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 high CNA high , 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.
Keyphrases
- copy number
- small cell lung cancer
- mitochondrial dna
- epidermal growth factor receptor
- tyrosine kinase
- genome wide
- cell cycle
- dna methylation
- end stage renal disease
- newly diagnosed
- ejection fraction
- wild type
- squamous cell carcinoma
- machine learning
- prognostic factors
- cell proliferation
- gene expression
- metabolic syndrome
- deep learning
- risk assessment
- patient reported outcomes
- transcription factor
- nucleic acid
- smoking cessation
- circulating tumor cells
- free survival