Related Experiment Video
Updated: Jan 15, 2026
07:58
Characterizing Mutational Load and Clonal Composition of Human Blood
Published on: July 11, 2019
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Co-mapping clonal and transcriptional heterogeneity in somatic evolution via GoT-Multi.
Minwoo Pak1, Mirca S Saurty-Seerunghen1, Kellie Wise2
1Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY 10065, USA.
Cell Genomics
|October 11, 2025
Summary
Genotyping of Transcriptomes for multiple targets and sample types (GoT-Multi) reveals how cancer cell genotypes drive therapy resistance. This single-cell multi-omics method links genetic mutations to distinct cellular states, uncovering convergent resistance mechanisms.
Area of Science:
- Cancer Biology
- Genomics
- Molecular Oncology
Background:
- Somatic evolution causes clonal heterogeneity, driving cancer progression and treatment resistance.
- Understanding clonal architecture and transcriptional states is crucial for deciphering cancer complexity.
Purpose of the Study:
- To develop a high-throughput single-cell multi-omics method for co-detecting somatic genotypes and transcriptomes.
- To reconstruct clonal architectures and link them to transcriptional programs in therapy-resistant cancers.
Main Methods:
- Development of Genotyping of Transcriptomes for multiple targets and sample types (GoT-Multi).
- Application of GoT-Multi to formalin-fixed paraffin-embedded (FFPE) and frozen samples.
- Utilizing an ensemble-based machine learning pipeline for genotyping optimization.
Main Results:
- GoT-Multi successfully deconvoluted complex clonal architectures and linked genotypes to transcriptional states.
- Analysis of Richter transformation samples revealed heterogeneous cancer cell states with up to 27 mutations.
- Distinct subclones, including those with therapy-resistant mutations, converged on inflammatory or proliferative/MYC transcriptional programs.
Conclusions:
- GoT-Multi is a powerful tool for dissecting clonal heterogeneity and its functional consequences.
- Convergent transcriptional states, driven by distinct genotypes, can mediate therapy resistance in cancer.
- This approach provides new insights into the molecular mechanisms underlying cancer progression and treatment failure.
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