MicroRNAs as biomarkers for prostate cancer prognosis: a systematic review and a systematic reanalysis of public data.

BACKGROUND: Reliable prognostic biomarkers to distinguish indolent from aggressive prostate cancer (PCa) are lacking. Many studies investigated microRNAs (miRs) as PCa prognostic biomarkers, often reporting inconsistent findings. We present a systematic review of these; also systematic reanalysis of public miR-profile datasets to identify tissue-derived miRs prognostic of biochemical recurrence (BCR) in patients undergoing radical prostatectomy. METHODS: Independent PubMed searches were performed for relevant articles from January 2007 to December 2019. For the review, 128 studies were included. Pooled-hazard-ratios (HRs) for miRs in multiple studies were calculated using a random-effects model (REM). For the reanalysis, five studies were included and Cox proportional-hazard models, testing miR association with BCR, performed for miRs profiled in all. RESULTS: Systematic review identified 120 miRs as prognostic. Five (let-7b-5p, miR-145-5p, miR152-3p, miR-195-5p, miR-224-5p) were consistently associated with progression in multiple cohorts/studies. In the reanalysis, ten (let-7a-5p, miR-148a-3p, miR-203a-3p, miR-26b-5p, miR30a-3p, miR-30c-5p, miR-30e-3p, miR-374a-5p, miR-425-3p, miR-582-5p) were significantly prognostic of BCR. Of these, miR-148a-3p (HR = 0.80/95% CI = 0.68-0.94) and miR-582-5p (HR = 0.73/95% CI = 0.61-0.87) were also reported in prior publication(s) in the review. CONCLUSIONS: Fifteen miRs were consistently associated with disease progression in multiple publications or datasets. Further research into their biological roles is warranted to support investigations into their performance as prognostic PCa biomarkers.

Whole-genome characterization of chemoresistant ovarian cancer.

Patients with high-grade serous ovarian cancer (HGSC) have experienced little improvement in overall survival, and standard treatment has not advanced beyond platinum-based combination chemotherapy, during the past 30 years. To understand the drivers of clinical phenotypes better, here we use whole-genome sequencing of tumour and germline DNA samples from 92 patients with primary refractory, resistant, sensitive and matched acquired resistant disease. We show that gene breakage commonly inactivates the tumour suppressors RB1, NF1, RAD51B and PTEN in HGSC, and contributes to acquired chemotherapy resistance. CCNE1 amplification was common in primary resistant and refractory disease. We observed several molecular events associated with acquired resistance, including multiple independent reversions of germline BRCA1 or BRCA2 mutations in individual patients, loss of BRCA1 promoter methylation, an alteration in molecular subtype, and recurrent promoter fusion associated with overexpression of the drug efflux pump MDR1.

A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization.

Genetic screens in cancer cell lines inform gene function and drug discovery. More comprehensive screen datasets with multi-omics data are needed to enhance opportunities to functionally map genetic vulnerabilities. Here, we construct a second-generation map of cancer dependencies by annotating 930 cancer cell lines with multi-omic data and analyze relationships between molecular markers and cancer dependencies derived from CRISPR-Cas9 screens. We identify dependency-associated gene expression markers beyond driver genes, and observe many gene addiction relationships driven by gain of function rather than synthetic lethal effects. By combining clinically informed dependency-marker associations with protein-protein interaction networks, we identify 370 anti-cancer priority targets for 27 cancer types, many of which have network-based evidence of a functional link with a marker in a cancer type. Mapping these targets to sequenced tumor cohorts identifies tractable targets in different cancer types. This target prioritization map enhances understanding of gene dependencies and identifies candidate anti-cancer targets for drug development.

A mathematical-descriptor of tumor-mesoscopic-structure from computed-tomography images annotates prognostic- and molecular-phenotypes of epithelial ovarian cancer.

The five-year survival rate of epithelial ovarian cancer (EOC) is approximately 35-40% despite maximal treatment efforts, highlighting a need for stratification biomarkers for personalized treatment. Here we extract 657 quantitative mathematical descriptors from the preoperative CT images of 364 EOC patients at their initial presentation. Using machine learning, we derive a non-invasive summary-statistic of the primary ovarian tumor based on 4 descriptors, which we name "Radiomic Prognostic Vector" (RPV). RPV reliably identifies the 5% of patients with median overall survival less than 2 years, significantly improves established prognostic methods, and is validated in two independent, multi-center cohorts. Furthermore, genetic, transcriptomic and proteomic analysis from two independent datasets elucidate that stromal phenotype and DNA damage response pathways are activated in RPV-stratified tumors. RPV and its associated analysis platform could be exploited to guide personalized therapy of EOC and is potentially transferrable to other cancer types.

Clinical value of bioelectrical properties of cancerous tissue in advanced epithelial ovarian cancer patients.

Currently, there are no valid pre-operatively established biomarkers or algorithms that can accurately predict surgical and clinical outcome for patients with advanced epithelial ovarian cancer (EOC). In this study, we suggest that profiling of tumour parameters such as bioelectrical-potential and metabolites, detectable by electronic sensors, could facilitate the future development of devices to better monitor disease and predict surgical and treatment outcomes. Biopotential was recorded, using a potentiometric measurement system, in ex vivo paired non-cancerous and cancerous omental tissues from advanced stage EOC (n = 36), and lysates collected for metabolite measurement by microdialysis. Consistently different biopotential values were detected in cancerous tissue versus non-cancerous tissue across all cases (p < 0.001). High tumour biopotential levels correlated with advanced tumour stage (p = 0.048) and tumour load, and negatively correlated with stroma. Within our EOC cohort and specifically the high-grade serous subtype, low biopotential levels associated with poorer progression-free survival (p = 0.0179, p = 0.0143 respectively). Changes in biopotential levels significantly correlated with common apoptosis related pathways. Lactate and glucose levels measured in paired tissues showed significantly higher lactate/glucose ratio in tissues with low biopotential (p < 0.01, n = 12). Our study proposes the feasibility of biopotential and metabolite monitoring as a biomarker modality profiling EOC to predict surgical and clinical outcomes.

A putative biomarker signature for clinically effective AKT inhibition: correlation of in vitro, in vivo and clinical data identifies the importance of modulation of the mTORC1 pathway.

Our identification of dysregulation of the AKT pathway in ovarian cancer as a platinum resistance specific event led to a comprehensive analysis of in vitro, in vivo and clinical behaviour of the AKT inhibitor GSK2141795. Proteomic biomarker signatures correlating with effects of GSK2141795 were developed using in vitro and in vivo models, well characterised for related molecular, phenotypic and imaging endpoints. Signatures were validated in temporally paired biopsies from patients treated with GSK2141795 in a clinical study. GSK2141795 caused growth-arrest as single agent in vitro, enhanced cisplatin-induced apoptosis in vitro and reduced tumour volume in combination with platinum in vivo. GSK2141795 treatment in vitro and in vivo resulted in ~50-90% decrease in phospho-PRAS40 and 20-80% decrease in fluoro-deoxyglucose (FDG) uptake. Proteomic analysis of GSK2141795 in vitro and in vivo identified a signature of pathway inhibition including changes in AKT and p38 phosphorylation and total Bim, IGF1R, AR and YB1 levels. In patient biopsies, prior to treatment with GSK2141795 in a phase 1 clinical trial, this signature was predictive of post-treatment changes in the response marker CA125. Development of this signature represents an opportunity to demonstrate the clinical importance of AKT inhibition for re-sensitisation of platinum resistant ovarian cancer to platinum.

Dose-Finding Quantitative 18F-FDG PET Imaging Study with the Oral Pan-AKT Inhibitor GSK2141795 in Patients with Gynecologic Malignancies.

UNLABELLED: AKT (a serine/threonine-specific protein kinase) regulates many cellular processes contributing to cytotoxic drug resistance. This study's primary objective examined the relationship between GSK2141795, an oral, pan-AKT inhibitor, and (18)F-FDG PET markers of glucose metabolism in tumor tissue to determine whether (18)F-FDG PET could be used to guide personalized dosing of GSK2141795. Biomarker analysis of biopsies was also undertaken. METHODS: Twelve patients were enrolled in 3 cohorts; all underwent dynamic (18)F-FDG PET scans and serial pharmacokinetic sampling at baseline, week 2, and week 4 with tumor biopsies before treatment and at week 4. Response was evaluated by RECIST v1.1 and Gynecologic Cancer Intergroup criteria. Biopsy samples were analyzed for mutations and protein expression. RESULTS: GSK2141795 did not significantly influence blood glucose levels. No dose-response relationship was observed between GSK2141795 pharmacokinetics and (18)F-FDG PET pharmacodynamic measures; however, an exposure-response relationship was seen between maximum drug concentrations and maximal decrease in (18)F-FDG uptake in the best-responding tumor. This relationship also held for pharmacokinetic parameters of exposure and 1,5-anhydroglucitol (a systemic measure of glucose metabolism). Phospho-AKT upregulation at week 4 in biopsies confirmed AKT inhibition by GSK2141795. Single-agent activity was observed with a clinical benefit rate of 27% (3/11) and 30% (3/10) CA125 response in the study's platinum-resistant ovarian patients. AKT pathway activation by PIK3CA/PIK3R1 mutation did not correlate with clinical activity, whereas RAS/RAF pathway mutations did segregate with resistance to AKT inhibition. CONCLUSION: GSK2141795 demonstrated an exposure-response relationship with decreased (18)F-FDG uptake and is active and tolerable. This study's design integrating (18)F-FDG PET, pharmacokinetics, and biomarker analyses demonstrates the potential for clinical development for personalized treatment.

Epigenome-wide association study reveals decreased average methylation levels years before breast cancer diagnosis.

BACKGROUND: Interest in the potential of DNA methylation in peripheral blood as a biomarker of cancer risk is increasing. We aimed to assess whether epigenome-wide DNA methylation measured in peripheral blood samples obtained before onset of the disease is associated with increased risk of breast cancer. We report on three independent prospective nested case-control studies from the European Prospective Investigation into Cancer and Nutrition (EPIC-Italy; n = 162 matched case-control pairs), the Norwegian Women and Cancer study (NOWAC; n = 168 matched pairs), and the Breakthrough Generations Study (BGS; n = 548 matched pairs). We used the Illumina 450k array to measure methylation in the EPIC and NOWAC cohorts. Whole-genome bisulphite sequencing (WGBS) was performed on the BGS cohort using pooled DNA samples, combined to reach 50× coverage across ~16 million CpG sites in the genome including 450k array CpG sites. Mean ß values over all probes were calculated as a measurement for epigenome-wide methylation. RESULTS: In EPIC, we found that high epigenome-wide methylation was associated with lower risk of breast cancer (odds ratio (OR) per 1 SD = 0.61, 95 % confidence interval (CI) 0.47-0.80; -0.2 % average difference in epigenome-wide methylation for cases and controls). Specifically, this was observed in gene bodies (OR = 0.51, 95 % CI 0.38-0.69) but not in gene promoters (OR = 0.92, 95 % CI 0.64-1.32). The association was not replicated in NOWAC (OR = 1.03 95 % CI 0.81-1.30). The reasons for heterogeneity across studies are unclear. However, data from the BGS cohort was consistent with epigenome-wide hypomethylation in breast cancer cases across the overlapping 450k probe sites (difference in average epigenome-wide methylation in case and control DNA pools = -0.2 %). CONCLUSIONS: We conclude that epigenome-wide hypomethylation of DNA from pre-diagnostic blood samples may be predictive of breast cancer risk and may thus be useful as a clinical biomarker.