The potential drug for treatment in pancreatic adenocarcinoma: a bioinformatical study based on distinct drug databases

Prioritizing exhausted T cell marker genes highlights immune subtypes in pan-cancer

Exhausted T (TEX) cells are main immunotherapy targets in cancer, but it lacks a general identification method to characterize TEX cell in disease. To assess the characterization of TEX cell, we extract signature of TEX cell from large cancer and chronic infection cohorts. Based on single-cell transcriptomes, a systematic T cell exhaustion prediction (TEXP) model is designed to define TEX cell in cancer and chronic infection. We then prioritize 42 marker genes, including HAVCR2, PDCD1, TOX, TIGIT and LAG3, which are associated with T cell exhaustion. TEXP could identify high TEX and low TEX subtypes in pan-cancer of TCGA. The high TEX subtypes are characterized by high immune score, immune cell infiltration, high expression of TEX marker genes and poor prognosis. In summary, TEXP and marker genes provide a resource for understanding the function of TEX cell, with implications for immune prediction and immunotherapy in chronic infection and cancer.

Robust identification of common genomic biomarkers from multiple gene expression profiles for the prognosis, diagnosis, and therapies of pancreatic cancer

Pancreatic cancer (PC) is one of the leading causes of cancer-related death globally. So, identification of potential molecular signatures is required for diagnosis, prognosis, and therapies of PC. In this study, we detected 71 common differentially expressed genes (cDEGs) between PC and control samples from four microarray gene-expression datasets (GSE15471, GSE16515, GSE71989, and GSE22780) by using robust statistical and machine learning approaches, since microarray gene-expression datasets are often contaminated by outliers due to several steps involved in the data generating processes. Then we detected 8 cDEGs (ADAM10, COL1A2, FN1, P4HB, ITGB1, ITGB5, ANXA2, and MYOF) as the PC-causing key genes (KGs) by the protein-protein interaction (PPI) network analysis. We validated the expression patterns of KGs between case and control samples by box plot analysis with the TCGA and GTEx databases. The proposed KGs showed high prognostic power with the random forest (RF) based prediction model and Kaplan-Meier-based survival probability curve. The KGs regulatory network analysis detected few transcriptional and post-transcriptional regulators for KGs. The cDEGs-set enrichment analysis revealed some crucial PC-causing molecular functions, biological processes, cellular components, and pathways that are associated with KGs. Finally, we suggested KGs-guided five repurposable drug molecules (Linsitinib, CX5461, Irinotecan, Timosaponin AIII, and Olaparib) and a new molecule (NVP-BHG712) against PC by molecular docking. The stability of the top three protein-ligand complexes was confirmed by molecular dynamic (MD) simulation studies. The cross-validation and some literature reviews also supported our findings. Therefore, the finding of this study might be useful resources to the researchers and medical doctors for diagnosis, prognosis and therapies of PC by the wet-lab validation.

bub1 as a potential oncogene and a prognostic biomarker for neuroblastoma

Background

Neuroblastoma is the most common malignant extracranial tumor for children. Molecular mechanisms underpinning the pathogenesis of this disease are yet to be fully clarified. This study aimed to identify a novel oncogene that could be used as a biomarker informing the prognosis of neuroblastoma, and to predict its biological functions, using bioinformatics and molecular biology tools.

Methods

Three data sets from the TARGET, GSE62564, and GSE85047 databases were used for analysis. Survivals of patients with high or low expression of bub1 were compared, using the Kaplan-Meier curve and log-rank test. Immune infiltration was evaluated using ESTIMATE and MCP-counter algorithms. Synthetic small interfering RNAs (siRNAs) were employed to silence bub1 expression in neuroblastoma cell lines SH-SY5Y and SK-N-SH, in order to characterize its biological functions. Gene enrichment analyses of bub1 were carried out, using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses.

Results

Expression of bub1 was found to significantly affect overall survival and event-free survival of patients with neuroblastoma, positively correlate with the expressions of tpx2 and the ASPM gene, and negatively correlate with host immune infiltration. Expression of bub1 was elevated in patients with neuroblastoma. Silencing bub1 expression using siRNAs in SH-SY5Y and SK-N-SH resulted in decreased cell growth (p < 0.05), reduced migration (p < 0.05), and increased apoptosis (p < 0.05). Function analysis of bub1 revealed cancer-promoting effects, probably via regulating several important downstream molecules, including that related to the apoptosis process and epithelial-mesenchymal transition.

Conclusion

We identified a potential tumor-promoting gene bub1 for neuroblastoma that could also serve as a prognostic biomarker.

The Four Key Genes Participated in and Maintained Atrial Fibrillation Process via Reprogramming Lipid Metabolism in AF Patients

Atrial fibrillation (AF) is always in high incidence in the population, which can lead to serious complications. The structural and electrical remodeling of atrial muscle induced by inflammatory reaction or oxidative stress was considered as the major mechanism of AF. The treatment effect is not ideal based on current mechanisms. Recent studies demonstrated that lipid metabolism disorder of atrial muscle played an important role in the occurrence of AF. What key genes are involved is unclear. The purpose of the present study was to explore the lipid metabolism mechanism of AF. With the GEO database and the genomics of AF patients, metabolic related pathways and the key genes were analyzed. At the same time, the rat model of cecal ligation and puncture (CLP) was used to confirm the results. GSE 31821 and GSE 41177 were used as data sources, and the merged differentially expressed genes (DEGs) analysis showed that a total of 272 DEGs were found. GO annotation, KEGG, and gene set enrichment analysis (GSEA) showed that the fatty acid metabolism and the lipid biosynthetic process were involved in AF. Cholesterol biosynthesis, arachidonic acid metabolism, and the lipid droplet pathway were obviously increased in AF. Further analysis showed that four key genes, including ITGB1, HSP90AA1, CCND1, and HSPA8 participated in pathogenesis of AF regulating lipid biosynthesis. In CLP rats, metabolic profiling in the heart showed that the pyrimidine metabolism, the biosynthesis of unsaturated fatty acid metabolism, arginine and proline metabolism, and the fatty acid biosynthesis were involved. The four key genes were confirmed increased in the heart of CLP rats (p < 0.05 or 0.01). The results suggest that the lipid metabolism disorder participates in the occurrence of AF. ITGB1, HSP90AA1, CCND1, and HSPA8 are the key genes involved in the regulation of lipid biosynthesis.

Molecular docking investigation of calotropone as a potential natural therapeutic agent against pancreatic cancer

A natural bioactive compound named calotropone has been reported as a drug candidate for several cancers, including pancreatic cancers. Herein, we used molecular docking approach to test the possible mechanisms of action of calotropone in inhibiting the growth of pancreatic cell cancer with gemcitabine as the positive control. By employing AutoDock Vina, we studied the molecular interaction between calotropone and pancreatic cancer-associated proteins, namely Glucosaminyl (N-Acetyl) Transferase 3, Glutamic-Oxaloacetic Transaminase 1, Tyrosine-protein kinase Met (c-Met), peroxisome proliferator-activated receptor γ, Budding Uninhibited by Benzimidazole 1, A Disintegrin and Metalloproteinase 10, Sex-determining region Y and Nuclear Factor kappa Beta (Nf-Kβ). Higher affinity energies of calotropone toward the aforementioned proteins (ranging from ‒7.3 to ‒9.3 kcal/mol) indicate that calotropone may work in the same manner as anticancer drug gemcitabine. Highest docking score was found at the interaction of calotropone and Nf-Kβ (‒9.3 kcal/mol).

MK8722, an AMPK activator, inhibiting carcinoma proliferation, invasion and migration in human pancreatic cancer cells

BACKGROUND

MK8722 is a potent and systemic pan-AMPK activator. It is an effective, direct, allosteric activator of AMPK complex in many mammals. This study tried to explore the underlying anti-cancer molecular mechanism of MK8722 in human pancreatic cancer cells (PCCs).

METHODS

The anti-proliferation, invasion and migration functions of MK8722 in human pancreatic cancer analyzed by real time cellular analysis, colony formation assay, cell migration assay, transwell assay and flow cytometery analysis. Moreover, the potential targeted signaling pathway was tested via RNA-seq and pathway enrichment analysis.

RESULTS

In the present study, we investigated the anti-PCCs effects of MK8722 on two different human pancreatic cancer cell lines (PANC-1 and Patu8988). The results showed that MK8722 significantly inhibited human tumor cells proliferation and migration/invasion in a dose-dependent manner. Additionally, the influence of MK8722 was examined by analyzing the expression of potential key genes and pathways, which may provide novel insights to the mechanism of MK8722.

CONCLUSION

The inhibition of pancreatic cancer by MK8722 through a number of pathways that inhibit carcinoma proliferation, invasion and migration. The potential effect of MK8722 might be determined by regulating the expression of AL162151, IER2, REPIN1, KRT80 to inhibit cycle arrest and migration.

Molecular docking of two cytotoxic compounds from Calotropis gigantea leaves against therapeutic molecular target of pancreatic cancer

The utilization of natural compounds as therapeutic agents to treat pancreatic cancer has recently focused on natural drug research. Calotropis gigantea has long been believed to be a medicinal plant that helps in treating various diseases. The bioactive compounds 9-metoxipinoresinol and isoliquiritigenin isolated from C. gigantea leaves are proven to act as therapeutic agents by inhibiting the cancer cell growth of Panc-1 cells. This study aimed to screen the potential molecular inhibition mechanisms of 9-metoxipinoresinol and isoliquiritigenin against pancreatic cancer development in-silico. We analyzed the activity of the aforementioned two compounds as inhibitors of several proteins that play a role in the growth of pancreatic cancer cells, such as GCNT3, GOT1, c-Met, PPARγ, BUB1, and NF-κβ, through molecular docking investigation. Our data suggested that 9-metoxipinoresinol and isoliquiritigenin were able to have well interaction with the target proteins, in which the predicted affinity energy ranged between -6.8 and 8.7 kcal/mol. The docking scores of 9-metoxipinoresinol and isoliquiritigenin were higher than the standard drug used (gemcitabine). Based on the binding affinity energy, GCNT3 and BUB1 are potentially to be used as target molecules for cancer therapy using 9-metoxipinoresinol and isoliquiritigenin, respectively.

Comprehensive analysis of prognostic gene signatures based on immune infiltration of ovarian cancer

BACKGROUND

Ovarian cancer (OV) is one of the most common malignant tumors of gynecology oncology. The lack of effective early diagnosis methods and treatment strategies result in a low five-year survival rate. Also, immunotherapy plays an important auxiliary role in the treatment of advanced OV patient, so it is of great significance to find out effective immune-related tumor markers for the diagnosis and treatment of OV.

METHODS

Based on the consensus clustering analysis of single-sample gene set enrichment analysis (ssGSEA) score transformed via The Cancer Genome Atlas (TCGA) mRNA profile, we obtained two groups with high and low levels of immune infiltration. Multiple machine learning methods were conducted to explore prognostic genes associated with immune infiltration. Simultaneously, the correlation between the expression of mark genes and immune cells components was explored.

RESULTS

A prognostic classifier including 5 genes (CXCL11, S1PR4, TNFRSF17, FPR1 and DHRS95) was established and its robust efficacy for predicting overall survival was validated via 1129 OV samples. Some significant variations of copy number on gene loci were found between two risk groups and it showed that patients with fine chemosensitivity has lower risk score than patient with poor chemosensitivity (P = 0.013). The high and low-risk groups showed significantly different distribution (P < 0.001) of five immune cells (Monocytes, Macrophages M1, Macrophages M2, T cells CD4 menory and T cells CD8).

CONCLUSION

The present study identified five prognostic genes associated with immune infiltration of OV, which may provide some potential clinical implications for OV treatment.