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Background: Colon adenocarcinoma (COAD) is an incurable malignancy and the third most common tumor worldwide. Advances in biomarkers screening have greatly contributed to explore the new diagnostic and prognostic biomarkers for the early detection and prognostic of COAD. However, the heterogeneity-specific nature of COAD in patients of different cancer stages, different races, genders and age are still the major challenge to clinical treatment. Methods: Gene expression, copy number (CN), and dependency score (DS) data were obtained from the Cancer Cell Line Encyclopedia (CCLE), and linear regression analyses were performed using R language. We conducted receiver operating characteristic (ROC) curve analysis and compared the area under the ROC curve area under the curve (AUC) values to evaluate the sensitivity and specificity of nuclear cap binding protein subunit 2 (NCBP2) for the diagnosis of COAD in The Cancer Genome Atlas (TCGA) database. Survival analysis was performed in the distinct NCBP2 expression groups. In vitro experiments and bioinformatics analysis were used to investigate the molecular mechanisms of NCBP2 in COAD and its biological roles. A Connectivity Map (Cmap) was used to identify potential small molecule targeted drugs for NCBP2 in COAD. Results: Through the linear regression analysis of DS, CN, and gene expression, we determined that NCBP2 met our criteria. The mean AUC of the ROC curve of NCBP2 was 0.940±0.050. Survival analysis showed that high NCBP2 expression was associated with a worse prognosis [hazard ratio (HR) =1.98, P<0.007]. NCBP2 knockdown inhibited COAD cell proliferation and caused G0/G1 phase arrest in COAD cells. Conclusions: NCBP2 was the novel diagnostic and prognostic biomarker of in COAD. Our research had implications for the treatment of colon cancer.
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Acute pancreatitis (AP), as a common kind of pancreas-based inflammatory disease, is accompanied by a serious and abnormal metabolism. However, the specific metabolic process of AP is still unclear. Novel and effective drugs against acute pancreatitis are urgently required. To explore the metabolic biomarkers and regulation pathways of acute pancreatitis, ultra-performance liquid chromatography (UPLC) combined with a mass spectrometry (MS)-based metabolomics strategy was used. Sixteen male adult Sprague-Dawley rats were divided into two groups: a sham operation group (SO) and an AP model group. The AP animal model was induced via the retrograde ductal infusion of 3.5% sodium taurocholate, and rats in the SO group were infused with 0.9% saline. After serum sample collection and sacrifice, a metabolomics strategy based on UPLC-MS was used to detect serum metabolites and metabolic pathways by comparing the SO and AP model groups through full-scan analysis. A total of 19 metabolites were detected in the serum for highlighting the differences between the two groups: l-arabitol, citric acid, isocitric acid, l-phenylalanine, l-tyrosine, dihydroxyacetone, l-valine, succinic acid, 3-hydroxybutyric acid, uric acid, acetylglycine, palmitic amide, homocysteine, d-glutamine, l-arginine, arachidonic acid, N-acetylserotonin, (R)-3-hydroxy-hexadecanoic acid, and d-mannose. Six crucial metabolic pathways, phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, glyoxylate and dicarboxylate metabolism and the citrate cycle, were involved; these have potential to become novel targets for the treatment of AP. The ingenuity pathway analysis (IPA) platform is used to gain insights into the metabolic targets in the system, referring to development disorders, cell-to-cell signaling and interactions, cellular assembly and organization, cell compromise, cell growth and proliferation, carbohydrate metabolism and others. It is suggested that UPLC-MS-based metabolomics is capable of accurately depicting the pathological mechanisms of acute pancreatitis, which can drive new drug development.