Pharmacol Res. 2015;93:1–10.

    Article  CAS  PubMed  Google Scholar 

  153. Chen L, Wang J, Wang B, Yang J, Gong Z, Zhao X, Zhang C, Du K. MiR-126 inhibits vascular endothelial cell apoptosis through targeting PI3K/Akt signaling. Ann Hematol. 2016;95:365–74.

    Article  CAS  PubMed  Google Scholar 

  154. Elgene Lim M, Metzger-Filho O, Winer EP. The natural history of hormone receptor-positive breast cancer. Oncology. 2012;26:688.

    PubMed  Google Scholar 

  155. Viedma-Rodríguez R, Baiza-Gutman L, Salamanca-Gómez F, Diaz-Zaragoza M, Martínez-Hernández G, Ruiz Esparza-Garrido R, Velázquez-Flores MA, Arenas-Aranda D. Mechanisms associated with resistance to tamoxifen in estrogen receptor-positive breast cancer. Oncol Rep. 2014;32:3–15.

    Article  PubMed  Google Scholar 

  156. Maharaj K, Powers JJ, Achille A, Mediavilla-Varela M, Gamal W, Burger KL, Fonseca R, Jiang K, Miskin HP, Maryanski D. The dual PI3Kδ/CK1ε inhibitor umbralisib exhibits unique immunomodulatory effects on CLL T cells. Blood Adv. 2020;4:3072–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Pompura SL, Dominguez-Villar M. The PI3K/AKT signaling pathway in regulatory T-cell development, stability, and function. J Leukoc Biol. 2018;103:1065–76.

    Article  CAS  Google Scholar 

  158. Tarantelli C, Argnani L, Zinzani PL, Bertoni F. PI3Kδ inhibitors as immunomodulatory agents for the treatment of lymphoma patients. Cancers (Basel). 2021;13:5535.

    Article  CAS  PubMed  Google Scholar 

  159. Abu-Eid R, Samara RN, Ozbun L, Abdalla MY, Berzofsky JA, Friedman KM, Mkrtichyan M, Khleif SN. Selective inhibition of regulatory T cells by targeting the PI3K–Akt pathway. Cancer Immunol Res. 2014;2:1080–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Curnock AP, Logan MK, Ward SG. Chemokine signalling: pivoting around multiple phosphoinositide 3-kinases. Immunology. 2002;105:125–36.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  161. Sotgia F, Martinez-Outschoorn UE, Pavlides S, Howell A, Pestell RG, Lisanti MP. Understanding the Warburg effect and the prognostic value of stromal caveolin-1 as a marker of a lethal tumor microenvironment. Breast Cancer Res. 2011;13:213.

    Article  PubMed  PubMed Central  Google Scholar 

  162. Liu S, Li Y, Yuan M, Song Q, Liu M. Correlation between the Warburg effect and progression of triple-negative breast cancer. Front Oncol. 2023;12:1060495.

    Article  PubMed  PubMed Central  Google Scholar 

  163. Zhang Z, Richmond A. The role of PI3K Inhibition in the treatment of breast cancer, alone or combined with immune checkpoint inhibitors. Front Mol Biosci. 2021;8: 648663.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  164. Fillbrunn M, Signorovitch J, André F, Wang I, Lorenzo I, Ridolfi A, Park J, Dua A, Rugo HS. PIK3CA mutation status, progression and survival in advanced HR + /HER2- breast cancer: a meta-analysis of published clinical trials. BMC Cancer. 2022;22:1002.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  165. Zardavas D, Phillips WA, Loi S. PIK3CA mutations in breast cancer: reconciling findings from preclinical and clinical data. Breast Cancer Res. 2014;16:201.

    Article  PubMed  PubMed Central  Google Scholar 

  166. Wang L, Zhang S, Wang X. The metabolic mechanisms of breast cancer metastasis. Front Oncol. 2021;10: 602416.

    Article  PubMed  PubMed Central  Google Scholar 

  167. Yang J, Nie J, Ma X, Wei Y, Peng Y, Wei X. Targeting PI3K in cancer: mechanisms and advances in clinical trials. Mol Cancer. 2019;18:26.

    Article  PubMed  PubMed Central  Google Scholar 

  168. Fritsch C, Huang A, Chatenay-Rivauday C, Schnell C, Reddy A, Liu M, Kauffmann A, Guthy D, Erdmann D, De Pover A, et al. Characterization of the novel and specific PI3Kα inhibitor NVP-BYL719 and development of the patient stratification strategy for clinical trials. Mol Cancer Ther. 2014;13:1117–29.

    Article  CAS  PubMed  Google Scholar 

  169. Ferreira-Gonzalez A. Plasma PIK3CA mutation testing in advanced breast cancer patients for personalized medicine: a value proposition. J Appl Lab Med. 2020;5:1076–89.

    Article  PubMed  Google Scholar 

  170. Yu Y, Xie Z, Zhao M, Lian X. Identification of PIK3CA multigene mutation patterns associated with superior prognosis in stomach cancer. BMC Cancer. 2021;21:368.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  171. Zhang M, Jang H, Nussinov R. PI3K inhibitors: review and new strategies. Chem Sci. 2020;11:5855–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  172. Dawood S, Konstantionva M, Dent R, Perazzo F, Kim S-B, Villarreal-Garza C, Franco S, Dai M-S, Simon S. Optimizing treatment selection, and sequencing decisions for Management of HR-Positive, HER2-Negative advanced breast cancer – Proceedings from breast cancer expert group meeting. BMC Proc. 2021;15:15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Varkaris A, Fece de la Cruz F, Martin EE, Norden BL, Chevalier N, Kehlmann AM, Leshchiner I, Barnes H, Ehnstrom S, Stavridi A-M, et al. Allosteric PI3K-alpha inhibition overcomes on-target resistance to orthosteric inhibitors mediated by secondary PIK3CA mutations. Cancer Discov. 2023. https://doi.org/10.1158/2159-8290.CD-23-0704.

    Article  PubMed  Google Scholar 

  174. Drullinsky PR, Hurvitz SA. Mechanistic basis for PI3K inhibitor antitumor activity and adverse reactions in advanced breast cancer. Breast Cancer Res Treat. 2020;181:233–48.

    Article  CAS  PubMed  Google Scholar 

  175. Moestue SA, Dam CG, Gorad SS, Kristian A, Bofin A, Mælandsmo GM, Engebråten O, Gribbestad IS, Bjørkøy G. Metabolic biomarkers for response to PI3K inhibition in basal-like breast cancer. Breast Cancer Res. 2013;15:R16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  176. Li CI, Malone KE, Daling JR. Differences in breast cancer stage, treatment, and survival by race and ethnicity. Arch Intern Med. 2003;163:49–56.

    Article  PubMed  Google Scholar 

  177. Wang J, Zhang Y, Xiao Y, Yuan X, Li P, Wang X, Duan Y, Seewaldt VL, Yu D. Boosting immune surveillance by low-dose PI3K inhibitor facilitates early intervention of breast cancer. Am J Cancer Res. 2005;2021:11.

    Google Scholar 

  178. Sledge GW Jr. Adjuvant therapy for early stage breast cancer. Semin Oncol. 1996;23:51–4.

    CAS  PubMed  Google Scholar 

  179. Stravodimou A, Voutsadakis IA. The future of ER+/HER2− metastatic breast cancer therapy: beyond PI3K Inhibitors. Anticancer Res. 2020;40:4829–41.

    Article  CAS  PubMed  Google Scholar 

  180. Testa U, Castelli G, Pelosi E. Breast cancer: a molecularly heterogenous disease needing subtype-specific treatments. Med Sci. 2020;8:18.

    CAS  Google Scholar 

  181. Davis AA, Luo J, Zheng T, Dai C, Dong X, Tan L, Suresh R, Ademuyiwa FO, Rigden C, Rearden TP. Genomic complexity predicts resistance to endocrine therapy and CDK4/6 inhibition in hormone receptor-positive (HR+)/HER2-negative metastatic breast cancer. Clin Cancer Res. 2023;29:1719–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Jusino S, Fadul CE, Dillon P. Systematic review of the management of brain metastases from hormone receptor positive breast cancer. J Neurooncol. 2023;162:45–57.

    Article  PubMed  PubMed Central  Google Scholar 

  183. Swain SM, Shastry M, Hamilton E. Targeting HER2-positive breast cancer: advances and future directions. Nat Rev Drug Discov. 2023;22:101–26.

    Article  CAS  PubMed  Google Scholar 

  184. Nader-Marta G, Martins-Branco D, De Azambuja E. How we treat patients with metastatic HER2-positive breast cancer. ESMO open. 2022;7: 100343.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  185. Kumar H, Gupta NV, Jain R, Madhunapantula SV, Babu CS, Kesharwani SS, Dey S, Jain V. A review of biological targets and therapeutic approaches in the management of triple-negative breast cancer. J Adv Res. 2023. https://doi.org/10.1016/j.jare.2023.02.005.

    Article  PubMed  PubMed Central  Google Scholar 

  186. Loizides S, Constantinidou A. Triple negative breast cancer: immunogenicity, tumor microenvironment, and immunotherapy. Front Genet. 2023;13:1095839.

    Article  PubMed  PubMed Central  Google Scholar 

  187. Ji Y, Whitney HM, Li H, Liu P, Giger ML, Zhang X. Differences in molecular subtype reference standards impact AI-based breast cancer classification with dynamic contrast-enhanced MRI. Radiology. 2023;307: 220984.

    Article  Google Scholar 

  188. Zhang X. Molecular classification of breast cancer: relevance and challenges. Arch Pathol Lab Med. 2023;147:46–51.

    Article  PubMed  Google Scholar 

  189. Zhao S, Zuo W-J, Shao Z-M, Jiang Y-Z. Molecular subtypes and precision treatment of triple-negative breast cancer. Ann Transl Med. 2020;8:499.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  190. Schwartzberg LS, Vidal GA. Targeting PIK3CA alterations in hormone receptor-positive, human epidermal growth factor receptor-2–negative advanced breast cancer: new therapeutic approaches and practical considerations. Clin Breast Cancer. 2020;20:e439–49.

    Article  CAS  PubMed  Google Scholar 

  191. Miranda F, Prazeres H, Mendes F, Martins D, Schmitt F. Resistance to endocrine therapy in HR+ and/or HER2+ breast cancer: the most promising predictive biomarkers. Mol Biol Rep. 2022;49:717–33.

    Article  CAS  PubMed  Google Scholar 

  192. Ouedraogo SY, Zoure AA, Zeye MMJ, Kiendrebeogo TI, Zhou X, Sawadogo AY, Simpore J, Chen H. BRCA1, BRCA2, TP53, PIK3CA, PTEN and AKT1 genes mutations in Burkina Faso breast cancer patients: prevalence, spectrum and novel variant. Mol Genet Genomics. 2022;297:1257–68.

    Article  CAS  PubMed  Google Scholar 

  193. Kalinsky K, Jacks LM, Heguy A, Patil S, Drobnjak M, Bhanot UK, Hedvat CV, Traina TA, Solit D, Gerald W. PIK3CA mutation associates with improved outcome in breast cancerPIK3CA mutation and improved outcome in breast cancer. Clin Cancer Res. 2009;15:5049–59.

    Article  CAS  PubMed  Google Scholar 

  194. Vora SR, Juric D, Kim N, Mino-Kenudson M, Huynh T, Costa C, Lockerman EL, Pollack SF, Liu M, Li X. CDK 4/6 inhibitors sensitize PIK3CA mutant breast cancer to PI3K inhibitors. Cancer Cell. 2014;26:136–49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  195. Li SY, Rong M, Grieu F, Iacopetta B. PIK3CA mutations in breast cancer are associated with poor outcome. Breast Cancer Res Treat. 2006;96:91–5.

    Article  CAS  PubMed  Google Scholar 

  196. Samuels Y, Wang Z, Bardelli A, Silliman N, Ptak J, Szabo S, Yan H, Gazdar A, Powell SM, Riggins GJ. High frequency of mutations of the PIK3CA gene in human cancers. Science. 2004;304:554–554.

    Article  CAS  PubMed  Google Scholar 

  197. Horlings HM, Weigelt B, Anderson EM, Lambros MB, Mackay A, Natrajan R, Ng CK, Geyer FC, van de Vijver MJ, Reis-Filho JS. Genomic profiling of histological special types of breast cancer. Breast Cancer Res Treat. 2013;142:257–69.

    Article  CAS  PubMed  Google Scholar 

  198. Zhang HY, Liang F, Jia ZL, Song ST, Jiang ZF. PTEN mutation, methylation and expression in breast cancer patients. Oncol Lett. 2013;6:161–8.

    Article  PubMed  PubMed Central  Google Scholar 

  199. Yehia L, Keel E, Eng C. The clinical spectrum of PTEN mutations. Annu Rev Med. 2020;71:103–16.

    Article  CAS  PubMed  Google Scholar 

  200. Stemke-Hale K, Gonzalez-Angulo AM, Lluch A, Neve RM, Kuo W-L, Davies M, Carey M, Hu Z, Guan Y, Sahin A, et al. An integrative genomic and proteomic analysis of PIK3CA, PTEN, and AKT mutations in breast cancer. Can Res. 2008;68:6084–91.

    Article  CAS  Google Scholar 

  201. Cizkova M, Cizeron-Clairac G, Vacher S, Susini A, Andrieu C, Lidereau R, Bièche I. Gene expression profiling reveals new aspects of PIK3CA mutation in ERalpha-positive breast cancer: major implication of the Wnt signaling pathway. PLoS ONE. 2010;5: e15647.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  202. Dowsett M, Dunbier AK. Emerging biomarkers and new understanding of traditional markers in personalized therapy for breast cancer. Clin Cancer Res. 2008;14:8019–26.

    Article  CAS  PubMed  Google Scholar 

  203. Rodrigues-Ferreira S, Nahmias C. Predictive biomarkers for personalized medicine in breast cancer. Cancer Lett. 2022;545: 215828.

    Article  CAS  PubMed  Google Scholar 

  204. Ambrosone CB, Hong C-C, Goodwin PJ. Host factors and risk of breast cancer recurrence: genetic, epigenetic and biologic factors and breast cancer outcomes. Improv Outcomes Breast Cancer Surviv. 2015;862:143–53.

    Article  Google Scholar 

  205. Hurria A, Wong FL, Villaluna D, Bhatia S, Chung CT, Mortimer J, Hurvitz S, Naeim A. Role of age and health in treatment recommendations for older adults with breast cancer: the perspective of oncologists and primary care providers. J Clin Oncol. 2008;26:5386–92.

    Article  PubMed  PubMed Central  Google Scholar 

  206. De Aguiar SS, Bergmann A, Mattos IE. Quality of life as a predictor of overall survival after breast cancer treatment. Qual Life Res. 2014;23:627–37.

    Article  PubMed  Google Scholar 

  207. Karami Fath M, Azargoonjahromi A, Kiani A, Jalalifar F, Osati P, Akbari Oryani M, Shakeri F, Nasirzadeh F, Khalesi B, Nabi-Afjadi M. The role of epigenetic modifications in drug resistance and treatment of breast cancer. Cell Mol Biol Lett. 2022;27:1–25.

    Article  Google Scholar 

  208. Crombag MR, Joerger M, Thürlimann B, Schellens JH, Beijnen JH, Huitema AD. Pharmacokinetics of selected anticancer drugs in elderly cancer patients: focus on breast cancer. Cancers (Basel). 2016;8:6.

    Article  PubMed  Google Scholar 

  209. Singh JC, Lichtman SM. Effect of age on drug metabolism in women with breast cancer. Expert Opin Drug Metab Toxicol. 2015;11:757–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  210. Alur-Gupta S, Fruchtman H, Paroder V. Fertility-sparing options for cancer patients. Abdominal Radiology. 2023;48:1618–28.

    Article  PubMed  Google Scholar 

  211. Catalano M, Aprile G, Conca R, Petrioli R, Ramello M, Roviello G. The impact of age, performance status and comorbidities on nab-paclitaxel plus gemcitabine effectiveness in patients with metastatic pancreatic cancer. Sci Rep. 2022;12:8244.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  212. Bosch TM, Meijerman I, Beijnen JH, Schellens JH. Genetic polymorphisms of drug-metabolising enzymes and drug transporters in the chemotherapeutic treatment of cancer. Clin Pharmacokinet. 2006;45:253–85.

    Article  CAS  PubMed  Google Scholar 

  213. Maruthanila V, Elancheran R, Kunnumakkara A, Kabilan S, Kotoky J. Recent development of targeted approaches for the treatment of breast cancer. Breast Cancer. 2017;24:191–219.

    Article  CAS  PubMed  Google Scholar 

  214. Costa C, Wang Y, Ly A, Hosono Y, Murchie E, Walmsley CS, Huynh T, Healy C, Peterson R, Yanase S. PTEN loss mediates clinical cross-resistance to CDK4/6 and PI3Kα inhibitors in breast cancer. Cancer Discov. 2020;10:72–85.

    Article  CAS  PubMed  Google Scholar 

  215. Wang DG, Barrios DM, Blinder VS, Bromberg JF, Drullinsky PR, Funt SA, Jhaveri KL, Lake DE, Lyons T, Modi S. Dermatologic adverse events related to the PI3Kα inhibitor alpelisib (BYL719) in patients with breast cancer. Breast Cancer Res Treat. 2020;183:227–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  216. Dunn S, Eberlein C, Yu J, Gris-Oliver A, Ong SH, Yelland U, Cureton N, Staniszewska A, McEwen R, Fox M. AKT-mTORC1 reactivation is the dominant resistance driver for PI3Kβ/AKT inhibitors in PTEN-null breast cancer and can be overcome by combining with Mcl-1 inhibitors. Oncogene. 2022;41:5046–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  217. Gonzalez ME, DuPrie ML, Krueger H, Merajver SD, Ventura AC, Toy KA, Kleer CG. Histone methyltransferase EZH2 induces Akt-dependent genomic instability and BRCA1 inhibition in breast cancer. Can Res. 2011;71:2360–70.

    Article  CAS  Google Scholar 

  218. Lohiya G, Katti DS. Carboxylated chitosan-mediated improved efficacy of mesoporous silica nanoparticle-based targeted drug delivery system for breast cancer therapy. Carbohyd Polym. 2022;277: 118822.

    Article  CAS  Google Scholar 

  219. Alamdari SG, Amini M, Jalilzadeh N, Baradaran B, Mohammadzadeh R, Mokhtarzadeh A, Oroojalian F. Recent advances in nanoparticle-based photothermal therapy for breast cancer. J Control Release. 2022;349:269–303.

    Article  CAS  PubMed  Google Scholar 

  220. Marmé F. Antibody-drug conjugates for breast cancer. Oncol Res Treat. 2022;45:26–36.

    Article  PubMed  Google Scholar 

  221. Santa-Maria CA, Wolff AC. Antibody-drug conjugates in breast cancer: searching for magic bullets. J Clin Oncol. 2023;41:732–5.

    Article  PubMed  Google Scholar 

  222. Miller MS, Thompson PE, Gabelli SB. Structural determinants of isoform selectivity in PI3K inhibitors. Biomolecules. 2019;9:82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  223. Carnero A. Novel inhibitors of the PI3K family. Expert Opin Investig Drugs. 2009;18:1265–77.

    Article  CAS  PubMed  Google Scholar 

  224. Bertho M, Patsouris A, Augereau P, Robert M, Frenel J-S, Blonz C, Campone M. A pharmacokinetic evaluation of alpelisib for the treatment of HR+, HER2-negative, PIK3CA-mutated advanced or metastatic breast cancer. Expert Opin Drug Metab Toxicol. 2021;17:139–52.

    Article  CAS  PubMed  Google Scholar 

  225. Hany D, Zoetemelk M, Bhattacharya K, Nowak-Sliwinska P, Picard D. Network-informed discovery of multidrug combinations for ERα+/HER2-/PI3Kα-mutant breast cancer. Cell Mol Life Sci. 2023;80:80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  226. Meng D, He W, Zhang Y, Liang Z, Zheng J, Zhang X, Zheng X, Zhan P, Chen H, Li W. Development of PI3K inhibitors: advances in clinical trials and new strategies. Pharmacol Res. 2021;173: 105900.

    Article  CAS  PubMed  Google Scholar 

  227. Wang X, Ding J. Meng L-h: PI3K isoform-selective inhibitors: next-generation targeted cancer therapies. Acta Pharmacol Sin. 2015;36:1170–6.

    Article  PubMed  PubMed Central  Google Scholar 

  228. Nunnery SE, Mayer IA. Management of toxicity to isoform α-specific PI3K inhibitors. Ann Oncol. 2019;30:x21–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  229. Ward SG, Finan P. Isoform-specific phosphoinositide 3-kinase inhibitors as therapeutic agents. Curr Opin Pharmacol. 2003;3:426–34.

    Article  CAS  PubMed  Google Scholar 

  230. Shah PD, Modi S, Datko FM, Moynahan ME, Zamora S, D’Andrea G, Lake D, Goldfarb SB, Patil S, Singh S. Phase I trial of daily PI3Kα inhibitor BYL719 plus letrozole (L) or exemestane (E) for patients (pts) with hormone receptor-positive (HR+) metastatic breast cancer (MBC). Am Soc Clin Oncol. 2014;32:2605.

    Article  Google Scholar 

  231. Shah PD, Moynahan ME, Modi S, Caravella BA, Datko FM, Zamora S, Comen E, Gilewski T, Sugarman SM, D’Andrea G. Abstract PD5–3: Phase I trial: PI3Kα inhibitor BYL719 plus aromatase inhibitor (AI) for patients with hormone receptor-positive (HR+) metastatic breast cancer (MBC). Cancer Res. 2015;75: PD5.

    Google Scholar 

  232. Kim IA, Han MG, Jang BS, Kang MH. PI3Kγδ inhibitor combined radiation enhances the antitumor immune effect of PD-1 blockade in syngenic triple negative breast cancer models. J Clin Oncol. 2021;39: e13041.

    Article  Google Scholar 

  233. Brandao M, Caparica R, Eiger D, De Azambuja E. Biomarkers of response and resistance to PI3K inhibitors in estrogen receptor-positive breast cancer patients and combination therapies involving PI3K inhibitors. Ann Oncol. 2019;30:x27–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  234. Levine DA, Bogomolniy F, Yee CJ, Lash A, Barakat RR, Borgen PI, Boyd J. Frequent mutation of the PIK3CA gene in ovarian and breast cancers. Clin Cancer Res. 2005;11:2875–8.

    Article  CAS  PubMed  Google Scholar 

  235. Anderson EJ, Mollon LE, Dean JL, Warholak TL, Aizer A, Platt EA, Tang DH, Davis LE. A systematic review of the prevalence and diagnostic workup of PIK3CA mutations in HR+/HER2–metastatic breast cancer. Int J Breast Cancer. 2020;2020:1–16.