BIOINFORMATICS ANALYSIS OF DIFFERENTIALLY EXPRESSED GENES IN PANCREATIC CANCER AND PREDICTION OF POTENTIAL THERAPEUTIC TRADITIONAL CHINESE MEDICINE

Abstract

Background: To study the potential Chinese medicine for the treatment of pancreatic cancer and its mechanism based on bioinformatics and molecular docking technology. Methods: The data were collected from The Cancer Genome Atlas (TCGA), the Genotype-Tissue Expression (GTEX) and Gene expression databases (Gene) Expression Omnibus (GEO) (GSE16515) obtained tumor tissues of pancreatic cancer patients and normal tissues of healthy people, GEO serves as the training set for the pancreatic cancer dataset, TCGA and GTEX serve as the validation set.And applied R software for data standardization and differentially expressed genes (DEGs) screening. The gene ontology (GO) and the Kyoto encyclopedia of genes and genomes (KEGG) were analyzed for enrichment. The protein interaction network diagram was constructed by STRING database and Cytoscape software, and key genes were screened by CytoHubba plug-in. Survival analysis and visualization of key genes were performed by Kaplan-Meier survival curve. Coremine Medical database was used to screen potential therapeutic TCM; The compounds and core genes of traditional Chinese medicine were analyzed by molecular docking. Results: A total of 94 differential genes and 7 key genes were screened. GO and KEGG pathway enrichment analysis showed that cellular response to xenobiotic stimulus, apical part of cell and other biological processes were involved. The pathway mainly involves Pancreatic cancer, Ras signaling pathway, and PI3K−Akt signaling pathway. Survival analysis of key genes showed that ABCB1 and TGFBR2 had a significant impact on overall prognosis and survival. Seven kinds of traditional Chinese medicine were screened by key genes, which were Hedyotis diffusa, Schisandra chinensis, salvia miltiorrhiza, Ephedrae Radix Et Rhizoma, Glycyrrhiza uralensis Fisch,Chinese Thorowax Root，Lamium barbatum sieb. The main compounds were Kaempferol, Isorhamnetin, β-Sitosterol and quercetin. Molecular docking results showed that the compounds were well bound to core targets ABCB1. Conclusion: The key genes of pancreatic cancer were screened by bioinformatics method, and the potential Chinese medicine for the treatment of pancreatic cancer was identified, which provided a new direction for the study of the pathogenesis, new therapeutic targets and new drug development of pancreatic cancer.the diagnostic value of procalcitonin (PCT), white blood cell count (WBC), and C-reactive protein (CRP) in respiratory infections within an ICU setting and their correlation with the Clinical Pulmonary Infection Score (CPIS) in athletes. This study aims to understand how these biomarkers can help predict and manage respiratory infections in a population that might experience different immunological responses due to their physical conditioning and sports-related stress factors. Methods: This retrospective study included 130 athletes admitted to the ICU with suspected respiratory infections between January 2019 and December 2021. Athletes were divided into two groups based on the presence or absence of respiratory infections, confirmed via clinical assessment and CPIS scoring. Levels of PCT, WBC, and CRP were measured upon admission and 48 hours post-admission, using standard laboratory techniques. The effectiveness of these biomarkers in diagnosing respiratory infections was assessed by calculating their sensitivity, specificity, and predictive values based on CPIS scores. Results: Elevated levels of PCT, WBC, and CRP were significantly associated with higher CPIS scores, indicating respiratory infections (P < 0.05). The combined diagnostic approach using all three biomarkers showed improved accuracy over individual biomarker assessments, with a combined sensitivity of 92% and specificity of 89%. Athletes with respiratory infections had higher mean values of PCT, WBC, and CRP compared to those without infections. The correlation analysis reinforced the positive relationship between the severity of infection (as indicated by CPIS) and increased levels of these biomarkers. Conclusion: The integration of PCT, WBC, and CRP measurements offers a robust diagnostic tool for detecting respiratory infections in athletes in ICU settings. This approach not only helps in the early diagnosis but also in monitoring the severity of infections, which is crucial for managing treatment plans effectively and potentially reducing recovery time, ensuring a faster return to training and competition for athletes.