Systematically identification of survival-associated eQTLs in a Japanese kidney cancer cohort.

IF 4 2区生物学 Q1 GENETICS & HEREDITY

PLoS Genetics Pub Date : 2025-07-07 eCollection Date: 2025-07-01 DOI:10.1371/journal.pgen.1011770

Xiya Song, Han Jin, Xiangyu Li, Meng Yuan, Hong Yang, Yusuke Sato, Haruki Kume, Seishi Ogawa, Cheng Zhang, Adil Mardinoglu

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引用次数: 0

Abstract

Background: Clear cell renal carcinoma (ccRCC) is the predominant form of kidney cancer, but the prognostic value of expression quantitative trait loci (eQTLs) remains underexplored, particularly in Asian populations.

Objective: We analyzed whole-exome sequencing and RNA sequencing data from 100 Japanese ccRCC patients to identify eQTLs. Multiple Cox proportional hazard models assessed survival associations, with validation in the Cancer Genome Atlas ccRCC cohort (n = 287).

Results: We identified 805 eGenes and 4,558 cis-eQTLs in the Japanese cohort. Survival analysis revealed a total of 9 eGenes significantly associated with overall survival (FDR < 0.05). Further exploratory analysis were performed using 158 eGenes and 711 eQTLs (p-value <0.05) as potential prognostic signals. Among these, 223 eQTLs regulating 54 eGenes showed consistent prognostic effects at both expression and genetic levels. Cross-population validation identified eight eQTLs regulating 11 eGenes with reproducible survival associations across ethnicities, including a missense mutation in ERV3-1 and regulatory variants near ANKRD20A7P. These variants demonstrated consistent allelic effects on both gene expression and patient survival in both cohorts.

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日本肾癌队列中生存相关的eqtl的系统鉴定

背景：透明细胞肾癌（ccRCC）是肾癌的主要形式，但表达数量性状位点（eqtl）的预后价值仍未得到充分研究，特别是在亚洲人群中。目的：分析100例日本ccRCC患者的全外显子组测序和RNA测序数据，以鉴定eqtl。多个Cox比例风险模型评估了生存相关性，并在癌症基因组图谱ccRCC队列中进行了验证（n = 287）。结果：我们在日本队列中鉴定了805个eGenes和4558个cis- eqtl。生存分析显示，共有9个eGenes与总生存（FDR）显著相关

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来源期刊

PLoS Genetics GENETICS & HEREDITY-

自引率

2.20%

发文量

438

期刊介绍： PLOS Genetics is run by an international Editorial Board, headed by the Editors-in-Chief, Greg Barsh (HudsonAlpha Institute of Biotechnology, and Stanford University School of Medicine) and Greg Copenhaver (The University of North Carolina at Chapel Hill). Articles published in PLOS Genetics are archived in PubMed Central and cited in PubMed.