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Genomic and proteomic profiles reveal the association of gelsolin to TP53 status and bladder cancer progression.

ABSTRACT: Bladder cancer transformation and immortalization require the inactivation of key regulatory genes, including TP53. Genotyping of a large cohort of bladder cancer patients (n = 256) using the TP53 GeneChip showed mutations in 103 cases (40.2%), the majority of them mapping to the DNA-binding core domain. TP53 mutation status was significantly associated with tumor stage (P = 0.0001) and overall survival for patients with advanced disease (P = 0.01). Transcript profiling using oligonucleotide arrays was performed on a subset of these cases (n = 46). Supervised analyses identified genes differentially expressed between invasive bladder tumors with wild-type (n = 24) and mutated TP53 (n = 22). Pathway analyses of top-ranked genes supported the central role of TP53 in the functional network of such gene patterns. A proteomic strategy using reverse phase arrays with protein extracts of bladder cancer cell lines validated the association of identified differentially expressed genes, such as gelsolin, to TP53 status. Immunohistochemistry on tissue microarrays (n = 294) revealed that gelsolin was associated with tumor stage and overall survival, correlating positively with TP53 status in a subset of these patients. This study further reveals that TP53 mutations are frequent events in bladder cancer progression and identified gelsolin related to TP53 status, tumor staging, and clinical outcome by independent high-throughput strategies.

SUBMITTER: Sanchez-Carbayo M

PROVIDER: S-EPMC2043525 | biostudies-literature | 2007 Nov

REPOSITORIES: biostudies-literature

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Genomic and proteomic profiles reveal the association of gelsolin to TP53 status and bladder cancer progression.

Sanchez-Carbayo Marta M Socci Nicholas D ND Richstone Lee L Corton Marta M Behrendt Nille N Wulkfuhle Julia J Bochner Bernard B Petricoin Emmanuel E Cordon-Cardo Carlos C

The American journal of pathology 20071101 5

Bladder cancer transformation and immortalization require the inactivation of key regulatory genes, including TP53. Genotyping of a large cohort of bladder cancer patients (n = 256) using the TP53 GeneChip showed mutations in 103 cases (40.2%), the majority of them mapping to the DNA-binding core domain. TP53 mutation status was significantly associated with tumor stage (P = 0.0001) and overall survival for patients with advanced disease (P = 0.01). Transcript profiling using oligonucleotide arr ...[more]

PMID: 17982131

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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:BackgroundTargeting differentially activated or perturbed tumour pathways is the key idea in individualised cancer therapy, which is emerging as an important option in treating cancers with poor prognostic profiles. TP53 mutation status is known as a core determinant of survival in breast cancer. The pathways disrupted in association with TP53 mutation status in tumours are not well characterised.MethodIn this study, we stratify breast cancers based on their TP53 mutation status and identify the set of dysregulated tumorigenic pathways and corresponding candidate driver genes using breast cancer gene expression profiles. Expressions of these genes were evaluated for their effect on patient survival first in univariate models, followed by multivariate models with TP53 status as a covariate.ResultsThe most strongly differentially enriched pathways between breast cancers stratified by TP53 mutation status include in addition to TP53 signalling, several known cancer pathways involved in renal, prostate, pancreatic, colorectal, lung and other cancers, and signalling pathways such as calcium signalling, MAPK, ERBB and vascular endothelial growth factor (VEGF) signalling pathways. We found that mutant TP53 in conjunction with active estrogen receptor (ER) signalling significantly influence survival. We also found that upregulation of VEGFA mRNA levels in association with active ER signalling is a significant marker for poor survival, even in the presence of wild-type TP53.ConclusionMutation status of TP53 in breast cancer involves wide ranging derangement of several pathways. Among the candidate genes of the significantly deranged pathways, we identified VEGFA expression as an important marker of survival even when controlled by TP53 mutation status. Interestingly, independent of the TP53 mutation status, the survival effect of VEGFA was found significant in patients with active ER signalling (ER/PgR+), but not in those with ER/PgR- status. Therefore, we propose more studies to focus on the role of complex interplay between TP53, ER and VEGF signalling from therapeutic and prognostic context in breast cancer.

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.

Project description:BackgroundChinese Bama Yao Autonomous County is a well-known longevity region in the world. In the past 30 years, population and genome studies were undertaken to investigate the secret of longevity and showed that longevity is the result of a combination of multiple factors, such as genetic, environmental and other causes. In this study, characteristics of the blood plasma proteomic and autoantibody profiles of people from Bama longevity family were investigated.MethodsSixty-six plasma donors from Chinese Bama longevity area were recruited in this study. Thirty-three offsprings of longevous families were selected as case studies (Longevous group) and 33 ABO (blood type), age, and gender-matched subjects from non-longevous families were selected as controls (Normal group). Each group contains 3 biological replicates. Tandem mass tag-based proteomic technique was used to investigate the differentially expressed plasma proteins between the two groups. The auto-reactive IgG antibody profiles of the 3 pooled samples in each group were revealed by human proteome microarrays with 17,000 recombinant human proteins.ResultsFirstly, 525 plasma proteins were quantified and 12 proteins were discovered differentially expressed between the two groups. Secondly, more than 500 proteins were recognized by plasma antibodies, 14 proteins ware differentially reacted with the autoantibodies in the two groups. Bioinformatics analysis showed some of the differential proteins and targeted autoantigens were involved in cancer, cardiovascular disease and immunity.ConclusionsProteomic and autoantibody profiles varied between the offspring of longevous and normal families which are from the same area and shared the same environmental factors. The identified differences were reported to be involved in several physiological and pathological pathways. The identified proteins will contribute to a better understanding of the proteomic characteristics of people from Bama longevous area and a revelation of the molecular mechanisms of longevity.

Project description:Background TP53 mutations are associated with poor outcome for patients with endometrial carcinoma (EC). However, to date, there have been no studies focused on the construction of TP53 mutational status-associated signature in EC. In this study, we aim to conduct a TP53 mutation-associated prognostic gene signature for EC. Methods Hence, we explored the mutational landscape of TP53 in patients with EC based on the simple nucleotide variation data downloaded from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and least absolute shrinkage and selection operator (LASSO)–Cox analysis was used to establish TP53 mutation-associated prognostic gene signature. The overall survival rate between the high-risk and low-risk groups was compared by the Kaplan–Meier (K-M) method. Results We found that the TP53 mutation was associated with poor outcome, older age, lower BMI, and higher grade and stage of EC in patients. A TP53 mutational status-associated signature was established based on transcriptome profiling data. Moreover, the patients in TCGA database were categorized into high- and low-risk groups. Kaplan–Meier (K-M) analysis indicated that the patients in the high-risk group have poor survival outcome. Furthermore, receiver operating characteristic (ROC) curves confirmed the robust prognostic prediction efficiency of the TP53 mutational status-associated signature. Finally, the prognostic ability was successfully verified in the other two datasets from cBioPortal database as well as in 60 clinical specimens. Univariate (hazard ratio (HR) = 1.041, 95%CI = 1.031–1.051, p < 0.001) and multivariate (hazard ratio (HR) = 1.029, 95%CI = 1.018–1.040, p < 0.001) Cox regression analyses indicated that the TP53 mutational status-associated signature could be used as an independent prognostic factor for EC patients. Conclusion In summary, our research constructed a powerful TP53 mutational status-associated signature that could be a potential novel prognostic biomarker and therapeutic target for EC.

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Genomic and proteomic profiles reveal the association of gelsolin to TP53 status and bladder cancer progression.

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Genomic and proteomic profiles reveal the association of gelsolin to TP53 status and bladder cancer progression.

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