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Related Concept Videos

Introduction to the Human Microbiota01:22

Introduction to the Human Microbiota

Microorganisms colonize various regions of the human body, including the mouth, nasal passages, throat, stomach, intestines, urogenital tract, and skin. The total number of microbial cells is estimated to range from 10¹³ to 10¹⁴—comparable to, or exceeding, the number of human somatic cells. This host–microbiome relationship has led to the conceptualization of humans as supraorganisms, wherein microbial communities perform vital roles in development, immunity, and disease...

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Related Experiment Video

Updated: Jun 29, 2026

Enrichment and Characterization of the Tumor Immune and Non-immune Microenvironments in Established Subcutaneous Murine Tumors
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Systematic evaluation of TCGA tumor microbiota reveals context-dependent reliability.

Chenchen Ma1,2, Changxing Su1,2, Jiaxuan Li1,2

  • 1Department of Human Cell Biology and Genetics, School of Medicine, Southern University of Science and Technology, Shenzhen, Guangdong, China.

Msystems
|April 22, 2026
PubMed
Summary

This study benchmarks The Cancer Genome Atlas (TCGA) microbial profiles, revealing variable accuracy in detecting oncomicrobes and unreliable host-microbe associations. A new framework and web portal (MOMAC2) help identify trustworthy cancer microbiome signals for future research.

Keywords:
TCGAbenchmarkinghost-microbe interactionpan-cancer analysistumor microbiome

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Monitoring the Cancer-Immunity Cycle and Exploring Tumor Microenvironment Dynamics
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Area of Science:

  • Oncology
  • Microbiology
  • Bioinformatics

Background:

  • Tumor-associated bacteria are crucial in cancer biology, but the reliability of The Cancer Genome Atlas (TCGA) microbial data is uncertain.
  • Existing TCGA microbial profiles (TMPs) are widely used, yet their accuracy and consistency in host-microbe association studies require systematic evaluation.

Purpose of the Study:

  • To systematically benchmark TCGA microbial profiles for consistency, accuracy, and reliability in host-microbe association studies across 24 cancer types.
  • To develop a statistical framework to differentiate true biological signals from spurious associations in tumor microbiome data.
  • To introduce the Multi-Omics and Microbiome Associations in Cancer 2 (MOMAC2) web portal for accessing reliability-graded findings.

Main Methods:

  • Systematic benchmarking of two leading TCGA microbial profiles (TMPs) focusing on bacterial components.
  • Assessment of TMP accuracy for known oncomicrobes (e.g., HPV, Helicobacter pylori).
  • Evaluation of host-microbe association concordance across gene expression, methylation, and protein data.
  • Development of a permutation-based statistical framework to assess reliability.
  • Experimental validation of high-confidence associations using co-culture models.

Main Results:

  • TCGA microbial profiles showed substantial agreement in microbial composition but variable accuracy for specific oncomicrobes.
  • Host-microbe association concordance was moderate for gene expression but low for methylation and protein data.
  • A significant portion of associations, particularly those involving cell type and patient survival, were found to be statistically spurious.
  • High-confidence associations identified HPV-driven axes and implicated Streptococcus anginosus in promoting oral cancer cell proliferation and migration.

Conclusions:

  • TCGA microbial data requires careful, multi-layered validation for robust biological insights due to variable reliability.
  • The developed statistical framework and MOMAC2 web portal provide essential tools for interpreting and validating tumor microbiome data.
  • Validated associations, such as the role of Streptococcus anginosus, can guide experimental research and uncover novel cancer mechanisms.