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

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.

Cell-free multi-omics analysis reveals tumor status-informative signatures in gastrointestinal cancer patients’ plasma

“…In addition, microbial cfRNA abundance derived from the total cfRNA-seq data better classified the two cancer types than the features of human cfRNAs (Fig. 3d), which is consistent with the result we previously reported(12).…”

“…The data’s qualities were well controlled (see quality control steps in Methods, Supplementary Tables 2,3): intra-omics correlation between samples was above 0.75 in every single omics; inter-omics correlations were mostly close to zero (Extended Data Fig. 1d); concentration, read length, and read distribution of the data were consistent with previous studies(5, 12, 19) (Extended Data Fig. 2).…”

“…Microbial cfRNA abundance: Reads unaligned to genome were classified using kraken2 with its standard database to identify microbial cfRNA at genus level. Potential contaminations were filtered according to previous study(12). Counts at the genus level were also nor-malized by total genera counts.…”

“…To prove that the signatures derived from the plasma cfRNAs are able to monitor clinical status of cancer patients, we assayed 143 total cfRNA-seq datasets from colorectal and stomach cancer patients, where previous data we published (GSE174302) (12) were also included. We calculated various cell type signature scores based on deconvolution of the total cfRNA-seq data (see Methods) (Fig.…”

“…Many cfDNA features, such as methylation, mutation, copy number, fragment pattern, and nucleosome footprint, have been utilized for noninvasive diagnosis and prognosis of diseases(5–7). Meanwhile, many cfRNA features can also be used as biomarkers, such as the abundance of miRNAs(8) and circRNAs(9), fragment copy and alternative splicing of mRNAs and lncRNAs(10–12). Moreover, many other RNA regulation events altered in tumor cells, such as RNA editing(13), can potentially be utilized in liquid biopsy as well.…”