Project description:BackgroundWe analyzed whether co-occurring mutations influence the outcome of systemic therapy in ALK-rearranged non-small-cell lung cancer (NSCLC).Patients and methodsALK-rearranged stage IIIB/IV NSCLC patients were analyzed with next-generation sequencing and fluorescence in situ hybridization analyses on a centralized diagnostic platform. Median progression-free survival (PFS) and overall survival (OS) were determined in the total cohort and in treatment-related sub-cohorts. Cox regression analyses were carried out to exclude confounders.ResultsAmong 216 patients with ALK-rearranged NSCLC, the frequency of pathogenic TP53 mutations was 23.8%, while other co-occurring mutations were rare events. In ALK/TP53 co-mutated patients, median PFS and OS were significantly lower compared with TP53 wildtype patients [PFS 3.9 months (95% CI: 2.4-5.6) versus 10.3 months (95% CI: 8.6-12.0), P < 0.001; OS 15.0 months (95% CI: 5.0-24.9) versus 50.0 months (95% CI: 22.9-77.1), P = 0.002]. This difference was confirmed in all treatment-related subgroups including chemotherapy only [PFS first-line chemotherapy 2.6 months (95% CI: 1.3-4.1) versus 6.2 months (95% CI: 1.8-10.5), P = 0.021; OS 2.0 months (95% CI: 0.0-4.6) versus 9.0 months (95% CI: 6.1-11.9), P = 0.035], crizotinib plus chemotherapy [PFS crizotinib 5.0 months (95% CI: 2.9-7.2) versus 14.0 months (95% CI: 8.0-20.1), P < 0.001; OS 17.0 months (95% CI: 6.7-27.3) versus not reached, P = 0.049] and crizotinib followed by next-generation ALK-inhibitor [PFS next-generation inhibitor 5.4 months (95% CI: 0.1-10.7) versus 9.9 months (95% CI: 6.4-13.5), P = 0.039; OS 7.0 months versus 50.0 months (95% CI: not reached), P = 0.001).ConclusionsIn ALK-rearranged NSCLC co-occurring TP53 mutations predict an unfavorable outcome of systemic therapy. Our observations encourage future research to understand the underlying molecular mechanisms and to improve treatment outcome of the ALK/TP53 co-mutated subgroup.

Project description:Background: Gene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene, in a group of breast cancer patients with long-term (12-16 years) follow-up. Methods: The clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using TTGE and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples. Results: Both univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. The TP53 mutation status showed strong association with the ?basal-like? and ?ERBB2+? gene expression subgroups, and tumors with mutation had a characteristic gene expression pattern. Conclusions: TP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease. Experiment set consisting of 80 primary breast carcinomas collected at Ulleval University Hospital (ULL-samples), Oslo, Norway from 1990-94, and one normal sample from breast reduction surgery.

Project description:IntroductionGene expression profiling of breast carcinomas has increased our understanding of the heterogeneous biology of this disease and promises to impact clinical care. The aim of this study was to evaluate the prognostic value of gene expression-based classification along with established prognostic markers and mutation status of the TP53 gene (tumour protein p53) in a group of breast cancer patients with long-term (12 to 16 years) follow-up.MethodsThe clinical and histopathological parameters of 200 breast cancer patients were studied for their effects on clinical outcome using univariate/multivariate Cox regression. The prognostic impact of mutations in the TP53 gene, identified using temporal temperature gradient gel electrophoresis and sequencing, was also evaluated. Eighty of the samples were analyzed for gene expression using 42 K cDNA microarrays and the patients were assigned to five previously defined molecular expression groups. The strength of the gene expression based classification versus standard markers was evaluated by adding this variable to the Cox regression model used to analyze all samples.ResultsBoth univariate and multivariate analysis showed that TP53 mutation status, tumor size and lymph node status were the strongest predictors of breast cancer survival for the whole group of patients. Analyses of the patients with gene expression data showed that TP53 mutation status, gene expression based classification, tumor size and lymph node status were significant predictors of survival. Breast cancer cases in the 'basal-like' and 'ERBB2+' gene expression subgroups had a very high mortality the first two years, while the 'highly proliferating luminal' cases developed the disease more slowly, showing highest mortality after 5 to 8 years. The TP53 mutation status showed strong association with the 'basal-like' and 'ERBB2+' subgroups, and tumors with mutation had a characteristic gene expression pattern.ConclusionTP53 mutation status and gene-expression based groups are important survival markers of breast cancer, and these molecular markers may provide prognostic information that complements clinical variables. The study adds experience and knowledge to an ongoing characterization and classification of the disease.

Dataset Information

Analysis of TP53 mutation status in human cancer cell lines: a reassessment.

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Analysis of TP53 mutation status in human cancer cell lines: a reassessment.

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