Computational methods and challenges in analyzing intratumoral microbiome data

Qi Wang; Zhaoqian Liu; Anjun Ma; Zihai Li; Bingqiang Liu; Qin Ma

doi:10.1016/j.tim.2023.01.011

Computational methods and challenges in analyzing intratumoral microbiome data

Trends Microbiol. 2023 Jul;31(7):707-722. doi: 10.1016/j.tim.2023.01.011. Epub 2023 Feb 23.

Authors

Qi Wang¹, Zhaoqian Liu¹, Anjun Ma², Zihai Li³, Bingqiang Liu⁴, Qin Ma⁵

Affiliations

¹ School of Mathematics, Shandong University, Jinan, Shandong, 250100, China.
² Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, 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 School of Mathematics, Shandong University, Jinan, Shandong, 250100, China; Shandong National Center for Applied Mathematics, Jinan, Shandong, 250100, China. Electronic address: bingqiang@sdu.edu.cn.
⁵ Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA; Pelotonia Institute for Immuno-Oncology, The James Comprehensive Cancer Center, The Ohio State University, Columbus, OH 43210, USA. Electronic address: qin.ma@osumc.edu.

PMID: 36841736
PMCID: PMC10272078 (available on 2024-07-01)
DOI: 10.1016/j.tim.2023.01.011

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.

Keywords: cancer treatment and diagnosis; computational methods; immuno-oncology-microbiome; immunotherapy; intratumoral microbiome.

Publication types

Review
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural

MeSH terms

Computational Biology / methods
Forecasting
Humans
Immunotherapy / methods
Microbiota*
Neoplasms* / therapy

Grants and funding

R01 GM131399/GM/NIGMS NIH HHS/United States