Multi-omics analysis: Paving the path toward achieving precision medicine in cancer treatment and immuno-oncology

被引:32
|
作者
Raufaste-Cazavieille, Virgile [1 ]
Santiago, Raoul [1 ,2 ]
Droit, Arnaud [1 ]
机构
[1] Univ Laval, CHU Quebec Res Ctr, Quebec City, PQ, Canada
[2] Univ Laval, Ctr Hosp Univ, Charles Bruneau Canc Ctr, Div Pediat Hematol Oncol, Quebec City, PQ, Canada
关键词
multi-omics; machine learning; immunology; immunomics; microbiome; cancer; precision medicine; LATENT VARIABLE MODEL; TUMOR HETEROGENEITY; INTEGRATIVE ANALYSIS; MOLECULAR SUBTYPES; PATTERN DISCOVERY; DRUG RESPONSE; MICROBIOME; EXPRESSION; CELLS; CLASSIFICATION;
D O I
10.3389/fmolb.2022.962743
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The acceleration of large-scale sequencing and the progress in high-throughput computational analyses, defined as omics, was a hallmark for the comprehension of the biological processes in human health and diseases. In cancerology, the omics approach, initiated by genomics and transcriptomics studies, has revealed an incredible complexity with unsuspected molecular diversity within a same tumor type as well as spatial and temporal heterogeneity of tumors. The integration of multiple biological layers of omics studies brought oncology to a new paradigm, from tumor site classification to pan-cancer molecular classification, offering new therapeutic opportunities for precision medicine. In this review, we will provide a comprehensive overview of the latest innovations for multi-omics integration in oncology and summarize the largest multi-omics dataset available for adult and pediatric cancers. We will present multi-omics techniques for characterizing cancer biology and show how multi-omics data can be combined with clinical data for the identification of prognostic and treatment-specific biomarkers, opening the way to personalized therapy. To conclude, we will detail the newest strategies for dissecting the tumor immune environment and host-tumor interaction. We will explore the advances in immunomics and microbiomics for biomarker identification to guide therapeutic decision in immuno-oncology.
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收藏
页数:18
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