iop - cancer:鉴定影响癌症表型的突变顺序对。

IF 7.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Yijing Zhang, Shaobo Kang, Renjie Dou, Wanmei Zhang, Yuanyuan Liu, Yang Wu, Dongxue Li, Fangfang Fan, Yanyan Ping
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引用次数: 0

摘要

癌症的发展和进展是由体细胞遗传改变的积累所驱动的,这些改变发生在特定的时间顺序中。然而,突变的顺序如何影响实体瘤的癌症表型仍然知之甚少。为了解决这个问题,我们开发了一个新的计算框架,IMOP-Cancer(识别癌症中的突变顺序对),以识别影响癌症表型的突变基因对。我们将IMOP-Cancer应用于癌症基因组阿特拉斯-肺腺癌(TCGA-LUAD)队列,鉴定出446对关键突变序列,其中34对与预后显著相关。突变顺序影响癌症表型,正如CSMD3和PTPRD(肿瘤增殖)以及TP53和NAV3(免疫调节)所证明的那样,并在四个独立的数据集中证实了这种影响。我们通过对膀胱尿路上皮癌(BLCA)和结肠腺癌(COAD)的TCGA队列的病例研究,进一步介绍了突变对癌症表型的影响。我们将这一分析扩展到来自TCGA门户网站的33个癌症队列,确定了17种癌症中的106 034对关键突变对,其中3036对同时发生在多种癌症中。癌症之间的共享突变对也显示出对癌症表型的不同影响。我们的研究强调了突变顺序在癌症进展和多样性中的重要性,为共同发生突变的时间动态提供了新的见解,并为个性化治疗策略和改进诊断铺平了道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
IMOP-Cancer: identifying mutation order pairs impacting cancer phenotypes.

Cancer development and progression are driven by the accumulation of somatic genetic alterations, which occur in a specific temporal order. However, how the order of mutations impacts cancer phenotypes of solid tumors remains poorly understood. To address this, we developed a novel computational framework, IMOP-Cancer (Identifying Mutation Order Pairs in Cancer), to identify mutation gene pairs whose order influences cancer phenotypes. We applied IMOP-Cancer to The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD) cohort and identified 446 key mutation order pairs, with 34 pairs significantly associated with prognosis. Mutation order impacts cancer phenotypes, as demonstrated by CSMD3 and PTPRD (tumor proliferation) and TP53 and NAV3 (immune modulation), with effects validated in four independent datasets. We further presented the impact of mutation pairs on cancer phenotypes through case studies in the TCGA cohorts of bladder urothelial carcinoma (BLCA), and colon adenocarcinoma (COAD). We extended this analysis to 33 cancer cohorts from TCGA portal, identifying 106 034 critical mutation pairs across 17 cancers, with 3036 pairs co-occurring in multiple cancers. Shared mutation pairs across cancers also showed distinct effects on cancer phenotype. Our study highlights the importance of mutation order in cancer progression and diversity, offering new insights into the temporal dynamics of co-occurring mutations and paving the way for personalized treatment strategies and improved diagnosis.

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来源期刊
Briefings in bioinformatics
Briefings in bioinformatics 生物-生化研究方法
CiteScore
13.20
自引率
13.70%
发文量
549
审稿时长
6 months
期刊介绍: Briefings in Bioinformatics is an international journal serving as a platform for researchers and educators in the life sciences. It also appeals to mathematicians, statisticians, and computer scientists applying their expertise to biological challenges. The journal focuses on reviews tailored for users of databases and analytical tools in contemporary genetics, molecular and systems biology. It stands out by offering practical assistance and guidance to non-specialists in computerized methodologies. Covering a wide range from introductory concepts to specific protocols and analyses, the papers address bacterial, plant, fungal, animal, and human data. The journal's detailed subject areas include genetic studies of phenotypes and genotypes, mapping, DNA sequencing, expression profiling, gene expression studies, microarrays, alignment methods, protein profiles and HMMs, lipids, metabolic and signaling pathways, structure determination and function prediction, phylogenetic studies, and education and training.
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