Genetic Profiling of Advanced Melanoma: Candidate Mutations for Predicting Sensitivity and Resistance to Targeted Therapy
Year: 2020
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Molecularly targeted therapy has revolutionized the treatment of advanced melanoma. However, despite its high efficiency, a majority of patients experience relapse within 1 year of treatment because of acquired resistance, and approximately 10-25% patients gain no benefit from these agents owing to intrinsic resistance. This is mainly caused by the genetic heterogeneity of melanoma cells. OBJECTIVE: We aimed to validate the predictive significance of selected genes in advanced melanoma patients before treatment with BRAF/MEK inhibitors. PATIENTS AND METHODS: Archival DNA derived from 37 formalin-fixed paraffin-embedded pre-treatment advanced melanoma samples of patients treated with targeted therapy was used for next-generation sequencing analysis using the Ion Torrent platform. The AmpliSeq Custom Panel comprised coding sequences or hot spots of 23 melanoma genes: ATM, BRAF, CDK4, CDKN2A, CTNNB1, EGFR, HOXD8, HRAS, IDH1, KIT, KRAS, MAP3K8, MAP2K1, MAP2K2, MITF, MYC, NF1, NRAS, PAX5, PIK3R1, PTEN, RAC1, and RB1. The sequences were evaluated for genomic alterations and further validated using Sanger sequencing. RESULTS: Our analysis revealed non-BRAF genetic alterations in 28 out of 37 samples (75.7%). Genetic changes were identified in PTEN, CDK4, CDKN2A, CTNNB1, EGFR, HOXD8, HRAS, KIT, MAP2K1, MAP2K2, MITF, MYC, NF1, PAX5, RAC1, and RB1. Fifteen known pathogenic mutations (single nucleotide variants or indels) and 11 variants of unknown significance were detected. Statistical analysis revealed an association between the presence of pathogenic mutations and time to progression during treatment with combination therapy. CONCLUSIONS: ) in the generation of resistance to BRAF/MEK inhibitors should be further investigated.
Source: Targeted Oncology
Language: English
Topic: Melanoma and MAPK Pathways
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: hybrid
Estimated APC paid: $3,860
Funder: Narodowym Centrum Nauki
Award: G6401455694
OpenAlex ID: W3000984240
