Dataset Information

PAC-5 Gene Expression Signature for Predicting Prognosis of Patients with Pancreatic Adenocarcinoma.

ABSTRACT: Pancreatic adenocarcinoma (PAC) is one of the most aggressive malignancies. Intratumoural molecular heterogeneity impedes improvement of the overall survival rate. Current pathological staging system is not sufficient to accurately predict prognostic outcomes. Thus, accurate prognostic model for patient survival and treatment decision is demanded. Using differentially expressed gene analysis between normal pancreas and PAC tissues, the cancer-specific genes were identified. A prognostic gene expression model was computed by LASSO regression analysis. The PAC-5 signature (LAMA3, E2F7, IFI44, SLC12A2, and LRIG1) that had significant prognostic value in the overall dataset was established, independently of the pathological stage. We provided evidence that the PAC-5 signature further refined the selection of the PAC patients who might benefit from postoperative therapies. SLC12A2 and LRIG1 interacted with the proteins that were implicated in resistance of EGFR kinase inhibitor. DNA methylation was significantly involved in the gene regulations of the PAC-5 signature. The PAC-5 signature provides new possibilities for improving the personalised therapeutic strategies. We suggest that the PAC-5 genes might be potential drug targets for PAC.

SUBMITTER: Kim J

PROVIDER: S-EPMC6896100 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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PAC-5 Gene Expression Signature for Predicting Prognosis of Patients with Pancreatic Adenocarcinoma.

Kim Jieun J Jo Yong Hwa YH Jang Miran M Nguyen Ngoc Ngo Yen NNY Yun Hyeong Rok HR Ko Seok Hoon SH Shin Yoonhwa Y Lee Ju-Seog JS Kang Insug I Ha Joohun J Choi Tae Gyu TG Kim Sung Soo SS

Cancers 20191107 11

Pancreatic adenocarcinoma (PAC) is one of the most aggressive malignancies. Intratumoural molecular heterogeneity impedes improvement of the overall survival rate. Current pathological staging system is not sufficient to accurately predict prognostic outcomes. Thus, accurate prognostic model for patient survival and treatment decision is demanded. Using differentially expressed gene analysis between normal pancreas and PAC tissues, the cancer-specific genes were identified. A prognostic gene exp ...[more]

PMID: 31703415

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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.

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.

Dataset Information

PAC-5 Gene Expression Signature for Predicting Prognosis of Patients with Pancreatic Adenocarcinoma.

Publications

PAC-5 Gene Expression Signature for Predicting Prognosis of Patients with Pancreatic Adenocarcinoma.

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