Genetic variants of the Wnt signaling pathway as predictors of aggressive disease and reclassification in men with early stage prostate cancer on active surveillance

Identification of Key MicroRNAs and Mechanisms in Prostate Cancer Evolution Based on Biomarker Prioritization Model and Carcinogenic Survey

Background: Prostate cancer (PCa) is occurred with increasing incidence and heterogeneous pathogenesis. Although clinical strategies are accumulated for PCa prevention, there is still a lack of sensitive biomarkers for the holistic management in PCa occurrence and progression. Based on systems biology and artificial intelligence, translational informatics provides new perspectives for PCa biomarker prioritization and carcinogenic survey.

Methods: In this study, gene expression and miRNA-mRNA association data were integrated to construct conditional networks specific to PCa occurrence and progression, respectively. Based on network modeling, hub miRNAs with significantly strong single-line regulatory power were topologically identified and those shared by the condition-specific network systems were chosen as candidate biomarkers for computational validation and functional enrichment analysis.

Results: Nine miRNAs, i.e., hsa-miR-1-3p, hsa-miR-125b-5p, hsa-miR-145-5p, hsa-miR-182-5p, hsa-miR-198, hsa-miR-22-3p, hsa-miR-24-3p, hsa-miR-34a-5p, and hsa-miR-499a-5p, were prioritized as key players for PCa management. Most of these miRNAs achieved high AUC values (AUC > 0.70) in differentiating different prostate samples. Among them, seven of the miRNAs have been previously reported as PCa biomarkers, which indicated the performance of the proposed model. The remaining hsa-miR-22-3p and hsa-miR-499a-5p could serve as novel candidates for PCa predicting and monitoring. In particular, key miRNA-mRNA regulations were extracted for pathogenetic understanding. Here hsa-miR-145-5p was selected as the case and hsa-miR-145-5p/NDRG2/AR and hsa-miR-145-5p/KLF5/AR axis were found to be putative mechanisms during PCa evolution. In addition, Wnt signaling, prostate cancer, microRNAs in cancer etc. were significantly enriched by the identified miRNAs-mRNAs, demonstrating the functional role of the identified miRNAs in PCa genesis.

Conclusion: Biomarker miRNAs together with the associated miRNA-mRNA relations were computationally identified and analyzed for PCa management and carcinogenic deciphering. Further experimental and clinical validations using low-throughput techniques and human samples are expected for future translational studies.

Pathway Analysis of Genes Identified through Post-GWAS to Underpin Prostate Cancer Aetiology

Understanding the functional role of risk regions identified by genome-wide association studies (GWAS) has made considerable recent progress and is referred to as the post-GWAS era. Annotation of functional variants to the genes, including cis or trans and understanding their biological pathway/gene network enrichments, is expected to give rich dividends by elucidating the mechanisms underlying prostate cancer. To this aim, we compiled and analysed currently available post-GWAS data that is validated through further studies in prostate cancer, to investigate molecular biological pathways enriched for assigned functional genes. In total, about 100 canonical pathways were significantly, at false discovery rate (FDR) < 0.05), enriched in assigned genes using different algorithms. The results have highlighted some well-known cancer signalling pathways, antigen presentation processes and enrichment in cell growth and development gene networks, suggesting risk loci may exert their functional effect on prostate cancer by acting through multiple gene sets and pathways. Additional upstream analysis of the involved genes identified critical transcription factors such as HDAC1 and STAT5A. We also investigated the common genes between post-GWAS and three well-annotated gene expression datasets to endeavour to uncover the main genes involved in prostate cancer development/progression. Post-GWAS generated knowledge of gene networks and pathways, although continuously evolving, if analysed further and targeted appropriately, will have an important impact on clinical management of the disease.

Genetic associations of T cell cancer immune response with tumor aggressiveness in localized prostate cancer patients and disease reclassification in an active surveillance cohort

Determining prostate cancer (PCa) aggressiveness and reclassification are critical events during the treatment of localized disease and for patients undergoing active surveillance (AS). Since T cells play major roles in cancer surveillance and elimination, we aimed to identify genetic biomarkers related to T cell cancer immune response which are predictive of aggressiveness and reclassification risks in localized PCa. The genotypes of 3,586 single nucleotide polymorphisms (SNPs) from T cell cancer immune response pathways were analyzed in 1762 patients with localized disease and 393 who elected AS. The aggressiveness of PCa was defined according to pathological Gleason score (GS) and D'Amico criteria. PCa reclassification was defined according to changes in GS or tumor characteristics during subsequent surveillance biopsies. Functional characterization and analysis of immune phenotypes were also performed. In the localized PCa cohort, seven SNPs were significantly associated with the risk of aggressive disease. In the AS cohort, another eight SNPs were identified as predictors for aggressiveness and reclassification. Rs1687016 of PSMB8 was the most significant predictor of reclassification. Cumulative analysis showed that a genetic score based on the identified SNPs could significantly predict risk of D'Amico high risk disease (P-trend = 2.4E-09), GS4 + 3 disease (P-trend = 1.3E-04), biochemical recurrence (P-trend = 0.01) and reclassification (P-trend = 0.01). In addition, the rs34309 variant was associated with functional somatic mutations in the PI3K/PTEN/AKT/MTOR pathway and tumor lymphocyte infiltration. Our study provides plausible evidence that genetic variations in T cell cancer immune response can influence risks of aggressiveness and reclassification in localized PCa, which may lead to additional biological insight into these outcomes. Abbreviations: PCa, prostate cancer; AS, active surveillance; GS, Gleason score; PSA, prostate specific antigen; TCGA, The Cancer Genome Atlas; SNP, single nucleotide polymorphisms; UFG, unfavorable genotype.

A Review of Prostate Cancer Genome-Wide Association Studies (GWAS)

Prostate cancer is the most common cancer in men in Europe and the United States. The genetic heritability of prostate cancer is contributed to by both rarely occurring genetic variants with higher penetrance and moderate to commonly occurring variants conferring lower risks. The number of identified variants belonging to the latter category has increased dramatically in the last 10 years with the development of the genome-wide association study (GWAS) and the collaboration of international consortia that have led to the sharing of large-scale genotyping data. Over 40 prostate cancer GWAS have been reported, with approximately 170 common variants now identified. Clinical utility of these variants could include strategies for population-based risk stratification to target prostate cancer screening to men with an increased genetic risk of disease development, while for those who develop prostate cancer, identifying genetic variants could allow treatment to be tailored based on a genetic profile in the early disease setting. Functional studies of identified variants are needed to fully understand underlying mechanisms of disease and identify novel targets for treatment. This review will outline the GWAS carried out in prostate cancer and the common variants identified so far, and how these may be utilized clinically in the screening for and management of prostate cancer. Cancer Epidemiol Biomarkers Prev; 27(8); 845-57. ©2018 AACR.