Construction of a prognostic model for lung adenocarcinoma based on membrane-tension-related genes.

Background: Lung adenocarcinoma (LUAD), which is the most common type of non-small cell lung cancer (NSCLC), is one of the most aggressive and fatal tumors. Therefore, the identification of key biomarkers affecting prognosis is important to improving the prognosis of patients with LUAD. Cell membranes have long been understood; however, few studies have focused on the role of membrane tension in LUAD. The present study aimed to construct a prognostic model associated with membrane-tension-related genes (MRGs) and explore its prognostic value in LUAD patients. Methods: RNA sequencing data and the corresponding clinical characteristics data of LUAD were obtained from The Cancer Genome Atlas (TCGA) database. Five membrane-tension prognosis-related genes (5-MRG) were screened by univariate and multifactorial COX regression and least absolute shrinkage and selection operator (LASSO) regression analyses. The data were then divided into testing, training, and all groups to build a prognostic model, and Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), copy number variations (CNV), tumor mutation burden (TMB), and tumor microenvironment (TME) analyses were performed to explore the potential mechanisms of MRGs. Finally, single-cell data from the GSE200972 dataset in the Gene Expression Omnibus (GEO) database were obtained to determine the distribution of prognostic MRGs. Results: Construction and validation of the prognostic risk models were conducted using 5-MRG in the trial, test, and all data sets. Patients in the low-risk group had a better prognosis than those in the high-risk group, and the Kaplan-Meier survival curve and receiver operating characteristic curve (ROC) confirmed that the model had a better predictive value for LUAD patients. GO and KEGG analyses of differential genes in the high- and low-risk groups were significantly enriched in immune-related pathways. Immune checkpoint (ICP) differential genes differed significantly in the high- and low-risk groups. By analyzing the single-cell sequencing data, the cells were divided into nine subpopulations and cell subpopulation localization through 5-MRG. Conclusions: The results of this study suggest that a prognostic model based on prognosis-associated MRGs can be used to predict the prognosis of LUAD patients. Therefore, prognosis-related MRGs could be potential prognostic biomarkers and therapeutic targets.

Expression of Polyadenylate-binding Protein Cytoplasmic 1 (PABPC1) in Combination With RAD51 as Prognostic Biomarker in Patients Who Underwent Postoperative Chemotherapy for Esophageal Squamous Cell Carcinoma.

Molecular markers in the prognosis of esophageal squamous cell carcinoma (ESCC) patients who received postoperative treatments are lacking. This research aims to evaluate the prognostic value of polyadenylate-binding protein cytoplasmic 1 (PABPC1) alone and in combination with RAD51 in ESCC patients who underwent postoperative chemotherapy (CT). A total of 103 ESCC patients who underwent postoperative CT and 103 matched ones who received surgery alone were analyzed in this study. PABPC1 and RAD51 expression was assessed in cancer samples by immunohistochemistry. PABPC1 high expression (PABPC1-HE) but not that of RAD51 was associated with poor patients' survival, regardless of the postoperative treatment or node status. Patients with PABPC1 low expression and RAD51 negative expression [RAD51- (PABPC1-LE/RAD51-)] tumor had good overall survival (OS) in both the CT treated and untreated groups. Patients with PABPC1-LE/RAD51+ and PABPC1-HE/RAD51+ tumors had longer OS in the CT treated group than in the untreated group. However, PABPC1-HE/RAD51- was associated with a poor outcome in both groups and the patients with PABPC1-HE/RAD51- tumor had hardly any benefit from CT in N+ status. PABPC1 alone and in combination with RAD51 was a prognostic biomarker for OS in ESCC patients who received postoperative CT.

Construction of a prognostic model for lung squamous cell carcinoma based on immune-related genes.

Lung squamous cell carcinoma (LUSC) lacks appropriate prognostic and diagnostic strategies. Available studies suggest the effectiveness of immunotherapy for LUSC, but effective molecular markers are still insufficient. We obtained mRNA expression and clinical information of LUSC samples from The Cancer Genome Atlas (TCGA) database. Enrichment levels of immune-related genes were revealed by single sample gene set enrichment analysis. Then, differentially expressed genes (DEGs) related to immunity were obtained by differential analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. In addition, Cox regression analysis combined with LASSO method was utilized to identify immune-related prognostic genes, and an immune-related prognostic model was constructed. Kaplan-Meier and receiver operating characteristic (ROC) curves were drawn to verify the accuracy of the model. Finally, a nomogram and calibration curve were drawn to predict LUSC patients' survival. Samples were assigned into high-, medium- and low-immune groups. Compared with low- and medium-immune groups, high-immune group enriched more immune cells, with higher immune infiltration degree, and higher expression of immune checkpoints and human leukocyte antigen. DEGs were enriched in biological processes and signaling pathways related to immunity. Eleven genes (ONECUT3, MAGED4, SULT2A1, HPR, S100A5, IRS4, DPP6, FGF8, TEX38, PLAAT1 and CLEC3A) were obtained to construct an immune-related prognostic model. Riskscore served as an independent prognostic factor. Besides, the nomogram prediction model could predict disease progression in LUSC patients. The constructed risk assessment model for LUSC immune-related genes could assess LUSC patients' prognoses with great efficacy, providing guidance for the clinical treatment of LUSC.

Transient receptor potential vanilloid 4 promotes the growth of non-small cell lung cancer by regulating Foxp3.

OBJECTIVE(S): Transient receptor potential vanilloid 4 (TRPV4) participates in malignant tumor. However, the role of TRPV4 in non-small cell lung cancer (NSCLC) remains unclear. In this study, we demonstrated TRPV4 was upregulated in NSCLC tissues and NSCLC cell lines. MATERIALS AND METHODS: TRPV4 level in the NSCLC patients and cell lines were detected, and its function was studied both in vivo and vitro. RESULTS: The level of TRPV4 showed a positive correlation with tumor size of NSCLC patients. Activation TRPV4 by agonist GSK1016790A promoted cell proliferation and decreased apoptosis in A549 cells, and these effects were enhanced when the cells have overexpressed TRPV4. Moreover, GSK1016790A induced inhibitory effects on apoptosis of A549 cells was impaired when GSK1016790A used together with TRPV4 selective antagonist HC-067047, or impaired when the cells have already downregulated TRPV4 expression by TRPV4 siRNA. In vivo study, pharmacological inhibition of TRPV4 prevented A549 cells transplanted tumor growth. It was showed Foxp3 level was significantly increased in the NSCLC tissues, and showed a positive correlation with the level of TRPV4. Deactivation of TRPV4 using TRPV4 siRNA or HC-067047 significantly reduced expression of Foxp3 in GSK1016790A treated NSCLC cells. Moreover, downregulation Foxp3 by transfection of Foxp3 siRNA significantly impaired TRPV4 induced NSCLC cells proliferations in vitro. CONCLUSIONS: Antitumor effects caused by TRPV4 inhibition in NSCLC might be attributed to the suppression of Foxp3 which induced subsequent cell apoptosis. Thus, pharmacological inhibition of TRPV4 may be a promising option for NSCLC treatment.