Which melanoma patient carries a BRAF-mutation? A comparison of predictive models.
Ontology highlight
ABSTRACT: Background
In patients with advanced melanoma the detection of BRAF mutations is considered mandatory before the initiation of an expensive treatment with BRAF/MEK inhibitors. Sometimes it is difficult to perform such an analysis if archival tumor tissue is not available and fresh tissue has to be collected.Results
514 of 1170 patients (44%) carried a BRAF mutation. All models revealed age and histological subtype of melanoma as the two major predictive variables. Accuracy ranged from 0.65-0.71, being best in the random forest model. Sensitivity ranged 0.76-0.84, again best in the random forest model. Specificity was low in all models ranging 0.51-0.55.Methods
We collected the clinical data and mutational status of 1170 patients with advanced melanoma and established three different predictive models (binary logistic regression, classification and regression trees, and random forest) to forecast the BRAF status.Conclusions
Up to date statistical models are not able to predict BRAF mutations in an acceptable accuracy. The analysis of the mutational status by sequencing or immunohistochemistry must still be considered as standard of care.
SUBMITTER: Eigentler T
PROVIDER: S-EPMC5094988 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BRAF is a serine/threonine protein kinase activating the MAP kinase/ERK-signaling pathway. About 50 % of melanomas harbors activating BRAF mutations (over 90 % V600E). BRAFV600E has been implicated in different mechanisms underlying melanomagenesis, most of which due to the deregulated activation of the downstream MEK/ERK effectors. The first selective inhibitor of mutant BRAF, vemurafenib, after highly encouraging results of the phase I and II trial, was compared to dacarbazine in a phase III trial in treatment-naïve patients (BRIM-3). The study results showed a relative reduction of 63 % in risk of death and 74 % in risk of tumor progression. Considering all trials so far completed, median overall survival reached approximately 16 months for vemurafenib compared to less than 10 months for dacarbazine treatment. Vemurafenib has been extensively tested on melanoma patients expressing the BRAFV600E mutated form; it has been demonstrated to be also effective in inhibiting melanomas carrying the V600K mutation. In 2011, both FDA and EMA therefore approved vemurafenib for metastatic melanoma carrying BRAFV600 mutations. Some findings suggest that continuation of vemurafenib treatment is potentially beneficial after local therapy in a subset of patients with disease progression (PD). Among who continued vemurafenib >30 days after local therapy of PD lesion(s), a median overall survival was not reached, with a median follow-up of 15.5 months from initiation of BRAF inhibitor therapy. For patients who did not continue treatment, median overall survival from the time of disease progression was 1.4 months. A clinical phase I/II trial is evaluating the safety, tolerability and efficacy of vemurafenib in combination with the CTLA-4 inhibitor mAb ipilimumab. In the BRIM-7 trial vemurafenib is tested in association with GDC-0973, a potent and highly selective inhibitor of MEK1/2. Preliminary data seem to indicate that an additional inhibitor of mutated BRAF, GSK2118436, might be also active on a wider range of BRAF mutations (V600E-K-D-R); actually, treatment with such a compound is under evaluation in a phase III study among stage III-IV melanoma patients positive for BRAF mutations. Overall, BRAF inhibitors were well tolerated; common adverse events are arthralgia, rash, fatigue, alopecia, keratoacanthoma or cutaneous squamous-cell carcinoma, photosensitivity, nausea, and diarrhea, with some variants between different inhibitors.
| S-EPMC3391993 | biostudies-other
Project description:In melanoma, a number of specific genetic and genomic aberrations have been identified to be important in tumorigenesis. In particular, the mutant B-Raf proto-oncogene, Serine/Threonine kinase (BRAF) gene is the target of tailored therapy with kinase inhibitor molecules. Identification of the array of mutations in patients with melanoma will be useful in determining a genetic profile of the tumor with potential implications for treatment decisions. A rare aminoacidic insertion in codon 599 of the BRAF gene (c.1797_1798insACA, T599insT) was detected by using both direct (Sanger) sequencing and pyrosequencing techniques in a metastatic melanoma of a female elderly patient. As suggested in other clinical contexts including pilocytic astrocytoma, papillary thyroid carcinomas and anaplastic thyroid carcinomas, this unusual mutation may be associated with a modified spatial structure of activated P-loop, resulting in a constitutional activation of the BRAF protein. The patient died shortly following the test, thus no biological therapy was performed. Comparable data regarding treatment of melanoma patients with rare BRAF mutations is lacking, and the response to BRAF inhibitors requires further investigation.
| S-EPMC5795802 | biostudies-literature
Project description:Malignant melanoma (MM) is one of the deadliest skin cancers. BRAF mutation status plays a predominant role in the management of MM patients. The aim of this study was to compare BRAF mutational testing performed by conventional nucleotide sequencing approaches with either real-time polymerase chain reaction (rtPCR) or next-generation sequencing (NGS) assays in a real-life, hospital-based series of advanced MM patients. Consecutive patients with AJCC (American Joint Committee on Cancer) stage IIIC and IV MM from Sardinia, Italy, who were referred for molecular testing, were enrolled into the study. Initial screening was performed to assess the mutational status of the BRAF and NRAS genes, using the conventional methodologies recognized by the nationwide guidelines, at the time of the molecular classification, required by clinicians: at the beginning, Sanger-based sequencing (SS) and, after, pyrosequencing. The present study was then focused on BRAF mutation detecting approaches only. BRAF wild-type cases with available tissue and adequate DNA were further tested with rtPCR (Idylla™) and NGS assays. Globally, 319 patients were included in the study; pathogenic BRAF mutations were found in 144 (45.1%) cases examined with initial screening. The rtPCR detected 11 (16.2%) and 3 (4.8%) additional BRAF mutations after SS and pyrosequencing, respectively. NGS detected one additional BRAF-mutated case (2.1%) among 48 wild-type cases previously tested with pyrosequencing and rtPCR. Our study evidenced that rtPCR and NGS were able to detect additional BRAF mutant cases in comparison with conventional sequencing methods; therefore, we argue for the preferential utilization of the aforementioned assays (NGS and rtPCR) in clinical practice, to eradicate false-negative cases and improve the accuracy of BRAF detection.
| S-EPMC7464760 | biostudies-literature
Project description:BackgroundPhase 1 and 2 clinical trials of the BRAF kinase inhibitor vemurafenib (PLX4032) have shown response rates of more than 50% in patients with metastatic melanoma with the BRAF V600E mutation.MethodsWe conducted a phase 3 randomized clinical trial comparing vemurafenib with dacarbazine in 675 patients with previously untreated, metastatic melanoma with the BRAF V600E mutation. Patients were randomly assigned to receive either vemurafenib (960 mg orally twice daily) or dacarbazine (1000 mg per square meter of body-surface area intravenously every 3 weeks). Coprimary end points were rates of overall and progression-free survival. Secondary end points included the response rate, response duration, and safety. A final analysis was planned after 196 deaths and an interim analysis after 98 deaths.ResultsAt 6 months, overall survival was 84% (95% confidence interval [CI], 78 to 89) in the vemurafenib group and 64% (95% CI, 56 to 73) in the dacarbazine group. In the interim analysis for overall survival and final analysis for progression-free survival, vemurafenib was associated with a relative reduction of 63% in the risk of death and of 74% in the risk of either death or disease progression, as compared with dacarbazine (P<0.001 for both comparisons). After review of the interim analysis by an independent data and safety monitoring board, crossover from dacarbazine to vemurafenib was recommended. Response rates were 48% for vemurafenib and 5% for dacarbazine. Common adverse events associated with vemurafenib were arthralgia, rash, fatigue, alopecia, keratoacanthoma or squamous-cell carcinoma, photosensitivity, nausea, and diarrhea; 38% of patients required dose modification because of toxic effects.ConclusionsVemurafenib produced improved rates of overall and progression-free survival in patients with previously untreated melanoma with the BRAF V600E mutation. (Funded by Hoffmann-La Roche; BRIM-3 ClinicalTrials.gov number, NCT01006980.).
| S-EPMC3549296 | biostudies-literature
Project description:Although BRAF and MEK inhibitors have proven clinical benefits in melanoma, most patients develop resistance. We report a de novo MEK2-Q60P mutation and BRAF gain in a melanoma from a patient who progressed on the MEK inhibitor trametinib and did not respond to the BRAF inhibitor dabrafenib. We also identified the same MEK2-Q60P mutation along with BRAF amplification in a xenograft tumor derived from a second melanoma patient resistant to the combination of dabrafenib and trametinib. Melanoma cells chronically exposed to trametinib acquired concurrent MEK2-Q60P mutation and BRAF-V600E amplification, which conferred resistance to MEK and BRAF inhibitors. The resistant cells had sustained MAPK activation and persistent phosphorylation of S6K. A triple combination of dabrafenib, trametinib, and the PI3K/mTOR inhibitor GSK2126458 led to sustained tumor growth inhibition. Hence, concurrent genetic events that sustain MAPK signaling can underlie resistance to both BRAF and MEK inhibitors, requiring novel therapeutic strategies to overcome it.
| S-EPMC3956616 | biostudies-literature
Project description:The adaptive acquisition of resistance to BRAF and MEK inhibitor-based therapy is a common feature of melanoma cells and contributes to poor patient treatment outcomes. Leveraging insights from a proteomic study and publicly available transcriptomic data, we evaluated the predictive capacity of a gene panel corresponding to proteins differentially abundant between treatment-sensitive and treatment-resistant cell lines, deciphering predictors of treatment resistance and potential resistance mechanisms to BRAF/MEK inhibitor therapy in patient biopsy samples. From our analysis, a 13-gene signature panel, in both test and validation datasets, could identify treatment-resistant or progressed melanoma cases with an accuracy and sensitivity of over 70%. The dysregulation of HMOX1, ICAM, MMP2, and SPARC defined a BRAF/MEK treatment-resistant landscape, with resistant cases showing a >2-fold risk of expression of these genes. Furthermore, we utilized a combination of functional enrichment- and gene expression-derived scores to model and identify pathways, such as HMOX1-mediated mitochondrial stress response, as potential key drivers of the emergence of a BRAF/MEK inhibitor-resistant state in melanoma cells. Overall, our results highlight the utility of these genes in predicting treatment outcomes and the underlying mechanisms that can be targeted to reduce the development of resistance to BRAF/MEK targeted therapy.
| S-EPMC10178962 | biostudies-literature
Project description:Objectives/experimental design Samples eligible for this study (n=84) were obtained from lymph node specimens (Melanoma Institute Australia (MIA) Biospecimen Bank) in which macroscopic tumor was observed, obtained from patients believed to be without distant metastases at the time of tumor banking based on clinical examination and computerised axial tomographic scanning of the brain, chest, abdomen and pelvis. Specimens were macro-dissected at time of banking and subsequently reviewed to meet minimum criteria for tumor cell content (>80%) and amount of necrosis (<30%). Linked clinical and pathologic data were obtained from the MIA research database. mRNA expression profiling information in the same samples is available: GSE54467.
| S-ECPF-GEOD-59334 | biostudies-other
Project description:BRAF inhibitors (BRAFi) have led to clinical benefit in patients with melanoma. The development of a blood-based assay to detect and quantify BRAF levels in these patients has diagnostic, prognostic, and predictive capabilities that could guide treatment decisions. Blood BRAF(V600E) detection and quantification were performed on samples from 128 patients with stage II (19), III (67), and IV (42) melanoma. Tissue BRAF analysis was performed in all patients with stage IV disease and in selected patients with stage II and III disease. Clinical outcomes were correlated to initial BRAF levels as well as BRAF level dynamics. Serial analysis was performed on 17 stage IV melanoma patients treated with BRAFi and compared with tumor measurements by RECIST. The assay was highly sensitive (96%) and specific (95%) in the stage IV setting, using a blood level of 4.8 pg as "positive." BRAF levels typically decreased following BRAFi. A subset of these patients (5) had an increase in BRAF(V600E) values 42 to 112 days before clinical or radiographic disease progression (PD). From 86 patients with resected, stage II or III melanoma, 39 had evidence of disease relapse (45.3%). Furthermore, BRAF mutation in the blood after surgical resection in these patients was not associated with a difference in relapse risk, although tissue BRAF status was only available for a subset of patients. In summary, we have developed a highly sensitive and specific, blood-based assay to detect BRAF(V600) mutation in patients with melanoma.
| S-EPMC4258469 | biostudies-literature
Project description:BRAF mutation plays an important role in the pathogenesis and progression of melanoma and is correlated to the prognosis of melanoma patients. However, fewer studies have attempted to develop a BRAF mutation-associated gene risk model for predicting the prognosis of melanoma. The current research explores BRAF mutation-related biological features in melanoma and establishes a prognostic signature. First, we identified three significantly enriched KEGG pathways (glycosphingolipid biosynthesis - ganglio series, ether lipid metabolism, and glycosaminoglycan biosynthesis - keratan sulfate) and corresponding genes in the BRAF mutant group by gene set enrichment analysis. We then developed a prognostic signature based on 7 BRAF-associated genes (PLA2G2D, FUT8, PLA2G4E, PLA2G5, PLA2G1B, B3GNT2, and ST3GAL5) and assessed its prediction accuracy using ROC curve analysis. Finally, the nomogram was established according to the prognostic signature and independent clinical characteristics to predict the survival of melanoma patients. Furthermore, we found higher proportions of naive B cells, plasma cells, CD8 T cells, CD4 memory-activated T cells, and regulatory T cells in the low-risk group. Whereas lower proportions of M0, M1, and M2 macrophages and resting NK cells were observed in the high-risk group. The analysis also showed a significantly higher expression of immune checkpoint molecules (PD-1, PD-L1, CTLA4, BTLA, CD28, CD80, CD86, HAVCR2, ICOS, LAG3, and TIGIT) in the low-risk group. Our results provide novel insights into the effect of BRAF mutation on melanoma growth and indicate a promising direction toward immunotherapy and precision medicine in melanoma patients.
| S-EPMC10189240 | biostudies-literature
Project description:We introduce an algorithm for learning patient-specific models from clinical data to predict outcomes. Patient-specific models are influenced by the particular history, symptoms, laboratory results, and other features of the patient case at hand, in contrast to the commonly used population-wide models that are constructed to perform well on average on all future cases. The patient-specific algorithm uses Markov blanket (MB) models, carries out Bayesian model averaging over a set of models to predict the outcome for the patient case at hand, and employs a patient-specific heuristic to locate a set of suitable models to average over. We evaluate the utility of using a local structure representation for the conditional probability distributions in the MB models that captures additional independence relations among the variables compared to the typically used representation that captures only the global structure among the variables. In addition, we compare the performance of Bayesian model averaging to that of model selection. The patient-specific algorithm and its variants were evaluated on two clinical datasets for two outcomes. Our results provide support that the performance of an algorithm for learning patient-specific models can be improved by using a local structure representation for MB models and by performing Bayesian model averaging.
| S-EPMC2933959 | biostudies-literature