Computational methods and challenges in analyzing intratumoral microbiome data.
Computational methods and challenges in analyzing intratumoral microbiome data.
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DOI：
10.1016/j.tim.2023.01.011
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发表时间：
2023-02
影响因子：
15.9
通讯作者：
Qi Wang;Zhaoqian Liu;A. Ma;Zihai Li;Bingqiang Liu;Q. Ma
中科院分区：
文献类型：
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作者：
Qi Wang;Zhaoqian Liu;A. Ma;Zihai Li;Bingqiang Liu;Q. Ma
人类微生物组与癌症生物学密切相关，在癌症治疗（包括免疫治疗）的疗效中起着至关重要的作用。非凡的证据表明，一些微生物通过与宿主免疫系统的相互作用影响肿瘤的发展，即免疫-肿瘤-微生物组（IOM）。这篇综述的重点是肿瘤内的微生物组，并描述了从宿主体、单细胞和空间测序数据中发现微生物谱的生物学见解的可用数据和计算方法。讨论了数据分析和集成中的关键挑战。具体而言，从文献中收集和整合与IOM背景下的癌症和癌症治疗相关的微生物。最后，对今后的研究方向提出了展望。
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.