Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-specific Transcriptome and Molecular Subtype
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Le résumé fourni par la source
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 predict consensus molecular subtypes in metastatic colorectal cancer patients. We further demonstrate the ability to monitor changes in transcriptomic subtype under treatment selection pressure and identify molecular pathways in evRNA associated with recurrence. Our approach also identified expressed gene fusions and neoepitopes from evRNA. These results demonstrate the feasibility of transcriptomic-based liquid biopsy platforms for precision oncology approaches, spanning from the longitudinal monitoring of tumor subtype changes to identification of expressed fusions and neoantigens as cancer-specific therapeutic targets, sans the need for tissue-based sampling. Statement of significance We have developed an approach to interrogate changes in cancer molecular subtypes and differentially expressed genes, through the analysis and deconvolution of RNA sequencing of plasma EVs. Serial analyses of tumor-encoded transcriptomes in liquid biopsies can enable facile cancer detection and monitor for recurrences and therapy-induced tumor evolution.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-specific Transcriptome and Molecular Subtype
- Date Crossref
- 28/10/2022
- Éditeur
- openRxiv
- Type
- posted-content
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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The University of Texas MD Anderson Cancer Center Department of Translational Molecular Pathology pays non établi dans la noticeÉtablissement de santé
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Cedars-Sinai Medical Center Department of Surgery pays non établi dans la noticeÉtablissement de santé
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National Cancer Institute Center for Cancer Research pays non établi dans la noticeOrganisme public
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Center for Cancer Research pays non établi dans la noticeStructure de recherche
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Rice University pays non établi dans la noticeUniversité ou école supérieure
Department of Translational Molecular Pathology — The University of Texas MD Anderson Cancer Center, Department of Surgery — Cedars-Sinai Medical Center et Center for Cancer Research — National Cancer Institute, avec 2 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.