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Myc promoter-binding protein-1 (MBP-1) is a novel potential prognostic marker in invasive ductal breast carcinoma.

ABSTRACT: BACKGROUND: Alpha-enolase is a glycolytic enzyme that catalyses the formation of phosphoenolpyruvate in the cell cytoplasm. ?-Enolase and the predominantly nuclear Myc promoter-binding protein-1 (MBP-1) originate from a single gene through the alternative use of translational starting sites. MBP-1 binds to the P2 c-myc promoter and competes with TATA-box binding protein (TBP) to suppress gene transcription. Although several studies have shown an antiproliferative effect of MBP-1 overexpression on several human cancer cells, to date detailed observations of ?-enolase and MBP-1 relative expression in primary tumors versus normal tissues and their correlation with clinicopathological features have not been undertaken. METHODOLOGY AND FINDINGS: We analyzed ?-enolase and MBP-1 expression in normal breast epithelium and primary invasive ductal breast carcinoma (IDC) from 177 patients by Western blot and immunohistochemical analyses, using highly specific anti-?-enolase monoclonal antibodies. A significant increase in the expression of cytoplasmic ?-enolase was observed in 98% of the tumors analysed, compared to normal tissues. Nuclear MBP-1 was found in almost all the normal tissues while its expression was retained in only 35% of the tumors. Statistically significant associations were observed among the nuclear expression of MBP-1 and ErbB2 status, Ki-67 expression, node status and tumor grade. Furthermore MBP-1 expression was associated with good survival of patients with IDC. CONCLUSIONS: MBP-1 functions in repressing c-myc gene expression and the results presented indicate that the loss of nuclear MBP-1 expression in a large number of IDC may be a critical step in the development and progression of breast cancer and a predictor of adverse outcome. Nuclear MBP-1 appears to be a novel and valuable histochemical marker with potential prognostic value in breast cancer.

SUBMITTER: Lo Presti M

PROVIDER: S-EPMC2944896 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Myc promoter-binding protein-1 (MBP-1) is a novel potential prognostic marker in invasive ductal breast carcinoma.

Lo Presti Mariavera M Ferro Arianna A Contino Flavia F Mazzarella Claudia C Sbacchi Silvia S Roz Elena E Lupo Carmelo C Perconti Giovanni G Giallongo Agata A Migliorini Paola P Marrazzo Antonio A Feo Salvatore S

PloS one 20100923 9

<h4>Background</h4>Alpha-enolase is a glycolytic enzyme that catalyses the formation of phosphoenolpyruvate in the cell cytoplasm. α-Enolase and the predominantly nuclear Myc promoter-binding protein-1 (MBP-1) originate from a single gene through the alternative use of translational starting sites. MBP-1 binds to the P2 c-myc promoter and competes with TATA-box binding protein (TBP) to suppress gene transcription. Although several studies have shown an antiproliferative effect of MBP-1 overexpre ...[more]

PMID: 20886042

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Project description:BackgroundInvasive ductal carcinoma (IDC) is a common pathological type of breast cancer that is characterized by high malignancy and rapid progression. Upregulation of glycolysis is a hallmark of tumor growth, and correlates with the progression of breast cancer. We aimed to establish a model to predict the prognosis of patients with breast IDC based on differentially expressed glycolysis-related genes (DEGRGs).MethodsTranscriptome data and clinical data of patients with breast IDC were from The Cancer Genome Atlas (TCGA). Glycolysis-related gene sets and pathways were from the Molecular Signatures Database (MSigDB). DEGRGs were identified by comparison of tumor tissues and adjacent normal tissues. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to screen for DEGRGs with prognostic value. A risk-scoring model based on DEGRGs related to prognosis was constructed. Receiver operating characteristic (ROC) analysis and calculation of the area under the curve (AUC) were used to evaluate the performance of the model. The model was verified in different clinical subgroups using an external dataset (GSE131769). A nomogram that included clinical indicators and risk scores was established. Gene function enrichment analysis was performed, and a protein-protein interaction network was developed.ResultsWe analyzed data from 772 tumors and 88 adjacent normal tissues from the TCGA database and identified 286 glycolysis-related genes from the MSigDB. There were 185 DEGRGs. Univariate Cox regression and LASSO regression indicated that 13 of these genes were related to prognosis. A risk-scoring model based on these 13 DEGRGs allowed classification of patients as high-risk or low-risk according to median score. The duration of overall survival (OS) was longer in the low-risk group (P < 0.001), and the AUC was 0.755 for 3-year OS and 0.726 for 5-year OS. The results were similar when using the GEO data set for external validation (AUC for 3-year OS: 0.731, AUC for 5-year OS: 0.728). Subgroup analysis showed there were significant differences in OS among high-risk and low-risk patients in different subgroups (T1-2, T3-4, N0, N1-3, M0, TNBC, non-TNBC; all P < 0.01). The C-index was 0.824, and the AUC was 0.842 for 3-year OS and 0.808 for 5-year OS from the nomogram. Functional enrichment analysis demonstrated the DEGRGs were mainly involved in regulating biological functions.ConclusionsOur prognostic model, based on 13 DEGRGs, had excellent performance in predicting the survival of patients with IDC of the breast. These DEGRGs appear to have important biological functions in the progression of this cancer.

Project description:AbstractThe tumor microenvironment (TME) plays an important role in the development of breast cancer. Due to limitations in experimental conditions, the molecular mechanism of TME in breast cancer has not yet been elucidated. With the development of bioinformatics, the study of TME has become convenient and reliable.Gene expression and clinical feature data were downloaded from The Cancer Genome Atlas database and the Molecular Taxonomy of Breast Cancer International Consortium database. Immune scores and stromal scores were calculated using the Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data algorithm. The interaction of genes was examined with protein-protein interaction and co-expression analysis. The function of genes was analyzed by gene ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes analysis and gene set enrichment analysis. The clinical significance of genes was assessed with Kaplan-Meier analysis and univariate/multivariate Cox regression analysis.Our results showed that the immune scores and stromal scores of breast invasive ductal carcinoma (IDC) were significantly lower than those of invasive lobular carcinoma. The immune scores were significantly related to overall survival of breast IDC patients and both the immune and stromal scores were significantly related to clinical features of these patients. According to the level of immune/stromal scores, 179 common differentially expressed genes and 5 hub genes with prognostic value were identified. In addition, the clinical significance of the hub genes was validated with data from the molecular taxonomy of breast cancer international consortium database, and gene set enrichment analysis analysis showed that these hub genes were mainly enriched in signaling pathways of the immune system and breast cancer.We identified five immune-related hub genes with prognostic value in the TME of breast IDC, which may partly determine the prognosis of breast cancer and provide some direction for development of targeted treatments in the future.

Project description:BackgroundThe breast cancer is the most prevalent cancer among women, on the other hand absence of myoepithelial cells play a pivotal role in pathogenesis of this cancer. Thus we aimed to investigate the possible abilities of the molecular assay technique to find a relationship between mammary serine protease inhibitor (Maspin) gene expression possibly secreted by myoepithelial cells, grade of breast cancer and other prognostics factors (ER, PR, and c-erb-B2).MethodsParaffin embedded blocks of 31 breast cancer patients together with two normal breast tissues were used for IHC staining and Maspin gene RNA detection uses the real-time PCR method. Applying QIAGEN kit, we were able to measure Maspin RNA and Extract the cDNA of different samples for evaluating the Maspin RNA level.ResultsWe found that the RNA level was considerably lowerin these cancer samples compared with normal samples. In addition, different grades of breast cancer in the obtained results adopt some distinguishable values. The Maspin expression in samples with grades II and III is much lower than the ones in normal group (P<0.05) which could be considered as a promising way in diagnosing of this disease. The results showed no considerable differences in Maspin gene expression of the c-erb-B2 scores in the tumor group except the samples having score 0. The other observation of this research study confirmed that Maspin gene expression couldn't show any differences between the values of both ER and PR in different scores of the tumor group. On the other hand, the cDNA of these patients showed lower values compared with normal samples.ConclusionMaspin expression was reduced in samples with grade II& III of invasive ductal carcinoma. Based on expression of Maspin Inc-erb-B2, it seems that more expression happened in normal group comparing with different scores of it. We could suggest that there was a reverse relationship between tumor formation and Maspin gene expression. These results showed possible role of Maspin as prognostic factor.

Dataset Information

Myc promoter-binding protein-1 (MBP-1) is a novel potential prognostic marker in invasive ductal breast carcinoma.

Publications

Myc promoter-binding protein-1 (MBP-1) is a novel potential prognostic marker in invasive ductal breast carcinoma.

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