Computational methods and challenges in analyzing intratumoral microbiome data |
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| Affiliation: | 1. School of Mathematics, Shandong University, Jinan, Shandong, 250100, China;2. Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA;3. Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA;4. Shandong National Center for Applied Mathematics, Jinan, Shandong, 250100, China;1. Institute for Glycomics, Griffith University, Gold Coast Campus, Southport, QLD 4222, Australia;2. School of Chemistry and Molecular Biosciences, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia;3. Center for Microbial Pathogenesis, Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, OH 43205, USA;4. Department of Pediatrics, The Ohio State University, Columbus, OH 43210, USA;1. Department of Biological Sciences, University of Arkansas, Fayetteville, AR, USA;2. Paul G. Allen School for Global Health, Washington State University, Pullman, WA, USA;1. State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen 361005, China;1. Department of Land, Air and Water Resources, University of California, Davis, CA, USA;2. Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA;3. Department of Plant Sciences, University of California, Davis, CA, USA;1. Cawthron Institute, 98 Halifax St East, Nelson, New Zealand;2. College of Science and Engineering, James Cook University, Townsville, Australia;3. Department of Zoology, University of Otago, Dunedin, New Zealand;1. Department of Life Sciences, Ben-Gurion University of the Negev, Be''er-Sheva, Israel |
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| Abstract: | 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. |
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