Evidence map›Paper›PMID 38757376›Full record

ArticleMolecular oncology2024

Oncogenic composite mutations can be predicted by co-mutations and their chromosomal location.

Asli Küçükosmanoglu, Carolien L van der Borden, Lisanne E A de Boer, Roel Verhaak, David Noske, Tom Wurdinger, Teodora Radonic, Bart A Westerman

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Article in Molecular oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Asli KüçükosmanogluDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Amsterdam University Medical Center, Cancer Center Amsterdam, The Netherlands.
Carolien L van der BordenDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Amsterdam University Medical Center, Cancer Center Amsterdam, The Netherlands.
Lisanne E A de BoerDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Amsterdam University Medical Center, Cancer Center Amsterdam, The Netherlands.
Roel VerhaakDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Amsterdam University Medical Center, Cancer Center Amsterdam, The Netherlands.
David NoskeDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Amsterdam University Medical Center, Cancer Center Amsterdam, The Netherlands.
Tom WurdingerDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Amsterdam University Medical Center, Cancer Center Amsterdam, The Netherlands.
Teodora RadonicDepartment of Pathology, Amsterdam University Medical Center, Cancer Center Amsterdam, The Netherlands.
Bart A WestermanDepartment of Neurosurgery, Brain Tumor Center Amsterdam, Amsterdam University Medical Center, Cancer Center Amsterdam, The Netherlands.ORCID 0000-0002-9898-9616

Funding

Brain Tumour Charity 488097Dutch Cancer Society KWF-11038Dutch Cancer Society KWF-4874Health~Holland AI-IMPACTVrije Universiteit Amsterdam APCA-PoC-2017
6 · The paper itself

Abstract

Genetic heterogeneity in tumors can show a remarkable selectivity when two or more independent genetic events occur in the same gene. This phenomenon, called composite mutation, points toward a selective pressure, which frequently causes therapy resistance to mutation-specific drugs. Since composite mutations have been described to occur in sub-clonal populations, they are not always captured through biopsy sampling. Here, we provide a proof of concept to predict composite mutations to anticipate which patients might be at risk for sub-clonally driven therapy resistance. We found that composite mutations occur in 5% of cancer patients, mostly affecting the PIK3CA, EGFR, BRAF, and KRAS genes, which are common precision medicine targets. Furthermore, we found a strong and significant relationship between the frequencies of composite mutations with commonly co-occurring mutations in a non-composite context. We also found that co-mutations are significantly enriched on the same chromosome. These observations were independently confirmed using cell line data. Finally, we show the feasibility of predicting compositive mutations based on their co-mutations (AUC 0.62, 0.81, 0.82, and 0.91 for EGFR, PIK3CA, KRAS, and BRAF, respectively). This prediction model could help to stratify patients who are at risk of developing therapy resistance-causing mutations.

Indexed as

MutationNeoplasmsCell Line, TumorChromosomes, HumanClass I Phosphatidylinositol 3-KinasesHumansOncogenesClass I Phosphatidylinositol 3-KinasesPIK3CA protein, humancomposite mutationsgenetic heterogeneityparallel evolutionpredictive modeltherapy resistance

Identifiers

PMID38757376
PMCPMC11459034

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.