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从奥米克戎分层到结直肠癌的个体化医学:未来之路。

From Omic Layers to Personalized Medicine in Colorectal Cancer: The Road Ahead.

机构信息

Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country (Universidad del País Vasco/Euskal Herriko Unibertsitatea), 48940 Leioa, Spain.

Biodonostia, Gastrointestinal Genetics Group, 20014 San Sebastián, Spain.

出版信息

Genes (Basel). 2023 Jul 11;14(7):1430. doi: 10.3390/genes14071430.

DOI:10.3390/genes14071430
PMID:37510334
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10379575/
Abstract

Colorectal cancer is a major health concern since it is a highly diagnosed cancer and the second cause of death among cancers. Thus, the most suitable biomarkers for its diagnosis, prognosis, and treatment have been studied to improve and personalize the prevention and clinical management of colorectal cancer. The emergence of omic techniques has provided a great opportunity to better study CRC and make personalized medicine feasible. In this review, we will try to summarize how the analysis of the omic layers can be useful for personalized medicine and the existing difficulties. We will discuss how single and multiple omic layer analyses have been used to improve the prediction of the risk of CRC and its outcomes and how to overcome the challenges in the use of omic layers in personalized medicine.

摘要

结直肠癌是一个主要的健康关注点,因为它是一种高度诊断的癌症,也是癌症死亡的第二大原因。因此,已经研究了最适合其诊断、预后和治疗的生物标志物,以改善和个性化结直肠癌的预防和临床管理。组学技术的出现为更好地研究 CRC 并使个性化医学成为可能提供了巨大的机会。在这篇综述中,我们将尝试总结分析组学层如何有助于个性化医学和现有的困难。我们将讨论如何使用单一和多种组学层分析来提高 CRC 风险及其结果的预测,以及如何克服个性化医学中使用组学层的挑战。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cc0/10379575/f66d191cbcab/genes-14-01430-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cc0/10379575/f66d191cbcab/genes-14-01430-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4cc0/10379575/f66d191cbcab/genes-14-01430-g001.jpg

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本文引用的文献

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Polygenic risk scores for the prediction of common cancers in East Asians: A population-based prospective cohort study.基于人群的前瞻性队列研究:东亚常见癌症的多基因风险评分预测。
Elife. 2023 Mar 27;12:e82608. doi: 10.7554/eLife.82608.
2
Multi-Omics Approaches in Colorectal Cancer Screening and Diagnosis, Recent Updates and Future Perspectives.结直肠癌筛查与诊断中的多组学方法:最新进展与未来展望
Cancers (Basel). 2022 Nov 11;14(22):5545. doi: 10.3390/cancers14225545.
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Host Genetics and Microbiota Interactions in Colorectal Cancer: Shared or Independent Risk?
通过机器学习鉴定与结肠腺癌肝转移相关的新型诊断生物标志物
Discov Oncol. 2024 Oct 10;15(1):542. doi: 10.1007/s12672-024-01398-y.
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Characterizing m6A modification factors and their interactions in colorectal cancer: implications for tumor subtypes and clinical outcomes.表征结直肠癌中m6A修饰因子及其相互作用:对肿瘤亚型和临床结局的影响
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Performance of the Use of Genetic Information to Assess the Risk of Colorectal Cancer in the Basque Population.利用遗传信息评估巴斯克人群患结直肠癌风险的效能
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Single-cell and bulk transcriptome sequencing identifies two epithelial tumor cell states and refines the consensus molecular classification of colorectal cancer.单细胞和批量转录组测序确定了两种上皮肿瘤细胞状态,并完善了结直肠癌的共识分子分类。
Nat Genet. 2022 Jul;54(7):963-975. doi: 10.1038/s41588-022-01100-4. Epub 2022 Jun 30.
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A Comprehensive Metabolomics Analysis of Fecal Samples from Advanced Adenoma and Colorectal Cancer Patients.晚期腺瘤和结直肠癌患者粪便样本的综合代谢组学分析
Metabolites. 2022 Jun 15;12(6):550. doi: 10.3390/metabo12060550.
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A multi-omics machine learning framework in predicting the survival of colorectal cancer patients.多组学生物机器学习框架预测结直肠癌患者的生存情况。
Comput Biol Med. 2022 Jul;146:105516. doi: 10.1016/j.compbiomed.2022.105516. Epub 2022 Apr 18.
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The gut microbial metabolite formate exacerbates colorectal cancer progression.肠道微生物代谢产物甲酸盐可加剧结直肠癌的进展。
Nat Metab. 2022 Apr;4(4):458-475. doi: 10.1038/s42255-022-00558-0. Epub 2022 Apr 18.
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Serum untargeted lipidomics by UHPLC-ESI-HRMS aids the biomarker discovery of colorectal adenoma.UHPLC-ESI-HRMS 进行非靶向脂质组学分析有助于结直肠腺瘤的生物标志物发现。
BMC Cancer. 2022 Mar 24;22(1):314. doi: 10.1186/s12885-022-09427-1.
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Cancers (Basel). 2022 Feb 6;14(3):817. doi: 10.3390/cancers14030817.