Omics-based molecular classifications empowering in precision oncology.

IF 6.6 2区医学 Q1 Medicine Cellular Oncology Pub Date : 2024-06-01 Epub Date: 2024-01-31 DOI:10.1007/s13402-023-00912-8

Zhaokai Zhou, Ting Lin, Shuang Chen, Ge Zhang, Yudi Xu, Haijiao Zou, Aoyang Zhou, Yuyuan Zhang, Siyuan Weng, Xinwei Han, Zaoqu Liu

{"title":"Omics-based molecular classifications empowering in precision oncology.","authors":"Zhaokai Zhou, Ting Lin, Shuang Chen, Ge Zhang, Yudi Xu, Haijiao Zou, Aoyang Zhou, Yuyuan Zhang, Siyuan Weng, Xinwei Han, Zaoqu Liu","doi":"10.1007/s13402-023-00912-8","DOIUrl":null,"url":null,"abstract":"Background: In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.Conclusion: This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.","PeriodicalId":9690,"journal":{"name":"Cellular Oncology","volume":null,"pages":null},"PeriodicalIF":6.6000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cellular Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s13402-023-00912-8","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/31 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}

引用次数: 0

Abstract

Background: In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.

Conclusion: This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于组学的分子分类为精准肿瘤学赋能。

背景：在过去的几十年里，癌症在不同表达水平上的神秘异质性可以解释治疗反应和预后的差异。它阻碍了精准医疗的发展，而精准医疗是一种根据肿瘤分子特征量身定制治疗方案的策略。单一组学分析在一定程度上剖析了与癌变相关的生物学特征，但仍未能如预期那样彻底改变癌症治疗。综合组学分析从不同层面整合了肿瘤生物网络，解读了癌症行为的整体概况，得出了精确的分子分类，促进了精准医疗的发展和完善：本综述概述了多个表达层的生物标志物，以指导分子分类和精确诊断肿瘤，并探讨了精准治疗的范式转变：从基于单一组学的亚型分析到基于多组学的亚型分析，以优化治疗方案。最终，我们坚信，通过解析分子特征，基于组学的分型将成为精准肿瘤学的有力助手。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Cellular Oncology Biochemistry, Genetics and Molecular Biology-Cancer Research

CiteScore

10.40

自引率

1.50%

发文量

审稿时长

16 weeks

期刊介绍： The Official Journal of the International Society for Cellular Oncology Focuses on translational research Addresses the conversion of cell biology to clinical applications Cellular Oncology publishes scientific contributions from various biomedical and clinical disciplines involved in basic and translational cancer research on the cell and tissue level, technical and bioinformatics developments in this area, and clinical applications. This includes a variety of fields like genome technology, micro-arrays and other high-throughput techniques, genomic instability, SNP, DNA methylation, signaling pathways, DNA organization, (sub)microscopic imaging, proteomics, bioinformatics, functional effects of genomics, drug design and development, molecular diagnostics and targeted cancer therapies, genotype-phenotype interactions. A major goal is to translate the latest developments in these fields from the research laboratory into routine patient management. To this end Cellular Oncology forms a platform of scientific information exchange between molecular biologists and geneticists, technical developers, pathologists, (medical) oncologists and other clinicians involved in the management of cancer patients. In vitro studies are preferentially supported by validations in tumor tissue with clinicopathological associations.