Combining cell-free RNA with cell-free DNA in liquid biopsy forhematologic and solid tumors

Combining cell-free RNA with cell-free DNA in liquid biopsy forhematologic and solid tumors

Maher Albitar, Hong Zhang, Ahmad Charifa, Andrew Ip, Wanlong Ma, James McCloskey, Michele Donato, David Siegel, Stanley Waintraub, Martin Gutierrez, Andrew Pecora, Andre Goy

Heliyon 9 (2023) e16261


Current use of liquid biopsy is based on cell-free DNA (cfDNA) and the evaluation of mutations or methylation pattern. However, expressed RNA can capture mutations, changes in expression levels due to methylation, and provide information on cell of origin, growth, and proliferation status. We developed an approach to isolate cell-free total nucleic acid (cfDNA) and used targeted next generation sequencing to sequence cell-free RNA (cfRNA) and cfDNA as new approach in liquid biopsy. We demonstrate that cfRNA is overall more sensitive than cfDNA in detecting mutations. We show that cfRNA is reliable in detecting fusion genes and cfDNA is reliable in detecting chromosomal gains and losses. cfRNA levels of various solid tumor biomarkers were significantly higher (P < 0.0001) in samples from solid tumors as compared with normal control. Similarly, cfRNA lymphoid markers and cfRNA myeloid markers were all higher in lymphoid and myeloid neoplasms, respectively as compared with control (P < 0.0001). Using machine learning we demonstrate cfRNA was highly predictive of diagnosis (AUC >0.98) of solid tumors, B-cell lymphoid neoplasms, T-cell lymphoid neoplasms, and myeloid neoplasms. In evaluating the host immune system, cfRNA CD4:CD8B and CD3D:CD19 ratios in normal controls were as expected (median: 5.92 and 6.87, respectively) and were significantly lower in solid tumors (P < 0.0002). This data suggests that liquid biopsy combining analysis of cfRNA with cfDNA is practical and may provide helpful information in predicting genomic abnormalities, diagnosis of neoplasms and evaluating both the tumor biology and the host response.


Liquid biopsy, Cell-free DNA, Cell-free RNA, Biomarkers, Mutations, Machine learning, Next generation sequencing, Expression profiling, Cancer diagnosis, Minimal residual disease


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