Transcriptomic data exploration of consensus genes and molecular mechanisms between chronic obstructive pulmonary disease and lung adenocarcinoma

The serine protease CORIN promotes progression of gastric cancer by mediating the ERK1/2 MAPK pathway

The serine protease CORIN catalyzes pro-atrial natriuretic peptide (pro-ANP) into an active ANP and maintains homeostasis of the internal environment. However, it is unclear whether CORIN participates in the regulation of tumor progression. We analyzed the expression profile of CORIN in gastric cancer tissues (GCs) and adjacent nontumoral tissues (NTs). We investigated the prognostic value of CORIN in GC patients. We characterized the in vitro and in vivo activity of CORIN in cultured GC cells with gain-of-function and loss-of-function experiments. The underlying mechanism was explored by using bioinformatics, a signaling antibody array, and confirmative western blot analyses, as well as rescue experiments with highly selective small-molecule inhibitors targeting the ERK1/2 MAPK signaling pathway. CORIN was upregulated in GCs than in NTs. Overexpression of CORIN was correlated with unfavorable prognoses in patients with GC. Ectopic expression of CORIN was promoted, whereas silencing of CORIN suppressed proliferation, colony formation, migration and invasion of GC cells, and tumor growth in vivo. Overexpression of CORIN-induced epithelial-mesenchymal transition (EMT) and activation of the ERK1/2 MAPK signaling pathway, while silencing of CORIN yielded opposite results. The in vitro tumor-promoting potency of CORIN could be antagonized by selective inhibitors targeting the ERK1/2 MAPK pathway. In conclusion, CORIN is a potential prognostic marker and therapeutic target for GC patients, which may promote tumor progression by mediating the ERK1/2 MAPK signaling pathway and EMT in GC cells.

Exploring risk factors and molecular targets in leukemia patients with COVID-19: a bioinformatics analysis of differential gene expression

The molecular mechanism of COVID-19's pathogenic effects in leukemia patients is still poorly known. Our study investigated the possible disease mechanism of COVID-19 and its associated risk factors in patients with leukemia utilizing differential gene expression analysis. We also employed network-based approaches to identify molecular targets that could potentially diagnose and treat COVID-19-infected leukemia patients. Our study demonstrated a shared set of 60 genes that are expressed differentially among patients with leukemia and COVID-19. Most of these genes are expressed in blood and bone marrow tissues and are predominantly implicated in the pathogenesis of different hematologic malignancies, increasingly imperiling COVID-19 morbidity and mortality among the affected patients. Additionally, we also found that COVID-19 may influence the expression of several cancer-associated genes in leukemia patients, such as CCR7, LEF1, and 13 candidate cancer-driver genes. Furthermore, our findings reveal that COVID-19 may predispose leukemia patients to altered blood homeostasis, increase the risk of COVID-19-related liver injury, and deteriorate leukemia-associated injury and patient prognosis. Our findings imply that molecular signatures, like transcription factors, proteins such as TOP21, and 25 different microRNAs, may be potential targets for diagnosing and treating COVID-19-infected leukemia patients. Nevertheless, additional experimental studies will contribute to further validating the study's findings.

CENPF Upregulation is Associated with Immunosuppressive Status and Poor Clinical Outcomes in Lung Adenocarcinoma Validated by qRT-PCR

OBJECTIVE

CENPF-differentially expressed in various types of cancers-is a marker of poor prognosis. However, studies on the impact of CENPF on patient prognosis in lung adenocarcinoma regarding immune infiltration are lacking.

METHODS

CENPF expression profiles were analyzed in the GEO and TCGA databases. qRT-PCR was used to verify CENPF mRNA expression in lung adenocarcinoma cell lines. The prognostic value of CENPF was evaluated by combining data from clinical samples in the GEPIA2 and TCGA databases. Metascape and WebGestalt were used for enrichment analysis of gene sets most positively associated with CENPF. Immune cell infiltration score data were retrieved from TCGA and the correlation between CENPF expression and immune cell infiltration was analyzed.

RESULTS

CENPF expression was elevated in 29 types of cancer. CENPF was highly expressed and increased with tumor grade in lung adenocarcinoma. Immunohistochemical and qRT-PCR analyses revealed that CENPF expression was upregulated in lung adenocarcinoma tissues and cells. High expression of CENPF significantly worsened prognoses in patients with multiple malignancies, including lung adenocarcinoma. Results from gene set enrichment analysis indicated significant enrichment of the progesterone-mediated oocyte maturation pathway. Immune infiltration analysis revealed that CD4+ Th2 cell infiltration was significantly higher in the high CENPF expression group.

CONCLUSION

Upregulation of CENPF expression was related to poor progression-free survival, disease- free survival, and overall survival in patients with lung adenocarcinoma. High expression of CENPF was markedly related to genes associated with the immune checkpoint. Lung adenocarcinoma samples with high CENPF expression had increased CD4+ Th2 cell infiltration. Our findings indicate that CENPF promotes CD4+ Th2 cell infiltration through oncogenic activity and may be used as a biomarker for predicting patient outcomes in lung adenocarcinoma.

The neurological and non-neurological roles of the primary microcephaly-associated protein ASPM

Primary microcephaly (MCPH), is a neurological disorder characterized by small brain size that results in numerous developmental problems, including intellectual disability, motor and speech delays, and seizures. Hitherto, over 30 MCPH causing genes (MCPHs) have been identified. Among these MCPHs, MCPH5, which encodes abnormal spindle-like microcephaly-associated protein (ASPM), is the most frequently mutated gene. ASPM regulates mitotic events, cell proliferation, replication stress response, DNA repair, and tumorigenesis. Moreover, using a data mining approach, we have confirmed that high levels of expression of ASPM correlate with poor prognosis in several types of tumors. Here, we summarize the neurological and non-neurological functions of ASPM and provide insight into its implications for the diagnosis and treatment of MCPH and cancer.

AURKA, TOP2A and MELK are the key genes identified by WGCNA for the pathogenesis of lung adenocarcinoma

The comprehensive analysis of single or multiple microarray datasets is currently available in Gene Expression Omnibus (GEO) databases, with several studies having identified genes strongly associated with the development of lung adenocarcinoma (LUAD). However, the mechanisms of LUAD development remain largely unknown and has not yet been systematically studied; thus, further studies are required in this field. In the present study, weighted gene co-expression network analysis (WGCNA) was used for the evaluation of key genes with potential high risk of LUAD, and to provide more reliable evidence concerning its pathogenesis. The GSE140797 dataset from the high-throughput GEO database was downloaded and was first analyzed using the Limma package in the R language in order to determine the differentially expressed genes. The dataset was then analyzed using the WGCNA package to analyze the co-expressed genes, and the modular genes with the highest correlation with the clinical phenotype were identified. Subsequently, the pathogenic genes shared in common between the result of the two analyses were imported into the STRING database for protein-protein interaction network analysis. The hub genes were screened out using Cytoscape, and then The Cancer Genome Atlas analysis, receiver operating characteristic analysis and survival analysis were subsequently performed. Finally, the key genes were evaluated using reverse transcription-quantitative PCR and western blot analysis. Bioinformatics analysis of the GSE140797 dataset revealed eight key genes: AURKA, BUB1, CCNB1, CDK1, MELK, NUSAP1, TOP2A and PBK. Finally, the AURKA, TOP2A and MELK genes were evaluated in samples from patients with lung cancer using WGCNA and RT-qPCR, western blot analysis experiments, providing basis for further research on the mechanisms of LUAD development and targeted therapy.