{"title":"晚期表皮生长因子受体突变肺癌患者预后分层的基因组特征。","authors":"Xiao Liang, Jiali Xu, Yuqin Jiang, Yuqian Yan, Hongshuai Wu, Jiali Dai, Yanan Cui, Chen Zhang, Wei Chen, Zhihong Zhang, Renhua Guo","doi":"10.1002/mc.23750","DOIUrl":null,"url":null,"abstract":"<p><p>This study aimed to explore the clinical significance of genomics features including tumor mutation burden (TMB) and copy number alteration (CNA) for advanced EGFR mutant lung cancer. We retrospectively identified 1378 patients with advanced EGFR mutant lung cancer and next-generation sequencing tests from three cohorts. Multiple co-occurring genomics alternations occurred in a large proportion (97%) of patients with advanced EGFR mutant lung cancers. Both TMB and CNA were predictive biomarkers for these patients. A joint analysis of TMB and CNA found that patients with high TMB and high CNA showed worse responses to EGFR-TKIs and predicted worse outcomes. TMB<sup>high</sup>CNA<sup>high</sup>, as a high-risk genomic feature, showed predictive ability in most of the subgroups based on clinical characteristics. These patients had larger numbers of metastatic sites, and higher rates of EGFR copy number amplification, TP53 mutations, and cell-cycle gene alterations, which showed more potential survival gain from combination treatment. Furthermore, a nomogram based on genomic features and clinical features was developed to distinguish prognosis. Genomic features could stratify prognosis and guide clinical treatment for patients with advanced EGFR mutant lung cancer.</p>","PeriodicalId":19003,"journal":{"name":"Molecular Carcinogenesis","volume":" ","pages":"1643-1653"},"PeriodicalIF":3.0000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Concomitant genomic features stratify prognosis to patients with advanced EGFR mutant lung cancer.\",\"authors\":\"Xiao Liang, Jiali Xu, Yuqin Jiang, Yuqian Yan, Hongshuai Wu, Jiali Dai, Yanan Cui, Chen Zhang, Wei Chen, Zhihong Zhang, Renhua Guo\",\"doi\":\"10.1002/mc.23750\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>This study aimed to explore the clinical significance of genomics features including tumor mutation burden (TMB) and copy number alteration (CNA) for advanced EGFR mutant lung cancer. We retrospectively identified 1378 patients with advanced EGFR mutant lung cancer and next-generation sequencing tests from three cohorts. Multiple co-occurring genomics alternations occurred in a large proportion (97%) of patients with advanced EGFR mutant lung cancers. Both TMB and CNA were predictive biomarkers for these patients. A joint analysis of TMB and CNA found that patients with high TMB and high CNA showed worse responses to EGFR-TKIs and predicted worse outcomes. TMB<sup>high</sup>CNA<sup>high</sup>, as a high-risk genomic feature, showed predictive ability in most of the subgroups based on clinical characteristics. These patients had larger numbers of metastatic sites, and higher rates of EGFR copy number amplification, TP53 mutations, and cell-cycle gene alterations, which showed more potential survival gain from combination treatment. Furthermore, a nomogram based on genomic features and clinical features was developed to distinguish prognosis. Genomic features could stratify prognosis and guide clinical treatment for patients with advanced EGFR mutant lung cancer.</p>\",\"PeriodicalId\":19003,\"journal\":{\"name\":\"Molecular Carcinogenesis\",\"volume\":\" \",\"pages\":\"1643-1653\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2024-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Molecular Carcinogenesis\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/mc.23750\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/11 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"BIOCHEMISTRY & MOLECULAR BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular Carcinogenesis","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/mc.23750","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/11 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOCHEMISTRY & MOLECULAR BIOLOGY","Score":null,"Total":0}
Concomitant genomic features stratify prognosis to patients with advanced EGFR mutant lung cancer.
This study aimed to explore the clinical significance of genomics features including tumor mutation burden (TMB) and copy number alteration (CNA) for advanced EGFR mutant lung cancer. We retrospectively identified 1378 patients with advanced EGFR mutant lung cancer and next-generation sequencing tests from three cohorts. Multiple co-occurring genomics alternations occurred in a large proportion (97%) of patients with advanced EGFR mutant lung cancers. Both TMB and CNA were predictive biomarkers for these patients. A joint analysis of TMB and CNA found that patients with high TMB and high CNA showed worse responses to EGFR-TKIs and predicted worse outcomes. TMBhighCNAhigh, as a high-risk genomic feature, showed predictive ability in most of the subgroups based on clinical characteristics. These patients had larger numbers of metastatic sites, and higher rates of EGFR copy number amplification, TP53 mutations, and cell-cycle gene alterations, which showed more potential survival gain from combination treatment. Furthermore, a nomogram based on genomic features and clinical features was developed to distinguish prognosis. Genomic features could stratify prognosis and guide clinical treatment for patients with advanced EGFR mutant lung cancer.
期刊介绍:
Molecular Carcinogenesis publishes articles describing discoveries in basic and clinical science of the mechanisms involved in chemical-, environmental-, physical (e.g., radiation, trauma)-, infection and inflammation-associated cancer development, basic mechanisms of cancer prevention and therapy, the function of oncogenes and tumors suppressors, and the role of biomarkers for cancer risk prediction, molecular diagnosis and prognosis.