Concomitant genomic features stratify prognosis to patients with advanced EGFR mutant lung cancer

Author:

Liang Xiao12,Xu Jiali1,Jiang Yuqin1,Yan Yuqian3,Wu Hongshuai4,Dai Jiali1,Cui Yanan1,Zhang Chen1,Chen Wei5,Zhang Zhihong6,Guo Renhua1

Affiliation:

1. Department of Medical Oncology The First Affiliated Hospital of Nanjing Medical University Nanjing China

2. Department of Medical Oncology The Affiliated Jiangyin Hospital of Nantong University Jiangyin China

3. Department of Epidemiology, School of Public Health Nanjing Medical University Nanjing China

4. Department of Central Laboratory, Wuxi Key Laboratory of Biomaterials for Clinical Application, Key Laboratory for Multidisciplinary Intersection of Radiotherapy and Immunology for Gastrointestinal Tumor Jiangyin Clinical College of Xuzhou Medical University Jiangyin China

5. Department of Radiotherapy, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Cancer Hospital Jiangsu Institue of Cancer Research Nanjing Jiangsu China

6. Department of Pathology The First Affiliated Hospital of Nanjing Medical University Nanjing China

Abstract

AbstractThis 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.

Publisher

Wiley

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