Effect of low dose of berberine on the radioresistance of cervical cancer cells via a PI3K/HIF-1 pathway under nutrient-deprived conditions.

Purpose: Radiotherapy (RT) is one of the major treatments of cervical cancer. Although the prognosis of clinical cervical cancer becomes better in recent years, some patients still suffer from the recurrence and metastasis. Insufficiency of glucose and oxygen supply could increase the radioresistance of cervical cancer cells through regulating hypoxia-inducible factor 1 (HIF-1) in tumor microenvironment and glucose metabolism. And, berberine can regulate HIF-1. However, how berberine regulates tumor microenvironment and radioresistance through HIF-1 remains to be elucidated.Materials and methods: The human HeLa cervical cancer cells were treated with berberine and radiation under the high and low concentrations of glucose and oxygen, respectively. The survival of cells was tested by CCK-8 assay and colony formation assay. We investigated the PI3K- and IDH3α-related pathway molecules that may regulate HIF-1α by qPCR and western blot. Differentially expressed genes (DEGs) were identified by integrating five related cohort profile datasets. Protein-protein interaction (PPI) network analyses of DEGs related to HIF-1α were conducted by using the STRING database and Cytoscape software.Results: Berberine dramatically damaged HeLa cells under hypoxic and low-glucose conditions compared with the normoxic and high-glucose conditions. The clonogenic assay indicated that the application of berberine decreased the number of colony counts compared to the negative control. Low doses of berberine might decrease the level of phospho-PI3K and HIF-1α under the nutrient-deprived conditions. Moreover, we found that most of the differentially expressed genes which were related to CDKN1B were the downstream molecules regulated by HIF-1α.Conclusion: The results indicated that berberine could dramatically overcome the low-glucose and hypoxia-induced radioresistance. And the regulation berberine on nutrition-deficient conditions might involve in PI3K/HIF-1 pathway. Thus, the interference of glucose metabolism by berberine might be an attractive method to eliminate radioresistant cells and improve radiotherapy efficacy.

Identification of key genes and pathways of diagnosis and prognosis in cervical cancer by bioinformatics analysis.

BACKGROUND: Cervical cancer as one of the most common malignant tumors lead to bad prognosis among women. Some researches already focus on the carcinogenesis and pathogenesis of cervical cancer, but it is still necessary to identify more key genes and pathways. METHODS: Differentially expressed genes were identified by GEO2R from the gene expression omnibus (GEO) website, then gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyzed by DAVID. Meanwhile, protein-protein interaction network was constructed by STRING, and both key genes and modules were found in visualizing network through Cytoscape. Besides, GEPIA did the differential expression of key genes and survival analysis. Finally, the expression of genes related to prognosis was further explored by UNLCAN, oncomine, and the human protein atlas. RESULTS: Totally 57 differentially expressed genes were founded, not only enriched in G1/S transition of mitotic cell cycle, mitotic nuclear division, and cell division but also participated in cytokine-cytokine receptor interaction, toll-like receptor signaling pathway, and amoebiasis. Additionally, 12 hub genes and 3 key modules were screened in the Cytoscape visualization network. Further survival analysis showed that TYMS (OMIM accession number 188350), MCM2 (OMIM accession number 116945), HELLS (OMIM accession number 603946), TOP2A (OMIM accession number 126430), and CXCL8 (OMIM accession number 146930) were associated with the prognosis of cervical cancer. CONCLUSION: This study aim to better understand the characteristics of some genes and signaling pathways about cervical cancer by bioinformatics, and could provide further research ideas to find new mechanism, more prognostic factors, and potential therapeutic targets for cervical cancer.

Comprehensive Analysis of Differential Gene Expression to Identify Common Gene Signatures in Multiple Cancers.

BACKGROUND With the development of research on cancer genomics and microenvironment, a new era of oncology focusing on the complicated gene regulation of pan-cancer research and cancer immunotherapy is emerging. This study aimed to identify the common gene expression characteristics of multiple cancers - lung cancer, liver cancer, kidney cancer, cervical cancer, and breast cancer - and the potential therapeutic targets in public databases. MATERIAL AND METHODS Gene expression analysis of GSE42568, GSE19188, GSE121248, GSE63514, and GSE66272 in the GEO database of multitype cancers revealed differentially expressed genes (DEGs). Then, GO analysis, KEGG function, and path enrichment analyses were performed. Hub-genes were identified by using the degree of association of protein interaction networks. Moreover, the expression of hub-genes in cancers was verified, and hub-gene-related survival analysis was conducted. Finally, infiltration levels of tumor immune cells with related genes were explored. RESULTS We found 12 cross DEGs in the 5 databases (screening conditions: "adj p<0.05" and "logFC>2 or logFC<-2"). The biological processes of DEGs were mainly concentrated in cell division, regulation of chromosome segregation, nuclear division, cell cycle checkpoint, and mitotic nuclear division. Furthermore, 10 hub-genes were obtained using Cytoscape: TOP2A, ECT2, RRM2, ANLN, NEK2, ASPM, BUB1B, CDK1, DTL, and PRC1. The high expression levels of the 10 genes were associated with the poor survival of these multiple cancers, as well as ASPM, may be associated with immune cell infiltration. CONCLUSIONS Analysis of the common DEGs of multiple cancers showed that 10 hub-genes, especially ASPM and CDK1, can become potential therapeutic targets. This study can serve as a reference to understand the characteristics of different cancers, design basket clinical trials, and create personalized treatments.

Tumor mutation burden predicts response and survival to immune checkpoint inhibitors: a meta-analysis.

BACKGROUND: Cancer is one of the world's top three causes of death now. Immune checkpoint inhibitors (ICIs) show encouraging ability to treat some malignancies due to its long-term efficacy and low side effects. However, the predictive biomarker of the immunotherapy efficacy has been inconclusive. Thus, exploring new biomarkers is important. METHODS: A meta-analysis was conducted to evaluate whether tumor mutation burden (TMB) could be a predictive biomarker of the efficacy of ICIs. Using the PubMed and Cochrane Library databases, we searched for articles about TMB and the prognosis of patients with multiple malignancies conducted from 1984 to May 22, 2020. We identified the relationship between TMB and the clinical efficacy of ICIs by using Stata 12.1 software. RESULTS: Eighteen articles with a total of 4,535 patients were included in this meta-analysis. Results showed that high-TMB patients had better progression-free survival (PFS) than low-TMB patients with cancer treated with ICIs (HR =0.45; 95% CI: 0.36-0.56, P=0.002). Moreover, high-TMB patients had longer overall survival (OS) than low-TMB patients. However, the heterogeneity was extremely high, so the result regarding OS was meaningless (HR =0.56; 95% CI: 0.44-0.70, P=0.000, I-squares: 72.6%). CONCLUSIONS: Our study indicates that high TMB is associated with better PFS. Thus, TMB can be considered as a predictive marker of PFS of patients treated with ICIs in the future.