Dataset Information

Overexpression of MYEOV predicting poor prognosis in patients with pancreatic ductal adenocarcinoma.

ABSTRACT: Myeloma Overexpressed (MYEOV) is closely related to cell growth and differentiation in many cancer types. However, the role of this protein-coding gene in pancreatic ductal adenocarcinoma (PDAC) has rarely been investigated. In this study, we demonstrated that MYEOV was higher expressed in tumor tissues compared with adjacent normal pancreas tissues (ANPTs) both in mRNA and protein levels. We also performed bioinformatic analysis and found high MYEOV expression was positively correlated with tumor differentiation (P = 0.004), lymph node metastasis (P = 0.016) and TNM stage (P = 0.001). Moreover, Kaplan-Meier and Cox proportional-hazards analyses indicated that high MYEOV expression was significantly associated with poor survival in patients with PDAC and that MYEOV was an independent prognostic factor for overall survival in patients with PDAC. Geneset Enrichment Analysis (GSEA) result showed that high expression of MYEOV facilitates glycolysis of tumor cells in PDAC and validated in cellular assays. In conclusion, our results suggest that MYEOV acts as an oncogene in PDAC and can therefore serve as a biomarker for the prognosis of patients with PDAC.

SUBMITTER: Tang R

PROVIDER: S-EPMC7469688 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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Overexpression of MYEOV predicting poor prognosis in patients with pancreatic ductal adenocarcinoma.

Tang Rui R Ji Jianmei J Ding Jun J Huang Jinxin J Gong Biao B Zhang Xiwen X Li Fu F

Cell cycle (Georgetown, Tex.) 20200518 13

Myeloma Overexpressed (MYEOV) is closely related to cell growth and differentiation in many cancer types. However, the role of this protein-coding gene in pancreatic ductal adenocarcinoma (PDAC) has rarely been investigated. In this study, we demonstrated that MYEOV was higher expressed in tumor tissues compared with adjacent normal pancreas tissues (ANPTs) both in mRNA and protein levels. We also performed bioinformatic analysis and found high MYEOV expression was positively correlated with tum ...[more]

PMID: 32420813

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Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is characterized by an important heterogeneity, reflected by different clinical outcomes and chemoresistance. During carcinogenesis, tumor cells display aberrant glycosylated structures, synthetized by deregulated glycosyltransferases, supporting the tumor progression. In this study, we aimed to determine whether PDAC could be stratified through their glycosyltransferase expression profiles better than the current binary classification (basal-like and classical) in order to improve detection of patients with poor prognosis.MethodsBioinformatic analysis of 169 glycosyltransferase RNA sequencing data were performed for 74 patient-derived xenografts (PDX) of resected and unresectable tumors. The Australian cohort of International Cancer Genome Consortium and the microarray dataset from Puleo patient's cohort were used as independent validation datasets.FindingsNew PDAC stratification based on glycosyltransferase expression profile allowed to distinguish different groups of patients with distinct clinical outcome (p-value = 0.007). A combination of 19 glycosyltransferases differentially expressed in PDX defined a glyco-signature, whose prognostic value was validated on datasets including resected whole tumor tissues. The glyco-signature was able to discriminate three clusters of PDAC patients on the validation cohorts, two clusters displaying a short overall survival compared to one cluster having a better prognosis. Both poor prognostic clusters having different glyco-profiles in Puleo patient's cohort were correlated with stroma activated or desmoplastic subtypes corresponding to distinct microenvironment features (p-value < 0.0001). Besides, differential expression and enrichment analyses revealed deregulated functional pathways specific to different clusters.InterpretationThis study identifies a glyco-signature relevant for a prognostic use, potentially applicable to resected and unresectable PDAC. Furthermore, it provides new potential therapeutic targets.FundingThis work was supported by INCa (Grants number 2018-078 and 2018-079), Fondation ARC (Grant number ARCPJA32020070002326), Cancéropôle PACA, DGOS (labelization SIRIC, Grant number 6038), Amidex Foundation and Ligue Nationale Contre le Cancer and by institutional fundings from INSERM and the Aix-Marseille Université.

Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies and is not a clinically homogeneous disease, but subsets of patients with distinct prognosis and response to therapy can be identified by genome-wide analyses. Mutations in major PDAC driver genes were associated with poor survival. By bioinformatics analysis, we identified protocadherins among the most frequently mutated genes in PDAC suggesting an important role of these genes in the biology of this tumor. Promoter methylation of protocadherins has been suggested as a prognostic marker in different tumors, but in PDAC this epigenetic modification has not been extensively studied. Thus, we evaluated whether promoter methylation of three frequently mutated protocadherins, PCDHAC2, PCDHGC5 and PCDH10 could be used as survival predictors in PDAC patients.MethodsDNA extracted from 23 PDACs and adjacent non-neoplastic pancreatic tissues were bisulfite treated. Combined Bisulfite Restriction Analysis (COBRA) coupled to denaturing high-performance liquid chromatography (dHPLC) detection and bisulfite genomic sequencing (BGS) were used to determine the presence of methylated CpG dinucleotides in the promoter amplicons analyzed.ResultsIn an exploratory analysis, two protocadherins showed the same pattern of CpG methylation in PDAC and adjacent non-neoplastic pancreatic tissues: lack of methylation for PCDHAC2, complete methylation for PCDHGC5. Conversely, the third protocadherin analyzed, PCDH10, showed a variable degree of CpG methylation in PDAC and absence of methylation in adjacent non-neoplastic pancreatic tissues. At Kaplan-Meier analysis, high levels of PCDH10 methylation defined according to the receiver operating characteristic (ROC) curve analysis were significantly associated with worse progression-free survival (PFS) rates (P = 0.008), but not with overall survival (OS). High levels of PCDH10 methylation were a prognostic factor influencing PFS (HR = 4.0: 95% CI, 1.3-12.3; P = 0.016), but not the OS.ConclusionsIn this study, we show for the first time that the methylation status of PCDH10 can predict prognosis in PDAC patients with a significant impact on the outcome in terms of progression-free survival. High levels of PCDH10 promoter methylation could be useful to identify patients at high risk of disease progression, contributing to a more accurate stratification of PDAC patients for personalized clinical management.

Project description:PurposePancreatic ductal adenocarcinoma (PDAC) is one of the highest fatality rate cancers with poor survival rates. The tumor microenvironment (TME) is vital for tumor immune responses, leading to resistance to chemotherapy and poor prognosis of PDAC patients. This study aimed to provide a comprehensive evaluation of the immune genes and microenvironment in PDAC that might help in predicting prognosis and guiding clinical treatments.MethodsWe developed a prognosis-associated immune signature (i.e., PAIS) based on immune-associated genes to predict the overall survival of patients with PDAC. The clinical significance and immune landscapes of the signature were comprehensively analyzed.ResultsOwing to gene expression profiles from TCGA database, functional enrichment analysis revealed a significant difference in the immune response between PDAC and normal pancreas. Using transcriptome data analysis of a training set, we identified an immune signature represented by 5 genes (ESR2, IDO1, IL20RB, PPP3CA, and PLAU) related to the overall survival of patients with PDAC, significantly. This training set was well-validated in a test set. Our results indicated a clear association between a high-risk score and a very poor prognosis. Stratification analysis and multivariate Cox regression analysis revealed that PAIS was an important prognostic factor. We also found that the risk score was positively correlated with the inflammatory response, antigen-presenting process, and expression level of some immunosuppressive checkpoint molecules (e.g., CD73, PD-L1, CD80, and B7-H3). These results suggested that high-risk patients had a suppressed immune response. However, they could respond better to chemotherapy. In addition, PAIS was positively correlated with the infiltration of M2 macrophages in PDAC.ConclusionsThis study highlighted the relationship between the immune response and prognosis in PDAC and developed a clinically feasible signature that might serve as a powerful prognostic tool and help further optimize the cancer therapy paradigm.

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Overexpression of MYEOV predicting poor prognosis in patients with pancreatic ductal adenocarcinoma.

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Overexpression of MYEOV predicting poor prognosis in patients with pancreatic ductal adenocarcinoma.

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