Microbiome analyses of blood and tissues suggest cancer diagnostic approach

Nature. 2020 Mar;579(7800):567-574. doi: 10.1038/s41586-020-2095-1. Epub 2020 Mar 11.


Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1-10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia-IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration.

MeSH terms

  • Case-Control Studies
  • Cohort Studies
  • DNA, Bacterial / blood
  • DNA, Viral / blood
  • Datasets as Topic
  • Female
  • Humans
  • Liquid Biopsy
  • Lung Neoplasms / blood
  • Lung Neoplasms / diagnosis
  • Lung Neoplasms / microbiology
  • Male
  • Melanoma / blood
  • Melanoma / diagnosis
  • Melanoma / microbiology
  • Microbiota / genetics*
  • Neoplasms / blood
  • Neoplasms / diagnosis*
  • Neoplasms / microbiology*
  • Plasma / microbiology*
  • Prostatic Neoplasms / blood
  • Prostatic Neoplasms / diagnosis
  • Prostatic Neoplasms / microbiology
  • Reproducibility of Results


  • DNA, Bacterial
  • DNA, Viral