Abstract
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.
| Original language | English |
|---|---|
| Article number | e16261 |
| Journal | Heliyon |
| Volume | 9 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 2023 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Biomarkers
- Cancer diagnosis
- Cell-free DNA
- Cell-free RNA
- Expression profiling
- Liquid biopsy
- Machine learning
- Minimal residual disease
- Mutations
- Next generation sequencing
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