bioRxivCancer Biology
Simplified Molecular Classification of Lung Adenocarcinomas Based on EGFR, KRAS, and TP53 Mutations
R. Ruiz-Cordero, J. Ma, A. Khanna, G. Lyons, W. Rinsurongkawong, R. Bassett, M. Guo, M. J. Routbort, J. Zhang, F. Sloulidis, J. V. Heymach, E. B. Roarty, Z. Tang, L. J. Medeiros, K. P. Patel, R. Luthra, S. Roy-Chowdhuri
Abstract
IntroductionGene expression profiling has consistently identified three molecular subtypes of lung adenocarcinoma that have prognostic implications. To facilitate stratification of patients with this disease into similar molecular subtypes, we developed and validated a simple, mutually exclusive classification.\n\nMethodsMutational status of EGFR, KRAS, and TP53 was used to define six mutually exclusive molecular subtypes. A development cohort of 283 cytology specimens of lung adenocarcinoma was used to evaluate the associations between the proposed classification and clinicopathologic variables including demographic characteristics, smoking history, fluorescence in situ hybridization and molecular results. For validation and prognostic assessment, 63 of the 283 cytology specimens with available survival data were combined with a separate cohort of 428 surgical pathology specimens of lung adenocarcinoma.\n\nResultsThe proposed classification yielded significant associations between these molecular subtypes and clinical and prognostic features. We found better overall survival in patients who underwent surgery and had tumors enriched for EGFR mutations. Worse overall survival was associated with older age, stage IV disease, and tumors with comutations in KRAS and TP53. Interestingly, neither chemotherapy nor radiation therapy showed benefit to overall survival.\n\nConclusionsThe mutational status of EGFR, KRAS, and TP53 can be used to easily classify lung adenocarcinoma patients into six subtypes that show a relationship with prognosis, especially in patients who underwent surgery, and these subtypes are similar to classifications based on more complex genomic methods reported previously.
- organism: human
- assay: DNA methylation
- assay: whole-exome sequencing
- research focus: clustering
- approach: statistical model
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