对内含子多腺苷酸化及其与癌症特征的关系进行泛癌症研究。

IF 6.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS Briefings in bioinformatics Pub Date : 2024-07-25 DOI:10.1093/bib/bbae376
Liang Liu, Peiqing Sun, Wei Zhang
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引用次数: 0

摘要

3'UTR-APAs已被广泛研究,但内含子多腺苷酸化(IPAs)在很大程度上仍未被探索。我们对癌症基因组图谱队列中 32 种癌症类型的 9679 份患者样本中的 22 260 个 IPA 进行了特征分析。通过比较肿瘤和配对的正常组织,我们在 22 种癌症类型的 690 个患者肿瘤的 132 ~ 2249 个基因中发现了 180 ~ 4645 个调控失调的 IPAs,这些 IPAs 在各个癌症类型中显示出一致的模式。我们选择了 2741 个在不同癌症类型中表现出一致模式的基因,其中包括 1834 个泛癌症肿瘤富集的 IPA 基因和 907 个肿瘤缺失的 IPA 基因;前者在脱氧核糖核酸损伤修复等功能通路中具有广泛的代表性。IPA同工酶的表达与肿瘤突变负荷和患者特征(如性别、种族、癌症分期和亚型)相关,具有癌症特异性和特征特异性,可以成为比基因表达(所有同工酶的汇总)更准确的预后标志物。总之,我们的研究揭示了肿瘤相关 IPAs 的作用和临床意义。
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A pan-cancer interrogation of intronic polyadenylation and its association with cancer characteristics.

3'UTR-APAs have been extensively studied, but intronic polyadenylations (IPAs) remain largely unexplored. We characterized the profiles of 22 260 IPAs in 9679 patient samples across 32 cancer types from the Cancer Genome Atlas cohort. By comparing tumor and paired normal tissues, we identified 180 ~ 4645 dysregulated IPAs in 132 ~ 2249 genes in each of 690 patient tumors from 22 cancer types that showed consistent patterns within individual cancer types. We selected 2741 genes that showed consistently patterns across cancer types, including 1834 pan-cancer tumor-enriched and 907 tumor-depleted IPA genes; the former were amply represented in the functional pathways such as deoxyribonucleic acid damage repair. Expression of IPA isoforms was associated with tumor mutation burden and patient characteristics (e.g. sex, race, cancer stages, and subtypes) in cancer-specific and feature-specific manners, and could be a more accurate prognostic marker than gene expression (summary of all isoforms). In summary, our study reveals the roles and the clinical relevance of tumor-associated IPAs.

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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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