用于解释肺腺癌演变的癌症时间估计。

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Yourui Han, Bolin Chen, Jun Bian, Ruiming Kang, Xuequn Shang
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引用次数: 0

摘要

肺腺癌的演化过程伴随着多种基因突变和功能障碍,使其表型状态和演化方向变得非常复杂。为了解释肺腺癌的进化,人们开发了各种方法来阐明其分子发病机制和功能进化过程。然而,这些方法大多受制于癌症时间信息的缺失和异质性特征的挑战。为了解决这些问题,本研究提出了一种病人准潜在景观方法,以估计进化过程中表型状态出现的癌变时间。随后,根据癌变时间和突变情况,共确定了39种不同的癌基因路径,反映了肺腺癌进化过程中的分子发病机制。为了解读肺腺癌的进化模式,通过合并肿瘤基因路径,得到了三个肿瘤基因图谱,作为共同的进化模式。此外,根据癌变时间将患者重新均匀地划分为早期、中期和晚期三个进化阶段,并建立了一个可行的框架来构建肺腺癌的功能进化网络。根据通路富集分析,从功能进化网络中发现了六个重要的功能进化过程,它们在理解肺腺癌的发展过程中发挥着关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cancerous time estimation for interpreting the evolution of lung adenocarcinoma.

The evolution of lung adenocarcinoma is accompanied by a multitude of gene mutations and dysfunctions, rendering its phenotypic state and evolutionary direction highly complex. To interpret the evolution of lung adenocarcinoma, various methods have been developed to elucidate the molecular pathogenesis and functional evolution processes. However, most of these methods are constrained by the absence of cancerous temporal information, and the challenges of heterogeneous characteristics. To handle these problems, in this study, a patient quasi-potential landscape method was proposed to estimate the cancerous time of phenotypic states' emergence during the evolutionary process. Subsequently, a total of 39 different oncogenetic paths were identified based on cancerous time and mutations, reflecting the molecular pathogenesis of the evolutionary process of lung adenocarcinoma. To interpret the evolution patterns of lung adenocarcinoma, three oncogenetic graphs were obtained as the common evolutionary patterns by merging the oncogenetic paths. Moreover, patients were evenly re-divided into early, middle, and late evolutionary stages according to cancerous time, and a feasible framework was developed to construct the functional evolution network of lung adenocarcinoma. A total of six significant functional evolution processes were identified from the functional evolution network based on the pathway enrichment analysis, which plays critical roles in understanding the development of lung adenocarcinoma.

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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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