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通过纳入非编码RNA推进泛癌基因表达生存分析

Advancing Pan-cancer Gene Expression Survial Analysis by Inclusion of Non-coding RNA.

作者信息

Ye Bo, Shi Jianxin, Kang Huining, Oyebamiji Olufunmilola, Hill Deirdre, Yu Hui, Ness Scott, Ye Fei, Ping Jie, He Jiapeng, Edwards Jeremy, Zhao Ying-Yong, Guo Yan

机构信息

Department of Thoracic Surgery, Shanghai Chest Hospital, Jiaotong University , Shanghai, China.

Comprehensive Cancer Center, University of New Mexico , Albuquerque, NM, USA.

出版信息

RNA Biol. 2020 Nov;17(11):1666-1673. doi: 10.1080/15476286.2019.1679585. Epub 2019 Oct 18.


DOI:10.1080/15476286.2019.1679585
PMID:31607216
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7567505/
Abstract

Non-coding RNAs occupy a significant fraction of the human genome. Their biological significance is backed up by a plethora of emerging evidence. One of the most robust approaches to demonstrate non-coding RNA's biological relevance is through their prognostic value. Using the rich gene expression data from The Cancer Genome Altas (TCGA), we designed Advanced Expression Survival Analysis (AESA), a web tool which provides several novel survival analysis approaches not offered by previous tools. In addition to the common single-gene approach, AESA computes the gene expression composite score of a set of genes for survival analysis and utilizes permutation test or cross-validation to assess the significance of log-rank statistic and the degree of over-fitting. AESA offers survival feature selection with post-selection inference and utilizes expanded TCGA clinical data including overall, disease-specific, disease-free, and progression-free survival information. Users can analyse either protein-coding or non-coding regions of the transcriptome. We demonstrated the effectiveness of AESA using several empirical examples. Our analyses showed that non-coding RNAs perform as well as messenger RNAs in predicting survival of cancer patients. These results reinforce the potential prognostic value of non-coding RNAs. AESA is developed as a module in the freely accessible analysis suite MutEx. ACC: Adrenocortical Carcinoma (n = 92); BLCA: Bladder Urothelial Carcinoma (n = 412); BRCA: Breast Invasive Carcinoma (n = 1098); CESC: Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (n = 307); CHOL: Cholangiocarcinoma (n = 51); COAD: Colon Adenocarcinoma (n = 461); DLBC: Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (n = 58); ESCA: Oesophageal Carcinoma (n = 185); GBM: Glioblastoma Multiforme (n = 617); HNSC: Head and Neck Squamous Cell Carcinoma (n = 528); KICH: Kidney Chromophobe (n = 113); KIRC: Kidney Renal Clear Cell Carcinoma (n = 537); KIRP: Kidney Renal Papillary Cell Carcinoma (n = 291); LAML: Acute Myeloid Leukaemia (n = 200); LGG: Brain Lower Grade Glioma (n = 516); LIHC: Liver Hepatocellular Carcinoma (n = 377); LUAD: Lung Adenocarcinoma (n = 585); LUSC: Lung Squamous Cell Carcinoma (n = 504); MESO: Mesothelioma (n = 87); OV: Ovarian Serous Cystadenocarcinoma (n = 608) PAAD: Pancreatic Adenocarcinoma (n = 185); PCPG: Pheochromocytoma and Paraganglioma (n = 179); PRAD: Prostate Adenocarcinoma (n = 500); READ: Rectum Adenocarcinoma (n = 172); SARC: Sarcoma (n = 261); SKCM: Skin Cutaneous Melanoma (n = 470); STAD: Stomach Adenocarcinoma (n = 443); TGCT: Testicular Germ Cell Tumours (n = 150); THCA: Thyroid Carcinoma (n = 507) THYM: Thymoma (n = 124); UCEC: Uterine Corpus Endometrial Carcinoma (n = 560); UCS: Uterine Carcinosarcoma (n = 57); UVM: Uveal Melanoma (n = 80).

摘要

非编码RNA占据了人类基因组的很大一部分。大量新出现的证据支持了它们的生物学意义。证明非编码RNA生物学相关性的最有力方法之一是通过它们的预后价值。利用来自癌症基因组图谱(TCGA)的丰富基因表达数据,我们设计了高级表达生存分析(AESA),这是一个网络工具,提供了几种以前的工具所没有的新颖生存分析方法。除了常见的单基因方法外,AESA还计算一组基因的基因表达综合得分用于生存分析,并利用置换检验或交叉验证来评估对数秩统计量的显著性和过拟合程度。AESA提供具有选择后推断的生存特征选择,并利用扩展的TCGA临床数据,包括总生存、疾病特异性生存、无病生存和无进展生存信息。用户可以分析转录组的蛋白质编码或非编码区域。我们通过几个实证例子证明了AESA的有效性。我们的分析表明,非编码RNA在预测癌症患者生存方面与信使RNA表现相当。这些结果强化了非编码RNA的潜在预后价值。AESA是作为免费可用的分析套件MutEx中的一个模块开发的。ACC:肾上腺皮质癌(n = 92);BLCA:膀胱尿路上皮癌(n = 412);BRCA:乳腺浸润性癌(n = 1098);CESC:宫颈鳞状细胞癌和宫颈管腺癌(n = 307);CHOL:胆管癌(n = 51);COAD:结肠腺癌(n = 461);DLBC:弥漫性大B细胞淋巴瘤(n = 58);ESCA:食管癌(n = 185);GBM:多形性胶质母细胞瘤(n = 617);HNSC:头颈部鳞状细胞癌(n = 528);KICH:肾嫌色细胞癌(n = 113);KIRC:肾透明细胞癌(n = 537);KIRP:肾乳头状细胞癌(n = 291);LAML:急性髓细胞白血病(n = 200);LGG:脑低级别胶质瘤(n = 516);LIHC:肝肝细胞癌(n = 377);LUAD:肺腺癌(n = 585);LUSC:肺鳞状细胞癌(n = 504);MESO:间皮瘤(n = 87);OV:卵巢浆液性囊腺癌(n = 608);PAAD:胰腺腺癌(n = 185);PCPG:嗜铬细胞瘤和副神经节瘤(n = 179);PRAD:前列腺腺癌(n = 500);READ:直肠腺癌(n = 172);SARC:肉瘤(n = 261);SKCM:皮肤黑色素瘤(n = 470);STAD:胃腺癌(n = 443);TGCT:睾丸生殖细胞肿瘤(n = 150);THCA:甲状腺癌(n = 507);THYM:胸腺瘤(n = 124);UCEC:子宫内膜癌(n = 560);UCS:子宫癌肉瘤(n = 57);UVM:葡萄膜黑色素瘤(n = 80)。

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本文引用的文献

[1]
MutEx: a multifaceted gateway for exploring integrative pan-cancer genomic data.

Brief Bioinform. 2020-7-15

[2]
A Panel of 12-lncRNA Signature Predicts Survival of Pancreatic Adenocarcinoma.

J Cancer. 2019-2-26

[3]
Prognostic and Clinicopathological Significance of lncRNA MVIH in Cancer Patients.

J Cancer. 2019-2-26

[4]
Genomic Positional Dissection of RNA Editomes in Tumor and Normal Samples.

Front Genet. 2019-3-20

[5]
Combined eight-long noncoding RNA signature: a new risk score predicting prognosis in elderly non-small cell lung cancer patients.

Aging (Albany NY). 2019-1-19

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A 15-lncRNA signature predicts survival and functions as a ceRNA in patients with colorectal cancer.

Cancer Manag Res. 2018-11-16

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Cancer-specific expression quantitative loci are affected by expression dysregulation.

Brief Bioinform. 2020-1-17

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A Six-LncRNA Expression Signature Associated with Prognosis of Colorectal Cancer Patients.

Cell Physiol Biochem. 2018

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Brief Funct Genomics. 2019-2-14

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Adv Exp Med Biol. 2018

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