Marker-free characterization of single live circulating tumor cell full-length transcriptomes
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Le résumé fourni par la source
Abstract The identification and characterization of circulating tumor cells (CTCs) are important for gaining insights into the biology of metastatic cancers, monitoring disease progression, and medical management of the disease. The limiting factor that hinders enrichment of purified CTC populations is their sparse availability, heterogeneity, and altered phenotypic traits relative to the tumor of origin. Intensive research both at the technical and molecular fronts led to the development of assays that ease CTC detection and identification from the peripheral blood. Most CTC detection methods use a mix of size selection, immune marker based white blood cells (WBC) depletion, and positive enrichment antibodies targeting tumor-associated antigens. However, the majority of these methods either miss out on atypical CTCs or suffer from WBC contamination. Single-cell RNA sequencing (scRNA-Seq) of CTCs provides a wealth of information about their tumors of origin as well as their fate and is a potent method of enabling unbiased identification of CTCs. We present unCTC, an R package for unbiased identification and characterization of CTCs from single-cell transcriptomic data. unCTC features many standard and novel computational and statistical modules for various analysis tasks. These include a novel method of scRNA-Seq clustering, named D eep D ictionary L earning using K -means clustering cost (DDLK), expression based copy number variation (CNV) inference, and combinatorial, marker-based verification of the malignant phenotypes. DDLK enables robust segregation of CTCs and WBCs in the pathway space, as opposed to the gene expression space. We validated the utility of unCTC on scRNA-Seq profiles of breast CTCs from six patients, captured and profiled using an integrated ClearCell ® FX and Polaris TM workflow that works by the principles of size-based separation of CTCs and marker based WBC depletion.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Marker-free characterization of single live circulating tumor cell full-length transcriptomes
- Date Crossref
- 19/11/2021
- 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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Indraprastha Institute of Information Technology Delhi Department of Computational Biology pays non établi dans la noticeUniversité ou école supérieure
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Indian Institute of Technology Delhi pays non établi dans la noticeUniversité ou école supérieure
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Translational Research Institute pays non établi dans la noticeStructure de recherche
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Queensland University of Technology pays non établi dans la noticeUniversité ou école supérieure
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National Cancer Centre Singapore pays non établi dans la noticeÉtablissement de santé
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Fluidigm (United States) pays non établi dans la noticeEntreprise
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National University of Singapore Institute for Health Innovation and Technology (iHealthtech) pays non établi dans la noticeUniversité ou école supérieure
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Rajiv Gandhi Cancer Institute and Research Centre Department of Research pays non établi dans la noticeÉtablissement de santé
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Faculty of Health Australian Prostate Cancer Research Centre-Queensland pays non établi dans la noticeUniversité ou école supérieure
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Biolidics Limited pays non établi dans la noticeInstitution
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Thermo Fisher Scientific pays non établi dans la noticeInstitution
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BioSkryb Corporation pays non établi dans la noticeInstitution
Department of Computational Biology — Indraprastha Institute of Information Technology Delhi, Indian Institute of Technology Delhi et Translational Research Institute, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.