生物
生物标志物
肺癌
腺癌
前瞻性队列研究
内科学
肺
甲骨文公司
表达式(计算机科学)
癌症
肿瘤科
遗传学
医学
计算机科学
软件工程
程序设计语言
作者
Dhruva Biswas,Yun-Hsin Liu,Javier Herrero,Yin Wu,David A. Moore,Takahiro Karasaki,Kristiana Grigoriadis,Wei-Ting Lu,Selvaraju Veeriah,Cristina Naceur‐Lombardelli,Neil Magno,Sophia Ward,Alexander M. Frankell,Mark S. Hill,Emma Colliver,Sophie de Carné Trécesson,Philip East,Aman Malhi,Daniel M. Snell,Olga O’Neill
出处
期刊:Nature cancer
[Nature Portfolio]
日期:2025-01-09
卷期号:6 (1): 86-101
被引量:1
标识
DOI:10.1038/s43018-024-00883-1
摘要
Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study. We prospectively validate the survival association of a clonal expression biomarker, Outcome Risk Associated Clonal Lung Expression (ORACLE), in combination with clinicopathological risk factors, and in stage I disease. We expand our mechanistic understanding, discovering that clonal transcriptional signals are detectable before tissue invasion, act as a molecular fingerprint for lethal metastatic clones and predict chemotherapy sensitivity. Lastly, we find that ORACLE summarizes the prognostic information encoded by genetic evolutionary measures, including chromosomal instability, as a concise 23-transcript assay.
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