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神经内分泌前列腺癌的长非编码 RNA 图谱及其临床意义。

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

机构信息

Vancouver Prostate Centre & Department of Urologic Sciences, University of British Columbia, Vancouver, BC, Canada.

GenomeDx Biosciences Inc., Vancouver, BC, Canada.

出版信息

Gigascience. 2018 Jun 1;7(6). doi: 10.1093/gigascience/giy050.

Abstract

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.

摘要

背景

治疗诱导的神经内分泌前列腺癌(tNEPC)是晚期转移性去势抵抗性前列腺癌的一种侵袭性变体,通常通过神经内分泌转化(NEtD)产生。治疗选择有限且无效,而且对于大多数患者来说,不到一年就会导致死亡。我们之前开发了一种用于 NEtD 的首创患者衍生的异种移植(PDX)模型。该模型的纵向深度转录组谱分析使我们能够在 NEtD 过程中以及在去势剥夺的背景下监测动态转录变化。长非编码 RNA(lncRNA)在癌症中起作用,它们可以控制基因调控。直到现在,lncRNA 在 NEtD 期间的表达及其临床关联仍未得到探索。

结果

我们实施了一种可以检测低表达水平转录本的下一代测序分析管道,并构建了一个全基因组目录(n = 37749)的 lncRNA。我们将该管道应用于 927 个临床样本和我们的高保真 NEtD 模型 LTL331,并在 NEPC 中鉴定了 821 个 lncRNA。其中有 122 个 lncRNA 可以可靠地区分 NEPC 与前列腺腺癌(AD)患者肿瘤。该特征中表达最高的 lncRNA 是 H19、LINC00617 和 SSTR5-AS1。另外 742 个与 NEtD 过程相关,并在我们的 PDX 模型和临床样本中分为四个不同的表达模式(NEtD lncRNA 类 I、II、III 和 IV)。每个类都有显著的(z 分数>2)和独特的转录因子结合位点(TFBS)序列富集。富集的 TFBS 包括(1)类 I 中的 TP53 和 BRN1,(2)类 II 中的 ELF5、SPIC 和 HOXD1,(3)类 III 中的 SPDEF,(4)类 IV 中的 HSF1 和 FOXA1,以及(5)当将类 III 与类 IV 合并时的 TWIST1。还鉴定了所有 NEtD lncRNA 中常见的 TFBS,包括 E2F、REST、PAX5、PAX9 和 STAF。对具有长期随访(中位随访 18 年)的根治性前列腺切除术腺癌样本中前 100 个失调候选基因的检测揭示了显著的临床病理关联。具体而言,我们确定了 25 个与去势治疗后快速转移相关的候选基因。这两个 lncRNA(SSTR5-AS1 和 LINC00514)基于患者结局对接受 ADT 的患者进行了分层。

讨论

迄今为止,尚未对 NEtD 过程中 lncRNA 的动态景观进行全面描述。基于 PDX 的 NEtD 模型的时间分析首次提供了这种动态景观。TFBS 分析确定了 NEtD lncRNA 序列中存在的与 NEPC 相关的 TF 基序,表明这些 lncRNA 在 NEPC 发病机制中具有功能作用。此外,一些 NEtD lncRNA 似乎与转移和接受 ADT 的患者有关。治疗相关的转移是 NEPC 肿瘤的临床后果。在这项研究中确定的候选 lncRNA FENDRR、H19、LINC00514、LINC00617 和 SSTR5-AS1 与 NEPC 的发展有关。我们在这里首次提出了一个全基因组的 NEtD lncRNA 目录,该目录描述了转化过程和一个稳健的 NEPC lncRNA 患者表达特征。为了实现这一目标,我们进行了最大的整合研究,将 PDX NEtD 模型应用于临床样本。这些 NEtD 和 NEPC lncRNA 是临床生物标志物和治疗靶点的有力候选者,值得进一步研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a4cd/6007253/4d4a0cda52db/giy050fig1.jpg

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