Dataset Information

The Relationship between TP53 Gene Status and Carboxylesterase 2 Expression in Human Colorectal Cancer.

ABSTRACT: Irinotecan (CPT-11) is an anticancer prodrug that is activated by the carboxylesterase CES2 and has been approved for the treatment of many types of solid tumors, including colorectal cancer. Recent studies with cell lines show that CES2 expression is regulated by the tumor suppressor protein p53. However, clinical evidence for this regulatory mechanism in cancer is lacking. In this study, we examined the relationship between TP53 gene status and CES2 expression in human colorectal cancer. Most colorectal cancer specimens (70%; 26 of 37) showed lower CES2 mRNA levels (?1.5-fold lower) than the adjacent normal tissue, and only 30% (12 of 37) showed similar (<1.5-fold lower) or higher CES2 mRNA levels. However, TP53 gene sequencing revealed no relationship between CES2 downregulation and TP53 mutational status. Moreover, while colorectal cancer cells expressing wild-type p53 exhibited p53-dependent upregulation of CES2, PRIMA-1^MET, a drug that restores the transcriptional activity of mutant p53, failed to upregulate CES2 expression in cells with TP53 missense mutations. These results, taken together, suggest that CES2 mRNA expression is decreased in human colorectal cancer independently of p53.

SUBMITTER: Ishimine M

PROVIDER: S-EPMC5831679 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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The Relationship between <i>TP53</i> Gene Status and Carboxylesterase 2 Expression in Human Colorectal Cancer.

Ishimine Momoko M Lee Hyeon-Cheol HC Nakaoka Hirofumi H Orita Hajime H Kobayashi Toshiyuki T Mizuguchi Konomi K Endo Mikumi M Inoue Ituro I Sato Koichi K Yokomizo Takehiko T

Disease markers 20180131

Irinotecan (CPT-11) is an anticancer prodrug that is activated by the carboxylesterase CES2 and has been approved for the treatment of many types of solid tumors, including colorectal cancer. Recent studies with cell lines show that CES2 expression is regulated by the tumor suppressor protein p53. However, clinical evidence for this regulatory mechanism in cancer is lacking. In this study, we examined the relationship between <i>TP53</i> gene status and CES2 expression in human colorectal cancer ...[more]

PMID: 29651325

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Project description:TP53 mutations are a poor prognostic factor in breast cancers. This study sets out to identify the gene set that determine expression signature of the TP53 status (TP53 signature) and to correlate it with clinical outcome. Using comprehensive expression analysis and DNA sequencing of the TP53 gene in 38 Japanese breast cancer patients, we have isolated a gene set of 33 genes from differentially expressed genes in the learning set (n=26), depending on the TP53 status. Predictive accuracy of TP53 status by gene expression profile was 83.3% in the test set (n=12). As independent external datasets, two published datasets were introduced for validation of TP53 status prediction (251 Swedish samples) and survival analysis (both the Swedish and 295 Dutch samples). TP53 signature has the ability to predict recurrence-free survival (RFS) of 29 stage I and II Japanese breast cancers (log rank, P = 0.032), and RFS, overall survival of two independently published datasets (log rank, both P < 0.0001). Multivariate analysis has shown an independent and significant prognostic factor with a hazard ratio (HR) for recurrence and survival in two external datasets (P < 0.0001). The TP53 signature is also a strong prognostic factor in the subgroups: estrogen-receptor positive, lymph node (LN) positive and negative, intermediate/high risk in St. Gallen criteria, and high risk in National Cancer Institute (NCI) criteria (log rank, P < 0.0001). TP53 signature is a reliable and independent predictor of the outcome of disease in operated breast cancer. Experiment Overall Design: Microarray hybridizations (Agilent: Whole Human Genome Oligo Microarray; 41k unique probe) were carried out with 1μg Cy3 labeled cRNA and 1 μg Cy5 labeled cRNA, both prepared from each sample and reference pool, respectively. Experiment Overall Design: Fluorescent intensities of scanned images were quantified by ArrayVision Ver.8 rev.4 (Imaging research). Experiment Overall Design: The gene expression data was quantified and analyzed by GeneSpring 6.2 (Silicon Genetics). To identify the TP53 status predictor gene set, a Wilcoxon rank sum test along with Benjamini and Hochberg false discovery rate (FDR) was used.

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

The Relationship between TP53 Gene Status and Carboxylesterase 2 Expression in Human Colorectal Cancer.

Publications

The Relationship between <i>TP53</i> Gene Status and Carboxylesterase 2 Expression in Human Colorectal Cancer.

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