Background: Pancreatic cancer is one of the most lethal types of cancer, and immunotherapy has become a promising remedy with advancements in tumor immunology. However, predicting the clinical response to immunotherap...Background: Pancreatic cancer is one of the most lethal types of cancer, and immunotherapy has become a promising remedy with advancements in tumor immunology. However, predicting the clinical response to immunotherapy in pancreatic cancer remains a dilemma for clinicians. Methods: GEPIA database was used to analyze the differential expression of MMR and PD-L1 genes in 33 common cancer types including pancreatic cancer. The expression levels of MMR and PD-L1 genes were downloaded from the GEPIA and GEO databases to analyze the correlation between MMR genes and PD-L1, and the clinicopathological and survival information were downloaded from the TCGA databases to analyze the relationship between the expression of MMR, PD-L1 and clinicopathological characteristics, prognosis. Meanwhile, the tumor tissue samples of 41 patients with pancreatic cancer were collected, and the protein expression levels of MMR and PD-L1 were detected by immunohistochemical assay. Furthermore, we analyzed the correlation between MMR and PD-L1, and the correlation between the expression of MMR, PD-L1 and clinicopathological characteristics, prognosis of pancreatic cancer patients. Results: Bioinformatics analysis showed that MLH1, MLH3, MSH2, MSH3, and PMS2 were highly expressed in most cancer types including pancreatic cancer (P P = 0.012), clinical stage (I vs II: P = 0.016), MSH2 expression was related to clinical stage (P < 0.05), T stage (T3 vs T4: P = 0.039), and MSH3 expression was related to T stage (P < 0.05). Besides, both MSH2 expression (P P = 0.044) were significantly associated with prognosis. GEPIA data also showed that MSH2 expression was related to prognosis (P = 0.008). The correlation analysis revealed that the expressions MSH2, MLH1, PMS2 had strong correlations with PD-L1 both in GEPIA and GEO databases. Real-world data indicated that of the 41 pancreatic cancer patients, 5 cases had MLH1 deletion, 5 cases had MSH2 deletion, 4 cases had PMS2 deletion, and 12 cases had PD-L1 positive expression. Notably, PMS2 deletion w展开更多
Background: Resistance to cisplatin (DDP) leads to poor prognosis in patients with Lung Adenocarcinoma (LUAD) and limits its clinical application. It has been confirmed that autophagy promotes chemoresistance and, the...Background: Resistance to cisplatin (DDP) leads to poor prognosis in patients with Lung Adenocarcinoma (LUAD) and limits its clinical application. It has been confirmed that autophagy promotes chemoresistance and, therefore, novel strategies to reverse chemoresistance by regulating autophagy are desperately needed. Methods: The differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) between A549 and A549/DDP cell lines were identified using the limma package in R, after gene expression profiles were obtained from Gene Expression Omnibus (GEO) database. By combining Autophagy-Related Genes (ARGs) from Human Autophagy Database (HADb), the interactions lncRNA-miRNAs and the interactions miRNAs-mRNAs respectively predicted by miRcode and miRDB/Targetscan database, the autophagy-related ceRNA network was constructed. Then, extraction of ceRNA subnetwork and Cox regression analyses were performed. A prognosis-related ceRNA subnetwork was constructed, and the upstream Transcription Factors (TFs) regulating lncRNAs were predicted by the JASPAR database. Finally, the expression patterns of candidate genes were further verified by quantitative real-time polymerase chain reaction (qRT-PCR) experiments. Results: A total of 3179 DEmRNAs, 180 DEmiRNAs, and 160 DElncRNAs were identified, and 35 DEmRNAs were contained in the HADb. Based on the ceRNA hypothesis, we established a ceRNA network, including 10 autophagy-related DEmRNAs, 9 DEmiRNAs, and 14 DElncRNAs. Then, LINC00520, miR-181d, and BCL2 were identified to construct a risk score model, which was confirmed to be a well-predicting prognostic factor. Furthermore, 5 TF ZNF family members were predicted to regulate LINC00520, whereas the RT-PCR results showed that the 5 ZNFs were consistent with the bioinformatics analysis. Finally, a ZNF regulatory LINC00520/miR-181d/BCL2 ceRNA subnetwork was constructed. Conclusions: An ZNFs/LINC00520/miR-181d/BCL2 axis as a novel network in DDP-resistant LUAD has been constructed successfully, which may provid展开更多
文摘Background: Pancreatic cancer is one of the most lethal types of cancer, and immunotherapy has become a promising remedy with advancements in tumor immunology. However, predicting the clinical response to immunotherapy in pancreatic cancer remains a dilemma for clinicians. Methods: GEPIA database was used to analyze the differential expression of MMR and PD-L1 genes in 33 common cancer types including pancreatic cancer. The expression levels of MMR and PD-L1 genes were downloaded from the GEPIA and GEO databases to analyze the correlation between MMR genes and PD-L1, and the clinicopathological and survival information were downloaded from the TCGA databases to analyze the relationship between the expression of MMR, PD-L1 and clinicopathological characteristics, prognosis. Meanwhile, the tumor tissue samples of 41 patients with pancreatic cancer were collected, and the protein expression levels of MMR and PD-L1 were detected by immunohistochemical assay. Furthermore, we analyzed the correlation between MMR and PD-L1, and the correlation between the expression of MMR, PD-L1 and clinicopathological characteristics, prognosis of pancreatic cancer patients. Results: Bioinformatics analysis showed that MLH1, MLH3, MSH2, MSH3, and PMS2 were highly expressed in most cancer types including pancreatic cancer (P P = 0.012), clinical stage (I vs II: P = 0.016), MSH2 expression was related to clinical stage (P < 0.05), T stage (T3 vs T4: P = 0.039), and MSH3 expression was related to T stage (P < 0.05). Besides, both MSH2 expression (P P = 0.044) were significantly associated with prognosis. GEPIA data also showed that MSH2 expression was related to prognosis (P = 0.008). The correlation analysis revealed that the expressions MSH2, MLH1, PMS2 had strong correlations with PD-L1 both in GEPIA and GEO databases. Real-world data indicated that of the 41 pancreatic cancer patients, 5 cases had MLH1 deletion, 5 cases had MSH2 deletion, 4 cases had PMS2 deletion, and 12 cases had PD-L1 positive expression. Notably, PMS2 deletion w
文摘Background: Resistance to cisplatin (DDP) leads to poor prognosis in patients with Lung Adenocarcinoma (LUAD) and limits its clinical application. It has been confirmed that autophagy promotes chemoresistance and, therefore, novel strategies to reverse chemoresistance by regulating autophagy are desperately needed. Methods: The differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs) between A549 and A549/DDP cell lines were identified using the limma package in R, after gene expression profiles were obtained from Gene Expression Omnibus (GEO) database. By combining Autophagy-Related Genes (ARGs) from Human Autophagy Database (HADb), the interactions lncRNA-miRNAs and the interactions miRNAs-mRNAs respectively predicted by miRcode and miRDB/Targetscan database, the autophagy-related ceRNA network was constructed. Then, extraction of ceRNA subnetwork and Cox regression analyses were performed. A prognosis-related ceRNA subnetwork was constructed, and the upstream Transcription Factors (TFs) regulating lncRNAs were predicted by the JASPAR database. Finally, the expression patterns of candidate genes were further verified by quantitative real-time polymerase chain reaction (qRT-PCR) experiments. Results: A total of 3179 DEmRNAs, 180 DEmiRNAs, and 160 DElncRNAs were identified, and 35 DEmRNAs were contained in the HADb. Based on the ceRNA hypothesis, we established a ceRNA network, including 10 autophagy-related DEmRNAs, 9 DEmiRNAs, and 14 DElncRNAs. Then, LINC00520, miR-181d, and BCL2 were identified to construct a risk score model, which was confirmed to be a well-predicting prognostic factor. Furthermore, 5 TF ZNF family members were predicted to regulate LINC00520, whereas the RT-PCR results showed that the 5 ZNFs were consistent with the bioinformatics analysis. Finally, a ZNF regulatory LINC00520/miR-181d/BCL2 ceRNA subnetwork was constructed. Conclusions: An ZNFs/LINC00520/miR-181d/BCL2 axis as a novel network in DDP-resistant LUAD has been constructed successfully, which may provid
