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CaClust: Linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants.
Genome Biol. 25:286 (2024)
Tumours exhibit high genotypic and transcriptional heterogeneity. Both affect cancer progression and treatment, but have been predominantly studied separately in follicular lymphoma. To comprehensively investigate the evolution and genotype-to-phenotype maps in follicular lymphoma, we introduce CaClust, a probabilistic graphical model integrating deep whole exome, single-cell RNA and B-cell receptor sequencing data to infer clone genotypes, cell-to-clone mapping, and single-cell genotyping. CaClust outperforms a state-of-the-art model on simulated and patient data. In-depth analyses of single cells from four samples showcase effects of driver mutations, follicular lymphoma evolution, possible therapeutic targets, and single-cell genotyping that agrees with an independent targeted resequencing experiment.
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Publikationstyp
Artikel: Journalartikel
Dokumenttyp
Wissenschaftlicher Artikel
Schlagwörter
Cancer Genetics ; Follicular Lymphoma ; Statistical Methods ; Tumour Heterogeneity; Intratumor Heterogeneity; Phenotypic Heterogeneity; Clonal Evolution; Cell; Expression; Pathogenesis; Database
ISSN (print) / ISBN
1474-760X
e-ISSN
1465-6906
Zeitschrift
Genome Biology
Quellenangaben
Band: 25,
Heft: 1,
Artikelnummer: 286
Verlag
BioMed Central
Verlagsort
Campus, 4 Crinan St, London N1 9xw, England
Nichtpatentliteratur
Publikationen
Begutachtungsstatus
Peer reviewed
Institut(e)
Institute of AI for Health (AIH)
Förderungen
Narodowe Centrum Nauki