Variables that influence BRAF mutation probability: A next-generation sequencing, non-interventional investigation of BRAFV600 mutation status in melanoma

• Published in: PloS one 2017-11, Vol.12 (11), p.e0188602-e0188602
• Main Authors: Gaiser, Maria Rita, Skorokhod, Alexander, Gransheier, Diana, Weide, Benjamin, Koch, Winfried, Schif, Birgit, Enk, Alexander, Garbe, Claus, Bauer, Jürgen
• Format: Article
• Language: English
• Subjects: Age; Biology and Life Sciences; Cancer therapies; Clinical medicine; Complications and side effects; Deoxyribonucleic acid; Dermatology; Diagnosis; DNA; DNA sequencing; Exposure; Gene mutations; Genetic aspects; Kinases; Medical prognosis; Medicine and Health Sciences; Melanoma; Metastasis; Methods; Multivariate analysis; Mutation; Nucleotide sequencing; Patients; Physical Sciences; Proteins; Regression analysis; Reproducibility; Research and Analysis Methods; Samples; Skin cancer; Statistical analysis; Statistical methods; Statistics; Ultraviolet radiation
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0188602

The incidence of melanoma, particularly in older patients, has steadily increased over the past few decades. Activating mutations of BRAF, the majority occurring in BRAFV600, are frequently detected in melanoma; however, the prognostic significance remains unclear. This study aimed to define the probability and distribution of BRAFV600 mutations, and the clinico-pathological factors that may affect BRAF mutation status, in patients with advanced melanoma using next-generation sequencing. This was a non-interventional, retrospective study of BRAF mutation testing at two German centers, in Heidelberg and Tübingen. Archival tumor samples from patients with histologically confirmed melanoma (stage IIIB, IIIC, IV) were analyzed using PCR amplification and deep sequencing. Clinical, histological, and mutation data were collected. The statistical influence of patient- and tumor-related characteristics on BRAFV600 mutation status was assessed using multiple logistic regression (MLR) and a prediction profiler. BRAFV600 mutation status was assessed in 453 samples. Mutations were detected in 57.6% of patients (n = 261), with 48.1% (n = 102) at the Heidelberg site and 66.0% (n = 159) at the Tübingen site. The decreasing influence of increasing age on mutation probability was quantified. A main effects MLR model identified age (p = 0.0001), center (p = 0.0004), and melanoma subtype (p = 0.014) as significantly influencing BRAFV600 mutation probability; ultraviolet (UV) exposure showed a statistical trend (p = 0.1419). An interaction model of age versus other variables showed that center (p