Systems biology approaches have been applied to prostate cancer to model how individual cellular and molecular components interact to influence cancer development, progression, and treatment responses. The integration of multi-omic experimental data with computational models has provided insights into the molecular characteristics of prostate cancer and emerging treatment strategies that have the potential to improve patient outcomes. Here, we highlight recent advancements that have emerged from systems modeling in prostate cancer. These include descriptions of the molecular landscape of prostate cancer and how genomic alterations inform computational models of disease progression, how evolutionary processes give rise to mechanisms of therapeutic resistance, and the development of innovative treatment strategies such as adaptive therapy. We also highlight current challenges in prostate cancer that can be addressed through systems biology approaches. These include tumor heterogeneity, poor immunotherapy response, a paucity of experimental model systems, and the ongoing translation of computational models for clinical decision making. Leveraging systems biology approaches has the potential to lead to a better understanding of the disease and better patient outcomes in the treatment of prostate cancer.

Background:Prostate cancer is a leading cause of cancer-related deaths among men, marked by heterogeneous clinical and molecular characteristics. The complexity of the molecular landscape necessitates tools for identifying multi-gene co-alteration patterns that are associated with aggressive disease. The identification of such gene sets will allow for deeper characterization of the processes underlying prostate cancer progression and potentially lead to novel strategies for treatment.Methods:We developed ProstaMine to systematically identify co-alterations associated with aggressiveness in prostate cancer molecular subtypes defined by high-fidelity alterations in primary prostate cancer. ProstaMine integrates genomic, transcriptomic, and clinical data from five primary and one metastatic prostate cancer cohorts to prioritize co-alterations enriched in metastatic disease and associated with disease progression.Results:Integrated analysis of primary tumors defined a set of 17 prostate cancer alterations associated with aggressive characteristics. We applied ProstaMine to NKX3-1-loss and RB1-loss tumors and identified subtype-specific co-alterations associated with metastasis and biochemical relapse in these molecular subtypes. In NKX3-1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations known to regulate prostate cancer signaling pathways including MAPK, NF-kB, p53, PI3K, and Sonic hedgehog. In RB1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations involved in p53, STAT6, and MHC class I antigen presentation. Co-alterations impacting autophagy were noted in both molecular subtypes.Conclusion:ProstaMine is a method to systematically identify novel subtype-specific co-alterations associated with aggressive characteristics in prostate cancer. The results from ProstaMine provide insights into potential subtype-specific mechanisms of prostate cancer progression which can be formed into testable experimental hypotheses. ProstaMine is publicly available at: https://bioinformatics.cuanschutz.edu/prostamine.

Supplementary figure 4: Palmitate supplementation decreases the spliced/unspliced XBP-1 ratio: LNCaP cells were treated over 48 hours with etomoxir and and with or without 100uM palmitate conjugated to albumin. Supplements Figure 4A.

Prostate cancer (PC) is the second leading cause of cancer death in men in the United States. While diversified and improved treatment options for aggressive PC have improved patient outcomes, metastatic castration-resistant prostate cancer (mCRPC) remains incurable and an area of investigative therapeutic interest. This review will cover the seminal clinical data supporting the indication of new precision oncology-based therapeutics and explore their limitations, present utility, and potential in the treatment of PC. Systemic therapies for high-risk and advanced PC have experienced significant development over the past ten years. Biomarker-driven therapies have brought the field closer to the goal of being able to implement precision oncology therapy for every patient. The tumor agnostic approval of pembrolizumab (a PD-1 inhibitor) marked an important advancement in this direction. There are also several PARP inhibitors indicated for patients with DNA damage repair deficiencies. Additionally, theranostic agents for both imaging and treatment have further revolutionized the treatment landscape for PC and represent another advancement in precision medicine. Radiolabeled prostate-specific membrane antigen (PSMA) PET/CT is rapidly becoming a standard of care for diagnosis, and PSMA-targeted radioligand therapies have gained recent FDA approval for metastatic prostate cancer. These advances in precision-based oncology are detailed in this review.

Supplementary figure 1: Epithelial and stromal marker expression in human prostate-derived patient-matched cells, BPH-1 and WPMY-1 cells. Supplements Figure 1.

Table S10 shows IC50 and statistical data from several drugs tested that are presented in figure 1

Tables s1-9, 11, 13-15. These tables provide statistical data, gene list, and results from TRAP and GSEA that support the conclusions of the manuscript and provide full disclosure of our results.

The supplemental figures provide supporting data including controls, synergism studies, dose response curves, validation of knockdown, etc.

Supplementary Table Legends 1-7, Figure Legends 1-9 from Interleukin-1α Mediates the Antiproliferative Effects of 1,25-Dihydroxyvitamin D3 in Prostate Progenitor/Stem Cells

Table S12 shows quantitative statistical data from the curves presented in figure 4.

PDF file - 1MB, Hemizygous deletion of MAP3K7 in human prostatic tumorigenic cell lines.

Figure legends for supplementary figures and Tables. Supplementary Table 1: Primers used to analyze expression of the ER Stress-related genes and AR-related gene expression. Supplementary Table 2: Antibodies used for immunoblots and IHC.

Roughly 15% of the 268,490 men newly diagnosed with prostate cancer (PCa) will die from the disease. Pinpointing the drivers of aggressive PCa is the first step to improve patient outcomes. Correlative analyses have linked genetic aberrations, including copy number alterations due to loss of large genomic regions, to poor prostate cancer prognosis. Many groups have connected the loss of chromosome 8p and 16q to aggressive PCa, yet the genes on these regions responsible for aggressive phenotypes are unknown. Mining TCGA data, we identified minimum consensus deletions and associated gene expression with disease recurrence to nominate 48 genes on 8p and 58 genes on 16q for further study. We designed a pooled double knockout library to test all pairwise gene combinations of the nominated 8p-16q genes. Gene pairs will be targeted by 16 paired crRNA cassettes consisting of four crRNAs per gene and paired in all combinations. This library will be combined with stably expressing Cas12a prostate epithelial cell lines to screen for gene combinations that drive excessive cell proliferation. This will help pinpoint specific PCa tumor suppressors in combined 8p and 16q loss. Citation Format: Gabriel A. Yette, James C. Costello, Scott D. Cramer. Characterizing novel aggressive prostate cancer subtypes associated with loss of chromosomes 8p and 16q [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A075.

Supplementary Figures 1-9 from Interleukin-1α Mediates the Antiproliferative Effects of 1,25-Dihydroxyvitamin D3 in Prostate Progenitor/Stem Cells

Supplementary Tables 1-4 from Interleukin-1α Mediates the Antiproliferative Effects of 1,25-Dihydroxyvitamin D₃ in Prostate Progenitor/Stem Cells

PDF file - 1MB, Complete lineage differentiation of shControl cells in vivo.

PDF file - 6K, Primer sequences for detecting expression of the 5 genes within the consensus deletion regions in WFU3 cells.

PDF file - 1MB, Suppression of Tak1 promotes scatter growth of shTak1 PrP/SCs.

PDF file - 139K, Expression of Tak1 is progressively lost with increasing Gleason grade both within each cancer and across cancers.