Asli Küçükosmanoglu, Carolien L van der Borden, Lisanne E A de Boer, Roel Verhaak, David Noske, Tom Wurdinger, Teodora Radonic, Bart A Westerman
{"title":"Oncogenic composite mutations can be predicted by co-mutations and their chromosomal location.","authors":"Asli Küçükosmanoglu, Carolien L van der Borden, Lisanne E A de Boer, Roel Verhaak, David Noske, Tom Wurdinger, Teodora Radonic, Bart A Westerman","doi":"10.1002/1878-0261.13636","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":18764,"journal":{"name":"Molecular Oncology","volume":" ","pages":"2407-2422"},"PeriodicalIF":6.6000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11459034/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Oncology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/1878-0261.13636","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/5/16 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
引用次数: 0
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.
Molecular OncologyBiochemistry, Genetics and Molecular Biology-Molecular Medicine
CiteScore
11.80
自引率
1.50%
发文量
203
审稿时长
10 weeks
期刊介绍:
Molecular Oncology highlights new discoveries, approaches, and technical developments, in basic, clinical and discovery-driven translational cancer research. It publishes research articles, reviews (by invitation only), and timely science policy articles.
The journal is now fully Open Access with all articles published over the past 10 years freely available.