Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-Specific Transcriptome and Molecular Subtype.

ABSTRACT: Longitudinal monitoring of patients with advanced cancers is crucial to evaluate both disease burden and treatment response. Current liquid biopsy approaches mostly rely on the detection of DNA-based biomarkers. However, plasma RNA analysis can unleash tremendous opportunities for tumor state interrogation and molecular subtyping. Through the application of deep learning algorithms to the deconvolved transcriptomes of RNA within plasma extracellular vesicles (evRNA), we successfully predicted consensus molecular subtypes in patients with metastatic colorectal cancer. Analysis of plasma evRNA also enabled monitoring of changes in transcriptomic subtype under treatment selection pressure and identification of molecular pathways associated with recurrence. This approach also revealed expresse

SUBMITTER: Bahrambeigi V 

PROVIDER: S-EPMC11096054 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature