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

Autor: Mohammed Alshalalfa, Harrison Tsai, Sonal Brahmbhatt, Nicholas Erho, Robert Shukin, Colin Collins, Himisha Beltran, R Jefferey Karnes, Fan Mo, Noushin Nabavi, Yuzhuo Wang, Maxim Kobelev, Dong Lin, Tamara L. Lotan, Mannan Nouri, Alexander R. Gawronski, Amina Zoubeidi, Elai Davicioni, Mark A. Rubin, Cenk Sahinalp, Mandeep Takhar, Varune Rohan Ramnarine, Stanislav Volik, Martin E. Gleave, Alexander W. Wyatt
Jazyk: angličtina
Rok vydání: 2018
Předmět:
0301 basic medicine
Male
transdifferentiation
Health Informatics
Context (language use)
Computational biology
Kaplan-Meier Estimate
Biology
Metastasis
Androgen deprivation therapy
03 medical and health sciences
Prostate cancer
Mice
0302 clinical medicine
medicine
Animals
Humans
Neoplasm Metastasis
Nucleotide Motifs
small cell carcinoma
Binding Sites
neuroendocrine prostate cancer
long non-coding RNA
Research
Gene Expression Profiling
Cancer
Prostatic Neoplasms
medicine.disease
Xenograft Model Antitumor Assays
Long non-coding RNA
Computer Science Applications
Gene expression profiling
Gene Expression Regulation
Neoplastic
Neuroendocrine Tumors
030104 developmental biology
Phenotype
030220 oncology & carcinogenesis
Cell Transdifferentiation
Adenocarcinoma
RNA
Long Noncoding
Transcriptome
Transcription Factors
Zdroj: GigaScience
ISSN: 2047-217X
Popis: 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.
Databáze: OpenAIRE
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