Background Pancreatic adenocarcinoma (PAAD) is one of the common malignant tumors, with high mortality and poor prognosis. Long non-coding RNA (lncRNA) plays a vital role in the progression of tumors. Cuproptosis, a newly identified form of programmed cell death, is thought to play a role in tumorigenesis. However, the role and prognostic value of cuproptosis-related lncRNA in PAAD remains unknown. Therefore, our study is to construct the role of cuproptosis-related lncRNA signature for predicting the prognosis of PAAD patients. Material and methods The mRNAs and lncRNAs expression profiles and clinical data of PAAD were obtained from The Cancer Genome Atlas (TCGA) databases. The prognosis signature was constructed by least absolute shrinkage and selection operator (LASSO) regression and Cox regression analysis. Patients were separated into high and low risk groups according to the median score. Using Kaplan-Meier, Concordance index (C-index), area under the receiver operating characteristic (ROC) curves to assess prognostic ability of the signature. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes Enrichment (KEGG), immune-related functions, and tumor mutation burden (TMB) were analyzed based on the signature. The likelihood of an immunotherapy response was estimated using tumor immune dysfunction and exclusion (TIDE) algorithms. PRRophetic package was used to identify its sensitivity toward potential drugs for PAAD. Results In total, we obtained 4 cuproptosis-related lncRNAs and constructed a prognostic signature. High-risk patients were correlated with worse overall survival (OS) and progression-free survival (PFS) and higher mortality. Multivariate Cox regression was performed to identify independent risk factor poor prognosis of high risk scores. ROC, C-index, and nomogram also showed the signature can accurately predict the prognosis of patients. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed the biological functions of lncRNAs are associated with tumor development, especially immune response. Tumor Mutation Burden (TMB) and Tumor Immune Dysfunction and Exclusion (TIDE) scores were significantly different between high- and low-risk groups. The three drugs, including Paclitaxel, Gefitinib, and 17-AAG, were more sensitive in the high-risk group. Conclusion The 4 cuproptosis-related lncRNAs signature accurately predicted the prognosis of PAAD and led to better prognosis and treatment options for patients.

Background Hepatocellular carcinoma (HCC) is a common malignant tumor. The application of sorafenib has brought good results to the treatment of HCC, but the drug resistance of sorafenib cannot be ignored. Celecoxib can enhance the efficacy of sorafenib, but its mechanism is still unclear. The main purpose of this study is to study the efficacy and related mechanism of celecoxib and sorafenib in the treatment of hepatocellular carcinoma. Methods The GSE45340 data set was retrieved from the Gene Expression Database (GEO), and the differentially expressed genes were obtained by GEO2R. Then, the differentially expressed genes were screened, analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and then analyzed by Protein-Protein Interaction (PPI) network to obtain the hub genes, which were verified in TCGA database. Results Through the analysis of GEO2r, we got 2181 differentially expressed genes. We selected 50 of the most diverse genes for go and KEGG enrichment analysis, and obtained their main enrichment pathways. The protein-protein interaction network of 50 genes was further obtained. Thus, the relevant key genes were obtained, and twelve genes were screened. Twelve genes (MCM4, POLA1, MCM6, MCM3, RBBP4, DNA2, AP2B1, KIF11, KIF23, TUBA1B, KIF14, NUDT21) significantly related to the prognosis of HCC and the molecular pathways involved in these genes were screened, which explained how celecoxib enhanced the efficacy of sorafenib. Twelve genes were further enriched and analyzed, and their possible mechanism of action was obtained. Conclusions celecoxib combined with sorafenib can enhance the regulation of hepatocellular carcinoma gene and reduce the drug resistance to sorafenib, which is of great significance for the treatment of hepatocellular carcinoma.