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来自两个乳腺癌患者队列的全转录组图谱的共识分析揭示了与内在亚型和肿瘤微环境相关的长链非编码RNA。

Consensus Analysis of Whole Transcriptome Profiles from Two Breast Cancer Patient Cohorts Reveals Long Non-Coding RNAs Associated with Intrinsic Subtype and the Tumour Microenvironment.

作者信息

Bradford James R, Cox Angela, Bernard Philip, Camp Nicola J

机构信息

Sheffield Institute for Nucleic Acids (SInFoNiA), Department of Oncology and Metabolism, University of Sheffield, Sheffield, South Yorkshire, United Kingdom.

Department of Pathology, Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, United States.

出版信息

PLoS One. 2016 Sep 29;11(9):e0163238. doi: 10.1371/journal.pone.0163238. eCollection 2016.

Abstract

Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of cellular processes and diseases such as cancer; however, their functions remain poorly characterised. Several studies have demonstrated that lncRNAs are typically disease and tumour subtype specific, particularly in breast cancer where lncRNA expression alone is sufficient to discriminate samples based on hormone status and molecular intrinsic subtype. However, little attempt has been made to assess the reproducibility of lncRNA signatures across more than one dataset. In this work, we derive consensus lncRNA signatures indicative of breast cancer subtype based on two clinical RNA-Seq datasets: the Utah Breast Cancer Study and The Cancer Genome Atlas, through integration of differential expression and hypothesis-free clustering analyses. The most consistent signature is associated with breast cancers of the basal-like subtype, leading us to generate a putative set of six lncRNA basal-like breast cancer markers, at least two of which may have a role in cis-regulation of known poor prognosis markers. Through in silico functional characterization of individual signatures and integration of expression data from pre-clinical cancer models, we discover that discordance between signatures derived from different clinical cohorts can arise from the strong influence of non-cancerous cells in tumour samples. As a consequence, we identify nine lncRNAs putatively associated with breast cancer associated fibroblasts, or the immune response. Overall, our study establishes the confounding effects of tumour purity on lncRNA signature derivation, and generates several novel hypotheses on the role of lncRNAs in basal-like breast cancers and the tumour microenvironment.

摘要

长链非编码RNA(lncRNAs)正逐渐成为细胞过程和癌症等疾病的关键调节因子;然而,它们的功能仍未得到充分表征。多项研究表明,lncRNAs通常具有疾病和肿瘤亚型特异性,尤其是在乳腺癌中,仅lncRNA表达就足以根据激素状态和分子内在亚型区分样本。然而,几乎没有人尝试评估多个数据集之间lncRNA特征的可重复性。在这项工作中,我们通过整合差异表达分析和无假设聚类分析,基于两个临床RNA测序数据集(犹他州乳腺癌研究和癌症基因组图谱)得出了指示乳腺癌亚型的共识lncRNA特征。最一致的特征与基底样亚型乳腺癌相关,这使我们生成了一组推定的六个lncRNA基底样乳腺癌标志物,其中至少有两个可能在已知预后不良标志物的顺式调控中发挥作用。通过对个体特征的计算机功能表征以及整合临床前癌症模型的表达数据,我们发现不同临床队列得出的特征之间的不一致可能源于肿瘤样本中非癌细胞的强烈影响。因此,我们确定了九个可能与乳腺癌相关成纤维细胞或免疫反应相关的lncRNAs。总体而言,我们的研究确定了肿瘤纯度对lncRNA特征推导的混杂影响,并产生了几个关于lncRNAs在基底样乳腺癌和肿瘤微环境中作用的新假设。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0001/5042460/63d2feddaa7f/pone.0163238.g001.jpg

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