Rationale: Long extracellular RNAs (exRNAs) in plasma can be profiled by new sequencing technologies, even with low abundance. However, cancer-related exRNAs and their variations remain understudied. Methods: We investigated different variations (i.e. differential expression, alternative splicing, alternative polyadenylation, and differential editing) in diverse long exRNA species (e.g. long noncoding RNAs and circular RNAs) using 79 plasma exosomal RNA-seq (exoRNA-seq) datasets of multiple cancer types. We then integrated 53 exoRNA-seq datasets and 65 self-profiled cell-free RNA-seq (cfRNA-seq) datasets to identify recurrent variations in liver cancer patients. We further combined TCGA tissue RNA-seq datasets and validated biomarker candidates by RT-qPCR in an individual cohort of more than 100 plasma samples. Finally, we used machine learning models to identify a signature of 3 noncoding RNAs for the detection of liver cancer. Results: We found that different types of RNA variations identified from exoRNA-seq data were enriched in pathways related to tumorigenesis and metastasis, immune, and metabolism, suggesting that cancer signals can be detected from long exRNAs. Subsequently, we identified more than 100 recurrent variations in plasma from liver cancer patients by integrating exoRNA-seq and cfRNA-seq datasets. From these datasets, 5 significantly up-regulated long exRNAs were confirmed by TCGA data and validated by RT-qPCR in an independent cohort. When using machine learning models to combine two of these validated circular and structured RNAs ( SNORD3B-1, circ-0080695 ) with a miRNA ( miR-122 ) as a panel to classify liver cancer patients from healthy donors, the average AUROC of the cross-validation was 89.4%. The selected 3-RNA panel successfully detected 79.2% AFP-negative samples and 77.1% early-stage liver cancer samples in the testing and validation sets. Conclusions: Our study revealed that different types of RNA variations related to cancer can be detected in plasma and identified a 3-RNA detection panel for liver cancer, especially for AFP-negative and early-stage patients.

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.

Background: The utilities of cell free nucleic acids in monitoring cancer have been recognized by both scientists and clinicians. In addition to human transcripts, a fraction of cell free nucleic acids in human plasma were proved to derived from microbes, and reported to have some relevance to cancer. Methods: To get a better understanding of plasma cell free RNAs (cfRNAs) in cancer patients, we profiled cfRNAs in ~300 plasma samples of five cancer types (colorectal cancer, stomach cancer, liver cancer, lung cancer, esophageal cancer) and healthy donors with RNA-seq. Results: Microbe derived cfRNAs were consistently detected by different computational methods when potential contaminations were carefully filtered. Clinically relevant signals can be identified from human and microbial reads, and alteration in human cfRNA expression and virus abundance both suggests some cancer patients were immunosuppressed, as indicated by enriched KEGG pathways of downregulated human genes and higher prevalence torque teno virus. Our data supports the diagnostic value of human and microbe derived plasma cfRNAs for cancer detection, as an area under receiver operating characteristic (ROC) curve of 0.931 for distinguishing cancer patients from healthy donors was achieved on validation set, using both human and microbial features. Moreover, these cfRNAs both have some cancer type specificity, and could distinguish tumors of different primary locations. Compared to using human feature alone, combining human and microbial features improves the average validation accuracy of between cancer type classification by 11.5%. Conclusions: In summary, this work provides evidence for the clinical relevance of human and microbe derived plasma cfRNAs, and their potential utilities in cancer detection, and determination of tumor sites.

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