Could Reducing Body Fatness Reduce the Risk of Aggressive Prostate Cancer via the Insulin Signalling Pathway? A Systematic Review of the Mechanistic Pathway

Excess body weight is thought to increase the risk of aggressive prostate cancer (PCa), although the biological mechanism is currently unclear. Body fatness is positively associated with a diminished cellular response to insulin and biomarkers of insulin signalling have been positively associated with PCa risk. We carried out a two-pronged systematic review of (a) the effect of reducing body fatness on insulin biomarker levels and (b) the effect of insulin biomarkers on PCa risk, to determine whether a reduction in body fatness could reduce PCa risk via effects on the insulin signalling pathway. We identified seven eligible randomised controlled trials of interventions designed to reduce body fatness which measured insulin biomarkers as an outcome, and six eligible prospective observational studies of insulin biomarkers and PCa risk. We found some evidence that a reduction in body fatness improved insulin sensitivity although our confidence in this evidence was low based on GRADE (Grading of Recommendations, Assessment, Development and Evaluations). We were unable to reach any conclusions on the effect of insulin sensitivity on PCa risk from the few studies included in our systematic review. A reduction in body fatness may reduce PCa risk via insulin signalling, but more high-quality evidence is needed before any conclusions can be reached regarding PCa.

Conserved Structure Modules within the lncRNA SChLAP1 Mediate Protein Recognition Implicated in Aggressive Prostate Cancer

The lncRNA Second Chromosome Locus Associated with Prostate 1 (SChLAP1) was previously identified as a predictive biomarker and driver of aggressive prostate cancer. Recent work suggests that SChLAP1 may bind the SWI/SNF chromatin remodeling complex to promote prostate cancer metastasis, though the exact role of SWI/SNF recognition is debated. To date, there are no detailed biochemical studies of apo SChLAP1 or the SChLAP1:SWI/SNF complex. Herein, we report the first secondary structure model of SChLAP1 utilizing SHAPE-MaP both in vitro and in cellulo. Comparison of the in vitro and in cellulo data via ΔSHAPE identified putative protein binding sites within SChLAP1, specifically to evolutionarily conserved exons of the transcript. We also demonstrate that global SChLAP1 secondary structure is sensitive to both purification method and magnesium concentration. Further, we identified a 3'-fragment of SChLAP1 (SChLAP1Frag) that harbors multiple potential protein binding sites and presents a robustly folded secondary structure, supporting a functional role for this region. This work lays the foundation for future efforts in selective targeting and disruption of the SChLAP1:protein interface and the development of new therapeutic avenues in prostate cancer treatment.

The genes controlling normal function of citrate and spermine secretion is lost in aggressive prostate cancer and prostate model systems

Background: Secretion of the metabolites citrate and spermine into prostate lumen is a unique hallmark for normal prostate epithelial cells. However, the identity of the genes controlling citrate and spermine secretion remains mostly unknown despite their obvious relevance for progression to aggressive prostate cancer. Materials & Methods: In this study, we have correlated simultaneous measurement of citrate/spermine and transcriptomics data. We have refined these gene correlations in 12 prostate cancer cohorts containing 2915 tissue samples to create a novel gene signature of 150 genes connected with citrate and spermine secretion. We further explored the signature in public data, interrogating over 18 000 samples from various tissues and model systems, including 3826 samples from prostate and prostate cancer. Results: In prostate cancer, the expression of this gene signature is gradually lost in tissue from normal epithelial cells through PIN, low grade (Gleason <= 7), high grade cancer (Gleason >= 8) and metastatic lesions. The accuracy of the signature is validated by its unique enrichment in prostate compared to other tissues, and its strong enrichment in epithelial tissue compartments compared to stroma. Several zinc-binding proteins that are not previously investigated in the prostate are present in the gene signature, suggesting new mechanisms for controlling zinc homeostasis in citrate/spermine secretion. However, the absence of the gene signature in all common prostate normal and cancer cell-lines, as well as prostate organoids, underlines the challenge to study the role of these genes during prostate cancer progression in model systems. Conclusions: A large collection of transcriptomics data integrated with metabolomics identifies the genes related to citrate and spermine secretion in the prostate, and show that the expression of these genes gradually decreases on the path towards aggressive prostate cancer. In addition, the study questions the relevance of currently available model systems to study metabolism in prostate cancer development.

An integrated functional and clinical genomics approach reveals genes driving aggressive metastatic prostate cancer

Genomic sequencing of thousands of tumors has revealed many genes associated with specific types of cancer. Similarly, large scale CRISPR functional genomics efforts have mapped genes required for cancer cell proliferation or survival in hundreds of cell lines. Despite this, for specific disease subtypes, such as metastatic prostate cancer, there are likely a number of undiscovered tumor specific driver genes that may represent potential drug targets. To identify such genetic dependencies, we performed genome-scale CRISPRi screens in metastatic prostate cancer models. We then created a pipeline in which we integrated pan-cancer functional genomics data with our metastatic prostate cancer functional and clinical genomics data to identify genes that can drive aggressive prostate cancer phenotypes. Our integrative analysis of these data reveals known prostate cancer specific driver genes, such as AR and HOXB13, as well as a number of top hits that are poorly characterized. In this study we highlight the strength of an integrated clinical and functional genomics pipeline and focus on two top hit genes, KIF4A and WDR62. We demonstrate that both KIF4A and WDR62 drive aggressive prostate cancer phenotypes in vitro and in vivo in multiple models, irrespective of AR-status, and are also associated with poor patient outcome.