The evolution of long noncoding RNA acceptance in prostate cancer initiation, progression, and its clinical utility in disease management.

CONTEXT: It is increasingly evident that non-protein-coding regions of the genome can give rise to transcripts that form functional layers of the cancer genome. One of most abundant classes in these regions is long noncoding RNAs (lncRNAs). They have gained increasing attention in prostate cancer (PCa) and paved the way for a greater understanding of these cryptic regulators in cancer. OBJECTIVE: To review current research exploring the functional biology of lncRNAs in PCa over the past three decades. EVIDENCE ACQUISITION: A systematic review was performed using PubMed to search for reports with terms "long noncoding RNA", "prostate", and "cancer" over the past 30 yr (1988-2018). EVIDENCE SYNTHESIS: We comprehensively surveyed the literature collected and summarise experiments leading to the characterisation of lncRNAs in PCa. A historical timeline of lncRNA identification is described, where each lncRNA is categorised mechanistically and within the primary areas of carcinogenesis: tumour risk and initiation, tumour promotion, tumour suppression, and tumour treatment resistance. We describe select lncRNAs that exemplify these areas. We also review whether these lncRNAs have a clinical utility in PCa diagnosis, prognosis, and prediction, and as therapeutic targets. CONCLUSIONS: The biology of lncRNA is multifaceted, demonstrating a complex array of molecular and cellular functions. These studies reveal that lncRNAs are involved in every stage of PCa. Their clinical utility for diagnosis, prognosis, and prediction of PCa is well supported, but further evaluation for their therapeutic candidacy is needed. We provide a detailed resource and view inside the lncRNA landscape for other cancer biologists, oncologists, and clinicians. PATIENT SUMMARY: In this study, we review current knowledge of the non-protein-coding genome in prostate cancer (PCa). We conclude that many of these regions are functional and a source of accurate biomarkers in PCa. With a strong research foundation, they hold promise as future therapeutic targets, yet clinical trials are necessary to determine their intrinsic value to PCa disease management.

Metagenomic and metatranscriptomic analysis of human prostate microbiota from patients with prostate cancer.

BACKGROUND: Prostate cancer (PCa) is the most common malignant neoplasm among men in many countries. Since most precancerous and cancerous tissues show signs of inflammation, chronic bacterial prostatitis has been hypothesized to be a possible etiology. However, establishing a causal relationship between microbial inflammation and PCa requires a comprehensive analysis of the prostate microbiome. The aim of this study was to characterize the microbiome in prostate tissue of PCa patients and investigate its association with tumour clinical characteristics as well as host expression profiles. RESULTS: The metagenome and metatranscriptome of tumour and the adjacent benign tissues were assessed in 65 Chinese radical prostatectomy specimens. Escherichia, Propionibacterium, Acinetobacter and Pseudomonas were abundant in both metagenome and metatranscriptome, thus constituting the core of the prostate microbiome. The biodiversity of the microbiomes could not be differentiated between the matched tumour/benign specimens or between the tumour specimens of low and high Gleason Scores. The expression profile of ten Pseudomonas genes was strongly correlated with that of eight host small RNA genes; three of the RNA genes may negatively associate with metastasis. Few viruses could be identified from the prostate microbiomes. CONCLUSIONS: This is the first study of the human prostate microbiome employing an integrated metagenomics and metatranscriptomics approach. In this Chinese cohort, both metagenome and metatranscriptome analyses showed a non-sterile microenvironment in the prostate of PCa patients, but we did not find links between the microbiome and local progression of PCa. However, the correlated expression of Pseudomonas genes and human small RNA genes may provide tantalizing preliminary evidence that Pseudomonas infection may impede metastasis.

The long noncoding RNA landscape of neuroendocrine prostate cancer and its clinical implications.

Background: Treatment-induced neuroendocrine prostate cancer (tNEPC) is an aggressive variant of late-stage metastatic castrate-resistant prostate cancer that commonly arises through neuroendocrine transdifferentiation (NEtD). Treatment options are limited, ineffective, and, for most patients, result in death in less than a year. We previously developed a first-in-field patient-derived xenograft (PDX) model of NEtD. Longitudinal deep transcriptome profiling of this model enabled monitoring of dynamic transcriptional changes during NEtD and in the context of androgen deprivation. Long non-coding RNA (lncRNA) are implicated in cancer where they can control gene regulation. Until now, the expression of lncRNAs during NEtD and their clinical associations were unexplored. Results: We implemented a next-generation sequence analysis pipeline that can detect transcripts at low expression levels and built a genome-wide catalogue (n = 37,749) of lncRNAs. We applied this pipeline to 927 clinical samples and our high-fidelity NEtD model LTL331 and identified 821 lncRNAs in NEPC. Among these are 122 lncRNAs that robustly distinguish NEPC from prostate adenocarcinoma (AD) patient tumours. The highest expressed lncRNAs within this signature are H19, LINC00617, and SSTR5-AS1. Another 742 are associated with the NEtD process and fall into four distinct patterns of expression (NEtD lncRNA Class I, II, III, and IV) in our PDX model and clinical samples. Each class has significant (z-scores >2) and unique enrichment for transcription factor binding site (TFBS) motifs in their sequences. Enriched TFBS include (1) TP53 and BRN1 in Class I, (2) ELF5, SPIC, and HOXD1 in Class II, (3) SPDEF in Class III, (4) HSF1 and FOXA1 in Class IV, and (5) TWIST1 when merging Class III with IV. Common TFBS in all NEtD lncRNA were also identified and include E2F, REST, PAX5, PAX9, and STAF. Interrogation of the top deregulated candidates (n = 100) in radical prostatectomy adenocarcinoma samples with long-term follow-up (median 18 years) revealed significant clinicopathological associations. Specifically, we identified 25 that are associated with rapid metastasis following androgen deprivation therapy (ADT). Two of these lncRNAs (SSTR5-AS1 and LINC00514) stratified patients undergoing ADT based on patient outcome. Discussion: To date, a comprehensive characterization of the dynamic landscape of lncRNAs during the NEtD process has not been performed. A temporal analysis of the PDX-based NEtD model has for the first time provided this dynamic landscape. TFBS analysis identified NEPC-related TF motifs present within the NEtD lncRNA sequences, suggesting functional roles for these lncRNAs in NEPC pathogenesis. Furthermore, select NEtD lncRNAs appear to be associated with metastasis and patients receiving ADT. Treatment-related metastasis is a clinical consequence of NEPC tumours. Top candidate lncRNAs FENDRR, H19, LINC00514, LINC00617, and SSTR5-AS1 identified in this study are implicated in the development of NEPC. We present here for the first time a genome-wide catalogue of NEtD lncRNAs that characterize the transdifferentiation process and a robust NEPC lncRNA patient expression signature. To accomplish this, we carried out the largest integrative study that applied a PDX NEtD model to clinical samples. These NEtD and NEPC lncRNAs are strong candidates for clinical biomarkers and therapeutic targets and warrant further investigation.

Stromal Gene Expression is Predictive for Metastatic Primary Prostate Cancer.

BACKGROUND: Clinical grading systems using clinical features alongside nomograms lack precision in guiding treatment decisions in prostate cancer (PCa). There is a critical need for identification of biomarkers that can more accurately stratify patients with primary PCa. OBJECTIVE: To identify a robust prognostic signature to better distinguish indolent from aggressive prostate cancer (PCa). DESIGN, SETTING, AND PARTICIPANTS: To develop the signature, whole-genome and whole-transcriptome sequencing was conducted on five PCa patient-derived xenograft (PDX) models collected from independent foci of a single primary tumor and exhibiting variable metastatic phenotypes. Multiple independent clinical cohorts including an intermediate-risk cohort were used to validate the biomarkers. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: The outcome measurement defining aggressive PCa was metastasis following radical prostatectomy. A generalized linear model with lasso regularization was used to build a 93-gene stroma-derived metastasis signature (SDMS). The SDMS association with metastasis was assessed using a Wilcoxon rank-sum test. Performance was evaluated using the area under the curve (AUC) for the receiver operating characteristic, and Kaplan-Meier curves. Univariable and multivariable regression models were used to compare the SDMS alongside clinicopathological variables and reported signatures. AUC was assessed to determine if SDMS is additive or synergistic to previously reported signatures. RESULTS AND LIMITATIONS: A close association between stromal gene expression and metastatic phenotype was observed. Accordingly, the SDMS was modeled and validated in multiple independent clinical cohorts. Patients with higher SDMS scores were found to have worse prognosis. Furthermore, SDMS was an independent prognostic factor, can stratify risk in intermediate-risk PCa, and can improve the performance of other previously reported signatures. CONCLUSIONS: Profiling of stromal gene expression led to development of an SDMS that was validated as independently prognostic for the metastatic potential of prostate tumors. PATIENT SUMMARY: Our stroma-derived metastasis signature can predict the metastatic potential of early stage disease and will strengthen decisions regarding selection of active surveillance versus surgery and/or radiation therapy for prostate cancer patients. Furthermore, profiling of stroma cells should be more consistent than profiling of diverse cellular populations of heterogeneous tumors.

The long non-coding RNA PCGEM1 is regulated by androgen receptor activity in vivo.

BACKGROUND: Long non-coding RNAs (lncRNAs) can orchestrate oncogenic or tumor-suppressive functions in cancer biology. Accordingly, PCGEM1 and PRNCR1 were implicated in progression of prostate cancer (PCa) as transcriptional co-regulators of the androgen receptor (AR). However, these findings were recently refuted asserting that neither gene physically binds to the AR. Despite evidence for differing AR transcriptional programs in vivo and in vitro, studies investigating AR-regulation of these genes hitherto have only been conducted in vitro. Here, we further examine the relevance of PCGEM1 and PRNCR1 in PCa, and their relationship with AR signaling, using patient-derived xenograft models. FINDINGS: RNA sequencing of two distinct androgen-dependent models shows PCGEM1 to be considerably expressed, while PRNCR1 showed scant basal expression. PCGEM1 was sharply down-regulated following castration and up-regulated upon AR activation in vivo. However, we found no parallel evidence following AR stimulation in vitro. A PCGEM1-associated gene expression signature (PES) was significantly repressed in response to androgen ablation therapy and in hormone-refractory versus hormone-naïve PCa patients. Furthermore, we found PCGEM1 was uniformly distributed in PCa cell nucleus and cytoplasm which remained unaltered upon AR transcriptional activation. PCGEM1 was up-regulated in primary PCa but not in metastasized PCa. Accordingly, the PES was significantly down-regulated in advanced and higher grade PCa patients from multiple independent studies. CONCLUSION: Our results demonstrate PCGEM1 as an in vivo androgen-regulated transcript with potential nuclear and/or cytoplasmic function(s). Importantly, the clinical expression profile of PCGEM1 implicates it in the early stages of PCa warranting further research in this direction.

Protease nexin 1 inhibits hedgehog signaling in prostate adenocarcinoma.

Prostate adenocarcinoma (CaP) patients are classified into low-, intermediate-, and high-risk groups that reflect relative survival categories. While there are accepted treatment regimens for low- and high-risk patients, intermediate-risk patients pose a clinical dilemma, as treatment outcomes are highly variable for these individuals. A better understanding of the factors that regulate the progression of CaP is required to delineate risk. For example, aberrant activation of the Hedgehog (Hh) pathway is implicated in CaP progression. Here, we identify the serine protease inhibitor protease nexin 1 (PN1) as a negative regulator of Hh signaling in prostate. Using human CaP cell lines and a mouse xenograft model of CaP, we demonstrate that PN1 regulates Hh signaling by decreasing protein levels of the Hh ligand Sonic (SHH) and its downstream effectors. Furthermore, we show that SHH expression enhanced tumor growth while overexpression of PN1 inhibited tumor growth and angiogenesis in mice. Finally, using comparative genome hybridization, we found that genetic alterations in Hh pathway genes correlated with worse clinical outcomes in intermediate-risk CaP patients, indicating the importance of this pathway in CaP.

Allelic loss of the loci containing the androgen synthesis gene, StAR, is prognostic for relapse in intermediate-risk prostate cancer.

BACKGROUND: Androgen deprivation therapy (ADT) and novel agents targeting the androgen synthesis axis (e.g., abiraterone acetate) are adjuvant therapies that are currently, or may in the future be, combined with radiotherapy to reduce the chance of disease relapse. Little is known about allelic loss or gain pertaining to genes associated with the androgen synthesis axis and whether this is prognostic in patients who receive localized radiotherapy. In this hypothesis generating study, we conducted an array comparative genomic hybridization (aCGH) analysis of 33 androgen synthesis genes to identify potential prognostic factors for radiotherapy outcome. METHODS: aCGH analysis of tumor DNA prospectively derived from frozen needle biopsies of 126 men with intermediate-risk disease who underwent image-guided radiotherapy (IGRT) to a mean dose of 76.4 Gy was conducted. Statistical analyses were conducted for allelic loss or gain in genes as potential prognostic factors relative to prostate specific antigen, Gleason-score, and T-category. RESULTS: We observed that allelic losses of loci containing the genes StAR and HSD17B2 were associated with increased genetic instability (as determined by percentage genome alteration). On multivariate analyses these loci were prognostic for biochemical disease-free relapse (StAR: HR = 2.84, 95% CI: 1.44-5.61, P = 0.00269; HSD17B2: HR = 1.97, 95% CI: 1.06-3.64, P = 0.031). The results were validated in a surgical cohort of 131 intermediate-risk patients. CONCLUSIONS: Allelic losses of the loci containing StAR and HSD17B2 have significant prognostic value for intermediate-risk prostate cancer. With this hypothesis generating information future studies should test StAR and HSD17B2 losses as biomarkers of androgen response in combined modality protocols.

Copy number alterations of c-MYC and PTEN are prognostic factors for relapse after prostate cancer radiotherapy.

Despite the use of PSA, Gleason score, and T-category as prognosticators in intermediate-risk prostate cancer, 20-40% of patients will fail local therapy. In order to optimize treatment approaches for intermediate-risk patients, additional genetic prognosticators are needed. Previous reports using array comparative genomic hybridization (aCGH) in radical prostatectomy cohorts suggested a combination of allelic loss of the PTEN gene on 10q and allelic gain of the c-MYC gene on 8q were associated with metastatic disease. We tested whether copy number alterations (CNAs) in PTEN (allelic loss) and c-MYC (allelic gain) were associated with biochemical relapse following modern-era, image-guided radiotherapy (mean dose 76.4 Gy). We used aCGH analyses validated by fluorescence in-situ hybridization (FISH) of DNA was derived from frozen, pre-treatment biopsies in 126 intermediate-risk prostate cancer patients. Patients whose tumors had CNAs in both PTEN and c-MYC had significantly increased genetic instability (percent genome alteration; PGA) compared to tumors with normal PTEN and c-MYC status (p < 0.0001). We demonstrate that c-MYC gain alone, or combined c-MYC gain and PTEN loss, were increasingly prognostic for relapse on multivariable analyses (hazard ratios (HR) of 2.58/p = 0.005 and 3.21/p = 0.0004; respectively). Triaging patients by the use of CNAs within pre-treatment biopsies may allow for better use of systemic therapies to target sub-clinical metastases or locally recurrent disease and improve clinical outcomes.

NKX3.1 haploinsufficiency is prognostic for prostate cancer relapse following surgery or image-guided radiotherapy.

BACKGROUND: Despite the use of prostate specific antigen (PSA), Gleason-score, and T-category as prognostic factors, up to 40% of patients with intermediate-risk prostate cancer will fail radical prostatectomy or precision image-guided radiotherapy (IGRT). Additional genetic prognosticators are needed to triage these patients toward intensified combination therapy with novel targeted therapeutics. We tested the role of the NKX3.1 gene as a determinant of treatment outcome given its reported roles in tumor initiating cell (TIC) renewal, the DNA damage response, and cooperation with c-MYC during prostate cancer progression. METHODS: Using high-resolution array comparative genomic hybridization (aCGH), we profiled the copy number alterations in TIC genes using tumor DNA from frozen needle biopsies derived from 126 intermediate-risk patients who underwent IGRT. These data were correlated to biochemical relapse-free rate (bRFR) by the Kaplan-Meier method and Cox proportional hazards models. RESULTS: A screen of the aCGH-IGRT data for TIC genes showed frequent copy number alterations for NKX3.1, PSCA, and c-MYC. NKX3.1 haploinsufficiency was associated with increased genomic instability independent of PSA, T-category, and Gleason-score. After adjusting for clinical factors in a multivariate model, NKX3.1 haploinsufficiency was associated with bRFR when tested alone (HR = 3.05, 95% CI: 1.46-6.39, P = 0.0030) or when combined with c-MYC gain (HR = 3.88, 95% CI: 1.78-8.49, P = 0.00067). A similar association was observed for patients following radical prostatectomy with a public aCGH database. NKX3.1 status was associated with positive biopsies post-IGRT and increased clonogen radioresistance in vitro. CONCLUSIONS: Our results support the use of genomic predictors, such as NKX3.1 status, in needle biopsies for personalized approaches to prostate cancer management.

Prognostic gene-expression signature of carcinoma-associated fibroblasts in non-small cell lung cancer.

The tumor microenvironment strongly influences cancer development, progression, and metastasis. The role of carcinoma-associated fibroblasts (CAFs) in these processes and their clinical impact has not been studied systematically in non-small cell lung carcinoma (NSCLC). We established primary cultures of CAFs and matched normal fibroblasts (NFs) from 15 resected NSCLC. We demonstrate that CAFs have greater ability than NFs to enhance the tumorigenicity of lung cancer cell lines. Microarray gene-expression analysis of the 15 matched CAF and NF cell lines identified 46 differentially expressed genes, encoding for proteins that are significantly enriched for extracellular proteins regulated by the TGF-ß signaling pathway. We have identified a subset of 11 genes (13 probe sets) that formed a prognostic gene-expression signature, which was validated in multiple independent NSCLC microarray datasets. Functional annotation using protein-protein interaction analyses of these and published cancer stroma-associated gene-expression changes revealed prominent involvement of the focal adhesion and MAPK signaling pathways. Fourteen (30%) of the 46 genes also were differentially expressed in laser-capture-microdissected corresponding primary tumor stroma compared with the matched normal lung. Six of these 14 genes could be induced by TGF-ß1 in NF. The results establish the prognostic impact of CAF-associated gene-expression changes in NSCLC patients.