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Translational and clinical implications of the genetic landscape of prostate cancer.

ABSTRACT: Over the past several years, analyses of data from high-throughput studies have elucidated many fundamental insights into prostate cancer biology. These insights include the identification of molecular alterations and subtypes that drive tumour progression, recurrent aberrations in signalling pathways, the existence of substantial intertumoural and intratumoural heterogeneity, Darwinian evolution in response to therapeutic pressures and the complicated multidirectional patterns of spread between primary tumours and metastatic sites. However, these concepts have not yet been fully translated into clinical tools to improve prognostication, prediction and personalization of treatment of patients with prostate cancer. The current and future clinical implications of 'omics' level knowledge is not only revolutionizing our understanding of prostate cancer biology, but is also shaping ongoing, and future clinical investigations and practice. In this Review, we summarize these advances, and the remaining challenges surrounding tumour heterogeneity and the ability to overcome treatment resistance are also described.

SUBMITTER: Spratt DE

PROVIDER: S-EPMC5030163 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Translational and clinical implications of the genetic landscape of prostate cancer.

Spratt Daniel E DE Zumsteg Zachary S ZS Feng Felix Y FY Tomlins Scott A SA

Nature reviews. Clinical oncology 20160601 10

Over the past several years, analyses of data from high-throughput studies have elucidated many fundamental insights into prostate cancer biology. These insights include the identification of molecular alterations and subtypes that drive tumour progression, recurrent aberrations in signalling pathways, the existence of substantial intertumoural and intratumoural heterogeneity, Darwinian evolution in response to therapeutic pressures and the complicated multidirectional patterns of spread between ...[more]

PMID: 27245282

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Project description: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. 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. 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.

Dataset Information

Translational and clinical implications of the genetic landscape of prostate cancer.

Publications

Translational and clinical implications of the genetic landscape of prostate cancer.

Similar Datasets

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