BRAF mutation testing in melanoma: results from a German observational multicenter study.

Quality control of BRAF mutation testing methods used in routine practice is crucial for optimal treatment selection. In this prospective study, we assessed the impact of patient/sample characteristics on BRAF mutation testing results in patients with melanoma, during clinical practice. Data were collected on routine testing practices and documented mutation status in patients with melanoma stages IIIB, IIIC, or IV across 28 diagnostic pathology centers in Germany. Patient/sample data collected included: patient age, location of primary melanoma and metastases, origin of sample, melanoma subtype, and quality of tissue. Statistical influence of patient/sample characteristics on BRAF mutation rate was assessed using multiple logistic regression analyses and statistical models developed to predict the probability of BRAF mutations for individual patient cohorts. Data/samples from 642 patients with melanoma were analyzed. BRAF mutations were documented in 241/642 patients (37.5%). The primary statistical model to predict BRAF mutation rates included: age (continuous), origin of sample, method of mutation analysis, and quality of tissue. Analyses of post hoc collected data identified major deviations between documented mutation rates included in this study vs. routinely recorded mutation rates for three centers. When samples from these centers were excluded, the influence of testing method was no longer statistically significant. The final model included patient age, origin of sample (including metastasis location), and quality of tissue. Once validated in an independent population, this type of model could allow pathology centers to compare the performance of their testing methods with what would be expected based on patient, tumor, and sample characteristics.

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

BACKGROUND: 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. MATERIALS AND METHODS: 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. RESULTS: 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<0.0001) and melanoma subtype (p = 0.0038) significantly influenced BRAF mutation probability; age had a statistically significant effect only as part of an interaction with both UV exposure (p = 0.0110) and melanoma subtype (p = 0.0134). CONCLUSIONS: This exploratory study highlights that testing center, melanoma subtype, and age in combination with UV exposure and melanoma subtype significantly influence BRAFV600 mutation probability in patients with melanoma. Further validation of this model, in terms of reproducibility and broader relevance, is required.

SOCS1 mutation subtypes predict divergent outcomes in diffuse large B-Cell lymphoma (DLBCL) patients.

Suppressor of cytokine signaling 1 (SOCS1) is frequently mutated in primary mediastinal and diffuse large B-cell lymphomas (DLBCL). Currently, the prognostic relevance of these mutations in DLBCL is unknown. To evaluate the value of the SOCS1 mutation status as a prognostic biomarker in DLBCL patients, we performed full-length SOCS1 sequencing in tumors of 154 comprehensively characterized DLBCL patients. We identified 90 SOCS1 mutations in 16% of lymphomas. With respect to molecular consequences of mutations, we defined two distinct subtypes: those with truncating (major) and those with non-truncating mutations (minor), respectively. The SOCS1 mutated subgroup or the minor/major subtypes cannot be predicted on clinical grounds; however, assignment of four established gene-expression profile-based classifiers revealed significant associations of SOCS1 major cases with germinal center and specific pathway activation pattern signatures. Above all, SOCS1 major cases have an excellent overall survival, even better than the GCB-like subgroup. SOCS1 minor cases had a dismal survival, even worse than the ABC gene signature group. The SOCS1 mutation subsets retained prognostic significance in uni- and multivariate analyses. Together our data indicate that assessment of the SOCS1 mutation status is a single gene prognostic biomarker in DLBCL.