Joint analysis of mutational and transcriptional landscapes in human cancer reveals key perturbations during cancer evolution.

Jae-Won Cho, Jingyi Cao, Martin Hemberg

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Article in Genome biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed

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2 citing papers in PubMed.

Optimal adaptive cancer therapy based on evolutionary game theory.PloS one · 2025
Article
Comparative Copy Number Variation Profiling of GL01, an Immortalized Non-small Cell Lung Cancer Cell Line Derived from a Filipino Patient, and A549 Lung Adenocarcinoma Cells.Acta medica Philippina · 2025
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3 authors.

Jae-Won ChoThe Gene Lay Institute of Immunology and Inflammation, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Jingyi CaoThe Gene Lay Institute of Immunology and Inflammation, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.

Martin HembergThe Gene Lay Institute of Immunology and Inflammation, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. mhemberg@bwh.harvard.edu.ORCID 0000-0001-8895-5239

Funding

Leona M. and Harry B. Helmsley Charitable Trust 2008-04050

6 · The paper itself

Abstract

backgroundTumors are able to acquire new capabilities, including traits such as drug resistance and metastasis that are associated with unfavorable clinical outcomes. Single-cell technologies have made it possible to study both mutational and transcriptomic profiles, but as most studies have been conducted on model systems, little is known about cancer evolution in human patients. Hence, a better understanding of cancer evolution could have important implications for treatment strategies.

resultsHere, we analyze cancer evolution and clonal selection by jointly considering mutational and transcriptomic profiles of single cells acquired from tumor biopsies from 49 lung cancer samples and 51 samples with chronic myeloid leukemia. Comparing the two profiles, we find that each clone is associated with a preferred transcriptional state. For metastasis and drug resistance, we find that the number of mutations affecting related genes increases as the clone evolves, while changes in gene expression profiles are limited. Surprisingly, we find that mutations affecting ligand-receptor interactions with the tumor microenvironment frequently emerge as clones acquire drug resistance.

conclusionsOur results show that lung cancer and chronic myeloid leukemia maintain a high clonal and transcriptional diversity, and we find little evidence in favor of clonal sweeps. This suggests that for these cancers selection based solely on growth rate is unlikely to be the dominating driving force during cancer evolution.

Indexed as

Leukemia, Myelogenous, Chronic, BCR-ABL PositiveLung NeoplasmsClonal EvolutionHumansMutationTumor MicroenvironmentCancer evolutionClonal selectionDrug resistanceGenetic-transcription perturbationMetabolismMetastasisTumor microenvironment

Identifiers

PMID38459554

DOI10.1186/s13059-024-03201-1

PMCPMC10921788

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