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Identification of non-actionable mutations with prognostic and predictive value in patients with advanced or metastatic non-small cell lung cancer

Mariano Provencio, Diego Pérez-Parente, Sara Olson, Haroon Hasan, Begoña Campos, Delvys Rodríguez‐Abreu, M. Piqueras, Navdeep Pal, Samantha Wilkinson, Esther Vilas, Pedro Ruiz‐Gracia, Manuel Cobo

2024Clinical & Translational Oncology9 citationsDOIOpen Access PDF

Abstract

INTRODUCTION: Lung cancer is one of the most prevalent cancers and the leading cause of cancer death. Advanced non-small cell lung cancer (aNSCLC) patients frequently harbor mutations that impact their survival outcomes. There are limited data regarding the prognostic and predictive significance of these mutations on survival outcomes in the real-world setting. METHODS: This observational retrospective study analyzed de-identified electronic medical records from the Flatiron Health Clinico-Genomic and FoundationCore® databases to identify patients with aNSCLC who initiated first-line immune checkpoint inhibitors (ICI; alone or in combination) or chemotherapy under routine care between 2016 and 2021. The primary objectives were to assess the prevalence of non-actionable mutations and to determine their association with overall survival (OS). Real-world progression-free survival (rwPFS) and real-world response (rwR) were investigated as secondary exploratory outcomes. RESULTS: Based on an assessment of 185 non-actionable mutations in 2999 patients, the most prevalent mutations were TP53 (70%), KRAS (42%), CDKN2A/B (31%), and STK11 (21%). STK11, KEAP1, and CDKN2A/B mutations were significantly associated with lower rwR, shorter rwPFS and OS. KRAS mutations were clinically associated with shorter rwPFS in CIT-treated patients. Subgroup analysis revealed that fast progressors were significantly more likely to harbor STK11, KEAP1, and CDKN2A/B mutations. Accordingly, long-term survivors (LTS) showed a significantly lower prevalence of these mutations. CONCLUSION: Our results provide evidence on the prognostic value of STK11, KEAP1, and CDKN2A/B mutations in patients with aNSCLC. Further research is required to better understand the implications of these findings on patient management and future trial design and treatment selection.

Topics & Concepts

MedicinePredictive valueIdentification (biology)OncologyInternal medicineCancerLung cancerValue (mathematics)LungBioinformaticsMachine learningBiologyComputer scienceBotanyLung Cancer Treatments and MutationsCancer Immunotherapy and BiomarkersLung Cancer Research Studies
Identification of non-actionable mutations with prognostic and predictive value in patients with advanced or metastatic non-small cell lung cancer | Litcius