Skip to main content
Download PDF

HDAC1 and FOXK1 mediate EGFR-TKI resistance of non-small cell lung cancer through miR-33a silencing

Journal of Translational Medicine volume 22, Article number: 793 (2024) Cite this article

Abstract

Background

The development of acquired EGFR-TKI treatment resistance is still a major clinical challenge in the treatment of non-small cell lung cancer (NSCLC). This study aimed to investigate the role of HDAC1/FOXK1/miR-33a signaling in EGFR-TKI resistance.

Methods

The expression levels of miR‐33a, HDAC1, and FOXK1 were examined using quantitative polymerase chain reaction (PCR) and bioinformatics analysis. Cell proliferation, migration, and apoptosis were explored by cell number assay, Transwell, and flow cytometry assays, respectively. After overexpression or knockdown of HDAC1, miR-33a expression in the cells, cell functions were tested. Immunoprecipitation and correlation analyses were used to evaluate the interaction between HDAC1 and FOXK1 protein. The tumor-suppressive role of miR-33a was investigated by animal experiments.

Results

The suppression of miR-33a increased TKI resistance by affecting cell proliferation, migration, and apoptosis in gefitinib-resistant cells. HDAC1 is the key upstream molecule that inhibits miR-33 expression. HDAC1 upregulation increased gefitinib resistance by its binding to FOXK1 in cells to silence miR-33a expression. MiR-33a overexpression exerts tumor-suppressive effects by negatively regulating ABCB7 and p70S6K1 expression. Moreover, overexpression of miR-33a inhibited tumor growth in a xenograft nude mouse model.

Conclusions

HDAC1/FOXK1 upregulation and miR-33a silencing are new mechanisms of EGFR-TKI resistance in NSCLC.

Background

Non-small cell lung cancer (NSCLC) is the most prevalent type of lung cancer and is the primary cause of death on a global scale [1]. In most cases, NSCLC is at an advanced stage at diagnosis and has a poor prognosis and survival [2]. In NSCLC patients with EGFR-sensitizing mutations, EGFR tyrosine kinase inhibitors (EGFR-TKIs) significantly improve the prognosis compared to traditional platinum-based chemotherapy [3, 4]. However, the development of acquired EGFR-TKI resistance during treatment is still a major clinical challenge in the management of NSCLC [5]. There are several potential mechanisms of EGFR-TKI resistance. The most common mutations associated with resistance are gatekeeper mutations in EGFRs (such as the secondary T790M or tertiary C797S). Additionally, the activation of bypass signaling pathways (such as the MET, K-RAS, or HGF pathway), small-cell lung cancer (SCLC) transformation, and epithelial-to-mesenchymal transition (EMT), are implicated as causes of EGFR-TKI resistance [6, 7]. Recent studies have shown that patients with poor responses to EGFR-TKIs typically exhibit epigenetic changes, which may affect the cytotoxic effects of antitumor therapy [8,9,10]. However, new mechanisms of EGFR-TKI resistance remain to be elucidated.

Histone deacetylase 1 (HDAC1) is an epigenetic factor that inhibits histone acetylation. Eighteen HDACs have been identified [11]. HDAC1 is known to be correlated with cancer progression and development [12, 13]. Silencing of HDAC1 in breast and colon cancer cells results in cell cycle arrest, cell growth inhibition, and apoptosis [14, 15]. It was also found that MCM5 and HDAC1 aggravated EMT-dependent malignant progression in lung cancer [16]. The inhibition of HDAC1 and HDAC2 induces the expression of NKG2D ligands and enhances antitumor immunity [17]. It was reported that exosomal miR-2682-5p inhibited NSCLC cell viability and migration, and promoted apoptosis via the HDAC1/ADH1A axis, suggesting that this miRNA is a new therapeutic target for NSCLC [18]. An increasing number of studies suggest that HDAC inhibitors are effective at treating lung cancer [19,20,21,22]. A new class of peptide-based HDAC inhibitors has been shown to exert excellent antiproliferative effects on cancer stem cells [19]. The pan-HDAC inhibitor GCJ-490 A was found to effectively inhibit NSCLC cell proliferation and induce apoptosis in vitro and in vivo by inhibiting HDAC1, HDAC3, and HDAC6 [20]. In preclinical studies, HDAC inhibitors exhibited antitumor activity on NSCLC cells resistant to EGFR-TKIs [21, 22]. It may be possible to improve acquired resistance to gefitinib by upregulating DUSP1 with HDAC inhibitors [23]. Another reason may be that HDAC promotes EMT by downregulating E-cadherin and upregulating vimentin [24]. The present study identified a new epigenetic mechanism for EGFR-TKI resistance through the HDAC1/FOXK1-miR-33a axis. FOXK1, a member of the FOX family, is a transcription factor that has been linked to the progression of different types of cancer [25].

It was reported that miR-33a functions as a tumor suppressor by inhibiting the transcription of SREBP2 [26, 27]. Data mining based on online databases suggested that miR-33a was involved in lung cancer proliferation and cell migration [28]. miR-33a was reported to affect DICER1 regulation via APE1 expression, which is involved in lung cancer chemoresistance and invasion [29]. However, whether HDAC1 and miR-33a are linked to TKI resistance and lung cancer development is unknown. Here, we provide the first evidence that HDAC1 is important for EGFR-TKI resistance through HDAC1/FOXK1-mediated silencing of miR-33a and that HDAC1 may be a potential novel treatment target for overcoming EGFR-TKI resistance in the near future.

Materials and methods

Bioinformatics analysis

A comprehensive comparison of miR-33a-5p expression across malignant pathologies (comparative comparison between normal tissues and tumor tissues) was carried out using the dbDEMC 3.0 database (www.biosino.org/dbDEMC/index) [30]. In total, 403 miRNA expression datasets were collected from public repositories using microarray or miRNA-seq platforms. The current 3.0 version contains 3,268 differentially expressed miRNAs from 40 cancer types, while the human version includes 2,584 differentially expressed miRNAs. We also examined miR-33a expression levels in the GSE15008 and GSE135918 datasets via the GEO2R online tool (www.ncbi.nlm.nih.gov/geo/geo2r/). The miRNA expression profile data of normal lung tissues and lung cancer tissues were downloaded and analyzed. GraphPad Prism 7.0 was used to create the boxplots. The mRNA expression levels of HDAC1 were evaluated in ten GEO datasets, namely, GSE10072, GSE19188, GSE27262, GSE30219, GSE31210, GSE32863, GSE33532, GSE40791, GSE63459, and GSE75037, using the GEO2R online tool. The clinical trials utilizing epigenetic modulators in NSCLC were obtained from ClinicalTrials.gov ( https://clinicaltrials.gov ) and the cutoff date was May 23, 2024. Numerous epigenetic modifiers have been involved, including DNA methyltransferases (DNMTs), histone lysine methyltransferases (KMTs), histone lysine demethylases (KDMs), histone acetyltransferases (HATs), histone deacetylases (HDACs), and histone readers.

We also downloaded the mRNA and protein expression data from TCGA-LUAD using the cBioPortal website [31] and the UALCAN database [32], respectively. To determine the differences in the mRNA expression levels of HDAC1 and FOXK1 between TKI-sensitive and TKI-resistant lung cancer cells, we analyzed three independent datasets, GSE169513, GSE34228, and GSE74575, through the use of the GEO2R tool. The above mentioned databases are open-access public databases, and all patients provided written informed consent.

Cell culture and patient plasma samples

Human bronchial epithelial BEAS-2B (B2B) cells and human lung cancer cell lines (PC9, A549, H1299, H1975, and HCC827) were obtained from American Type Culture Collection (Manassas, VA, USA). PC9/G and HCC827/G cells were obtained from Shanghai Pulmonary Hospital, Tongji University. All the cells except B2B cells were grown in RPMI 1640 medium (Invitrogen, Carlsbad, USA) supplemented with 10% FBS and antibiotics. B2B cells were cultured in DMEM (Invitrogen, Carlsbad, USA) supplemented with 10% FBS and antibiotics. B2B cells were maintained in DMEM containing 0.5 µM Cr (VI) for six months to select Cr-resistant cells (CrT cells). Parallel cultures grown in Cr-free DMEM were used as passage-matched controls. After long-term Cr (VI) exposure, CrT cells were confirmed to have the ability to transform and build tumors, as previously described [33, 34]. Gefitinib was purchased from Selleck Chemicals (Houston, TX, USA).

Plasma samples of NSCLC patients were procured and obtained from the Biobank of Zhengzhou University’s Affiliated Cancer Hospital in Zhengzhou, China. The samples included plasma samples of three patients diagnosed with Stages IIIB or IV NSCLC, characterized by activating EGFR mutations (exon 19 deletion or 21 L858R mutations). The samples were from the blood samples collected before and after the treatment with gefitinib between May 2022 and March 2024. Paired plasma samples were obtained at two distinct time points: prior to the initiation of gefitinib therapy and after the development of gefitinib resistance, and used for the analysis of miR-33a and FOXK1 expression levels.

EdU staining

CrT cells (1.25×104) were seeded in an 8-well Glass of Millicell® EZ slide (Millipore Sigma, USA) for 24 h, and then transfected with the miR-33a mimic or scramble miR mimic (miR-NC). After 48 h, following the manufacturer’s instructions for the EdU kit (Cell-Light™ EdU Apollo567 In Vitro Kit; Ribobio, Guangzhou, China), the CrT cells were incubated with EdU medium for 2 h in a CO2-incubator at 37 °C and 5% CO2. Two hours later, we washed CrT cells twice with PBS, incubated them for 30 min with 4% PFA at room temperature, neutralized them with 2 mg/mL glycine solution, and then washed them with PBS. After Apollo staining, we took pictures under a positive fluorescence microscope (Olympus, Japan) after 1 h of DAPI staining (Servicebio, Wuhan, China) at room temperature.

Cell viability and cell proliferation assay

For cell viability, we first plated 4×104 cells in 96-well plates (Corning, USA) at 100 µL per well for 24 h. The 96-well plate was subsequently injected with gefitinib or erlotinib medium following the drug concentration gradient. After 48 h, the cells were cultured. CCK8 diluent (CCK8: RPMI-1640 = 1:10, 70 µL) was added to each well and OD450 nm values were obtained. GraphPad Prism 7.0 was used to create the graphs. Cell proliferation was analyzed using the CCK − 8 assay after transfecting PC9/G and HCC827/G cells with miR-NC and miR-33a mimics for 48 h. We seeded cells (1.5×103/100 µL /well) in 96-well plates for 24 h, and measured the absorbance at 450 nm by a spectrophotometer (Molecular Devices, Shanghai, China) after adding CCK8 reagent to the 96-well plates. Further culture was performed on a 96-well plate in an incubator and the OD values of the samples were subsequently determined by the same method after 48 h, 72 h, 96 h, and 120 h. The percentages of cell growth were calculated as follows: cell proliferation (%) = [OD value of 48 h - OD value of Blank]/ [OD value of 24 h - OD value of Blank] ×100%. Each experiment was conducted at least three times.

RNA extractions and qRT-PCR

Total RNA extractions and qRT-PCR assays were conducted as we previously described [34]. Briefly, total RNA was isolated from cells using TRIzol (Invitrogen, CA, USA) according to the manufacturer’s instructions. cDNA synthesis was performed using M-MLV reverse transcriptase (Invitrogen) from 1µg of total RNA. qRT-PCR was performed using the Power SYBR Green PCR Master Mix Kit (Applied Biosystems, Carlsbad, CA, USA) and carried out on a LightCycler 480 Real-Time PCR System (Roche Applied Science). We applied Bulge-Loop hsa-miR-33a-5p Primer Set to analyze miR-33a levels in cells, which was purchased from RIBOBIO Biotechnology (Cat No. MQPS0001085-1-100, Guangzhou, China). The primers used for qRT-PCR were as follows: HDAC1 forward: 5’-CTACTACGACGGGGATGTTGG-3’ and reverse: 5’-GAGTCATGCGGATTCGGTGAG-3’; FOXK1 forward: 5’-ACACGTCTGGAGGAGACAGC-3’ and reverse: 5’-GAGAGGTTGTGCCGGATAGA-3’; GAPDH forward: 5’-AGCCACATCGCTCAGACAC-3’ and reverse: 5’-GCCCAATACGACCAAATCC-3’. miRNA and mRNA PCRs were normalized using U6 snRNA and GAPDH, respectively. The Ct (2 − ΔΔCt) method was used in the analysis of PCR data. All the reactions were performed in triplicate.

Small RNA interference and plasmid transfection

The cells (1 × 105) were cultured in six-well plates and transfected with jetPRIME reagent (Polyplus transfection) with 110 pmol of ON‐TARGETplus SMARTpool‐Human HDAC1 siRNA (L-003493-00-20, Dharmacon) or ON‐TARGETplus Nontargeting Pool (D-001810-10-50, Dharmacon) according to the manufacturer’s protocols. To overexpress HDAC1, 2 × 106 PC9 and HCC827 cells were transfected with 1 µg of pHDAC1-FLAG (Addgene plasmid, 13820). Control cells were transfected with the empty vector pcDNA3.1. For transient transfection experiments, Polyplus Jetprime and Thermo Scientific Lipofectamine 3000 were used according to the kit instructions.

Immunoblotting

Western blotting was performed as we previously described [33]. Briefly, the cells were washed in cold 1× PBS buffer and lysed in ice-cold RIPA buffer (Beyotime of Biotechnology, Shanghai, China) supplemented with protease inhibitors on ice for 30 min. Following the manufacturer’s instructions, BCA was used to quantify the protein concentrations. The protein samples were subjected to SDS-PAGE and then transferred onto membranes (Bio-Rad, USA). The membrane was blocked with 5% nonfat milk for one hour, followed by overnight incubation with primary antibodies diluted in 2% BSA. After washing, the membranes were incubated with HRP-conjugated secondary antibodies for one hour, and then exposed to an imager (Bio-Rad ChemiDoc MP, Bio‐Rad). The antibodies used were as follows: ABCB7 (#ab65149, Abcam, UK), p70S6K1 (#9202, Cell Signaling Technology, Danvers, MA), FOXK1 (#ab18196, Abcam, UK) Caspase 3 (#9662, Cell Signaling Technology, Danvers, MA), cleaved Caspase-3 (#9664, Cell Signaling Technology, Danvers, MA), BAX (#ab32503, Abcam, UK) BCL2 (#ab182858, Abcam, UK), and β-actin (#ab8227, Abcam, UK). The enhanced chemiluminescence reagent Supersignal was used to visualize the blots (Pierce, Rockford, IL, USA).

Immunoprecipitations

The 293T cells were transfected with the HADC1/FOXK1 plasmid and polyethyleneimine (PEI) reagent (Millipore Sigma, USA) for 2 days, after which the cells were treated with protein lysis buffer. The lysates were centrifuged at 12,000 g and 4℃ for 15 min, after which the protein supernatants were removed from the nonspecific protein mixture with 20 µL of protein G-agarose (Sigma-Aldrich, USA). After centrifugation, part of the obtained supernatant was used as an input, and the other part was transferred to another tube supplemented with primary antibody against HDAC1 (ab7028, Abcam) or FOXK1 (ab18196, Abcam) and incubated overnight at 4℃. Then, the protein complexes were collected by incubation with 50 µL of Protein G-Agarose for 2-4 h. Finally, the protein complexes were washed with protein lysis buffer and analyzed via Western blot.

Luciferase activity assay

Cells were plated in a 24-well plate. The wild-type plasmid and mutant plasmids pGL3-HDAC1 and pGL3-ABCB7/pGL3-p70S6K1 were constructed, and the plasmids were subsequently transfected into the cells together with FOXK1 or the miR-NC/miR-33a mimic. A luciferase assay was also conducted using cells that were cotransfected with either wild-type or mutant-type pGL3-ABCB7/pGL3-p70S6K1 plasmids, together with a miR-NC mimic or miR-33a-5p mimic. These luciferase activities were determined using a Dual-Luciferase Reporter Assay Kit (Promega, Madison, WI, USA) according to the manufacturer’s instructions. The relative luciferase activities were normalized to those of Renilla. The data were processed and plotted by GraphPad Prism 7.0.

Cell migration and apoptosis assays

The Transwell migration assay was carried out using a Transwell chamber (#MCEP24H48, Millipore, USA). Target cells (1 × 105) were cultured with 200 µl serum-free medium for 18 h. After incubation, the cells were fixed in methanol for 15 min and then stained with 0.1% crystal violet (Sigma-Aldrich, USA) for 30 min. The number of migrated cells was photographed and counted after fixation and staining. For the cell apoptosis assay, target cells were transfected with miR-NC, miR-33a or siNC/siHDAC1, and cultured in the presence of gefitinib for 48 h. The cells were then collected and stained with an Annexin V/PI apoptosis detection kit (Vazyme, Nanjing, China) according to the manufacturer’s instructions. The results were detected by flow cytometry.

Tumor xenograft model

Four-week-old nude mice were purchased from GemPharmatech™ (Nanjing, China). In the next step, the mice were divided into two groups (n = 5). A subcutaneous tumorigenesis assay was performed by injecting 5 × 106 PC9/G/ miR-NC or miR-33a cells under the skin of each mouse. Several weeks later, the mouse’s subcutaneous tumors had fully developed. Images of the tumors were taken after they were removed. Daily measurement of the tumor volumes was conducted during this period.

To further explore the effect of HDAC1 silencing on the efficacy of gefitinib, twenty nude mice were randomly divided into four groups (Control vs. Gefitinib vs. HDAC-KD vs. HDAC-KD + Gefitinib,n = 5). They were subcutaneously injected with 5 × 106PC9/G cells expressing the vector control or with HDAC1 knockdown in the cells, then mice were treated with the solvent or 50 mg/kg gefitinib respectively every other day as indicated. The tumor weights were analyzed at Day 22 and volumes were recorded at the indicated days.

Statistical methods

SPSS 19.0 and GraphPad Prism 7.0 were used for statistical assessment. A Kaplan-Meier curve was generated to estimate the prognosis. The data are presented as the mean ± standard error of the values from independent experiments and were subsequently analyzed using Student’s t-test or Pearson correlation analysis. A p-value of less than 0.05 was regarded as significant. ∗, ∗∗ and *** indicate p < 0.05, p < 0.01, and p < 0.001, respectively.

Results

miR-33a-5p expression is downregulated in CrT cells and lung cancer tissues

In our previous research, we established an in vitro model to study the effect of long-term Cr (VI) exposure on human epithelial cells and the whole body [33, 34]. Normal human bronchial epithelial BEAS-2B cells can be transformed into malignant cells (CrT cells) by Cr (VI), which results in typical malignant transformation and tumorigenic properties. We found that miR-33a-5p expression was significantly lower in CrT cells and lung cancer cells (A549, H1299, and H1975) than in BEAS-2B cells (B2B) (Fig. 1A and B). Further EdU proliferation experiments indicated that miR-33a-5p reduced the proliferation rate of CrT cells (Supplementary Fig. 1). The further study also showed that miRNA-33a-5p levels were strongly downregulated in lung cancer tissues compared to paired adjacent normal lung tissues in GSE15008 (Fig. 1C) and unpaired normal lung tissues in GSE135918 (Fig. 1D). We also analyzed miR-33a-5p expression levels across cancers using the dbDEMC 3.0 database. A heatmap showed that miR-33-5p expression was significantly downregulated in lung cancer tissues (Fig. 1E).

Fig. 1
figure 1

miR-33a is downregulated in lung cancer. (A) miR-33a expression was dramatically downregulated in Cr (VI) - transformed cells (CrT) compared to that in human lung epithelial BEAS-2B (B2B) cells. (B) miR-33a levels were significantly down-regulated in lung cancer cells (A549, H1299, and H1975) compared to the normal control B2B cells. (C) miRNA-33a was downregulated in lung cancer tissues compared to paired adjacent normal lung tissues in GSE15008. (D) miRNA-33a expression levels were lower in lung cancer tissues than in normal lung tissues in the GSE135918. (E) Pan-cancer analysis of the differential expression of miR-33a between cancer tissues and normal tissues is shown in the dbDEMC 3.0 database. *, **, and *** indicate significant differences at P < 0.05, P < 0.01, and P < 0.001, respectively

Full size image

miR-33a is downregulated to regulate cell proliferation, migration, and apoptosis in gefitinib-resistant cells

Among the LUAD cell lines, HCC827 and PC9 cells both carry EGFR exon 19 deletions (Del E746-A750). The two cell lines were then exposed to increasing concentrations of gefitinib for the development of gefitinib-resistant cell lines as reported previously [35]. Two independent resistant cell lines (PC9/G and HCC827/G) were ultimately derived, and the cell resistance was verified. Compared with control cells, PC9/G and HCC827/G cells had significantly greater half-maximal inhibitory concentration (IC50) values (Fig. 2A and B). Quantitative PCR analyses for miR-33a were performed in the PC9/G and HCC827/G cell lines, and miR-33a expression was downregulated in both the PC9/G and HCC827/G cell lines (Fig. 2C). We also found that the expression levels of miR-33a in human samples from the gefitinib resistant NSCLC patients were significantly decreased compared to those from gefitinib sensitive patients (Fig. 2D).

To explore how miR-33a affects the cellular function of gefitinib-resistant cells, we overexpressed miR-33a and detected the effect on cell proliferation by CCK8 assay in PC9/G and HCC827/G cells. Overexpression of miR-33a inhibited the proliferation of PC9/G cells and HCC827/G cells (Fig. 2E). We then performed cell migration experiments using a Transwell migration assay, and the results showed that miR-33a overexpression inhibited the migration of PC9/G and HCC827/G cells (Fig. 2F). To examine the effects of miR-33a on gefitinib sensitivity, miR-33a was overexpressed in gefitinib-resistant PC9/G cells, which were subsequently seeded in 96-well plates. After adding different concentrations of gefitinib, the cell viability was determined after 48 h of culture. The results showed that overexpression of miR-33a enhanced the sensitivity of PC9/G cells to gefitinib treatment (Fig. 2G). To further clarify whether miR-33a regulates gefitinib resistance by affecting apoptosis, we overexpressed miR-33a in gefitinib-resistant PC9/G cells, and the level of apoptosis was detected after 48 h of culture by flow cytometry. The results demonstrated that miR-33a significantly promoted cell apoptosis in PC9/G cells (Fig. 2H). We then analyzed the expression levels of apoptosis regulators including Caspase 3, cleaved Caspase-3, Bax, and Bcl2, and found that levels of Caspase 3, cleaved Caspase-3 and Bax were upregulated in miR-33a-overexpressed cells, whereas levels of Bcl2 were downregulated in miR-33a-overexpressed cells (Supplementary Fig. 2A). The above results together demonstrated that miR-33a is involved in gefitinib resistance. To examine the effects of miR-33a on erlotinib sensitivity, we overexpressed miR-33a in PC9/G cells. After adding different concentrations of erlotinib for 72 h, the cell viability levels were determined. The results showed that overexpression of miR-33a significantly enhanced the sensitivity of PC9/G cells to erlotinib treatment (Supplementary Fig. 2B).

Fig. 2
figure 2

Establishment of gefitinib-resistant lung cancer cell lines and expression level and functional studies of miR-33a. (A, B) Establishment and characterization of gefitinib-resistant lung cancer cell lines (PC9/G and HCC827/G), with the resistant cells having significantly higher half maximal inhibitory concentration (IC50) values according to the CCK8 assay than the control cells. (C) miR-33a expression in the PC9/G and HCC827/G cell lines. (D) miR-33a levels in the human samples from the gefitinib resistant NSCLC patients were significantly decreased compared to those from gefitinib sensitive patients. (E) miR-33a overexpression inhibited the proliferation of PC9/G cells and HCC827/G cells. (F) Overexpression of miR-33a inhibited cell migration by Transwell assay. (G) Overexpression of miR-33a enhanced the sensitivity of PC9/G cells to gefitinib treatment. (H) Overexpression of miR-33a significantly increased cell apoptosis in PC9/G cells. * and ** indicate significant differences at P < 0.05 and P < 0.01, respectively

Full size image

HDAC1 is upregulated to inhibit miR-33a expression

HDAC1 expression was upregulated in the PC9/G and HCC827/G cell lines compared to the parental cells (Fig. 3A). Similarly, we found that the expression levels of HDAC1 were significantly higher in LUAD (Fig. 3B) and lung squamous cell carcinoma (LUSC) tissues (Fig. 3C) than in paired normal tissues from TCGA RNA-seq data. We also evaluated the differences in the expression levels of HDAC1 between tumor and normal tissues in multiple LUAD datasets, including GSE10072, GSE19188, GSE27262, GSE30219, GSE31210, GSE32863, GSE33532, GSE40791, GSE63459, GSE75037, and TCGA. The mRNA levels of HDAC1 were found to be significantly upregulated in almost all the databases (Fig. 3D). Subsequently, we analyzed HDAC1 protein expression levels in LUAD tissues using the CPTAC database and found that HDAC1 expression was strongly increased in tumor tissues (Supplementary Fig. 2C). Gefitinib-sensitive cells were transfected with the HDAC1-overexpression plasmid for 48 h. The levels of miR-33a were decreased after transfection with HDAC1 cDNA in both PC9 and HCC827 cells (Fig. 3E). The clinical trials utilizing epigenetic modulators in NSCLC were summarized in Supplementary Table 1. The HDAC1 inhibitor Endostat is a synthetic benzamide derivative with highly selective activity against HDAC1, 2, and 3 [36]. MiR-33a expression was significantly upregulated after PC9/G and HCC827/G cells were transfected with the HDAC1 inhibitor entinostat (Selleckchem, Houston, TX, USA) (Fig. 3F). The levels of miR-33a were significantly increased in two different gefitinib-resistant cell lines after transfection with HDAC1 siRNA for 48 h (Fig. 3G). Moreover, HDAC1 mRNA levels were also determined with GEO database, and HDAC1 levels were also increased in gefitinib resistant cell lines as suggested in the GSE169513 (Fig. 3H), GSE34228 (Fig. 3I), and GSE74575 (Fig. 3J) datasets.

Fig. 3
figure 3

HDAC1 is upregulated to inhibit miR-33a expression. (A) Quantitative PCR analyses of HDAC1 expression in the PC9/G and HCC827/G cell lines. (B) The expression levels of HDAC1 were significantly higher in lung adenocarcinoma tissues than in paired samples according to RNA-seq data from the TCGA-LUAD cohort. (C) The expression levels of HDAC1 were significantly higher in lung squamous cell carcinoma samples than in paired samples according to RNA-seq data from the TCGA-LUSC cohort. (D) The mRNA levels of HDAC1 were found to be significantly upregulated in multiple LUAD datasets, including GSE10072, GSE19188, GSE27262, GSE30219, GSE31210, GSE32863, GSE33532, GSE40791, GSE63459, GSE75037, and TCGA. (E) The levels of miR-33a were decreased after transfection of PC9 and HCC827 cells with HDAC1 cDNA. (F) MiR-33a expression was upregulated after PC9/G and HCC827/G cells were transfected with the HDAC1 inhibitor entinostat. (G) The levels of miR-33a were increased in PC9/G and HCC827/G cells after transfection with HDAC1 siRNA. (H-J) HDAC1 mRNA levels were determined using the GSE169513 (H), GSE34228 (I), and GSE74575 (J) datasets, respectively. *,**, and *** indicate significant differences at P < 0.05, P < 0.01, and P < 0.001, respectively

Full size image

HDAC1 regulates cell apoptosis and viability in PC9/G cells, and higher HDAC1 expression levels are correlated with a poor prognosis

To further clarify whether HDAC1 regulates gefitinib resistance by affecting apoptosis, we knocked down HDAC1 in gefitinib-resistant PC9/G cells, and found that the level of apoptosis was significantly higher in the knockdown cells after 48-72 h of culture than in the control (Fig. 4A). We also interfered with the expression of HDAC1 in PC9/G cells and found that HDAC1 knockdown significantly increased drug sensitivity to gefitinib treatment (Fig. 4B). In addition, we showed that high HDAC1 expression levels in clinical LUAD specimens were positively correlated with poor patient prognosis using three independent LUAD datasets, including GSE31210. GSE63459, and GSE37745 (Fig. 4C and E). We next studied the effect of HDAC1 silencing on the gefitinib efficacy in vivo using a nude mice tumor xenograft model. Representative images of tumors from the mice were shown in Supplementary Fig. 3A. The tumor weights (Supplementary Fig. 3B) and volumes (Supplementary Fig. 3C) were recorded and analyzed as indicated. The new result showed that HDAC1 silencing increased the effect of gefitinib treatment in vivo.

Fig. 4
figure 4

HDAC1 regulates cell functions and higher HDAC1 expression levels are correlated with poor patient prognosis. (A) HDAC1 knockdown induced apoptotic activity in PC9/G cells. (B) HDAC1 knockdown increased the drug sensitivity of PC9/G cells to gefitinib treatment. (C-E) Increased HDAC1 gene expression in clinical lung adenocarcinoma specimens was correlated with poor patient prognosis according to three independent lung adenocarcinoma datasets, including GSE31210 (C), GSE63459 (D), and GSE37745 (E). * and ** indicates significant difference at P < 0.05 and P < 0.01, separately

Full size image

HDAC1 directly interacts with FOXK1 to suppress miR-33a expression, and FOXK1 expression is upregulated in gefitinib-resistant tumor samples

Immunoprecipitation analysis indicated that HDAC1 interacts with FOXK1 (Fig. 5A). Using RNA-seq data from TCGA-LUAD and TCGA-LUSC, we found a strong positive correlation between HDAC1 and FOXK1 gene expression levels (Supplementary Fig. 2D, 2E). Bioinformatics analysis via the JASPAR database (http://jaspar.genereg.net/) was used to predict the potential transcription factor involved in regulating miR-33a expression, and the miR-33a promoter region was predicted to contain a binding site for the transcription factor FOXK1. Potential transcription factor binding sites between FOXK1 and miR-33a are shown in Fig. 5B. ChIP analysis confirmed that FOXK1 can bind to the promoter region of miR-33a (Fig. 5C).

Quantitative PCR analyses for FOXK1 were performed and the results revealed that FOXK1 was upregulated in the PC9/G and HCC827/G cell lines (Fig. 5D). Interestingly, the LUAD samples tended to have elevated FOXK1 expression, but the increase did not reach statistical significance (Fig. 5E). Compared with paired normal tissue samples, LUSC tissue samples had higher FOXK1 mRNA levels (Fig. 5F). After identifying the difference in the expression of FOXK1 between gefitinib-sensitive and gefitinib-resistant cell lines, we found that FOXK1 expression was much higher in gefitinib-resistant cell lines than in sensitive cell lines according to three independent datasets from the Gene Expression Omnibus (GEO) database (GSE169513, GSE34228, and GSE74575) (Fig. 5G and I). The protein levels of FOXK1 were also significantly higher in LUAD tissues than in normal tissues (Supplementary Fig. 4A). We further analyzed the mRNA and protein expression levels of FOXK1 in lung cancer cell lines, and found that FOXK1 levels were increased in lung cancer cells (A549, H1299, PC9, HCC827, and H1975) compared to the control cells (Supplementary Fig. 4B, 4 C). In addition, FOXK1 levels were increased in the gefitinib resistant NSCLC cancer samples compared to gefitinib sensitive samples (Supplementary Fig. 4D).

Fig. 5
figure 5

HDAC1 directly interacts with FOXK1 to affect miR-33a expression and FOXK1 expression is upregulated in gefitinib-resistant samples. (A) Immunoprecipitation analysis showed that HDAC1 interacted with FOXK1. (B) Potential transcription factor binding sites between FOXK1 and miR-33a are shown. (C) ChIP analysis confirmed that FOXK1 is bound to the promoter region of miR-33a. (D) FOXK1 was found to be upregulated in the PC9/G and HCC827/G cell lines. (E) The LUAD samples tended to have elevated FOXK1 expression. (F) LUSC tissues had higher FOXK1 mRNA levels than paired normal tissues. (G-I) FOXK1 mRNA levels were determined using the GSE169513 (G), GSE34228 (H), and GSE74575 (I) datasets. *, **, and *** indicate significant differences at P < 0.05, P < 0.01, and P < 0.001, respectively

Full size image

MiR-33a overexpression negatively regulates ABCB7 and p70S6K1 expression

Using bioinformatics software (TargetScan), we predicted the binding sites of miR-33a in the 3`-untranslated regions (3`UTR) of ABCB7 and p70s6k (Fig. 6A). We subsequently constructed wild-type (wild) and mutant (mutant) gene reporter constructs containing binding sites for subsequent reporter gene experiments. The results showed that overexpression of miR-33a significantly decreased the wild-type luciferase activity of ABCB7 and p70S6K1, but not that of the corresponding mutant reporters (Fig. 6B). Overexpressing of miR-33a inhibited ABCB7 and p70S6K1 expression at the protein level in the PC9/G and HCC827/G cell lines, as determined by immunoblotting (Fig. 6C).

Fig. 6
figure 6

MiR-33a negatively regulates ABCB7 and p70S6K1 expression. (A) The potential binding sites for miR-33a in ABCB7 and p70S6K1 were predicted using TargetScan bioinformatics software. (B) Overexpression of miR-33a significantly decreased the luciferase activities of ABCB7 and p70S6K1, but did not affect their mutant reporter activities. (C) Overexpression of miR-33a inhibited ABCB7 and p70S6K1 expression at the protein level. ** indicates significant differences at P < 0.01

Full size image

Overexpression of miR-33a inhibits tumor growth in a xenograft nude mouse model

To study the effect of miR-33a on the growth of lung cancer in vivo, we harvested the stable cell lines PC9/G/miR-NC and PC9/G/miR-33a in the logarithmic growth phase. We then suspended the cells in serum-free medium and injected them subcutaneously into the thigh roots of the nude mice with a 1 ml syringe. After the tumors became visible to the naked eye, the diameter and transverse diameter of each tumor were measured, and a growth curve was drawn. The results showed that miR-33a inhibited tumor growth in the xenograft nude mouse model, and the tumor nodule weight in the miR-33a overexpression group was lower than that in the control group (Fig. 7A and B).

Fig. 7
figure 7

Overexpression of miR-33a inhibits tumor growth in a xenograft nude mouse model. (A) miR-33a inhibited tumor growth in the xenograft mouse model. (B) The tumor weights in the miR-33a overexpression group were significantly lower than those in the control group. * and ** indicate significant differences at P < 0.05 and P < 0.01, respectively

Full size image

Discussion

In this study, we revealed a novel HDAC1/FOXK1-miR-33a pathway involved in regulating EGFR-TKI resistance, and HDAC1, FOXK1, and/or miR-33a may be potential new therapeutic targets for overcoming EGFR-TKI resistance. Inhibitors of HDACs are a class of epigenetic drugs tested against a wide array of disorders, and five HDAC inhibitors have been approved by the FDA for therapeutic use [37]. They may target just one type of HDAC (selective inhibitor) or may target all types of cancer (pan inhibitors). It has been shown that HDAC inhibitors inhibit the proliferation of a variety of transformed cells in vitro, including lymphoma, myeloma, leukemia, and NSCLC cells, and inhibit the progression of certain solid tumors, including lung cancer [38].

There is increasing interest in combinations of HDAC inhibitors with other chemotherapeutic agents, immune checkpoint inhibitors, or tyrosine kinase inhibitors [39]. We are currently participating in a phase II trial to further confirm the antitumor activity and safety profile of an HDAC inhibitor (chidamide) plus tislelizumab combined with chemotherapy in advanced NSCLC (ChiCTR2000041542, https://www.chictr.org.cn/index.html/). Another phase II clinical trial of nivolumab in combination with a receptor tyrosine kinase inhibitor and the HDAC inhibitor mocetinostat in NSCLC has also been conducted (NCT02954991, https://clinicaltrials.gov/). As successful epigenetic therapies, pan HDAC inhibitors are the most commonly used HDAC inhibitors for treating cancer [37, 39]. To reduce the adverse effects on normal cells, future studies should focus on improving selective HDAC inhibitors to increase their accumulation in tumor cells. A novel HDAC1/2 inhibitor (compound 9) was reported to suppress colorectal cancer by inducing apoptosis and regulating the cell cycle [40]. CBUD-1001, another novel HDAC1 inhibitor inhibited the motility of CRC cells by downregulating the EMT signaling pathway, making it a promising candidate for CRC therapy [41]. Additionally, CBUD-1001 sensitized colorectal cancer cells to TRAIL-induced apoptosis by upregulating DR5, and the combination of CBUD-1001 and TRAIL overcame TRAIL resistance [42]. Other new selective HDAC1 inhibitors exhibited acceptable safety profiles and significant antitumor activity in an A549 tumor xenograft model in vivo [43]. This study is the first to demonstrate that HDAC1 is important for EGFR-TKI resistance, and HDAC1-specific inhibitors may be promising drugs for reversing EGFR-TKI resistance, but have fewer side effects in the future.

Epigenetic modifications are known to serve a crucial role in tumor development by regulating gene transcription and expression [44,45,46]. Additionally, increasing research evidence has shown that epigenetic dysregulation is involved in drug resistance, including EGFR TKI resistance. As a histone methyltransferase, EHMT2 participates in multiple epigenetic regulatory processes [47]. A previous study reported that inhibitors of EHMT2 increase the sensitivity of NSCLC to EGFR-TKIs [10]. We showed here that higher HDAC1 expression induced EGFR-TKI resistance. This result was supported by other observations that the overexpression of HDACs was associated with acquired gefitinib resistance [48, 49]. In addition, some preclinical studies have shown the antitumor activity of HDAC inhibitors in NSCLC cells resistant to EGFR-TKIs [21,22,23]. These recent reports suggest the importance of potential mechanistic studies of HDACs in regulating EGFR-TKI resistance. Our study revealed a novel HDAC1/FOXK1-miR-33a pathway involved in regulating EGFR-TKI resistance.

HDAC1 is commonly known to participate in cellular epigenetic reprogramming as an epigenetic regulator. Here, we found that HDAC1 inhibited the transcriptional activation of miR-33a to induce EGFR-TKI resistance. MiR-33a was reported to inhibit the development of various types of cancer including lung cancer [50, 51]. It was also found that the transcription of EGFR related genes was strongly downregulated in mesenchymal stromal cells when miR-33a-3p was overexpressed, whereas miR-33a-3p inhibition upregulated EGFR, ERK2, and ERK3 [52]. However, similar studies of the role of miR-33a in the regulation of EGFR-TKI resistance have not yet been reported. We found that miR-33a regulated EGFR-TKI resistance in lung cancer by targeting ABCB7 and p70S6K1. Previous studies by our group demonstrated that blockade of S6K1 (p70S6K1) by the specific inhibitor PF-4,708,671 synergistically overcomes acquired resistance to EGFR-TKIs in NSCLC without notable toxicity [53]. Increasing evidence suggests that ABCB7 is involved in cancer development [54, 55] and chemoresistance [56]. However, to our knowledge, ABCB7 has not been reported to be involved in EGFR-TKI resistance.

Taken together, our study not only reveals a new mechanism underlying the epigenetic regulation of EGFR-TKI resistance, but also suggests a novel treatment strategy involving the use of HDAC1 inhibitors and targeting the FOXK1-miR-33a pathway to overcome TKI resistance in NSCLC therapy in the future.

Data availability

The data utilized and/or analyzed during this study are available from the corresponding author upon reasonable request.

Abbreviations

NSCLC:

non-small cell lung cancer

PCR:

polymerase chain reaction

3`UTR:

3`-untranslated regions

EGFR-TKIs:

EGFR tyrosine kinase inhibitors

SCLC:

small-cell lung cancer

EMT:

epithelial-to-mesenchymal transition

HDAC1:

Histone deacetylase 1

PEI:

polyethyleneimine

FOXK1:

Forkhead Box K1

NKG2D:

Natural killer group 2 member D

GEO:

Gene Expression Omnibus

DAPI:

4`,6-diamidino-2-phenylindole

CRC:

colorectal cancer

TRAIL:

TNF-related apoptosis-inducing ligand

FDA:

Food and Drug Administration

ABCB7:

ATP Binding Cassette Subfamily B Member 7

p70S6K1:

Phosphorylation and degradation of S6K1

LUAD:

Lung adenocarcinoma

LUSC:

Lung squamous cell carcinoma

SDS-PAGE:

Sodium dodecyl-sulfate polyacrylamide gel electrophoresis

TCGA:

The Cancer Genome Atlas

References

  1. Ghosh A, Yan H. Hydrogen bond analysis of the EGFR-ErbB3 heterodimer related to non-small cell lung cancer and drug resistance. J Theor Biol. 2019;464:63–71.

    Article  CAS  PubMed  Google Scholar 

  2. Lin JJ, Cardarella S, Lydon CA, Dahlberg SE, Jackman DM, Janne PA, Johnson BE. Five-year survival in EGFR-Mutant metastatic lung adenocarcinoma treated with EGFR-TKIs. J Thorac Oncol. 2016;11:556–65.

    Article  PubMed  Google Scholar 

  3. Soria JC, Ohe Y, Vansteenkiste J, Reungwetwattana T, Chewaskulyong B, Lee KH, Dechaphunkul A, Imamura F, Nogami N, Kurata T, et al. Osimertinib in untreated EGFR-Mutated Advanced Non-small-cell Lung Cancer. N Engl J Med. 2018;378:113–25.

    Article  CAS  PubMed  Google Scholar 

  4. Mok TS, Wu YL, Thongprasert S, Yang CH, Chu DT, Saijo N, Sunpaweravong P, Han B, Margono B, Ichinose Y, et al. Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma. N Engl J Med. 2009;361:947–57.

    Article  CAS  PubMed  Google Scholar 

  5. Oxnard GR, Thress KS, Alden RS, Lawrance R, Paweletz CP, Cantarini M, Yang JC, Barrett JC, Janne PA. Association between Plasma Genotyping and outcomes of treatment with Osimertinib (AZD9291) in Advanced Non-small-cell Lung Cancer. J Clin Oncol. 2016;34:3375–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Nakagawa T, Takeuchi S, Yamada T, Ebi H, Sano T, Nanjo S, Ishikawa D, Sato M, Hasegawa Y, Sekido Y, Yano S. EGFR-TKI resistance due to BIM polymorphism can be circumvented in combination with HDAC inhibition. Cancer Res. 2013;73:2428–34.

    Article  CAS  PubMed  Google Scholar 

  7. He J, Huang Z, Han L, Gong Y, Xie C. Mechanisms and management of 3rd–generation EGFR–TKI resistance in advanced non–small cell lung cancer (review). Int J Oncol 2021, 59.

  8. Chen Z, Chen Q, Cheng Z, Gu J, Feng W, Lei T, Huang J, Pu J, Chen X, Wang Z. Long non-coding RNA CASC9 promotes gefitinib resistance in NSCLC by epigenetic repression of DUSP1. Cell Death Dis. 2020;11:858.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Raoof S, Mulford IJ, Frisco-Cabanos H, Nangia V, Timonina D, Labrot E, Hafeez N, Bilton SJ, Drier Y, Ji F, et al. Targeting FGFR overcomes EMT-mediated resistance in EGFR mutant non-small cell lung cancer. Oncogene. 2019;38:6399–413.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Sun L, Gao L, Zhao Y, Wang Y, Xu Q, Zheng Y, Chen J, Wang H, Wang L. Understanding and targeting the epigenetic regulation to Overcome EGFR-TKIs Resistance in Human Cancer. Recent Pat Anticancer Drug Discov. 2023;18:506–16.

    Article  CAS  PubMed  Google Scholar 

  11. King J, Patel M, Chandrasekaran S. Metabolism, HDACs, and HDAC inhibitors: a systems Biology Perspective. Metabolites 2021, 11.

  12. Shao LW, Peng Q, Dong M, Gao K, Li Y, Li Y, Li CY, Liu Y. Histone deacetylase HDA-1 modulates mitochondrial stress response and longevity. Nat Commun. 2020;11:4639.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Cao LL, Song X, Pei L, Liu L, Wang H, Jia M. Histone deacetylase HDAC1 expression correlates with the progression and prognosis of lung cancer: a meta-analysis. Med (Baltim). 2017;96:e7663.

    Article  CAS  Google Scholar 

  14. Weichert W, Roske A, Niesporek S, Noske A, Buckendahl AC, Dietel M, Gekeler V, Boehm M, Beckers T, Denkert C. Class I histone deacetylase expression has independent prognostic impact in human colorectal cancer: specific role of class I histone deacetylases in vitro and in vivo. Clin Cancer Res. 2008;14:1669–77.

    Article  CAS  PubMed  Google Scholar 

  15. Senese S, Zaragoza K, Minardi S, Muradore I, Ronzoni S, Passafaro A, Bernard L, Draetta GF, Alcalay M, Seiser C, Chiocca S. Role for histone deacetylase 1 in human tumor cell proliferation. Mol Cell Biol. 2007;27:4784–95.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Zhang LL, Li Q, Zhong DS, Zhang WJ, Sun XJ, Zhu Y. MCM5 aggravates the HDAC1-Mediated malignant progression of Lung Cancer. Front Cell Dev Biol. 2021;9:669132.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Cho H, Son WC, Lee YS, Youn EJ, Kang CD, Park YS, Bae J. Differential effects of Histone Deacetylases on the expression of NKG2D ligands and NK cell-mediated anticancer immunity in Lung Cancer cells. Molecules 2021, 26.

  18. Mao G, Mu Z, Wu D. Exosome-derived mir-2682-5p suppresses cell viability and migration by HDAC1-silence-mediated upregulation of ADH1A in non-small cell lung cancer. Hum Exp Toxicol. 2021;40:S318–30.

    Article  CAS  PubMed  Google Scholar 

  19. Wang D, Li W, Zhao R, Chen L, Liu N, Tian Y, Zhao H, Xie M, Lu F, Fang Q, et al. Stabilized peptide HDAC inhibitors derived from HDAC1 substrate H3K56 for the treatment of Cancer Stem-Like cells in vivo. Cancer Res. 2019;79:1769–83.

    Article  CAS  PubMed  Google Scholar 

  20. He T, Gao Y, Fang Y, Zhang Y, Zhang S, Nan F, Ding J, Chen Y. The HDAC inhibitor GCJ-490A suppresses c-Met expression through IKKalpha and overcomes gefitinib resistance in non-small cell lung cancer. Cancer Biol Med. 2022;19:1172–92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Edwards A, Li J, Atadja P, Bhalla K, Haura EB. Effect of the histone deacetylase inhibitor LBH589 against epidermal growth factor receptor-dependent human lung cancer cells. Mol Cancer Ther. 2007;6:2515–24.

    Article  CAS  PubMed  Google Scholar 

  22. Witta SE, Gemmill RM, Hirsch FR, Coldren CD, Hedman K, Ravdel L, Helfrich B, Dziadziuszko R, Chan DC, Sugita M, et al. Restoring E-cadherin expression increases sensitivity to epidermal growth factor receptor inhibitors in lung cancer cell lines. Cancer Res. 2006;66:944–50.

    Article  CAS  PubMed  Google Scholar 

  23. Lin YC, Lin YC, Shih JY, Huang WJ, Chao SW, Chang YL, Chen CC. DUSP1 expression induced by HDAC1 inhibition mediates gefitinib sensitivity in non-small cell lung cancers. Clin Cancer Res. 2015;21:428–38.

    Article  CAS  PubMed  Google Scholar 

  24. Wang JH, Lee EJ, Ji M, Park SM. HDAC inhibitors, trichostatin A and valproic acid, increase E–cadherin and vimentin expression but inhibit migration and invasion of cholangiocarcinoma cells. Oncol Rep. 2018;40:346–54.

    CAS  PubMed  Google Scholar 

  25. Wang Y, Sun L, Qiu W, Qi W, Qi Y, Liu Z, Liu S, Lv J. Inhibiting forkhead box K1 induces autophagy to reverse epithelial-mesenchymal transition and metastasis in gastric cancer by regulating myc-associated zinc finger protein in an acidic microenvironment. Aging. 2020;12:6129–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Du M, Zhang Y, Mao Y, Mou J, Zhao J, Xue Q, Wang D, Huang J, Gao S, Gao Y. MiR-33a suppresses proliferation of NSCLC cells via targeting METTL3 mRNA. Biochem Biophys Res Commun. 2017;482:582–9.

    Article  CAS  PubMed  Google Scholar 

  27. Marquart TJ, Allen RM, Ory DS, Baldan A. miR-33 links SREBP-2 induction to repression of sterol transporters. Proc Natl Acad Sci U S A. 2010;107:12228–32.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Kang M, Li Y, Zhao Y, He S, Shi J. miR-33a inhibits cell proliferation and invasion by targeting CAND1 in lung cancer. Clin Transl Oncol. 2018;20:457–66.

    Article  CAS  PubMed  Google Scholar 

  29. Antoniali G, Dalla E, Mangiapane G, Zhao X, Jing X, Cheng Y, De Sanctis V, Ayyildiz D, Piazza S, Li M, Tell G. APE1 controls DICER1 expression in NSCLC through miR-33a and miR-130b. Cell Mol Life Sci. 2022;79:446.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Xu F, Wang Y, Ling Y, Zhou C, Wang H, Teschendorff AE, Zhao Y, Zhao H, He Y, Zhang G, Yang Z. dbDEMC 3.0: functional exploration of differentially expressed miRNAs in cancers of human and model organisms. Genomics Proteom Bioinf 2022.

  31. Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, Sun Y, Jacobsen A, Sinha R, Larsson E, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6:pl1.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Chandrashekar DS, Bashel B, Balasubramanya SAH, Creighton CJ, Ponce-Rodriguez I, Chakravarthi B, Varambally S. UALCAN: a portal for facilitating Tumor Subgroup Gene expression and survival analyses. Neoplasia. 2017;19:649–58.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Wang L, Qiu JG, He J, Liu WJ, Ge X, Zhou FM, Huang YX, Jiang BH, Liu LZ. Suppression of miR-143 contributes to overexpression of IL-6, HIF-1alpha and NF-kappaB p65 in cr(VI)-induced human exposure and tumor growth. Toxicol Appl Pharmacol. 2019;378:114603.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. He J, Qian X, Carpenter R, Xu Q, Wang L, Qi Y, Wang ZX, Liu LZ, Jiang BH. Repression of miR-143 mediates cr (VI)-induced tumor angiogenesis via IGF-IR/IRS1/ERK/IL-8 pathway. Toxicol Sci. 2013;134:26–38.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Ni J, Zhou LL, Ding L, Zhang XQ, Zhao X, Li H, Cao H, Liu S, Wang Z, Ma R, et al. Efatutazone and T0901317 exert synergistically therapeutic effects in acquired gefitinib-resistant lung adenocarcinoma cells. Cancer Med. 2018;7:1955–66.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Tellez CS, Grimes MJ, Picchi MA, Liu Y, March TH, Reed MD, Oganesian A, Taverna P, Belinsky SA. SGI-110 and entinostat therapy reduces lung tumor burden and reprograms the epigenome. Int J Cancer. 2014;135:2223–31.

    Article  CAS  PubMed  Google Scholar 

  37. Bondarev AD, Attwood MM, Jonsson J, Chubarev VN, Tarasov VV, Schioth HB. Recent developments of HDAC inhibitors: emerging indications and novel molecules. Br J Clin Pharmacol. 2021;87:4577–97.

    Article  PubMed  Google Scholar 

  38. Miyanaga A, Gemma A, Noro R, Kataoka K, Matsuda K, Nara M, Okano T, Seike M, Yoshimura A, Kawakami A, et al. Antitumor activity of histone deacetylase inhibitors in non-small cell lung cancer cells: development of a molecular predictive model. Mol Cancer Ther. 2008;7:1923–30.

    Article  CAS  PubMed  Google Scholar 

  39. Shanmugam G, Rakshit S, Sarkar K. HDAC inhibitors: targets for tumor therapy, immune modulation and lung diseases. Transl Oncol. 2022;16:101312.

    Article  CAS  PubMed  Google Scholar 

  40. Lee HY, Tang DW, Liu CY, Cho EC. A novel HDAC1/2 inhibitor suppresses colorectal cancer through apoptosis induction and cell cycle regulation. Chem Biol Interact. 2022;352:109778.

    Article  CAS  PubMed  Google Scholar 

  41. Kim SL, La MT, Shin MW, Kim SW, Kim HK. A novel HDAC1 inhibitor, CBUD–1001, exerts anticancer effects by modulating the apoptosis and EMT of colorectal cancer cells. Int J Oncol. 2020;57:1027–38.

    CAS  PubMed  Google Scholar 

  42. Shin MW, Kim SL, Yang HC, Yim SK, Seo SY, Lee ST, Kim HK, Kim SW. The HDAC1 inhibitor CBUD-1001 enhances TRAIL-induced apoptosis in Colorectal Cancer cells. Anticancer Res. 2021;41:4353–64.

    Article  CAS  PubMed  Google Scholar 

  43. Zhang Z, Zhang Q, Zhang H, Jiao M, Guo Z, Peng X, Fu L, Li J. Discovery of quinazolinyl-containing benzamides derivatives as novel HDAC1 inhibitors with in vitro and in vivo antitumor activities. Bioorg Chem. 2021;117:105407.

    Article  CAS  PubMed  Google Scholar 

  44. Pajares MJ, Alemany-Cosme E, Goni S, Bandres E, Palanca-Ballester C, Sandoval J. Epigenetic regulation of microRNAs in Cancer: shortening the Distance from Bench to Bedside. Int J Mol Sci 2021, 22.

  45. Acha-Sagredo A, Uko B, Pantazi P, Bediaga NG, Moschandrea C, Rainbow L, Marcus MW, Davies MPA, Field JK, Liloglou T. Long non-coding RNA dysregulation is a frequent event in non-small cell lung carcinoma pathogenesis. Br J Cancer. 2020;122:1050–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Sarkar S, Deyoung T, Ressler H, Chandler W. Brain tumors: Development, Drug Resistance, and sensitization - an Epigenetic Approach. Epigenetics. 2023;18:2237761.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Tian YF, Wang HC, Luo CW, Hung WC, Lin YH, Chen TY, Li CF, Lin CY, Pan MR. Preprogramming therapeutic response of PI3K/mTOR dual inhibitor via the regulation of EHMT2 and p27 in pancreatic cancer. Am J Cancer Res. 2018;8:1812–22.

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Wang Z, Tang F, Hu P, Wang Y, Gong J, Sun S, Xie C. HDAC6 promotes cell proliferation and confers resistance to gefitinib in lung adenocarcinoma. Oncol Rep. 2016;36:589–97.

    Article  CAS  PubMed  Google Scholar 

  49. Zang H, Qian G, Zong D, Fan S, Owonikoko TK, Ramalingam SS, Sun SY. Overcoming acquired resistance of epidermal growth factor receptor-mutant non-small cell lung cancer cells to osimertinib by combining osimertinib with the histone deacetylase inhibitor panobinostat (LBH589). Cancer. 2020;126:2024–33.

    Article  CAS  PubMed  Google Scholar 

  50. Pan J, Fang S, Tian H, Zhou C, Zhao X, Tian H, He J, Shen W, Meng X, Jin X, Gong Z. lncRNA JPX/miR-33a-5p/Twist1 axis regulates tumorigenesis and metastasis of lung cancer by activating Wnt/beta-catenin signaling. Mol Cancer. 2020;19:9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Wang Y, Zhao W, Zhang S. STAT3-induced upregulation of circCCDC66 facilitates the progression of non-small cell lung cancer by targeting miR-33a-5p/KPNA4 axis. Biomed Pharmacother. 2020;126:110019.

    Article  CAS  PubMed  Google Scholar 

  52. Costa V, Carina V, Raimondi L, De Luca A, Bellavia D, Conigliaro A, Salamanna F, Alessandro R, Fini M, Giavaresi G. MiR-33a controls hMSCS osteoblast commitment modulating the Yap/Taz expression through EGFR Signaling Regulation. Cells 2019, 8.

  53. Shen H, Wang GC, Li X, Ge X, Wang M, Shi ZM, Bhardwaj V, Wang ZX, Zinner RG, Peiper SC, et al. S6K1 blockade overcomes acquired resistance to EGFR-TKIs in non-small cell lung cancer. Oncogene. 2020;39:7181–95.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Feng S, Jia J, Lv G, Wang Y. Knockdown of ABCB7 inhibits esophageal cancer progression by inhibiting the TGF-beta/Smad signaling. Arch Biochem Biophys. 2023;742:109620.

    Article  CAS  PubMed  Google Scholar 

  55. Kim JY, Kim JK, Kim H. ABCB7 simultaneously regulates apoptotic and non-apoptotic cell death by modulating mitochondrial ROS and HIF1alpha-driven NFkappaB signaling. Oncogene. 2020;39:1969–82.

    Article  CAS  PubMed  Google Scholar 

  56. Po A, Citarella A, Catanzaro G, Besharat ZM, Trocchianesi S, Gianno F, Sabato C, Moretti M, De Smaele E, Vacca A, et al. Hedgehog-GLI signalling promotes chemoresistance through the regulation of ABC transporters in colorectal cancer cells. Sci Rep. 2020;10:13988.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This work was supported by the National Natural Science Foundation of China (grant numbers 82102916 and 82073393), the Science and Technology Research Project of Henan province (grant number LHGJ20210176), and Beijing Science and Technology Innovation Fund (grant number KC2021-JX-0186-44).

Author information

Authors and Affiliations

  1. The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China

    Jie Liu, Wenjing Liu, Yanqiu Zhao & Bing-Hua Jiang

  2. Academy of Medical Sciences, Zhengzhou University, Zhengzhou, 450000, China

    Wei Wang, Kunkun Wang & Lin Wang

  3. Department of Prenatal Diagnosis Center, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, 450052, China

    Xiao Han

Authors
  1. Jie Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kunkun Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wenjing Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yanqiu Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xiao Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Lin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Bing-Hua Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization, LW and BHJ; data curation, XH, WW, and WJL; funding acquisition, JL and BHJ; investigation, YQZ, WW, and KKW; methodology, WW, JL, YQZ, and KKW; writing (original draft), JL, XH, and WJL; writing (review and editing), LW and BHJ. All authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Lin Wang or Bing-Hua Jiang.

Ethics declarations

Ethics approval and consent to participate

The study was approved by Ethics Committee of Zhengzhou University. The study was conducted in accordance with the local legislation and institutional requirements.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, J., Wang, W., Wang, K. et al. HDAC1 and FOXK1 mediate EGFR-TKI resistance of non-small cell lung cancer through miR-33a silencing. J Transl Med 22, 793 (2024). https://doi.org/10.1186/s12967-024-05563-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12967-024-05563-3

Keywords

Journal of Translational Medicine

ISSN: 1479-5876

Contact us