Association of prostate cancer risk variants with gene expression in normal and tumor tissue

Identification of circadian clock-related immunological prognostic index and molecular subtypes in prostate cancer

BACKGROUND

Evidence suggests that the circadian clock (CIC) is among the important factors for tumorigenesis. We aimed to provide new insights into CIC-mediated molecular subtypes and gene prognostic indexes for prostate cancer (PCa) patients undergoing radical prostatectomy (RP) or radical radiotherapy (RT).

METHODS

PCa data from TCGA was analyzed to identify differentially expressed genes (DEGs) with significant fold changes and p-values. A prognostic index called CIC-related gene prognostic index (CICGPI) was developed through clustering methods and survival analysis and validated on multiple data sets. The diagnostic accuracy of CICGPI for resistance to chemotherapy and radiotherapy was confirmed. Additionally, the interaction between tumor immune environment and CICGPI score was explored, along with their correlation with prognosis.

RESULTS

TOP2A, APOE, and ALDH2 were used to classify the PCa patients into two subtypes. Cluster 2 had a higher risk of biochemical recurrence (BCR) than cluster 1 for PCa patients undergoing RP or RT. A CIC-related gene prognostic index (CICGPI) was constructed using the above three genes for PCa patents in the TCGA database. The CICGPI score showed good prognostic value in the TCGA database and was externally confirmed by PCa patients in GSE116918, MSKCC2010 and GSE46602. In addition, the CICGPI score had a certain and high diagnostic accuracy for tumor chemoresistance (AUC: 0.781) and radioresistance (AUC: 0.988). For gene set variation analysis, we observed that both beta alanine metabolism and limonene and pinene degradation were upregulated in cluster 1 for PCa patients undergoing RP or RT. For PCa patients undergoing RP, cell cycle, homologous recombination, mismatch repair, and DNA replication were upregulated in cluster 2. A strongly positive relationship between cancer-related fibroblasts and CICGPI score was observed in PCa patients undergoing RP or RT. Moreover, a high density of CAFs was highly closely associated with poorer BCR-free survival of PCa patients.

CONCLUSIONS

In this study, we established CIC-related immunological prognostic index and molecular subtypes, which might be useful for the clinical practice.

Inhibition of the Sterol Regulatory Element Binding Protein SREBF-1 Overcomes Docetaxel Resistance in Advanced Prostate Cancer

Resistance to antiandrogens and chemotherapy (Cx) limits therapeutic options for patients with hormone-sensitive and hormone-resistant prostate cancer (mCRPC). In this context, up-regulation of the glucocorticoid receptor has been identified as a potential bypass mechanism in mCRPC, and a combination of docetaxel and mifepristone (Doc + RU-486), an inhibitor of the glucocorticoid receptor, re-sensitized docetaxel-resistant cell models to Cx. This study was designed to elucidate the molecular mechanisms responsible for this phenomenon. RNA sequencing was performed in docetaxel-resistant prostate cancer cell models after Doc + RU-486 treatment with consecutive functional assays. Expression of selected proteins was verified in prostatic tissue from prostate cancer patients with progressive disease. Treatment with Doc + RU-486 significantly reduced cancer cell viability, and RNA sequencing revealed sterol regulatory element of binding transcription factor 1 (SREBF-1), a transcription factor of cholesterol and lipid biosynthesis, as a significantly down-regulated target. Functional assays confirmed that SREBF-1 down-regulation is partially responsible for this observation. In concordance, SREBF-1 knockdown and pharmacologic sterol regulatory element binding protein inhibition, together with other key enzymes in the cholesterol pathway, showed similar results. Furthermore, SREBF-1 expression is significantly elevated in advanced prostate cancer tissues, showing its potential involvement in tumor progression and emerging therapy resistance. Therefore, specific inhibition of cholesterol and lipid biosynthesis might also target Cx-resistant cancer cells and represents a potential additive future therapeutic option to improve mCRPC therapy.

An Inherited Allele Confers Prostate Cancer Progression and Drug Resistance via RFX6/HOXA10-Orchestrated TGFβ Signaling

Genetic and epigenetic alterations are cancer hallmark characteristics. However, the role of inherited cancer predisposition alleles in co-opting lineage factor epigenetic reprogramming and tumor progression remains elusive. Here the FinnGen cohort phenome-wide analysis, along with multiple genome-wide association studies, has consistently identified the rs339331-RFX6/6q22 locus associated with prostate cancer (PCa) risk across diverse populations. It is uncovered that rs339331 resides in a reprogrammed androgen receptor (AR) binding site in PCa tumors, with the T risk allele enhancing AR chromatin occupancy. RFX6, an AR-regulated gene linked to rs339331, exhibits synergistic prognostic value for PCa recurrence and metastasis. This comprehensive in vitro and in vivo studies demonstrate the oncogenic functions of RFX6 in promoting PCa cell proliferation and metastasis. Mechanistically, RFX6 upregulates HOXA10 that profoundly correlates with adverse PCa outcomes and is pivotal in RFX6-mediated PCa progression, facilitating the epithelial-mesenchymal transition (EMT) and modulating the TGFβ/SMAD signaling axis. Clinically, HOXA10 elevation is associated with increased EMT scores, tumor advancement and PCa recurrence. Remarkably, reducing RFX6 expression restores enzalutamide sensitivity in resistant PCa cells and tumors. This findings reveal a complex interplay of genetic and epigenetic mechanisms in PCa pathogenesis and drug resistance, centered around disrupted prostate lineage AR signaling and abnormal RFX6 expression.

Combined SNPs sequencing and allele specific proteomics capture reveal functional causality underpinning the 2p25 prostate cancer susceptibility locus

Genome wide association studies (GWASs) have identified numerous risk loci associated with prostate cancer, yet unraveling their functional significance remains elusive. Leveraging our high-throughput SNPs-seq method, we pinpointed rs4519489 within the multi-ancestry GWAS-discovered 2p25 locus as a potential functional SNP due to its significant allelic differences in protein binding. Here, we conduct a comprehensive analysis of rs4519489 and its associated gene, NOL10, employing diverse cohort data and experimental models. Clinical findings reveal a synergistic effect between rs4519489 genotype and NOL10 expression on prostate cancer prognosis and severity. Through unbiased proteomics screening, we reveal that the risk allele A of rs4519489 exhibits enhanced binding to USF1, a novel oncogenic transcription factor (TF) implicated in prostate cancer progression and prognosis, resulting in elevated NOL10 expression. Furthermore, we elucidate that NOL10 regulates cell cycle pathways, fostering prostate cancer progression. The concurrent expression of NOL10 and USF1 correlates with aggressive prostate cancer characteristics and poorer prognosis. Collectively, our study offers a robust strategy for functional SNP screening and TF identification through high-throughput SNPs-seq and unbiased proteomics, highlighting the rs4519489-USF1-NOL10 regulatory axis as a promising biomarker or therapeutic target for clinical diagnosis and treatment of prostate cancer.

Dampened Regulatory Circuitry of TEAD1/ITGA1/ITGA2 Promotes TGFβ1 Signaling to Orchestrate Prostate Cancer Progression

The extracellular matrix (ECM) undergoes substantial changes during prostate cancer (PCa) progression, thereby regulating PCa growth and invasion. Herein, a meta-analysis of multiple PCa cohorts is performed which revealed that downregulation or genomic loss of ITGA1 and ITGA2 integrin genes is associated with tumor progression and worse prognosis. Genomic deletion of both ITGA1 and ITGA2 activated epithelial-to-mesenchymal transition (EMT) in benign prostate epithelial cells, thereby enhancing their invasive potential in vitro and converting them into tumorigenic cells in vivo. Mechanistically, EMT is induced by enhanced secretion and autocrine activation of TGFβ1 and nuclear targeting of YAP1. An unbiased genome-wide co-expression analysis of large PCa cohort datasets identified the transcription factor TEAD1 as a key regulator of ITGA1 and ITGA2 expression in PCa cells while TEAD1 loss phenocopied the dual loss of α1- and α2-integrins in vitro and in vivo. Remarkably, clinical data analysis revealed that TEAD1 downregulation or genomic loss is associated with aggressive PCa and together with low ITGA1 and ITGA2 expression synergistically impacted PCa prognosis and progression. This study thus demonstrated that loss of α1- and α2-integrins, either via deletion/inactivation of the ITGA1/ITGA2 locus or via loss of TEAD1, contributes to PCa progression by inducing TGFβ1-driven EMT.

Lysine methyltransferase SMYD2 enhances androgen receptor signaling to modulate CRPC cell resistance to enzalutamide

Androgen receptors (ARs) play key roles in prostate cancer (PCa) progression and castration-resistant prostate cancer (CRPC) resistance to drug therapy. SET and MYND domain containing protein 2 (SMYD2), a lysine methyltransferase, has been reported to promote tumors by transcriptionally methylating important oncogenes or tumor repressor genes. However, the role of SMYD2 in CRPC drug resistance remains unclear. In this study, we found that SMYD2 expression was significantly upregulated in PCa tissues and cell lines. High SMYD2 expression indicated poor CRPC-free survival and overall survival in patients. SMYD2 knockdown dramatically inhibited the proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) potential of 22Rv1 and C4-2 cells. Conversely, ectopic overexpression of SMYD2 promoted these effects in 22Rv1 and C4-2 cells. Mechanistically, SMYD2 methylated and phosphorylated ARs to affect AR ubiquitination and proteasome degradation, which further alters the AR transcriptome in CRPC cells. Importantly, the SMYD2 inhibitor AZ505 had a synergistic therapeutic effect with enzalutamide in CRPC cells and mouse models; however, it could also re-sensitize resistant CRPC cells to enzalutamide. Our findings demonstrated that SMYD2 enhances the methylation and phosphorylation of ARs and affects AR ubiquitination and proteasome degradation to modulate CRPC cell resistance to enzalutamide, indicating that SMYD2 serves as a crucial oncogene in PCa and is an ideal therapeutic target for CRPC.

SLCO1B3 and SLCO2B1 genotypes, androgen deprivation therapy, and prostate cancer outcomes: a prospective cohort study and meta-analysis

Solute carrier organic anion (SLCO) transporters (OATP transporters) are involved in cellular uptake of drugs and hormones. Germline variants in SLCO1B3 and SLCO2B1 have been implicated in prostate cancer progression and therapy response, including to androgen deprivation and statin medications, but results have appeared heterogeneous. We conducted a cohort study of five single-nucleotide polymorphisms (SNPs) in SLCO1B3 and SLCO2B1 with prior evidence among 3208 men with prostate cancer who participated in the Health Professionals Follow-up Study or the Physicians' Health Study, following participants prospectively after diagnosis over 32 years (median, 14 years) for development of metastases and cancer-specific death (lethal disease, 382 events). Results were suggestive of, but not conclusive for, associations between some SNPs and lethal disease and differences by androgen deprivation and statin use. All candidate SNPs were associated with SLCO mRNA expression in tumor-adjacent prostate tissue. We also conducted a systematic review and harmonized estimates for a dose-response meta-analysis of all available data, including 9 further studies, for a total of 5598 patients and 1473 clinical events. The A allele of the exonic SNP rs12422149 (14% prevalence), which leads to lower cellular testosterone precursor uptake via SLCO2B1, was associated with lower rates of prostate cancer progression (hazard ratio per A allele, 0.80; 95% confidence interval, 0.69-0.93), with little heterogeneity between studies (I2, 0.27). Collectively, the totality of evidence suggests a strong association between inherited genetic variation in SLCO2B1 and prostate cancer prognosis, with potential clinical use in risk stratification related to androgen deprivation therapy.

Establishment of novel ferroptosis-related prognostic subtypes correlating with immune dysfunction in prostate cancer patients

Background

We aimed to identify two new prognostic subtypes and create a predictive index for prostate cancer (PCa) patients based on ferroptosis database.

Methods

The nonnegative matrix factorization approach was used to identify molecular subtypes. We investigate the differences between cluster 1 and cluster 2 in terms of clinical features, functional pathways, tumour stemness, tumour heterogeneity, gene mutation and tumour immune microenvironment score after identifying the two molecular subtypes. Colony formation assay and flow cytometry assay were performed.

Results

The stratification of two clusters was closely connected to BCR-free survival using the nonnegative matrix factorization method, which was validated in the other three datasets. Furthermore, multivariate Cox regression analysis revealed that this classification was an independent risk factor for patients with PCa. Ribosome, aminoacyl tRNA production, oxidative phosphorylation, and Parkinson's disease-related pathways were shown to be highly enriched in cluster 1. In comparison to cluster 2, patients in cluster 1 exhibited significantly reduced CD4+ T cells, CD8+ T cells, neutrophils, dendritic cells and tumor immune microenvironment scores. Only HHLA2 was more abundant in cluster 1. Moreover, we found that P4HB downregulation could significantly inhibit the colony formation ability and contributed to cell apoptosis of C4-2B and DU145 cell lines.

Conclusions

We discovered two new prognostic subtypes associated with immunological dysfunction in PCa patients based on ferroptosis-related genes and found that P4HB downregulation could significantly inhibit the colony formation ability and contributed to cell apoptosis of PCa cell lines.

The Oncogenic Protein Kinase/ATPase RIOK1 Is Up-Regulated via the c-myc/E2F Transcription Factor Axis in Prostate Cancer

The atypical protein kinase/ATPase RIO kinase (RIOK)-1 is involved in pre-40S ribosomal subunit production, cell-cycle progression, and protein arginine N-methyltransferase 5 methylosome substrate recruitment. RIOK1 overexpression is a characteristic of several malignancies and is correlated with cancer stage, therapy resistance, poor patient survival, and other prognostic factors. However, its role in prostate cancer (PCa) is unknown. In this study, the expression, regulation, and therapeutic potential of RIOK1 in PCa were examined. RIOK1 mRNA and protein expression were elevated in PCa tissue samples and correlated with proliferative and protein homeostasis-related pathways. RIOK1 was identified as a downstream target gene of the c-myc/E2F transcription factors. Proliferation of PCa cells was significantly reduced with RIOK1 knockdown and overexpression of the dominant-negative RIOK1-D324A mutant. Biochemical inhibition of RIOK1 with toyocamycin led to strong antiproliferative effects in androgen receptor-negative and -positive PCa cell lines with EC50 values of 3.5 to 8.8 nmol/L. Rapid decreases in RIOK1 protein expression and total rRNA content, and a shift in the 28S/18S rRNA ratio, were found with toyocamycin treatment. Apoptosis was induced with toyocamycin treatment at a level similar to that with the chemotherapeutic drug docetaxel used in clinical practice. In summary, the current study indicates that RIOK1 is a part of the MYC oncogene network, and as such, could be considered for future treatment of patients with PCa.

Prolyl 4-hydroxylase subunit beta (P4HB) could serve as a prognostic and radiosensitivity biomarker for prostate cancer patients

BACKGROUND

Prolyl 4-hydroxylase subunit beta (P4HB) has been reported as a suppressor in ferroptosis. However, no known empirical research has focused on exploring relationships between P4HB and prostate cancer (PCa). In this research, we initially examine the function of P4HB in PCa by thorough analysis of numerous databases and proliferation experiment.

METHODS

We analyzed the correlations of P4HB expression with prognosis, clinical features, mutation genes, tumor heterogeneity, stemness, tumor immune microenvironment and PCa cells using multiple databases and in vitro experiment with R 3.6.3 software and its suitable packages.

RESULTS

P4HB was significantly upregulated in tumor tissues compared to normal tissues and was closely related to biochemical recurrence-free survival. In terms of clinical correlations, we found that higher P4HB expression was significantly related to older age, higher Gleason score, advanced T stage and residual tumor. Surprisingly, P4HB had highly diagnostic accuracy of radiotherapy resistance (AUC 0.938). TGF beta signaling pathway and dorso ventral axis formation were upregulated in the group of low-expression P4HB. For tumor stemness, P4HB expression was positively related to EREG.EXPss and RNAss, but was negatively associated with ENHss and DNAss with statistical significance. For tumor heterogeneity, P4HB expression was positively related to MATH, but was negatively associated with tumor ploidy and microsatellite instability. For the overall assessment of TME, we observed that P4HB expression was negatively associated with all parameters, including B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score and ESTIMATE score. Spearman analysis showed that P4HB expression was negatively related to TIDE score with statistical significance. In vitro experiment, RT-qPCR and western blot showed that three siRNAs of P4HB were effective on the knockdown of P4HB expression. Furthermore, we observed that the downregulation of P4HB had significant influence on the cell proliferation of six PCa cell lines, including LNCap, C4-2, C4-2B, PC3, DU145 and 22RV1 cells.

CONCLUSIONS

In this study, we found that P4HB might serve as a prognostic biomarker and predict radiotherapy resistance for PCa patients. Downregulation of P4HB expression could inhibit the cell proliferation of PCa cells.

Differences in the pathogenetic characteristics of prostate cancer in the transitional and peripheral zones and the possible molecular biological mechanisms

Since the theory of modern anatomical partitioning of the prostate was proposed, the differences in the incidence and pathological parameters of prostate cancer between the peripheral zone and transition zone have been gradually revealed. It suggests that there are differences in the pathogenic pathways and molecular biology of prostate cancer between different regions of origin. Over the past decade, advances in sequencing technologies have revealed more about molecules, genomes, and cell types specific to the peripheral and transitional zones. In recent years, the innovation of spatial imaging and multiple-parameter magnetic resonance imaging has provided new technical support for the zonal study of prostate cancer. In this work, we reviewed all the research results and the latest research progress in the study of prostate cancer in the past two decades. We summarized and proposed several vital issues and focused directions for understanding the differences between peripheral and transitional zones in prostate cancer.

Biochemical activity induced by a germline variation in KLK3 (PSA) associates with cellular function and clinical outcome in prostate cancer

Genetic variation at the 19q13.3 KLK locus is linked with prostate cancer susceptibility. The non-synonymous KLK3 SNP, rs17632542 (c.536T>C; Ile163Thr-substitution in PSA) is associated with reduced prostate cancer risk, however, the functional relevance is unknown. Here, we identify that the SNP variant-induced change in PSA biochemical activity as a previously undescribed function mediating prostate cancer pathogenesis. The 'Thr' PSA variant led to small subcutaneous tumours, supporting reduced prostate cancer risk. However, 'Thr' PSA also displayed higher metastatic potential with pronounced osteolytic activity in an experimental metastasis in-vivo model. Biochemical characterization of this PSA variant demonstrated markedly reduced proteolytic activity that correlated with differences in in-vivo tumour burden. The SNP is associated with increased risk for aggressive disease and prostate cancer-specific mortality in three independent cohorts, highlighting its critical function in mediating metastasis. Carriers of this SNP allele had reduced serum total PSA and a higher free/total PSA ratio that could contribute to late biopsy decisions and delay in diagnosis. Our results provide a molecular explanation for the prominent 19q13.3 KLK locus, rs17632542 SNP, association with a spectrum of prostate cancer clinical outcomes.

The Prostate Stromal Transcriptome in Aggressive and Lethal Prostate Cancer

Prostate cancer has a heterogeneous prognosis. Most previous studies have focused on the identification of prognostic biomarkers in the prostate cancer tumor. However, it is increasingly recognized that the tumor microenvironment contributes to prostate cancer aggressiveness and progression. We therefore examined whole transcriptome expression of the prostate stroma and associations with aggressive and lethal prostate cancer. We performed RNA sequencing (Illumina TruSeq Exome Capture) of 272 tumor-adjacent and 120 benign-adjacent macrodissected prostate stromal samples from 293 men with prostate cancer from the Health Professionals Follow-up Study and Physicians' Health Study. We performed differential expression analysis comparing gene expression and pathways by Gleason score and lethal outcome. We also tested a previously developed stromal gene signature of Gleason score in these datasets. Comparing high- with low-Gleason score cancers, 26 genes (P < 0.001) and 12 pathways (FDR < 0.20) were significantly differentially expressed in tumor-adjacent stroma, including pathways related to stroma composition remodeling and DNA repair, with 73 genes and 65 pathways significant in benign-adjacent stroma. Comparing lethal with nonlethal prostate cancer, 11 genes were differentially expressed in tumor-adjacent and 15 genes in benign-adjacent stroma, and pathways involved in inflammatory response were differentially enriched in both tumor and benign-adjacent stroma. In addition, our previously identified Gleason stromal gene signature was validated to be associated with Gleason score in these data. Implications: Our study uncovers stroma-specific genes and pathways that are differentially enriched with high Gleason score and lethal prostate cancer, demonstrating that the molecular investigation of the tumor microenvironment can provide additional information about prostate cancer prognosis.

Prostate Cancer Transcriptomic Regulation by the Interplay of Germline Risk Alleles, Somatic Mutations, and 3D Genomic Architecture

Prostate cancer is one of the most heritable human cancers. Genome-wide association studies have identified at least 185 prostate cancer germline risk alleles, most noncoding. We used integrative three-dimensional (3D) spatial genomics to identify the chromatin interaction targets of 45 prostate cancer risk alleles, 31 of which were associated with the transcriptional regulation of target genes in 565 localized prostate tumors. To supplement these 31, we verified transcriptional targets for 56 additional risk alleles using linear proximity and linkage disequilibrium analysis in localized prostate tumors. Some individual risk alleles influenced multiple target genes; others specifically influenced only distal genes while leaving proximal ones unaffected. Several risk alleles exhibited widespread germline-somatic interactions in transcriptional regulation, having different effects in tumors with loss of PTEN or RB1 relative to those without. These data clarify functional prostate cancer risk alleles in large linkage blocks and outline a strategy to model multidimensional transcriptional regulation.

SIGNIFICANCE

Many prostate cancer germline risk alleles are enriched in the noncoding regions of the genome and are hypothesized to regulate transcription. We present a 3D genomics framework to unravel risk SNP function and describe the widespread germline-somatic interplay in transcription control. This article is highlighted in the In This Issue feature, p. 2711.

Differences in Prostate Cancer Transcriptomes by Age at Diagnosis: Are Primary Tumors from Older Men Inherently Different?

Older age at diagnosis is consistently associated with worse clinical outcomes in prostate cancer. We sought to characterize gene expression profiles of prostate tumor tissue by age at diagnosis. We conducted a discovery analysis in The Cancer Genome Atlas prostate cancer dataset (n = 320; 29% of men >65 years at diagnosis), using linear regressions of age at diagnosis and mRNA expression and adjusting for TMPRSS2:ERG fusion status and race. This analysis identified 13 age-related candidate genes at FDR < 0.1, six of which were also found in an analysis additionally adjusted for Gleason score. We then validated the 13 age-related genes in a transcriptome study nested in the Health Professionals Follow-up Study and Physicians' Health Study (n = 374; 53% of men >65 years). Gene expression differences by age in the 13 candidate genes were directionally consistent, and age at diagnosis was weakly associated with the 13-gene score. However, the age-related genes were not consistently associated with risk of metastases and prostate cancer-specific death. Collectively, these findings argue against tumor genomic differences as a main explanation for age-related differences in prostate cancer prognosis.

PREVENTION RELEVANCE

Older age at diagnosis is consistently associated with worse clinical outcomes in prostate cancer. This study with independent discovery and validation sets and long-term follow-up suggests that prevention of lethal prostate cancer should focus on implementing appropriate screening, staging, and treatment among older men without expecting fundamentally different tumor biology.

Leucine zipper protein 2 serves as a prognostic biomarker for prostate cancer correlating with immune infiltration and epigenetic regulation

Background

We sought to determine whether leucine zipper protein 2 (LUZP2) could benefit men with prostate cancer (PCa) undergoing radical radiotherapy (RT) or prostatectomy (RP).

Methods

Analysis was done on differentiating expression, clinical prognosis, co-expressed genes, immune infiltration, and epigenetic changes. All of our analyses were done using the R software (version 3.6.3) and the appropriate packages.

Results

In terms of PCa, tumor samples expressed LUZP2 more than normal samples did. In the TCGA database and GSE116918, we found that LUZP2 was the only independent risk factor for PCa. The shared enriched pathways for patients undergoing RP or RT were cell-cell adhesion, regulation of filopodium assembly, and extracellular matrix containing collagen. With the exception of TNFRSF14, we discovered that LUZP2 was negatively correlated with 21 immune checkpoints in PCa patients receiving RT. We found a significant inverse relationship between LUZP2 expression and the tumor immune environment, which included B cells, CD4+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score, in patients receiving RP or RT. Additionally, tumor purity was positively correlated with LUZP2. We found that the drug bortezomib may be susceptible to the LUZP2. DNA methylation was significantly associated with the mRNA expression of LUZP2 in PCa patients from the TCGA database, and LUZP2 methylation was positively correlated with immune cells. The proliferative activity of various PCa cells, which correlated to different stages of this disease, was also found to be significantly reduced by LUZP2 reduction, according to the results of our experimental work.

Conclusions

We proposed a relatively comprehensive understanding of the roles of LUZP2 on PCa from the fresh perspective of senescence.

Mitochondrial Aldehyde Dehydrogenase 2 Represents a Potential Biomarker of Biochemical Recurrence in Prostate Cancer Patients

BACKGROUND

We aimed to explore the role of mitochondrial aldehyde dehydrogenase 2 (ALDH2) in prostate cancer (PCa) patients and provide insights into the tumor immune microenvironment (TME) for those patients undergoing radical radiotherapy.

METHODS

We performed all analyses using R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish network of competing endogenous RNAs (ceRNAs).

RESULTS

Downregulation of ADLH2 was significantly associated with higher risk of BCR-free survival (HR: 0.40, 95%CI: 0.24-0.68, p = 0.001) and metastasis-free survival (HR: 0.21, 95%CI: 0.09-0.49, p = 0.002). Additionally, ALDH2 repression contributed to significantly shorter BCR-free survival in the TCGA database (HR: 0.55, 95%CI: 0.33-0.93, p = 0.027). For immune checkpoints, patients that expressed a higher level of CD96 had a higher risk of BCR than their counterparts (HR: 1.79, 95%CI: 1.06-3.03, p = 0.032), as well as NRP1 (HR: 2.18, 95%CI: 1.29-3.69, p = 0.005). In terms of the TME parameters, the spearman analysis showed that ALDH was positively associated with B cells (r: 0.13), CD8+ T cells (r: 0.19), neutrophils (r: 0.13), and macrophages (r: 0.17). Patients with higher score of neutrophils (HR: 1.75, 95%CI: 1.03-2.95, p = 0.038), immune score (HR: 1.92, 95%CI: 1.14-3.25, p = 0.017), stromal score (HR: 2.52, 95%CI: 1.49-4.26, p = 0.001), and estimate score (HR: 1.81, 95%CI: 1.07-3.06, p = 0.028) had higher risk of BCR than their counterparts. Our ceRNA network found that PART1 might regulate the expression of ALDH via has-miR-578 and has-miR-6833-3p. Besides, PHA-793887, PI-103, and piperlongumine had better correlations with ALDH2.

CONCLUSIONS

We found that ALDH2 might serve as a potential biomarker predicting biochemical recurrence for PCa patients.

A cellular senescence-related gene prognostic index for biochemical recurrence and drug resistance in patients with prostate cancer

In this study, we aimed to establish a novel cellular senescence-related gene prognostic index (CSG PI) to predict biochemical recurrence (BCR) and drug resistance in patients with prostate cancer (PCa) undergoing radical radiotherapy or prostatectomy. We performed all analyses using R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish a network of transcription factors and competing endogenous RNAs. Three cellular senescence-related genes were used to establish the CSGPI. We observed that CSGPI was an independent risk factor for BCR in PCa patients (HR: 2.62; 95% CI: 1.55-4.44), consistent with the results of external validation (HR: 1.88; 95% CI: 1.12-3.14). The CSGPI had a moderate diagnostic effect on drug resistance (AUC: 0.812, 95% CI: 0.586-1.000). The lncRNA PART1 was significantly associated with BCR (HR: 0.46; 95% CI: 0.27-0.77), and might modulate the mRNA expression of definitive genes through interactions with 57 miRNAs. Gene set enrichment analysis indicated that CSGPI was closely related to ECM receptor interaction, focal adhesion, TGF beta signaling pathway, pathway in cancer, regulation of actin cytoskeleton, and so on. Immune checkpoint analysis showed that PDCD1LG2 and CD96 were significantly higher in the BCR group compared to non-BCR group, and patients with higher expression of CD96 were more prone to BCR than their counterparts (HR: 1.79; 95% CI: 1.06-3.03). In addition, the CSGPI score was significantly associated with the mRNA expression of HAVCR2, CD96, and CD47. Analysis of mismatch repair and methyltransferase genes showed that DNMT3B was more highly expressed in the BCR group and that patients with higher expression of DNMT3B experienced a higher risk of BCR (HR: 2.08; 95% CI: 1.23-3.52). We observed that M1 macrophage, CD8+ T cells, stromal score, immune score, and ESTIMATE score were higher in the BCR group. In contrast, tumor purity was less scored in the BCR group. Spearman analysis revealed a positive relationship between CSGPI and M1 macrophages, CD4+ T cells, dendritic cells, stromal score, immune score, and ESTIMATE score. In conclusion, we found that the CSGPI might serve as a biomarker to predict BCR and drug resistance in PCa patients. Moreover, CD96 and DNMT3B might be potential treatment targets, and immune evasion might contribute to the BCR process of PCa.

Exploiting Dependence of Castration-Resistant Prostate Cancer on the Arginine Vasopressin Signaling Axis by Repurposing Vaptans

Men with advanced prostate cancer are treated by androgen deprivation therapy but the disease recurs as incurable castration-resistant prostate cancer (CRPC), requiring new treatment options. We previously demonstrated that the G protein-coupled receptor (GPCR) arginine vasopressin receptor type1A (AVPR1A) is expressed in CRPC and promotes castration-resistant growth in vitro and in vivo. AVPR1A is part of a family of GPCR's including arginine vasopressin receptor type 2 (AVPR2). Interrogation of prostate cancer patient sample data revealed that coexpression of AVPR1A and AVPR2 is highly correlated with disease progression. Stimulation of AVPR2 with a selective agonist desmopressin promoted CRPC cell proliferation through cAMP/protein kinase A signaling, consistent with AVPR2 coupling to the G protein subunit alpha s. In contrast, blocking AVPR2 with a selective FDA-approved antagonist, tolvaptan, reduced cell growth. In CRPC xenografts, antagonizing AVPR2, AVPR1A, or both significantly reduced CRPC tumor growth as well as decreased on-target markers of tumor burden. Combinatorial use of AVPR1A and AVPR2 antagonists promoted apoptosis synergistically in CRPC cells. Furthermore, we found that castration-resistant cells produced AVP, the endogenous ligand for arginine vasopressin receptors, and knockout of AVP in CRPC cells significantly reduced proliferation suggesting possible AVP autocrine signaling. These data indicate that the AVP/arginine vasopressin receptor signaling axis represents a promising and clinically actionable target for CRPC.

IMPLICATIONS

The arginine vasopressin signaling axis in CRPC provides a therapeutic window that is targetable through repurposing safe and effective AVPR1A and AVPR2 antagonists.

TRIM33 drives prostate tumor growth by stabilizing androgen receptor from Skp2-mediated degradation

Androgen receptor (AR) is a master transcription factor that drives prostate cancer (PCa) development and progression. Alterations in the expression or activity of AR coregulators significantly impact the outcome of the disease. Using a proteomics approach, we identified the tripartite motif-containing 33 (TRIM33) as a novel transcriptional coactivator of AR. We demonstrate that TRIM33 facilitates AR chromatin binding to directly regulate a transcription program that promotes PCa progression. TRIM33 further stabilizes AR by protecting it from Skp2-mediated ubiquitination and proteasomal degradation. We also show that TRIM33 is essential for PCa tumor growth by avoiding cell-cycle arrest and apoptosis, and TRIM33 knockdown sensitizes PCa cells to AR antagonists. In clinical analyses, we find TRIM33 upregulated in multiple PCa patient cohorts. Finally, we uncover an AR-TRIM33-coactivated gene signature highly expressed in PCa tumors and predict disease recurrence. Overall, our results reveal that TRIM33 is an oncogenic AR coactivator in PCa and a potential therapeutic target for PCa treatment.

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

High secretion of the metabolites citrate and spermine is a unique hallmark for normal prostate epithelial cells, and is reduced in aggressive prostate cancer. However, the identity of the genes controlling this biological process is mostly unknown. In this study, we have created a gene signature of 150 genes connected to citrate and spermine secretion in the prostate. We have computationally integrated metabolic measurements with multiple transcriptomics datasets from the public domain, including 3826 tissue samples from prostate and prostate cancer. The accuracy of the signature is validated by its unique enrichment in prostate samples and prostate epithelial tissue compartments. The signature highlights genes AZGP1, ANPEP and metallothioneins with zinc-binding properties not previously studied in the prostate, and the expression of these genes are reduced in more aggressive cancer lesions. However, the absence of signature enrichment in common prostate model systems can make it challenging to study these genes mechanistically.

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Novel 150 gene signature reflecting prostatic citrate and spermine secretion

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Identified several zinc-binding proteins not previously investigated in the prostate

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The signature is absent in prostate model systems

A gene prognostic index from cellular senescence predicting metastasis and radioresistance for prostate cancer

Background

Senescent cells have been identified in the aging prostate, and the senescence-associated secretory phenotype might be linked to prostate cancer (PCa). Thus, we established a cellular senescence-related gene prognostic index (CSGPI) to predict metastasis and radioresistance in PCa.

Methods

We used Lasso and Cox regression analysis to establish the CSGPI. Clinical correlation, external validation, functional enrichment analysis, drug and cell line analysis, and tumor immune environment analysis were conducted. All analyses were conducted with R version 3.6.3 and its suitable packages.

Results

We used ALCAM and ALDH2 to establish the CSGPI risk score. High-risk patients experienced a higher risk of metastasis than their counterparts (HR: 10.37, 95% CI 4.50–23.93, p < 0.001), consistent with the results in the TCGA database (HR: 1.60, 95% CI 1.03–2.47, p = 0.038). Furthermore, CSGPI had high diagnostic accuracy distinguishing radioresistance from no radioresistance (AUC: 0.938, 95% CI 0.834–1.000). GSEA showed that high-risk patients were highly associated with apoptosis, cell cycle, ribosome, base excision repair, aminoacyl-tRNA biosynthesis, and mismatch repair. For immune checkpoint analysis, we found that PDCD1LG2 and CD226 were expressed at significantly higher levels in patients with metastasis than in those without metastasis. In addition, higher expression of CD226 significantly increased the risk of metastasis (HR: 3.65, 95% CI 1.58–8.42, p = 0.006). We observed that AZD7762, PHA-793887, PI-103, and SNX-2112 might be sensitive to ALDH2 and ALCAM, and PC3 could be the potential cell line used to investigate the interaction among ALDH2, ALCAM, and the above drugs.

Conclusions

We found that CSGPI might serve as an effective biomarker predicting metastasis probability and radioresistance for PCa and proposed that immune evasion was involved in the process of PCa metastasis.

Mitochondria Dysfunction-Mediated Molecular Subtypes and Gene Prognostic Index for Prostate Cancer Patients Undergoing Radical Prostatectomy or Radiotherapy

Background

Given the age relevance of prostate cancer (PCa) and the role of mitochondrial dysfunction (MIDS) in aging, we orchestrated molecular subtypes and identified key genes for PCa from the perspective of MIDS.

Methods

Cluster analysis, COX regression analysis, function analysis, and tumor immune environment were conducted. We performed all analyses using software R 3.6.3 and its suitable packages.

Results

CXCL14, SFRP4, and CD38 were eventually identified to classify the PCa patients in The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) dataset into two distinct clusters. Patients in the cluster 2 had shorter BCR-free survival than those in the cluster 1 in terms of both TCGA database and GEO dataset. We divided the patients from the TCGA database and the GEO dataset into high- and low-risk groups according to the median of MIDS-related genetic prognostic index. For patients in the TCGA database, the biochemical recurrence (BCR) risk in high-risk group was 2.34 times higher than that in low-risk group. Similarly, for patients in the GEO dataset, the risk of BCR and metastasis in high-risk group was 2.35 and 3.04 times higher than that in low-risk group, respectively. Cluster 2 was closely associated with advanced T stage and higher Gleason score for patients undergoing radical prostatectomy or radiotherapy. For patients undergoing radical prostatectomy, the number of CD8⁺ T cells was significantly lower in cluster 2 than in cluster 1, while cluster 2 had significantly higher stromal score than cluster 1. For patients undergoing radical radiotherapy, cluster 2 had significantly higher level of CD8⁺ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score, but showed lower level of tumor purity than cluster 1.

Conclusions

We proposed distinctly prognosis-related molecular subtypes at genetic level and related formula for PCa patients undergoing radical prostatectomy or radiotherapy, mainly to provide a roadmap for precision medicine.

A Ferroptosis-Related Gene Prognostic Index Associated With Biochemical Recurrence and Radiation Resistance for Patients With Prostate Cancer Undergoing Radical Radiotherapy

Background: Ferroptosis is a new type of programmed cell death which has been reported to be involved in the development of various cancers. In this study, we attempted to explore the possible links between ferroptosis and prostate cancer (PCa), and a novel ferroptosis-related gene prognostic index (FGPI) was constructed to predict biochemical recurrence (BCR) and radiation resistance for PCa patients undergoing radical radiotherapy (RRT). Moreover, the tumor immune microenvironment (TME) of PCa was analyzed.

Methods: We merged four GEO datasets by removing batch effects. All analyses were conducted with R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish a network of transcriptional factor and competing endogenous RNA.

Results: We established the FGPI based on ACSL3 and EPAS1. We observed that FGPI was an independent risk factor of BCR for PCa patients (HR: 3.03; 95% CI: 1.68–5.48), consistent with the result of internal validation (HR: 3.44; 95% CI: 1.68–7.05). Furthermore, FGPI showed high ability to identify radiation resistance (AUC: 0.963; 95% CI: 0.882–1.00). LncRNA PART1 was significantly associated with BCR and might modulate the mRNA expression of EPAS1 and ACSL3 through interactions with 60 miRNAs. Gene set enrichment analysis indicated that FGPI was enriched in epithelial–mesenchymal transition, allograft rejection, TGF beta signaling pathway, and ECM receptor interaction. Immune checkpoint and m6A analyses showed that PD-L2, CD96, and METTL14 were differentially expressed between BCR and no BCR groups, among which CD96 was significantly associated with BCR-free survival (HR: 1.79; 95% CI: 1.06–3.03). We observed that cancer-related fibroblasts (CAFs), macrophages, stromal score, immune score, estimate score, and tumor purity were differentially expressed between BCR and no BCR groups and closely related to BCR-free survival (HRs were 2.17, 1.79, 2.20, 1.93, 1.92, and 0.52 for cancer-related fibroblasts, macrophages, stromal score, immune score, estimate score, and tumor purity, respectively). Moreover, cancer-related fibroblasts (coefficient: 0.20), stromal score (coefficient: 0.14), immune score (coefficient: 0.14), estimate score (coefficient: 0.15), and tumor purity (coefficient: −0.15) were significantly related to FGPI, among which higher positive correlation between cancer-related fibroblasts and FGPI was observed.

Conclusion: We found that FGPI based on ACSL3 and EPAS1 might be used to predict BCR and radiation resistance for PCa patients. CD96 and PD-L2 might be a possible target for drug action. Besides, we highlighted the importance of immune evasion in the process of BCR.

Prostate zones and cancer: lost in transition?

Localized prostate cancer shows great clinical, genetic and environmental heterogeneity; however, prostate cancer treatment is currently guided solely by clinical staging, serum PSA levels and histology. Increasingly, the roles of differential genomics, multifocality and spatial distribution in tumorigenesis are being considered to further personalize treatment. The human prostate is divided into three zones based on its histological features: the peripheral zone (PZ), the transition zone (TZ) and the central zone (CZ). Each zone has variable prostate cancer incidence, prognosis and outcomes, with TZ prostate tumours having better clinical outcomes than PZ and CZ tumours. Molecular and cell biological studies can improve understanding of the unique molecular, genomic and zonal cell type features that underlie the differences in tumour progression and aggression between the zones. The unique biology of each zonal tumour type could help to guide individualized treatment and patient risk stratification.

A Gene Prognostic Index Associated With Epithelial-Mesenchymal Transition Predicting Biochemical Recurrence and Tumor Chemoresistance for Prostate Cancer

BACKGROUND

We aimed to establish a novel epithelial-mesenchymal transition (EMT)-related gene prognostic index (EMTGPI) associated with biochemical recurrence (BCR) and drug resistance for prostate cancer (PCa).

METHODS

We used Lasso and Cox regression analysis to establish the EMTGPI. All analyses were conducted with R version 3.6.3 and its suitable packages.

RESULTS

We established the EMTGPI based on SFRP4 and SPP1. Patients in high-risk group had 2.23 times of BCR risk than those in low-risk group (p = 0.003), as well as 2.36 times of metastasis risk (p = 0.053). In external validation, we detected similar diagnostic efficacy and prognostic value in terms of BCR free survival. For drug resistance, we observe moderately diagnostic accuracy of EMTGPI score (AUC: 0.804). We found that PDCD1LG2 (p = 0.04) and CD96 (p = 0.01) expressed higher in BCR patients compared with their counterpart. For TME analysis, we detected that CD8+ T cells and M1 macrophages expressed higher in BCR group. Moreover, stromal score (p = 0.003), immune score (p = 0.01), and estimate score (p = 0.003) were higher in BCR patients. We found that EMTGPI was significantly related to HAVCR2 (r: 0.34), CD96 (r: 0.26), CD47 (r: 0.22), KIR3DL1 (r: -0.21), KLRD1 (r: -0.21), and CD2 (r: 0.21). In addition, we observed that EMTGPI was significantly associated with M1 macrophages (r: 0.6), M2 macrophages (r: -0.33), monocytes (r: -0.18), neutrophils (r: -0.43), CD8+ T cells (r: 0.13), and dendritic cells (r: 0.37). PHA-793887 was the common drug sensitive to SPP1 and SFRP4, and PC3 and DU145 were the common PCa-related cell lines of SPP1, SFRP4, and PHA-793887.

CONCLUSIONS

We concluded that the EMTGPI score based on SFRP4 and SPP1 could be used to predict BCR for PCa patients. We confirmed the impact of immune evasion on the BCR process of PCa.

A transcriptome-wide association study identifies novel candidate susceptibility genes for prostate cancer risk

A large proportion of heritability for prostate cancer risk remains unknown. Transcriptome-wide association study combined with validation comparing overall levels will help to identify candidate genes potentially playing a role in prostate cancer development. Using data from the Genotype-Tissue Expression Project, we built genetic models to predict normal prostate tissue gene expression using the statistical framework PrediXcan, a modified version of the unified test for molecular signatures and Joint-Tissue Imputation. We applied these prediction models to the genetic data of 79 194 prostate cancer cases and 61 112 controls to investigate the associations of genetically determined gene expression with prostate cancer risk. Focusing on associated genes, we compared their expression in prostate tumor vs normal prostate tissue, compared methylation of CpG sites located at these loci in prostate tumor vs normal tissue, and assessed the correlations between the differentiated genes' expression and the methylation of corresponding CpG sites, by analyzing The Cancer Genome Atlas (TCGA) data. We identified 573 genes showing an association with prostate cancer risk at a false discovery rate (FDR) ≤ 0.05, including 451 novel genes and 122 previously reported genes. Of the 573 genes, 152 showed differential expression in prostate tumor vs normal tissue samples. At loci of 57 genes, 151 CpG sites showed differential methylation in prostate tumor vs normal tissue samples. Of these, 20 CpG sites were correlated with expression of 11 corresponding genes. In this TWAS, we identified novel candidate susceptibility genes for prostate cancer risk, providing new insights into prostate cancer genetics and biology.

DDX52 knockdown inhibits the growth of prostate cancer cells by regulating c-Myc signaling

BACKGROUND

DDX52 is a type of DEAD/H box RNA helicase that was identified as a novel prostate cancer (PCa) genetic locus and possible causal gene in a European large-scale transcriptome-wide association study. However, the functions of DDX52 in PCa remain undetermined. The c-Myc oncogene plays a crucial role in the development of PCa, but the factors that regulate the activity of c-Myc in PCa are still unknown.

METHODS

We determined DDX52 protein levels in PCa tissues using immunohistochemistry (IHC). DDX52 expression and survival outcomes in other PCa cohorts were examined using bioinformatics analysis. The inhibition of DDX52 via RNA interference with shRNA was used to clarify the effects of DDX52 on PCa cell growth in vitro and in vivo. Gene set enrichment analysis and RNA sequencing were used to explore the signaling regulated by DDX52 in PCa. Western blotting and IHC were used to determine the possible DDX52 signaling mechanism in PCa.

RESULTS

DDX52 expression was upregulated in PCa tissues. Bioinformatics analysis showed that the level of DDX52 further increased in advanced PCa, with a high DDX52 level indicating a poor outcome. In vitro and in vivo experiments showed that downregulating DDX52 impeded the growth of PCa cells. High DDX52 levels contributed to activating c-Myc signaling in PCa patients and PCa cells. Furthermore, DDX52 expression was regulated by c-Myc and positively correlated with c-Myc expression in PCa.

CONCLUSION

DDX52 was overexpressed in PCa tissues in contrast to normal prostate tissues. DDX52 knockdown repressed the growth of PCa cells in vitro and in vivo. Deleting c-Myc inhibited DDX52 expression, which affected the activation of c-Myc signaling.

Transcriptional landscape of PTEN loss in primary prostate cancer

BACKGROUND

PTEN is the most frequently lost tumor suppressor in primary prostate cancer (PCa) and its loss is associated with aggressive disease. However, the transcriptional changes associated with PTEN loss in PCa have not been described in detail. In this study, we highlight the transcriptional changes associated with PTEN loss in PCa.

METHODS

Using a meta-analysis approach, we leveraged two large PCa cohorts with experimentally validated PTEN and ERG status by Immunohistochemistry (IHC), to derive a transcriptomic signature of PTEN loss, while also accounting for potential confounders due to ERG rearrangements. This signature was expanded to lncRNAs using the TCGA quantifications from the FC-R2 expression atlas.

RESULTS

The signatures indicate a strong activation of both innate and adaptive immune systems upon PTEN loss, as well as an expected activation of cell-cycle genes. Moreover, we made use of our recently developed FC-R2 expression atlas to expand this signature to include many non-coding RNAs recently annotated by the FANTOM consortium. Highlighting potential novel lncRNAs associated with PTEN loss and PCa progression.

CONCLUSION

We created a PCa specific signature of the transcriptional landscape of PTEN loss that comprises both the coding and an extensive non-coding counterpart, highlighting potential new players in PCa progression. We also show that contrary to what is observed in other cancers, PTEN loss in PCa leads to increased activation of the immune system. These findings can help the development of new biomarkers and help guide therapy choices.

Gene Expression Pathways in Prostate Tissue Associated with Vigorous Physical Activity in Prostate Cancer

BACKGROUND

Men engaged in high physical activity have lower risks of advanced and fatal prostate cancer. Mechanisms underlying this association are not well understood but may include systemic and tumor-specific effects. We investigated potential mechanisms linking physical activity and gene expression in prostate tissue from men with prostate cancer.

METHODS

We included a subset of 118 men in the Health Professionals Follow-up Study diagnosed with prostate cancer between 1986 and 2005 with whole-transcriptome gene expression profiling on tumor and adjacent normal prostate tissue and physical activity data. Long-term vigorous physical activity was self-reported as the average time spent engaged in various forms of recreational physical activity at baseline and biennially until prostate cancer diagnosis. Gene set enrichment analysis was performed among KEGG and Hallmark gene sets to identify pathways with differential expression based on vigorous physical activity.

RESULTS

In adjacent normal tissue, we identified 25 KEGG gene sets enriched (downregulated) in the highest compared with lowest quintile of vigorous physical activity at an FDR <0.10, including a number of cancer- and immune-related pathways. Although no gene sets reached statistical significance in tumor tissue, top gene sets differentially expressed included TGF beta, apoptosis, and p53 signaling pathways.

CONCLUSIONS

These findings suggest that physical activity may influence the tumor microenvironment. Future studies are needed to confirm these findings and further investigate potential mechanisms linking physical activity to lethal prostate cancer.

IMPACT

Identification of gene expression alterations in the prostate associated with physical activity can improve our understanding of prostate cancer etiology.

Validation of prostate cancer risk variants rs10993994 and rs7098889 by CRISPR/Cas9 mediated genome editing

GWAS have identified numerous SNPs associated with prostate cancer risk. One such SNP is rs10993994. It is located in the β-microseminoprotein (MSMB) promoter region, mediates MSMB prostate secretion levels, and is linked to mRNA expression changes in both MSMB and the adjacent gene NCOA4. In addition, our previous work showed a second SNP, rs7098889, is in positive linkage disequilibrium with rs10993994 and associated with MSMB expression independent of rs10993994. Here, we generate a series of clones with single alleles removed by double guide RNA (gRNA) mediated CRISPR/Cas9 deletions, through which we demonstrate that each of these SNPs independently and greatly alters MSMB expression in an allele-specific manner. We further show that these SNPs have no substantial effect on the expression of NCOA4. These data demonstrate that a single SNP can have a large effect on gene expression and illustrate the importance of functional validation studies to deconvolute observed correlations. The method we have developed is generally applicable to test any SNP for which a relevant heterozygous cell line is available. AUTHOR SUMMARY: In pursuing the underlying biological mechanism of prostate cancer pathogenesis, scientists utilized the existence of common single nucleotide polymorphisms (SNPs) in the human genome as genetic markers to perform large scale genome wide association studies (GWAS) and have so far identified more than a hundred prostate cancer risk variants. Such variants provide an unbiased and systematic new venue to study the disease mechanism, and the next big challenge is to translate these genetic associations to the causal role of altered gene function in oncogenesis. The majority of these variants are waiting to be studied and lots of them may act in oncogenesis through gene expression regulation. To prove the concept, we took rs10993994 and its linked rs7098889 as an example and engineered single cell clones by allelic-specific CRISPR/Cas9 deletion to separate the effect of each allele. We observed that a single nucleotide difference would lead to surprisingly high level of MSMB gene expression change in a gene specific and cell-type specific manner. Our study strongly supports the notion that differential level of gene expression caused by risk variants and their associated genetic locus play a major role in oncogenesis and also highlights the importance of studying the function of MSMB encoded β-MSP in prostate cancer pathogenesis.

A four-gene signature associated with clinical features can better predict prognosis in prostate cancer

Prostate cancer (PCa) is one of the most deadly urinary tumors in men globally, and the 5‐year over survival is poor due to metastasis of tumor. It is significant to explore potential biomarkers for early diagnosis and personalized therapy of PCa. In the present study, we performed an integrated analysis based on multiple microarrays in the Gene Expression Omnibus (GEO) dataset and obtained differentially expressed genes (DEGs) between 510 PCa and 259 benign issues. The weighted correlation network analysis indicated that prognostic profile was the most relevant to DEGs. Then, univariate and multivariate COX regression analyses were conducted and four prognostic genes were obtained to establish a four‐gene prognostic model. And the predictive effect and expression profiles of the four genes were well validated in another GEO dataset, The Cancer Genome Atlas and the Human Protein Atlas datasets. Furthermore, combination of four‐gene model and clinical features was analyzed systematically to guide the prognosis of patients with PCa to a largest extent. In summary, our findings indicate that four genes had important prognostic significance in PCa and combination of four‐gene model and clinical features could achieve a better prediction to guide the prognosis of patients with PCa.

Multiplex Immunofluorescence in Formalin-Fixed Paraffin-Embedded Tumor Tissue to Identify Single-Cell-Level PI3K Pathway Activation

PURPOSE

Identifying cancers with high PI3K pathway activity is critical for treatment selection and eligibility into clinical trials of PI3K inhibitors. Assessments of tumor signaling pathway activity need to consider intratumoral heterogeneity and multiple regulatory nodes.

EXPERIMENTAL DESIGN

We established a novel, mechanistically informed approach to assessing tumor signaling pathways by quantifying single-cell-level multiplex immunofluorescence using custom algorithms. In a proof-of-concept study, we stained archival formalin-fixed, paraffin-embedded (FFPE) tissue from patients with primary prostate cancer in two prospective cohort studies, the Health Professionals Follow-up Study and the Physicians' Health Study. PTEN, stathmin, and phospho-S6 were quantified on 14 tissue microarrays as indicators of PI3K activation to derive cell-level PI3K scores.

RESULTS

In 1,001 men, 988,254 tumor cells were assessed (median, 743 per tumor; interquartile range, 290-1,377). PI3K scores were higher in tumors with PTEN loss scored by a pathologist, higher Gleason grade, and a new, validated bulk PI3K transcriptional signature. Unsupervised machine-learning approaches resulted in similar clustering. Within-tumor heterogeneity in cell-level PI3K scores was high. During long-term follow-up (median, 15.3 years), rates of progression to metastases and death from prostate cancer were twice as high in the highest quartile of PI3K activation compared with the lowest quartile (hazard ratio, 2.04; 95% confidence interval, 1.13-3.68).

CONCLUSIONS

Our novel pathway-focused approach to quantifying single-cell-level immunofluorescence in FFPE tissue identifies prostate tumors with PI3K pathway activation that are more aggressive and may respond to pathway inhibitors.

Prostate cancer risk SNP rs10993994 is a trans-eQTL for SNHG11 mediated through MSMB

How genome-wide association studies-identified single-nucleotide polymorphisms (SNPs) affect remote genes remains unknown. Expression quantitative trait locus (eQTL) association meta-analysis on 496 prostate tumor and 602 normal prostate samples with 117 SNPs revealed novel cis-eQTLs and trans-eQTLs. Mediation testing and colocalization analysis demonstrate that MSMB is a cis-acting mediator for SNHG11 (P < 0.01). Removing rs10993994 in LNCaP cell lines by CRISPR/Cas9 editing shows that the C-allele corresponds with an over 100-fold increase in MSMB expression and 5-fold increase in SNHG11 compared with the T-allele. Colocalization analysis confirmed that the same set of SNPs associated with MSMB expression is associated with SNHG11 expression (posterior probability of shared variants is 66.6% in tumor and 91.4% in benign). These analyses further demonstrate variants driving MSMB expression differ in tumor and normal, suggesting regulatory network rewiring during tumorigenesis.

Targeting eIF3f Suppresses the Growth of Prostate Cancer Cells by Inhibiting Akt Signaling

Background

Eukaryotic initiation factor 3 (eIF3) is the largest translation initiation factor, and oncogenic roles have been discovered for its subunits, including the f subunit (ie, eIF3f), in various human cancers. However, the roles of eIF3f in the development and progression of prostate cancer (PCa) have not been reported.

Materials and Methods

We performed in silico analysis to screen the expression of eIF3 subunits. Relevant shRNAs were used to knock down eIF3 subunits in 22Rv1 cells and cell proliferation was analyzed. eIF3f expression in PCa specimens was confirmed by immunohistochemistry. eIF3f knockdown was established to evaluate the effects of eIF3f on cell proliferation in vitro and in vivo. RNA‐seq, bioinformatics analysis and Western blotting were applied to explore the molecular details underlying the biological function of eIF3f in PCa cells. shRNA-resistant eIF3f and myristoylated-Akt were used to rescue the effects of eIF3f disturbance on PCa cells.

Results

Functional analyses confirmed that eIF3f is essential for PCa proliferation. Notably, the expression of eIF3f was found to be elevated in human PCa tissues as well as in PCa cell lines. eIF3f silencing significantly suppressed the growth of PCa cells, both in vitro and in vivo. eIF3f expression was positively correlated with Akt signaling activity in RNA-seq profiles and published prostate cohorts. Knockdown of eIF3f markedly reduced the levels of phosphorylated Akt in PCa cells. Exogenous expression of shRNA-resistant eIF3f in eIF3f knockdown cells restored Akt phosphorylation levels and cell growth. Importantly, rescue experiments revealed that ectopic expression of myristoylated-Akt partially alleviated the suppressive effects of eIF3f disturbance with respect to the growth of PCa cells.

Conclusion

These results suggested that eIF3f has an oncogenic role in PCa, mediated at least partially through the regulation of Akt signaling, and that eIF3f represents a potential target for the inhibition of PCa growth and progression.

Aggressive prostate cancer phenotype and genome-wide association studies: where are we now?

The majority of prostate cancer (PCa) is indolent, however, a percentage of patients are initially diagnosed with metastatic disease, for which there is a worse prognosis. There is a lack of biomarkers to identify men at greater risk for developing aggressive PCa. Genome-wide association studies (GWAS) scan the genome to search associations of SNPs with specific traits, like cancer. To date, eight GWAS have resulted in the reporting of 16 SNPs associated with aggressive PCa (p < 5.00 × 10^-2). Still, validation studies need to be conducted to confirm the obtained results as GWAS can generate false-positive results. Furthermore, post-GWAS studies provide a better understanding of the functional consequences.

DNA methylation and cis-regulation of gene expression by prostate cancer risk SNPs

Genome-wide association studies have identified more than 100 SNPs that increase the risk of prostate cancer (PrCa). We identify and compare expression quantitative trait loci (eQTLs) and CpG methylation quantitative trait loci (meQTLs) among 147 established PrCa risk SNPs in primary prostate tumors (n = 355 from a Seattle-based study and n = 495 from The Cancer Genome Atlas, TCGA) and tumor-adjacent, histologically benign samples (n = 471 from a Mayo Clinic study). The role of DNA methylation in eQTL regulation of gene expression was investigated by data triangulation using several causal inference approaches, including a proposed adaptation of the Causal Inference Test (CIT) for causal direction. Comparing eQTLs between tumors and benign samples, we show that 98 of the 147 risk SNPs were identified as eQTLs in the tumor-adjacent benign samples, and almost all 34 eQTL identified in tumor sets were also eQTLs in the benign samples. Three lines of results support the causal role of DNA methylation. First, nearly 100 of the 147 risk SNPs were identified as meQTLs in one tumor set, and almost all eQTLs in tumors were meQTLs. Second, the loss of eQTLs in tumors relative to benign samples was associated with altered DNA methylation. Third, among risk SNPs identified as both eQTLs and meQTLs, mediation analyses suggest that over two-thirds have evidence of a causal role for DNA methylation, mostly mediating genetic influence on gene expression. In summary, we provide a comprehensive catalog of eQTLs, meQTLs and putative cancer genes for known PrCa risk SNPs. We observe that a substantial portion of germline eQTL regulatory mechanisms are maintained in the tumor development, despite somatic alterations in tumor genome. Finally, our mediation analyses illuminate the likely intermediary role of CpG methylation in eQTL regulation of gene expression.

Statin Use Is Associated with Lower Risk of PTEN-Null and Lethal Prostate Cancer

PURPOSE

Statins are associated with lower risk of aggressive prostate cancer, but lethal prostate cancer is understudied and contributing mechanisms are unclear. We prospectively examined statins and lethal prostate cancer risk in the Health Professionals Follow-up Study (HPFS), tested associations with molecular subtypes, and integrated gene expression profiling to identify putative mechanisms.

EXPERIMENTAL DESIGN

Our study included 44,126 men cancer-free in 1990, followed for prostate cancer incidence through 2014, with statin use recorded on biennial questionnaires. We used multivariable Cox regression to examine associations between statins and prostate cancer risk overall, by measures of clinically significant disease, and by ERG and PTEN status. In an exploratory analysis, age-adjusted gene set enrichment analysis identified statin-associated pathways enriched in tumor and adjacent normal prostate tissue.

RESULTS

During 24 years of follow-up, 6,305 prostate cancers were diagnosed and 801 (13%) were lethal (metastatic at diagnosis or metastatic/fatal during follow-up). Relative to never/past use, current statin use was inversely associated with risk of lethal prostate cancer [HR, 0.76; 95% confidence interval (CI), 0.60-0.96] but not overall disease. We found a strong inverse association for risk of PTEN-null cancers (HR, 0.40; 95% CI, 0.19-0.87) but not PTEN-intact cancers (HR, 1.18; 95% CI, 0.95-1.48; P heterogeneity = 0.01). Associations did not differ by ERG. Inflammation and immune pathways were enriched in normal prostate tissue of statin ever (n = 10) versus never users (n = 103).

CONCLUSIONS

Molecular tumor classification identified PTEN and inflammation/immune activation as potential mechanisms linking statins with lower lethal prostate cancer risk. These findings support a potential causal association and could inform selection of relevant biomarkers for statin clinical trials.

MLPH Accelerates the Epithelial-Mesenchymal Transition in Prostate Cancer

INTRODUCTION

Prostate cancer (PC) is the second greatest cause of cancer deaths globally. PC presents a poor prognosis once it metastasizes. There is considerable proof of vital epithelial-mesenchymal transition (EMT) functionality in PC metastasis. Previous studies revealed that melanophilin (MLPH) is associated with PC; however, its role in PC remains poorly understood.

METHODS

Bioinformatics analyses were performed. The cellular responses to MLPH knockdown were examined in HCC cell lines via wound healing assay, migration and invasion assay, Western blotting.

RESULTS

Analysis of the PROGgeneV2 database revealed that high MLPH expression might indicate poor overall survival. MLPH knockdown reduced PC cell migration, proliferation, and invasion. MLPH downregulation in vivo resulted in a lower growth rate and fewer metastatic nodules in lung tissues. Furthermore, MLPH knockdown recovered downregulated expression of the mesenchymal marker N-cadherin and the epithelial marker E-cadherin following a decrease in β-catenin.

CONCLUSION

These results indicate that progression of PC is stimulated via MLPH-dependent initiation of the EMT.

Multiplatform biomarker identification using a data-driven approach enables single-sample classification

BACKGROUND

High-throughput gene expression profiles have allowed discovery of potential biomarkers enabling early diagnosis, prognosis and developing individualized treatment. However, it remains a challenge to identify a set of reliable and reproducible biomarkers across various gene expression platforms and laboratories for single sample diagnosis and prognosis. We address this need with our Data-Driven Reference (DDR) approach, which employs stably expressed housekeeping genes as references to eliminate platform-specific biases and non-biological variabilities.

RESULTS

Our method identifies biomarkers with "built-in" features, and these features can be interpreted consistently regardless of profiling technology, which enable classification of single-sample independent of platforms. Validation with RNA-seq data of blood platelets shows that DDR achieves the superior performance in classification of six different tumor types as well as molecular target statuses (such as MET or HER2-positive, and mutant KRAS, EGFR or PIK3CA) with smaller sets of biomarkers. We demonstrate on the three microarray datasets that our method is capable of identifying robust biomarkers for subgrouping medulloblastoma samples with data perturbation due to different microarray platforms. In addition to identifying the majority of subgroup-specific biomarkers in CodeSet of nanoString, some potential new biomarkers for subgrouping medulloblastoma were detected by our method.

CONCLUSIONS

In this study, we present a simple, yet powerful data-driven method which contributes significantly to identification of robust cross-platform gene signature for disease classification of single-patient to facilitate precision medicine. In addition, our method provides a new strategy for transcriptome analysis.

epiTAD: a web application for visualizing chromosome conformation capture data in the context of genetic epidemiology

SUMMARY

Complementary advances in genomic technology and public data resources have created opportunities for researchers to conduct multifaceted examination of the genome on a large scale. To meet the need for integrative genome wide exploration, we present epiTAD. This web-based tool enables researchers to compare genomic 3D organization and annotations across multiple databases in an interactive manner to facilitate in silico discovery.

AVAILABILITY AND IMPLEMENTATION

epiTAD can be accessed at https://apps.gerkelab.com/epiTAD/ where we have additionally made publicly available the source code and a Docker containerized version of the application.

Exploring the Activities of RBPMS Proteins in Myocardial Biology

Numerous RNA-binding proteins (RBPs) are expressed in the heart, and mutations in several RBPs have been implicated in cardiovascular disease through genetic associations, animal modeling, and mechanistic studies. However, the functions of many more cardiac RBPs, and their relevance to disease states, remain to be elucidated. Recently, we have initiated studies to characterize the functions of the RBPs RBPMS and RBPMS2 in regulating myocardial biology in zebrafish and higher vertebrate species. These studies began when we learned, using an unbiased gene discovery approach, that rbpms2a and rbpms2b in zebrafish are robust markers of embryonic myocardium. This observation, which is consistent with published data, suggests that the encoded proteins are likely to be performing critical functions in regulating one or more aspects of cardiomyocyte differentiation, proliferation, survival, and/or contractility. This notion is supported by recent reports demonstrating that zebrafish embryos with disrupted Rbpms2 function exhibit gross signs of cardiac distress. Interestingly, a 20-year-old study determined that myocardial tissue from the frog, chick, and mouse also express high levels of Rbpms and/or Rbpms2, which is suggestive of evolutionary conservation of function. In this review, we will provide a historical account of how RBPMS and RBPMS2 genes were discovered, attempt to clarify some potentially confusing nomenclature, and summarize published observations that inform our ongoing studies.

High-fat diet fuels prostate cancer progression by rewiring the metabolome and amplifying the MYC program

Systemic metabolic alterations associated with increased consumption of saturated fat and obesity are linked with increased risk of prostate cancer progression and mortality, but the molecular underpinnings of this association are poorly understood. Here, we demonstrate in a murine prostate cancer model, that high-fat diet (HFD) enhances the MYC transcriptional program through metabolic alterations that favour histone H4K20 hypomethylation at the promoter regions of MYC regulated genes, leading to increased cellular proliferation and tumour burden. Saturated fat intake (SFI) is also associated with an enhanced MYC transcriptional signature in prostate cancer patients. The SFI-induced MYC signature independently predicts prostate cancer progression and death. Finally, switching from a high-fat to a low-fat diet, attenuates the MYC transcriptional program in mice. Our findings suggest that in primary prostate cancer, dietary SFI contributes to tumour progression by mimicking MYC over expression, setting the stage for therapeutic approaches involving changes to the diet.

Insights into cancer and neurodegenerative diseases through selenoproteins and the connection with gut microbiota - current analytical methodologies

Introduction: Selenium plays many key roles in health especially in connection with cancer and neurodegenerative diseases. However, it needs to be appreciated that the essentiality/toxicity of selenium depends on both, a narrow range of concentration and the chemical specie involved. In this context, selenoproteins are essential biomolecules against these disorders, mainly due to its antioxidant action. To this end, analytical methodologies may allow identifying and quantifying individual selenospecies in human biofluids and tissues. Areas covered: This review focus on the role of selenoproteins in medicine, with special emphasis in cancer and neurodegenerative diseases, considering the possible link with gut microbiota. In particular, this article reviews the analytical techniques and procedures recently developed for the absolute quantification of selenoproteins and selenometabolites in human biofluids and tissues. Expert commentary: The beneficial role of selenium in human health has been extensively studied and reviewed. However, several challenges remain unsolved as discussed in this article: (i) speciation of selenium (especially selenoproteins) in cancer and neurodegenerative disease patients; (ii) supplementation of selenium in humans using functional foods and nutraceuticals; (iii) the link between selenium and selenoproteins expression and the gut microbiota and (iv) analytical methods and pitfalls for the absolute quantification of selenoproteins and selenometabolites.

Identifying Putative Susceptibility Genes and Evaluating Their Associations with Somatic Mutations in Human Cancers

Genome-wide association studies (GWASs) have identified hundreds of genetic risk variants for human cancers. However, target genes for the majority of risk loci remain largely unexplored. It is also unclear whether GWAS risk-loci-associated genes contribute to mutational signatures and tumor mutational burden (TMB) in cancer tissues. We systematically conducted cis-expression quantitative trait loci (cis-eQTL) analyses for 294 GWAS-identified variants for six major types of cancer-colorectal, lung, ovary, prostate, pancreas, and melanoma-by using transcriptome data from the Genotype-Tissue Expression (GTEx) Project, the Cancer Genome Atlas (TCGA), and other public data sources. By using integrative analysis strategies, we identified 270 candidate target genes, including 99 with previously unreported associations, for six cancer types. By analyzing functional genomic data, our results indicate that 180 genes (66.7% of 270) had evidence of cis-regulation by putative functional variants via proximal promoter or distal enhancer-promoter interactions. Together with our previously reported associations for breast cancer risk, our results show that 24 genes are shared by at least two cancer types, including four genes for both breast and ovarian cancer. By integrating mutation data from TCGA, we found that expression levels of 33 and 66 putative susceptibility genes were associated with specific mutational signatures and TMB of cancer-driver genes, respectively, at a Bonferroni-corrected p < 0.05. Together, these findings provide further insight into our understanding of how genetic risk variants might contribute to carcinogenesis through the regulation of susceptibility genes that are related to the biogenesis of somatic mutations.

Analysis of Over 140,000 European Descendants Identifies Genetically Predicted Blood Protein Biomarkers Associated with Prostate Cancer Risk

Several blood protein biomarkers have been associated with prostate cancer risk. However, most studies assessed only a small number of biomarkers and/or included a small sample size. To identify novel protein biomarkers of prostate cancer risk, we studied 79,194 cases and 61,112 controls of European ancestry, included in the PRACTICAL/ELLIPSE consortia, using genetic instruments of protein quantitative trait loci for 1,478 plasma proteins. A total of 31 proteins were associated with prostate cancer risk including proteins encoded by GSTP1, whose methylation level was shown previously to be associated with prostate cancer risk, and MSMB, SPINT2, IGF2R, and CTSS, which were previously implicated as potential target genes of prostate cancer risk variants identified in genome-wide association studies. A total of 18 proteins inversely correlated and 13 positively correlated with prostate cancer risk. For 28 of the identified proteins, gene somatic changes of short indels, splice site, nonsense, or missense mutations were detected in patients with prostate cancer in The Cancer Genome Atlas. Pathway enrichment analysis showed that relevant genes were significantly enriched in cancer-related pathways. In conclusion, this study identifies 31 candidates of protein biomarkers for prostate cancer risk and provides new insights into the biology and genetics of prostate tumorigenesis. SIGNIFICANCE: Integration of genomics and proteomics data identifies biomarkers associated with prostate cancer risk.

Association of imputed prostate cancer transcriptome with disease risk reveals novel mechanisms

Here we train cis-regulatory models of prostate tissue gene expression and impute expression transcriptome-wide for 233,955 European ancestry men (14,616 prostate cancer (PrCa) cases, 219,339 controls) from two large cohorts. Among 12,014 genes evaluated in the UK Biobank, we identify 38 associated with PrCa, many replicating in the Kaiser Permanente RPGEH. We report the association of elevated TMPRSS2 expression with increased PrCa risk (independent of a previously-reported risk variant) and with increased tumoral expression of the TMPRSS2:ERG fusion-oncogene in The Cancer Genome Atlas, suggesting a novel germline-somatic interaction mechanism. Three novel genes, HOXA4, KLK1, and TIMM23, additionally replicate in the RPGEH cohort. Furthermore, 4 genes, MSMB, NCOA4, PCAT1, and PPP1R14A, are associated with PrCa in a trans-ethnic meta-analysis (N = 9117). Many genes exhibit evidence for allele-specific transcriptional activation by PrCa master-regulators (including androgen receptor) in Position Weight Matrix, Chip-Seq, and Hi-C experimental data, suggesting common regulatory mechanisms for the associated genes.

A Novel Mechanism Driving Poor-Prognosis Prostate Cancer: Overexpression of the DNA Repair Gene, Ribonucleotide Reductase Small Subunit M2 (RRM2)

PURPOSE

Defects in genes in the DNA repair pathways significantly contribute to prostate cancer progression. We hypothesize that overexpression of DNA repair genes may also drive poorer outcomes in prostate cancer. The ribonucleotide reductase small subunit M2 (RRM2) is essential for DNA synthesis and DNA repair by producing dNTPs. It is frequently overexpressed in cancers, but very little is known about its function in prostate cancer.

EXPERIMENTAL DESIGN

The oncogenic activity of RRM2 in prostate cancer cells was assessed by inhibiting or overexpressing RRM2. The molecular mechanisms of RRM2 function were determined. The clinical significance of RRM2 overexpression was evaluated in 11 prostate cancer clinical cohorts. The efficacy of an RRM2 inhibitor (COH29) was assessed in vitro and in vivo. Finally, the mechanism underlying the transcriptional activation of RRM2 in prostate cancer tissue and cells was determined.

RESULTS

Knockdown of RRM2 inhibited its oncogenic function, whereas overexpression of RRM2 promoted epithelial mesenchymal transition in prostate cancer cells. The prognostic value of RRM2 RNA levels in prostate cancer was confirmed in 11 clinical cohorts. Integrating the transcriptomic and phosphoproteomic changes induced by RRM2 unraveled multiple oncogenic pathways downstream of RRM2. Targeting RRM2 with COH29 showed excellent efficacy. Thirteen putative RRM2-targeting transcription factors were bioinformatically identified, and FOXM1 was validated to transcriptionally activate RRM2 in prostate cancer.

CONCLUSIONS

We propose that increased expression of RRM2 is a mechanism driving poor patient outcomes in prostate cancer and that its inhibition may be of significant therapeutic value.

Identification of Novel Susceptibility Loci and Genes for Prostate Cancer Risk: A Transcriptome-Wide Association Study in Over 140,000 European Descendants

Genome-wide association study-identified prostate cancer risk variants explain only a relatively small fraction of its familial relative risk, and the genes responsible for many of these identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61 × 10-6, a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61 × 10-6 after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology. SIGNIFICANCE: This study identifies novel prostate cancer genetic loci and possible causal genes, advancing our understanding of the molecular mechanisms that drive prostate cancer.

A novel RNA aptamer identifies plasma membrane ATP synthase beta subunit as an early marker and therapeutic target in aggressive cancer

PURPOSE

Primary breast and prostate cancers can be cured, but metastatic disease cannot. Identifying cell factors that predict metastatic potential could guide both prognosis and treatment.

METHODS

We used Cell-SELEX to screen an RNA aptamer library for differential binding to prostate cancer cell lines with high vs. low metastatic potential. Mass spectroscopy, immunoblot, and immunohistochemistry were used to identify and validate aptamer targets. Aptamer properties were tested in vitro, in xenograft models, and in clinical biopsies. Gene expression datasets were queried for target associations in cancer.

RESULTS

We identified a novel aptamer (Apt63) that binds to the beta subunit of F1Fo ATP synthase (ATP5B), present on the plasma membrane of certain normal and cancer cells. Apt63 bound to plasma membranes of multiple aggressive breast and prostate cell lines, but not to normal breast and prostate epithelial cells, and weakly or not at all to non-metastasizing cancer cells; binding led to rapid cell death. A single intravenous injection of Apt63 induced rapid, tumor cell-selective binding and cytotoxicity in MDA-MB-231 xenograft tumors, associated with endonuclease G nuclear translocation and DNA fragmentation. Apt63 was not toxic to non-transformed epithelial cells in vitro or adjacent normal tissue in vivo. In breast cancer tissue arrays, plasma membrane staining with Apt63 correlated with tumor stage (p < 0.0001, n = 416) and was independent of other cancer markers. Across multiple datasets, ATP5B expression was significantly increased relative to normal tissue, and negatively correlated with metastasis-free (p = 0.0063, 0.00039, respectively) and overall (p = 0.050, 0.0198) survival.

CONCLUSION

Ecto-ATP5B binding by Apt63 may disrupt an essential survival mechanism in a subset of tumors with high metastatic potential, and defines a novel category of cancers with potential vulnerability to ATP5B-targeted therapy. Apt63 is a unique tool for elucidating the function of surface ATP synthase, and potentially for predicting and treating metastatic breast and prostate cancer.