Cancer type classification using plasma cell-free RNAs derived from human and microbes

Elife. 2022 Jul 11:11:e75181. doi: 10.7554/eLife.75181.

Abstract

The utility of cell-free nucleic acids in monitoring cancer has been recognized by both scientists and clinicians. In addition to human transcripts, a fraction of cell-free nucleic acids in human plasma were proven to be derived from microbes and reported to have relevance to cancer. To obtain a better understanding of plasma cell-free RNAs (cfRNAs) in cancer patients, we profiled cfRNAs in ~300 plasma samples of 5 cancer types (colorectal cancer, stomach cancer, liver cancer, lung cancer, and esophageal cancer) and healthy donors (HDs) with RNA-seq. Microbe-derived cfRNAs were consistently detected by different computational methods when potential contaminations were carefully filtered. Clinically relevant signals were identified from human and microbial reads, and enriched Kyoto Encyclopedia of Genes and Genomes pathways of downregulated human genes and higher prevalence torque teno viruses both suggest that a fraction of cancer patients were immunosuppressed. Our data support the diagnostic value of human and microbe-derived plasma cfRNAs for cancer detection, as an area under the ROC curve of approximately 0.9 for distinguishing cancer patients from HDs was achieved. Moreover, human and microbial cfRNAs both have cancer type specificity, and combining two types of features could distinguish tumors of five different primary locations with an average recall of 60.4%. Compared to using human features alone, adding microbial features improved the average recall by approximately 8%. In summary, this work provides evidence for the clinical relevance of human and microbe-derived plasma cfRNAs and their potential utilities in cancer detection as well as the determination of tumor sites.

Keywords: biomarker; cancer classification; cell-free RNA; computational biology; genetics; genomics; human; liquid biopsy; microbiome; systems biology.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomarkers, Tumor / genetics
  • Cell-Free Nucleic Acids* / genetics
  • Humans
  • Lung Neoplasms* / diagnosis
  • Plasma
  • RNA-Seq
  • ROC Curve

Substances

  • Biomarkers, Tumor
  • Cell-Free Nucleic Acids

Associated data

  • GEO/GSE174302
  • GEO/GSE142987

Grants and funding

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.