Excerpts from the 1st international NTNU symposium on current and future clinical biomarkers of cancer: innovation and implementation, June 16th and 17th 2016, Trondheim, Norway
- Ana I. Robles1,
- Karina Standahl Olsen2,
- Dana W.T. Tsui3,
- Vassilis Georgoulias4,
- Jenette Creaney5,
- Katalin Dobra6,
- Mogens Vyberg7,
- Nagahiro Minato8,
- Robert A. Anders9,
- Anne-Lise Børresen-Dale10,
- Jianwei Zhou11,
- Pål Sætrom12,
- Boye Schnack Nielsen13,
- Michaela B. Kirschner14,
- Hans E. Krokan15,
- Vassiliki Papadimitrakopoulou16,
- Ioannis Tsamardinos17 and
- Oluf D. Røe15, 18, 19Email author
© The Author(s) 2016
Received: 1 September 2016
Accepted: 10 October 2016
Published: 19 October 2016
The goal of biomarker research is to identify clinically valid markers. Despite decades of research there has been disappointingly few molecules or techniques that are in use today. The “1st International NTNU Symposium on Current and Future Clinical Biomarkers of Cancer: Innovation and Implementation”, was held June 16th and 17th 2016, at the Knowledge Center of the St. Olavs Hospital in Trondheim, Norway, under the auspices of the Norwegian University of Science and Technology (NTNU) and the HUNT biobank and research center. The Symposium attracted approximately 100 attendees and invited speakers from 12 countries and 4 continents. In this Symposium original research and overviews on diagnostic, predictive and prognostic cancer biomarkers in serum, plasma, urine, pleural fluid and tumor, circulating tumor cells and bioinformatics as well as how to implement biomarkers in clinical trials were presented. Senior researchers and young investigators presented, reviewed and vividly discussed important new developments in the field of clinical biomarkers of cancer, with the goal of accelerating biomarker research and implementation. The excerpts of this symposium aim to give a cutting-edge overview and insight on some highly important aspects of clinical cancer biomarkers to-date to connect molecular innovation with clinical implementation to eventually improve patient care.
The “1st international NTNU symposium on current and future clinical biomarkers of cancer: innovation and implementation”, was held June 16th and 17th 2016, at the knowledge center of the St. Olavs Hospital in Trondheim, Norway, under the auspices of the Norwegian University of Science and Technology (NTNU) and the HUNT biobank and research center. The Symposium attracted approximately 100 attendees and invited speakers from 12 countries and 4 continents. Senior researchers and young investigators presented, reviewed and vividly discussed important new developments in the field of clinical biomarkers of cancer, with the goal of accelerating biomarker research and implementation.
Inspiration for arranging this Symposium in Trondheim came from worldwide rapid developments in the biomarker field and current research based on the Norwegian Nord-Trøndelag Health Study (HUNT), a population study founded in 1986 that has evolved to become a Biobank and Research Center under the NTNU (http://www.mensxmachina.org/cancer_biomarker_hunt/index.html). The center is situated in Levanger and houses hundreds of clinical data variables, serum and DNA from about 120,000 people that are accessible for researchers. The meeting highlighted the unique potential and growing network around this resource, as well as the necessity of discussing clinical cancer biomarkers and their implementation in a broad forum.
The Symposium served to remind us that cancer is a collection of very heterogeneous diseases, making molecular sub grouping increasingly relevant for diagnosis and treatment. Since the discovery of the estrogen receptor in breast cancer, science has unraveled hundreds of clinically relevant diagnostic, prognostic, predictive and therapeutic molecular markers of cancer, including HER2, KRAS, EGFR, ALK, BRAF, CTL4, PD1 and PD-L1, circulating tumor cells, protein and gene signatures, and microRNAs. New epigenetic and metabolic markers are also entering the stage, increasing the potential as well as the complexity of targeted treatments for defined groups of cancer patients. However, few markers have passed all clinical development and validation phases and are actually in clinical use today. Following the initial discovery, the road taking a biomarker to clinical use is usually long and complex. Moreover, clinicians should always be aware of caveats that affect a biomarker’s broad applicability.
An iconic example is HER2/ERBB2 in breast cancer, initially discovered as a negative prognostic marker, it has now become a positive predictive marker due to the receptor’s “targetability” with trastuzumab, pertuzumab and other agents. This observation urges for the need for a set of accurate molecular diagnostic tests for each treatment strategy. For example, the potential of the immune system to attack cancer cells using the PD1/PD-L1 interaction, one of the most important breakthroughs that change the cancer therapeutic algorithm in recent years. However, about one-third of the cases respond to anti-PD1 monotherapy , and with the current cost of the treatment, picking the right patients will be of enormous value, not only for the patients but also the society. But are biomarkers for immune checkpoint therapy ready for use? Lastly, it is becoming apparent that detection of microRNAs or other molecules in circulation could be the first sign of early stage cancer, and could eventually become a blood test that saves thousands of lives. How far in the process are those tests? To reach the goals of true precision medicine and fulfill the Cancer Moonshot initiative  we need to valid these biomarkers and their accompanying diagnostic tests in the appropriate environment.
The excerpts of this symposium aim to give a cutting-edge overview and insight on some highly important aspects of clinical cancer biomarkers to-date to connect molecular innovation with clinical implementation to eventually improve patient care.
Biomarkers in serum, plasma, urine and pleural fluid
Diagnostic, prognostic and predictive: catching all in one test, and how early?
MicroRNAs in serum 1–4 years before diagnosis of lung cancer. Significantly differentially expressed microRNAs targeted genes of several pathways that were enriched, including known pathways of their respective cancer types
SCLC vs controls
Small cell lung cancer
NSCLC vs controls
Non-small cell lung cancer
How many years before a clinical diagnosis can a cancer signature be detected? In a large Norwegian study presented by Karina Standahl Olsen, Department of Community Medicine, UiT The Artic University of Norway, Tromsø, Norway the answer was “Blood gene expression profiles reflect temporality and clinical parameters up to 6 years before breast cancer diagnosis—The Norwegian Women and Cancer Post-genome cohort (Kvinner og Kreft studien). Since the understanding of time related aspects of systemic processes during carcinogenesis is very limited, this study aimed to identify time- and metastasis-related blood gene expression patterns present years before cancer diagnosis. Blood samples were collected prospectively from healthy, middle-aged women participating in the Norwegian Women and Cancer Post-genome cohort. Breast cancer cases were identified via linkage to the Cancer Registry of Norway, and matched controls were drawn from the cohort biobank. Full-blood gene expression was measured using Illumina Bead chips. The Cancer Registry provided information on time of diagnosis relative to screening visits, and on lymph node status. The included 441 case–control pairs were ranked according to the time interval between blood sampling and cancer diagnosis, providing information on blood gene expression up to six years before diagnosis. A non-parametric statistical method was developed to study changes in gene expression over time, named curve group analysis, which detects small gene expression differences that vary over time, and groups genes that display similar expression curves . Blood gene expression differences between breast cancer cases and controls were dependent on time, and were strongest in the last year before diagnosis. Gene expression curves in the six years before diagnosis were only evident when stratifying cases according to mode of cancer detection and lymph node status. The study concludes that blood gene expression patterns do reflect clinical variability and temporality in the years before breast cancer diagnosis. These findings hold promise of increased insight into previously un-reachable aspects of systemic cancer biology. Blood gene expression patterns may be explored as potential biomarkers and/or used for development of tests .
Decades of studies on circulating tumor cells (CTC) have shown promise, but still not found a place in the clinic, In his talk “Circulating Tumor Cells in early and recurrent breast cancer: Research and clinical applications” Vassilis Georgoulias, leading the research at the Department of Medical Oncology, School of Medicine, University of Crete, Greece reported data indicating that the detection of CTCs in patients with early stage breast cancer is an independent unfavorable prognostic factor for disease recurrence and disease-related death [18, 19] since CTCs cannot be eliminated by adjuvant chemotherapy or hormone treatment in almost 50 % of the patients, probably because of their non-proliferating and/or dormant state. In addition, the measurement of CTCs in patients with metastatic disease (MBC) revealed that their increased number is associated with a decreased overall survival whereas numerous studies have reported that their decrease after one cycle of chemotherapy is associated with improved survival. Immunofluorescence studies have demonstrated that CTCs express phosphorylated EGFR (pEGFR) as well as HER2 (+) in 60–70 % of EBC patients, irrespective of the HER2 status of the primary tumor cells.
In a proof of principle study, pre-treated patients with MBC and pEGFR-expressing CTCs were treated with gefitinib, a specific tyrosine kinase inhibitor of the EGFR. A median reduction of 96.4 and 94.1 % in CTC count was observed in 11 of the 17 patients after one treatment cycle; it is to note, that after the 3rd course, most detected CTCs were pEGFR (−). One patient achieved a partial response and in two patients the progression-free survival (PFS) was 16.0 and 19.0 months. Similar results were obtained with lapatinib, a dual EGFR and HER2 tyrosine kinase inhibitor, as well as with trastuzumab, a monoclonal antibody against HER2. A randomized phase II study evaluating trastuzumab versus observation in women with HER2 (−) early breast cancer and detectable CTCs before and after adjuvant chemotherapy demonstrated a significantly higher disease free survival (DFS) in the treated patients compared to those who received the standard treatment [19, 20]. These data support the phenotypic and biological characterization of CTCs providing valuable information regarding molecular targets that may lead to a more selected and individualized treatment of patients with breast cancer.
Malignant mesothelioma is an asbestos-induced, aggressive tumor with limited treatment options and very poor outcome; median survival is less than 12 months and 5-year survival rates of between 5 and 10 % have been reported . Development of mesothelioma-specific biomarkers is an active area of research aimed not only at enhancing clinical care but also providing a means to screen at-risk asbestos exposed populations for early intervention . Soluble mesothelin is the most intensively investigated mesothelioma biomarker and has been approved by the USA Food and Drug Administration as a tool for monitoring mesothelioma patient response and progression  The limited expression of the molecule on normal, nonmalignant tissue makes mesothelin an attractive therapeutic target as well as a diagnostic biomarker. Jenette Creaney, National Centre for Asbestos Related Disease, University of Western Australia presented “Mesothelin, discovery of a diagnostic marker that became a target”. For over fifteen years strategies have been pursued to target mesothelin-expressing cells using antibody-based therapies several of which are being evaluated in the clinical setting. Some of these studies have produced spectacular tumor regressions in some patients. Preliminary results of these early trials have been encouraging, although many different treatment strategies are being pursued ranging from more non-specific immunotherapy approaches to personalized neo-antigen vaccine development.
The molecular landscape and bio signature of various malignancies is highly variable at this location and it requires detailed molecular characterisation [25–27] and optimized algorithms  to allow personalized treatment options and targeted therapy [29, 30]. In her presentation “Pleural effusion and bio-signature”, Katalin Dobra, Department of Laboratory Medicine, Division of Pathology Karolinska University Hospital in Huddinge, Sweden discussed their work.
Time to diagnosis by cytology versus histology in 77 epithelioid and mixed types of malignant pleural mesothelioma were studied. All diagnoses were supported by clinical findings, including CT scans. Clinical data, including evaluation of responses, were retrieved from hospital archives and survival data were obtained from the Swedish population database. The results showed that median time for diagnosis was 1 month less for cytology compared to histology. Preliminary data showed that the proportion of patients surviving 3 years was significantly better (p = 0,02) following a diagnosis based on effusion cytology, among treated patients 9/26 (38 %) versus only 1/23 (4 %), the median survival being 23 months and 14 months, respectively. The rate of initial responses to chemotherapy (stable disease + partial response) was slightly better in the cytology group. The earlier MM diagnosis obtained with effusion cytology seem to improve the overall survival after chemotherapy. Their findings show the importance of the cytological diagnosis and encourage the initiation of treatment as soon as the diagnosis is obtained.
Biomarkers in tumors
From the “gold-standard” immunohistochemistry to miR qISH, multi-level molecular analyses, immune checkpoint markers, DNA repair and novel clinical trial designs for diagnosis, stratification and avoiding overtreatment
Immunohistochemistry (IHC) has traditionally been employed in surgical pathology as an ancillary test in the analysis and classification of cancers. The availability of antibodies to cell specific proteins, and more recently to organ restricted transcription factors, has improved the accuracy of tumor diagnoses. Increasing numbers of tumors are defined by their underlying molecular alterations identifiable by IHC. Thus, as a protein based technique, IHC can act as a rapid and inexpensive surrogate for molecular studies. However, pre-analytical issues (e.g. improper tissue handling), analytical issues (e.g. less successful antibody clones, insufficient epitope retrieval, insensitive visualization systems) and post analytical issues (inconsistent reading and interpretation) frequently hamper the diagnostic utility of IHC.
In his talk “Immunohistochemistry in cancer diagnosis, the pitfalls and the future” Mogens Vyberg, Institute of Pathology, Aalborg University Hospital, Denmark explained how external quality assurance (EQA) of IHC, common definitions of controls, and digital image analysis are required to improve the reliability of IHC.
Since the proposal of cancer immunosurveillance concept by Burnet and Smith more than a half-century ago, numerous attempts of cancer immunotherapy have been made. Currently, immune checkpoint blockade therapy is revolutionizing cancer therapy, where one target is PD-1, originally discovered by Dr. Honjo’s group at Kyoto University in 1992, a TCR-coinhibitory receptor and playing a crucial role in the checkpoint of T-cell self-tolerance. One of the discoverers of the PD1 antibody and its function, Nagahiro Minato, Department of Immunology and Cell Biology, Graduate School of Medicine, Kyoto University, Japan took us through “PD-1 checkpoint blockade for cancer immunotherapy: History and future perspectives”.
In 2002, his group reported that the PD-1 checkpoint also takes an important role in restraining endogenous anti-tumor immunity, and demonstrated that the blockade of the PD-1 checkpoint provides a potent therapeutic effect on tumors in animal models. The proposal for PD-1 checkpoint cancer immunotherapy was followed by a number of reports for beneficial effects of humanized anti-PD-1 or anti-PD-L1 antibodies in large-scale human clinical trials for various types of cancers since 2012. FDA approved humanized anti-PD-1 antibody for melanoma in 2014 and for non-small and small cell lung cancers in 2015, and currently hundreds of clinical studies including various combination therapies and many cancer types are underway worldwide. In parallel, studies on biomarkers affecting the efficacy of the therapy are also in progress from diverse aspects. PD-L1 expression can be induced on cancer cells in various conditions, including microenvironmental stress such as inflammation, and irreversible genomic changes in cancer cells. A recent report has indicated that varying proportions of multiple human cancers show recurrent structural changes in PD-L1 gene locus at 3′ UT region, which leads to a remarkable increase in PD-L1 expression . Somatic mutations that occur frequently in cancer cells may lead to the emergence of potential neo-antigens, particularly when cancer cells have defective mismatch-repair capacity, recruiting and activating effector T cells with additional repertoire under checkpoint blockade . Large-scale studies under the support of Society for Immunotherapy of Cancer, for instance, have reinforced a significant prognostic value of immunoscore with standardized methodology in multiple cancers . Since the effects of checkpoint blockade immunotherapy count on endogenous immune response, verification of host immune status at tumor sites should also provide valuable biomarkers in his talk the history of PD-1 discovery, basic immuno biological studies, and several important future perspectives on PD-1 checkpoint blockade cancer immunotherapy were discussed.
Some cancers, including melanoma, kidney, and lung cancer, are naturally immunogenic, and can respond to checkpoint inhibitor therapy (anti-CTL4 or anti-PD1/L1). These agents block the physiologic stop signals that have been co-opted by tumor cells in order to evade a patient’s immune response. Checkpoint inhibitor blockade has demonstrated that a patient’s immune system can eliminate even widely metastatic cancer. There has been attention on defining the prognostic and predictive power of checkpoint inhibitors. The PD-L1 protein has been explored for its prognostic and predictive ability, discussed by Robert A. Anders, Johns Hopkins University, Baltimore, USA, in his talk “Prognostic and predictive role of PD1 and PD-L1 in cancers”. The prognostic role of PD-L1 expression in cancers is tumor type dependent. On the one hand PD-L1 expression indicates a better prognosis in melanoma and lung cancer. On the other hand it is a poor prognostic in gastric and kidney cancer. There are both technical and biologic reasons for these discrepancies. First, determining if a cancer expresses PD-L1 is complicated by the required level of expression, the type of cells expressing PD-L1 and the cellular location of PD-L1.
Second, each cancer type can have different tumor microenvironments.
The role of complex cancer biomarkers was further discussed by Anne-Lise Børresen-Dale, Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital The Norwegian Radiumhospital, Oslo, Norway in her talk “Role of multilevel molecular analyses in reducing over-treatment in breast cancer”. Several known prognostic factors are used to identify breast cancer patients with an unfavorable prognosis, such as tumor size, histological grade, hormone receptor status and axillary lymph node metastasis. However, a large majority of early stage breast cancer patients with small primary tumors receive such treatment without being at risk of developing recurrent disease. Thus a more precise stratification for treatment decisions is thus highly needed. A detailed characterization of the individual breast tumors at the molecular level may improve individualized prognostication and treatment decisions. High-throughput molecular analyses of tumor tissue at DNA, (copy number and methylation) mRNA, miRNA, protein (using reverse phase protein arrays, RPPA), and metabolic (HR-MAS MR) levels were performed. Dr. Børresen-Dale’s group has explored to which extent combining the various profiles derived from each level, can further subdivide the initially discovered PAM 50 expression subclasses [42, 43] and improve prognostic potential in individual patients. Combined analyses of gene regulation at various levels may point to specific biological functions and molecular pathways that are deregulated in individual breast cancers and may reveal novel subgroups of patients for tailored therapy and monitoring .
Several of the molecular layers, both individually and combined, could split the ER positive Luminal A group, the most frequent subtype of breast cancer, into two subgroups with different survival. The identification of patients with low-risk Luminal A tumors using a set of methylation markers  or a set of miRNAs  will guide in selecting patients not benefitting from further adjuvant treatment.
Gastric cancer is the fourth most common cancer and the second leading cause of cancer-related death worldwide. Chemotherapy both in resectable and advanced disease has only limited efficacy. There are no clinically validated prognostic or predictive biomarkers, and in his presentation “JWA and XRCC1 as predictive and prognostic factors in gastric cancer”, Jianwei Zhou, Department of Molecular Cell Biology & Toxicology, Cancer Center, School of Public Health, Nanjing Medical University, People’s Republic of China, took us through the journey of discovering the JWA and how it could be a valid clinical marker alone and together with XRCC1.
JWA and XRCC1 expression status in resectable gastric cancer cases treated with adjuvant chemotherapy compared with surgery was tested in a first training cohort, a second testing cohort and finally in a validation cohort (n = 80, 374 and 385 respectively)  showing that protein levels of both were significantly downregulated in gastric cancer lesions compared with adjacent non-cancerous tissues. Low tumoral JWA or XRCC1 expression significantly correlated with shorter overall survival (OS) and multivariate regression analysis showed that low JWA and XRCC1 expression, separately and together, were independent negative markers of OS. Adjuvant fluorouracil-leucovorin-oxaliplatin (FLO) significantly improved OS compared with surgery alone. However, this effect was evident only in the JWA or XRCC1 low expression group; similar effect was also observed in patients with fluorouracil- leucovorin-platinum (FLP) regimen for JWA and XRCC1. Therefore, JWA and XRCC1 protein expression in tumor are novel candidate prognostic markers and predictive factors for benefit of adjuvant platinum-based chemotherapy (FLO or FLP) in resectable human gastric carcinoma.
Further molecular analyses on the roles of JWA and XRCC1 were performed in cisplatin sensitive (SGC7901, BGC823) and resistant (SGC7901/DDP, BGC823/DDP) human gastric cancer cells and unraveled mechanistically that JWA regulated cisplatin induced DNA damage and apoptosis through CK2—P-XRCC1—XRCC1 pathway, indicating a putative target for reversing cisplatin resistance in gastric cancer .
The first two microRNAs (miRNAs) discovered—lin-4 in 1993 and let-7 in 2000—have critical roles in worm development, as loss of either results in retarded worm development due to lack of cell differentiation. Consequently, when miRNAs were recognized as a large and highly conserved class of genes in 2001, scientists quickly surmised miRNAs potential in cancer biology. Indeed, cancers are characterized by altered miRNA expression profiles and individual miRNAs can act as oncogenes and tumor suppressors. In his presentation “From worm to man: Discovery of microRNA and current potential as clinical biomarkers and targets”, Pål Sætrom, Department of Computer and Information Science took us through why microRNAs are considered promising candidates both as cancer biomarkers and as therapeutic targets. To illustrate, PubMed has presently indexed more than 60,000 papers and abstracts on miRNAs; 40 % of these are about cancer.
MicroRNAs are short, non-coding RNAs comprising 18–23 nucleotides, and more than 2000 microRNAs have been reported in the human genome. MicroRNAs exert cell-specific activity by binding to the 3′UTR of mRNAs and thereby negatively regulating translation. The mature microRNAs are bound in protein complexes in which they are stable in tissues and blood. Most current therapeutic strategies aim to address tumor imbalance in miRNA expression and individual miRNA’s role as oncogene or tumor suppressor. Specifically, tumors with down-regulated miRNAs that are tumor suppressors are treated by introducing molecules that mimic miRNAs, whereas tumors with up-regulated oncogenic miRNAs are treated by introducing molecules (anti-miRs) that prevent the oncomirs from binding their target RNAs. Currently, a mimic for miR-34 is in clinical trials for liver cancer, whereas multiple anti-miRs are at the preclinical stage for different cancers .
Most current therapeutic strategies aim to affect miRNAs canonical roles in regulating protein coding genes post transcription in the cytoplasm. However, miRNAs can also regulate genes by affecting gene transcription in the nucleus. Others and we have shown that artificial miRNA-like RNAs, so-called short activating RNAs (saRNAs) can transcriptionally up-regulate target genes . One such saRNA, targeting the transcription factor CCAAT/enhancer-binding protein alpha (CEBPA), can reduce tumor burden and improve liver function in liver cancer models and is currently in clinical Phase 1.
MicroRNAs can function as predictors and prognosticators in several types of cancer. For malignant pleural mesothelioma (MPM) prognosis is poor, but a subset of patients treated with multimodal treatment can have a long survival. However, this treatment is highly invasive and stressful for the patients, and there are no markers to predict outcome in this patient group. In “MicroRNAs as prognostic biomarkers for survival in surgically treated malignant pleural mesothelioma patients”, Michaela B Kirschner, Division of Thoracic Surgery, University Hospital Zurich, Switzerland presented the possibility of using a microRNA expression signature as prognostic factor for patients considered for multimodality treatment including surgical resection. This study used three independent series of MPM tumor samples: Series 1–3 were samples from 48 extrapleural pneumonectomies (EPP), 43 pleurectomy/decortications (P/D) and 100 EPP with matching diagnostic biopsies respectively. MicroRNA expression was analyzed by RT-qPCR and associations with survival are assessed by Kaplan–Meier log-rank analysis. In addition, a microRNA expression signature (miR-Score) for prediction of good prognosis (≥20 months survival) was built using binary logistic regression modeling, and evaluated by receiver operating characteristics curve analysis. The miR-Score including 6 microRNAs (miR−21, −23a, −30e, −221, −222, −31) was able to predict a good prognosis with an accuracy of 92.3 % in patients undergoing EPP and an accuracy of 71.9 % in patients receiving P/D. Score-positive patients showed increased median overall survival of 23 and 9 months for EPP and P/D, respectively. Hazard ratios for score-negative patients were 4.12 (95 % CI: 2.03–8.37, p = 0.00001) for EPP and 1.93 (95 % CI: 1.01–3.69, p = 0.047) for P/D. Furthermore, adding the miR-Score to a prognostic model consisting of clinical factors resulted in improved accuracy .
Further investigations on the effect of chemotherapy and the prognostic value of the miR-Score in series 3 are currently ongoing. In conclusion this study has identified a novel microRNA signature with prognostic value in MPM patients. Ongoing validation and refinement of the miR-Score has the potential to provide a novel biomarker for more accurate selection of MPM patients considered for multimodality treatment.
DNA repair is essential for cell survival and prevention of mutations and cancer. In addition, DNA repair is intimately integrated with immunity. In “DNA Repair in diagnosis and therapy of cancer—opportunities and problems”, Hans E. Krokan, Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology (NTNU) Trondheim, Norway, presented a historical overview of the DNA repair field an current implications. It has been known since 1968 that DNA excision repair deficiency causes sensitivity to UV-light and skin cancer in Xeroderma pigmentosum . It is now known that more common cancers can be caused by unrepaired DNA damage and repair deficiencies. Thus, inactivation of double strand break repair (DSBR) due to BRCA1 or 2 gene mutations results in defective DSBR and strongly increased risk of early onset breast cancer and ovarian cancer. A potential upside is that BRCA1/2-defective cancers are sensitive to single strand break repair protein poly(ADP)ribose polymerase (PARP) inhibitors, due to synthetic lethality . DNA mismatch-repair deficiency similarly causes hereditary non-polyposis colorectal cancer and several less common other cancers, the diagnosis of which is important to initiate preventive measures. Glioblastoma is a deadly form of brain tumor that is frequently deficient in direct repair of O6 methyl guanine by O6-meG-DNA methyltransferase (MGMT). MGMT-deficient tumors are sensitive to the methylating agent temozolomide (TMZ), whereas MGMT-overexpression causes TMZ resistance. Furthermore, untargeted DNA-cytosine deamination by AID/APOBECs causes increased genomic uracil and AID/APOBEC mutational signatures in B-cell malignancies and several other types of cancer. In line with this, it was observed that clustered mutations (kataegis) in B-cell malignancies predominantly carry AID-hotspot mutational signatures . Thus, AID/APOBEC-induced mutagenic U: G mismatches in DNA left unrepaired may be one fundamental and relatively common cause of several malignancies.
With the availability of widespread genomic sequencing, and the introduction of specific targeted agents for subsets of patients with adenocarcinoma, survival for patients with non-squamous metastatic non-small cell lung cancer (NSCLC) squamous cell cancer (SCC) has significantly improved [60, 61]. Comprehensive genomic surveys, have also vastly improved our understanding of the mutational profile of SCC . The Cancer Genome Atlas Project (TCGA) extensively profiled 178 SCC tumor specimens for genomic alterations and identified that TP53 was almost universally mutated in the tumor samples, but other genes such as CDKN2A/RB1, NFE2L2/KEAP1/CUL3, PI3 K/AKT, and SOX2/TP63/NOTCH1 signaling pathways were also commonly altered .
Handling of multiple datasets for biomarker discovery and validation
Bioinformatics is one of the most important keys in transforming molecular data to a clinically valid test
Clinical, epidemiological, environmental, molecular, and genetic data related to cancer are becoming more and more available. A main computational analysis task of these data is to identify the minimal-size sets of biomarkers and biosignatures that collectively carry all the information for optimal prediction or diagnosis of the outcome of interest (e.g., cancer stage, survival, metastasis, etc.). In his talk “Automated Computational Discovery of Biomarkers and Biosignatures from Data Using Machine Learning” Ioannis Tsamardinos, Department of Computer Science, University of Crete, Heraklion, Greece takes on his experience on biosignatures with these properties which provide useful insight to the causal mechanisms of disease or can be used for devising diagnostic tests of minimal cost. Computational methods that try to solve this problem may for example return a minimum set of genes and environmental factors whose interactions, collectively best predict metastasis. Tsamardinos also presented the computational problems arising when trying to identify biosignatures, such as identifying one or all equivalent biosignatures, constructing predictive models from their measurements, estimating the performance of the predictions, tuning the algorithms for optimal prediction performance, identifying anomalous cases (e.g., outliers), and estimating the information value of obtaining new samples. Finally he presented related computational tools, libraries, and an automated, intelligent analysis pipeline for use by a non-expert that can perform a quality-analysis with a few clicks. The pipeline is demonstrated on several cancer prediction and diagnostic related problems.
Through these Symposium presentations, the plurality, the various applications but also the pitfalls of current and potential future cancer biomarkers have been demonstrated. The use of tumor tissue is still the gold standard for diagnostic, prognostic and predictive biomarkers, including immunoscore of TILs, but circulating cells, tumor DNA and microRNA in blood are currently entering clinical practice. Multi-omics, poly-markers or multi-level tests may also be of high importance, as single type of molecules rarely can be sufficient to describe heterogeneous tumors. Pleural fluid and urine contain clinically relevant biological information, exemplified in mesothelioma and lung cancer. Bioinformatics is key to analysis, discovery and validation of biomarkers. Clinical use of biomarkers is hampered by their variable sensitivity and/specificity due to technical/laboratory variations and the heterogeneity of cancer phenotypes. Analysis of both ready-to-use open source high-throughput data as the TCGA but also of large prospective biobanks as the HUNT will be crucial for the timely discovery of non-invasive early diagnostic as well as predictive and prognostic markers. Finally, the integration of molecular knowledge in clinical trials was highlighted and seems likely be a key point for every future clinical study.
The Symposium excerpts were selected and summarized by ODR. Each presenter mentioned in the text carried the responsibility of writing their respective parts with their respective figures and tables and agreed to the final version of the manuscript. All authors read and approved the final manuscript.
We whish to thank all sponsors and supporters of the Symposium, the NTNU, the HUNT Research Center, Boeringer Ingelheim, Bristol Myers Squibb, Norwegian Biochemical Society, Roche, Astra Zeneca, Amgen, the PROMEC of NTNU, International Union of Basic and Clinical Pharmacology, Gastrointestinal Section, the organizing committee and international faculty.
The authors declare that they have no competing interests.
There was no funding for writing this meeting report.
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