A team led by Ludwig Stanford’s Ash Alizadeh and Maximilian Diehn described in an April publication in Nature a method for the analysis of cell-free (cf) RNA for liquid biopsies named RARE-seq (for random priming and affinity capture of cell-free RNA fragments for enrichment analysis by sequencing). In developing RARE-seq, the researchers identified and addressed a previously unrecognized technical challenge of cfRNA-based liquid biopsy: platelet contamination, they found, is a major confounder of cfRNA analysis and developed a computational model to cut through that noise. By zooming in on the transcripts of some 5,000 genes not likely to be picked up in plasma, the researchers made their analysis 50-fold more sensitive in detecting tumor-derived cfRNA than the sequencing of whole transcriptomes (RNA-seq). Ash, Max and their colleagues evaluated RARE-seq’s clinical utility using plasma samples from 369 individuals with disease and controls. They showed that its sensitivity in detecting non-small cell lung cancer (NSCLC) expression signatures increased with stage: 30% for stage I; 63% for stage II; 67% for stage III; and 83% in stage IV at 95% specificity. Further, RARE-seq could detect mutation-based mechanisms of resistance to tyrosine kinase inhibitors in patients with EGFR-mutant NSCLC. The researchers also demonstrated the use of RARE-seq for determining tissue of origin of various cancer types, assessing non-malignant pulmonary conditions and tracking dynamics of response to mRNA vaccines.
An ultrasensitive method for detection of cell-free RNA
Nature, 2025 April 16