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泰米斯:通过全面的分子分型和优化,推进精准肿瘤学。

Themis: advancing precision oncology through comprehensive molecular subtyping and optimization.

机构信息

Department of Reproductive Medicine, Central Hospital Affiliated to Shandong First Medical University, Jinan, Shandong Province, 250013, China.

Institute of Clinical Science, Zhongshan Hospital, Fudan University, Shanghai, China.

出版信息

Brief Bioinform. 2024 May 23;25(4). doi: 10.1093/bib/bbae261.

Abstract

Recent advances in tumor molecular subtyping have revolutionized precision oncology, offering novel avenues for patient-specific treatment strategies. However, a comprehensive and independent comparison of these subtyping methodologies remains unexplored. This study introduces 'Themis' (Tumor HEterogeneity analysis on Molecular subtypIng System), an evaluation platform that encapsulates a few representative tumor molecular subtyping methods, including Stemness, Anoikis, Metabolism, and pathway-based classifications, utilizing 38 test datasets curated from The Cancer Genome Atlas (TCGA) and significant studies. Our self-designed quantitative analysis uncovers the relative strengths, limitations, and applicability of each method in different clinical contexts. Crucially, Themis serves as a vital tool in identifying the most appropriate subtyping methods for specific clinical scenarios. It also guides fine-tuning existing subtyping methods to achieve more accurate phenotype-associated results. To demonstrate the practical utility, we apply Themis to a breast cancer dataset, showcasing its efficacy in selecting the most suitable subtyping methods for personalized medicine in various clinical scenarios. This study bridges a crucial gap in cancer research and lays a foundation for future advancements in individualized cancer therapy and patient management.

摘要

近年来,肿瘤分子分型的进展彻底改变了精准肿瘤学,为患者特异性治疗策略提供了新的途径。然而,这些分型方法的全面和独立比较仍有待探索。本研究引入了 'Themis'(肿瘤异质性分析分子分型系统),这是一个评估平台,包含了几种有代表性的肿瘤分子分型方法,包括干性、失巢凋亡、代谢和基于通路的分类,利用从癌症基因组图谱(TCGA)和重要研究中提取的 38 个测试数据集。我们自行设计的定量分析揭示了每种方法在不同临床环境中的相对优势、局限性和适用性。至关重要的是,Themis 是识别特定临床情况下最合适的分型方法的重要工具。它还指导对现有分型方法进行微调,以实现更准确的与表型相关的结果。为了展示其实用性,我们将 Themis 应用于乳腺癌数据集,展示了它在各种临床情况下为个性化医学选择最合适的分型方法的功效。这项研究弥合了癌症研究中的一个重要差距,为个体化癌症治疗和患者管理的未来发展奠定了基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b6b6/11149663/b67e4bf34e11/bbae261ga1.jpg

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