Computational methods and challenges in analyzing intratumoral microbiome data

The gut and intratumoral microbiota significantly affect cancer development and progression by interacting with the host's immune system, that is, the immuno–oncology–microbiome (IOM).Available microbial data in IOM studies are mined from existing host bulk sequencing and single-cell sequencing...

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Veröffentlicht in:Trends in microbiology (Regular ed.) 2023-07, Vol.31 (7), p.707-722
Hauptverfasser: Wang, Qi, Liu, Zhaoqian, Ma, Anjun, Li, Zihai, Liu, Bingqiang, Ma, Qin
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Sprache:eng
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Zusammenfassung:The gut and intratumoral microbiota significantly affect cancer development and progression by interacting with the host's immune system, that is, the immuno–oncology–microbiome (IOM).Available microbial data in IOM studies are mined from existing host bulk sequencing and single-cell sequencing datasets to provide unprecedented opportunities for investigating IOM in various cancer types.The development of rigorous computational methods for characterizing and elucidating IOM is urgently needed to guide researchers to unravel new biological insights and develop precision cancer therapeutics.A reliable benchmarking system is needed to model IOM interactions, analyze IOM data, and evaluate computational predictions.In-depth functional analyses of IOM mechanisms are necessary to develop novel therapeutic strategies targeting microbiota to improve cancer treatment outcomes. The human microbiome is intimately related to cancer biology and plays a vital role in the efficacy of cancer treatments, including immunotherapy. Extraordinary evidence has revealed that several microbes influence tumor development through interaction with the host immune system, that is, immuno–oncology–microbiome (IOM). This review focuses on the intratumoral microbiome in IOM and describes the available data and computational methods for discovering biological insights of microbial profiling from host bulk, single-cell, and spatial sequencing data. Critical challenges in data analysis and integration are discussed. Specifically, the microorganisms associated with cancer and cancer treatment in the context of IOM are collected and integrated from the literature. Lastly, we provide our perspectives for future directions in IOM research.
ISSN:0966-842X
1878-4380
1878-4380
DOI:10.1016/j.tim.2023.01.011