CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants

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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Publication Details

Journal
Genome biology
Published
2024-11-05
DOI
https://doi.org/10.1186/s13059-024-03417-1
Citations
1
Primary Topic
Lymphoma Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.42

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article

CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants

Julieta Sepúlveda-Yáñez, Szymon M. Kiełbasa, Cornelis A.M. van Bergen, Edwin Quinten et al.
1 citations
Genome biology
Lymphoma Diagnosis and Treatment
0.42
article

CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants

Julieta Sepúlveda-Yáñez, Szymon M. Kiełbasa, Cornelis A.M. van Bergen, Edwin Quinten, Marcelo A. Navarrete, Ewa Szczurek, Shadi Darvish Shafighi, Hendrik Veelken, Joost S.P. Vermaat, Ruben A. L. de Groen, Kazimierz Oksza-Orzechowski, Hugo W. van Kessel
article en
1 citations

Abstract

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.

Genome biologyVol. 25(1)
Leiden University Medical Center (NL), Center for Environmental Health (US), Helmholtz Zentrum München (DE), Cancer Research UK Cambridge Center (GB), University of Warsaw (PL), Universidad de Magallanes (CL)
Universiteit Leiden, Narodowe Centrum Nauki, KWF Kankerbestrijding, Leids Universitair Medisch Centrum, Agencia Nacional de Investigación y Desarrollo
Good health and well-being
Openalex Percentile: Top 33%
Lymphoma Diagnosis and Treatment
0.42
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