TMPRSS:ERG fusion in prostate cancer: from experimental approaches to prognostic studies

Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

Merging new-age biomarkers and nanodiagnostics for precision prostate cancer management

The accurate identification and stratified treatment of clinically significant early-stage prostate cancer have been ongoing concerns since the outcomes of large international prostate cancer screening trials were reported. The controversy surrounding clinical and cost benefits of prostate cancer screening has highlighted the lack of strategies for discriminating high-risk disease (that requires early treatment) from low-risk disease (that could be managed using watchful waiting or active surveillance). Advances in molecular subtyping and multiomics nanotechnology-based prostate cancer risk delineation can enable refinement of prostate cancer molecular taxonomy into clinically meaningful and treatable subtypes. Furthermore, the presence of intertumoural and intratumoural heterogeneity in prostate cancer warrants the development of novel nanodiagnostic technologies to identify clinically significant prostate cancer in a rapid, cost-effective and accurate manner. Circulating and urinary next-generation prostate cancer biomarkers for disease molecular subtyping and the newest complementary nanodiagnostic platforms for enhanced biomarker detection are promising tools for precision prostate cancer management. However, challenges in merging both aspects and clinical translation still need to be overcome.

COMMD3:BMI1 Fusion and COMMD3 Protein Regulate C-MYC Transcription: Novel Therapeutic Target for Metastatic Prostate Cancer

Gene rearrangement is reported to be associated to the aggressive phenotype and poor prognosis in prostate cancer. We identified a gene fusion between a transcription repressor (BMI1) and transcriptional factor (COMMD3) in human prostate cancer. We show that COMMD3:BMI1 fusion expression is significantly increased in prostate cancer disease in an order: normal tissue < primary < metastatic tumors (Mets). Although elevated TMPRSS-ERG/ETV fusion is reported in prostate cancer, we identified a subtype of Mets exhibiting low TMPRSS:ETV and high COMMD3:BMI1 We delineated the mechanism and function of COMMD3 and COMMD3:BMI1 in prostate cancer. We show that COMMD3 level is elevated in prostate cancer cell models, PDX models (adenocarcinoma, NECaP), and Mets. The analysis of TCGA/NIH/GEO clinical data showed a positive correlation between increased COMMD3 expression to the disease recurrence and poor survival in prostate cancer. We show that COMMD3 drives proliferation of normal cells and promotes migration/invasiveness of neoplastic cells. We show that COMMD3:BMI1 and COMMD3 regulate C-MYC transcription and C-MYC downstream pathway. The ChIP analysis showed that COMMD3 protein is recruited at the promoter of C-MYC gene. On the basis of these data, we investigated the relevance of COMMD3:BMI1 and COMMD3 as therapeutic targets using in vitro and xenograft mouse models. We show that siRNA-mediated targeting of COMMD3:BMI1 and COMMD3 significantly decreases (i) C-MYC expression in BRD/BET inhibitor-resistant cells, (ii) proliferation/invasion in vitro, and (iii) growth of prostate cancer cell tumors in mice. The IHC analysis of tumors confirmed the targeting of COMMD3-regulated molecular pathway under in vivo conditions. We conclude that COMMD3:BMI1 and COMMD3 are potential progression biomarkers and therapeutic targets of metastatic prostate cancer.

Retrospective study testing next generation sequencing of selected cancer-associated genes in resected prostate cancer

PURPOSE

Prostate cancer (PCa) has a highly heterogeneous outcome. Beyond Gleason Score, Prostate Serum Antigen and tumor stage, nowadays there are no biological prognostic factors to discriminate between indolent and aggressive tumors.The most common known genomic alterations are the TMPRSS-ETS translocation and mutations in the PI3K, MAPK pathways and in p53, RB and c-MYC genes.The aim of this retrospective study was to identify by next generation sequencing the most frequent genetic variations (GVs) in localized and locally advanced PCa underwent prostatectomy and to investigate their correlation with clinical-pathological variables and disease progression.

RESULTS

Identified non-synonymous GVs included TP53 p.P72R (78% of tumors), two CSFR1 SNPs, rs2066934 and rs2066933 (70%), KDR p.Q472H (67%), KIT p.M541L (28%), PIK3CA p.I391M (19%), MET p.V378I (10%) and FGFR3 p.F384L/p.F386L (8%). TP53 p.P72R, MET p.V378I and CSFR1 SNPs were significantly associated with the HI risk group, TP53 and MET variations with T≥T2c. FGFR3 p.F384L/p.F386L was correlated with T≤T2b. MET p.V378I mutation, detected in 20% of HI risk patients, was associated with early biochemical recurrence.

EXPERIMENTAL DESIGN

Nucleic acids were obtained from tissue samples of 30 high (HI) and 30 low-intermediate (LM) risk patients, according to D'Amico criteria. Genomic DNA was explored with the Ion_AmpliSeq_Cancer_Hotspot_Panel_v.2 including 50 cancer-associated genes. GVs with allelic frequency (AF) ≥10%, affecting protein function or previously associated with cancer, were correlated with clinical-pathological variables.

CONCLUSION

Our results confirm a complex mutational profile in PCa, supporting the involvement of TP53, MET, FGFR3, CSF1R GVs in tumor progression and aggressiveness.