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Purpose: Patients with pancreatic cancer (PC) can be classified into various molecular subtypes and benefit from some precise therapy. Nevertheless, the interaction between metabolic and immune subtypes in the tumor microenvironment (TME) remains unknown. We hope to identify molecular subtypes related to metabolism and immunity in pancreatic cancer Methods: Unsupervised consensus clustering and ssGSEA analysis were utilized to construct molecular subtypes related to metabolism and immunity. Diverse metabolic and immune subtypes were characterized by distinct prognoses and TME. Afterward, we filtrated the overlapped genes based on the differentially expressed genes (DEGs) between the metabolic and immune subtypes by lasso regression and Cox regression, and used them to build risk score signature which led to PC patients was categorized into high- and low-risk groups. Nomogram were built to predict the survival rates of each PC patient. RT-PCR, in vitro cell proliferation assay, PC organoid, immunohistochemistry staining were used to identify key oncogenes related to PC Results: High-risk patients have a better response for various chemotherapeutic drugs in the Genomics of Drug Sensitivity in Cancer (GDSC) database. We built a nomogram with the risk group, age, and the number of positive lymph nodes to predict the survival rates of each PC patient with average 1-year, 2-year, and 3-year areas under the curve (AUCs) equal to 0.792, 0.752, and 0.751. FAM83A, KLF5, LIPH, MYEOV were up-regulated in the PC cell line and PC tissues. Knockdown of FAM83A, KLF5, LIPH, MYEOV could reduce the proliferation in the PC cell line and PC organoids Conclusion: The risk score signature based on the metabolism and immune molecular subtypes can accurately predict the prognosis and guide treatments of PC, meanwhile, the metabolism-immune biomarkers may provide novel target therapy for PC [ABSTRACT FROM AUTHOR]

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive human malignancies. Cell-cycle-related and expression-elevated protein in tumor (CREPT) plays an important role in the phosphorylation of RNA Pol II, and has been implicated in the development of several types of cancer. As yet, however, there have been no reports on its role in PDAC. Here, we aimed to explore the value of CREPT as a prognostic biomarker in PDAC. Methods: CREPT expression was assessed by immunohistochemistry (IHC) on a tissue microarray containing samples from 375 PDAC patients. Kaplan-Meier and Cox regression analyses were performed to explore the independent prognostic value of CREPT expression for the disease-free survival (DFS) and overall survival (OS) of PDAC patients. A Cell Counting Kit-8 (CCK8) assay was used to determine the growth rates and gemcitabine sensitivities of PDAC cells, while a Transwell assay was used to determine the migration and invasion abilities of PDAC cells. Subcutaneous xenografts were used to explore the effect of CREPT expression on tumor growth in vivo. Results: We found that CREPT is highly expressed in tumor tissues and may serve as an independent prognostic biomarker for DFS and OS of PDAC patients. In vitro assays revealed that CREPT expression promotes the proliferation, migration, invasion and gemcitabine resistance of PDAC cells, and in vivo assays showed that CREPT expression knockdown led to inhibition of PDAC tumor growth. Conclusions: We conclude that high CREPT expression enhances the proliferation, migration, invasion and gemcitabine resistance of PDAC cells. In addition, we conclude that CREPT may serve as an independent prognostic biomarker and therapeutic target for PDAC patients. [ABSTRACT FROM AUTHOR]