Pan-cancer blood plasma cell-free RNA profiles reveal cancer type and patient-specific changes

PhD student Annelien Morlion presents her recent work on plasma cell-free RNA profiles in cancer type and patient-specific changes.

Background: Circulating nucleic acids in blood plasma form an attractive resource to study human health and disease. While the presence of extracellular RNAs in plasma has been firmly established, their origin and clinical utility for management of cancer patients is less understood.

Methods: In this study, we applied messenger RNA capture sequencing of blood plasma cell-free RNA from 266 cancer patients and cancer-free controls (discovery n=208, 25 cancer types; validation n=58, 3 types). Direct and indirect cancer signals in these plasma cell-free transcriptomes were evaluated by fusion transcript detection, cellular deconvolution, differential abundance and gene set enrichment analysis between cancer and control groups. Individual patient profiles were also compared to an independent reference of control samples and the number of strongly deviating genes per sample was used for binary (cancer/control) classification. The latter approach was also applied to cell-free RNA profiles in two additional cohorts: a plasma cohort (n=65, 2 lymphoma subtypes) and a urine cohort (n=24, bladder cancer).

Results: We observed cancer-type specific as well as pan-cancer alterations in cell-free transcriptomes compared to controls, including tumor-derived RNAs, RNAs reflecting the tumor tissue-of-origin and RNAs from various immune cell types. However, differentially abundant RNAs were very heterogenous between patients and between cohorts, hampering identification of robust cancer biomarkers. To this end, we developed a novel method that compares each individual cancer patient to a reference control population to identify so-called biomarker tail genes. We demonstrate that these biomarker tail genes can discriminate patients from controls with very high accuracy (AUC = 0.980). The applicability of this method was confirmed in the additional plasma and urine cohort.

Conclusions: Together, our findings demonstrate heterogeneity in cell-free RNA alterations between cancer patients and indicate that case-specific alterations can be exploited for classification purposes.