Identification of a chemotherapy-associated gene signature for a risk model of prognosis in gastric adenocarcinoma through bioinformatics analysis

CRTAC1 identified as a promising diagnosis and prognostic biomarker in lung adenocarcinoma

CRTAC1, one of the pyroptosis-related genes, has been identified as a protective factor in certain kinds of cancer, such as gastric adenocarcinoma and bladder cancer. The study aimed to investigate the role of CRTAC1 in lung adenocarcinoma (LUAD). LUAD datasets were obtained from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA), pyroptosis-related genes from GeneCard. Limma package used to find differentially expressed genes (DEGs), least absolute shrinkage and selection operator (LASSO) regression and weighted genes co-expression network analysis (WGCNA) to identify CRTAC1 as hub gene. CRTAC1 expression was confirmed in a real-world cohort using quantitative polymerase chain reaction (qPCR) and Western Blot (WB) analyses. Cellular experiments were conducted to investigate CRTAC1's potential oncogenic mechanisms. CRTAC1 mRNA expression was significantly lower in LUAD tissues (p < 0.05) and showed high accuracy in diagnosing LUAD. Reduced CRTAC1 expression was associated with a poor prognosis. Higher CRTAC1 expression correlated with increased immune cell infiltration. Individuals with high CRTAC1 expression showed increased drug sensitivity. Additionally, qPCR and WB analyses showed that CRTAC1 expression was lower in tumor tissue compared to adjacent normal tissue at both the RNA and protein levels. Upregulation of CRTAC1 significantly inhibited LUAD cell proliferation, invasion, and migration in cellular experiments. CRTAC1 has the potential to serve as a diagnostic and prognostic biomarker in LUAD.

Identification of a fatty acid metabolism-related gene signature to predict prognosis in stomach adenocarcinoma

BACKGROUND

Fatty acid metabolism (FAM) contributes to tumorigenesis and tumor development, but the role of FAM in the progression of stomach adenocarcinoma (STAD) has not been comprehensively clarified.

METHODS

The expression data and clinical follow-up information were obtained from The Cancer Genome Atlas (TCGA). FAM pathway was analyzed by gene set enrichment analysis (GSEA) and single-sample GSEA (ssGSEA) methods. Univariate Cox regression analysis was conducted to select prognosis genes. Molecular subtypes were classified by consensus clustering analysis. Furthermore, least absolute shrinkage and selection operator (Lasso) analysis was employed to develop a risk model. ESTIMATE and tumour immune dysfunction and exclusion (TIDE) algorithm were used to assess immunity. pRRophetic package was conducted to predict drug sensitivity.

RESULTS

Based on 14 FAM related prognosis genes (FAMRG), 2 clusters were determined. Patients in C2 showed a worse overall survival (OS). Furthermore, a 7-FAMRG risk model was established as an independent predictor for STAD, with a higher riskscore indicating an unfavorable OS. High riskscore patients had higher TIDE score and these patients were more sensitive to anticancer drugs such as Bortezomib, Dasatinib and Pazopanib. A nomogram based on riskscore was an effective prediction tool applicable to clinical settings. The results from pan-cancer analysis supported a prominent application value of riskscore model in other cancer types.

CONCLUSION

The FAMRGs model established in this study could help predict STAD prognosis and offer new directions for future studies on dysfunctional FAM-induced damage and anti-tumor drugs in STAD disease.

Prostate transmembrane androgen inducible protein 1 (PMEPA1): regulation and clinical implications

Prostate transmembrane androgen inducible protein 1 (PMEPA1) can promote or inhibit prostate cancer cell growth based on the cancer cell response to the androgen receptor (AR). Further, it can be upregulated by transforming growth factor (TGF), which downregulates transforming growth factor-β (TGF-β) signaling by interfering with R-Smad phosphorylation to facilitate TGF-β receptor degradation. Studies have indicated the increased expression of PMEPA1 in some solid tumors and its functioning as a regulator of multiple signaling pathways. This review highlights the multiple potential signaling pathways associated with PMEPA1 and the role of the PMEPA1 gene in regulating prognosis, including transcriptional regulation and epithelial mesenchymal transition (EMT). Moreover, the relevant implications in and outside tumors, for example, as a biomarker and its potential functions in lysosomes have also been discussed.

Evaluation of vital genes correlated with CD8 + T cell infiltration as prognostic biomarkers in stomach adenocarcinoma

BACKGROUND

Infiltration of CD8 + T cells in the tumor microenvironment is correlated with better prognosis in various malignancies. Our study aimed to investigate vital genes correlated with CD8 + T cell infiltration in stomach adenocarcinoma (STAD) and develop a new prognostic model.

METHODS

Using the STAD dataset, differentially expressed genes (DEGs) were analyzed, and co-expression networks were constructed. Combined with the CIBERSORT algorithm, the most relevant module of WGCNA with CD8 + T cell infiltration was selected for subsequent analysis. The vital genes were screened out by univariate regression analysis to establish the risk score model. The expression of the viral genes was verified by lasso regression analysis and in vitro experiments.

RESULTS

Four CD8 + T cell infiltration-related genes (CIDEC, EPS8L3, MUC13, and PLEKHS1) were correlated with the prognosis of STAD. Based on these genes, a risk score model was established. We found that the risk score could well predict the prognosis of STAD, and the risk score was positively correlated with CD8 + T cell infiltration. The validation results of the gene expression were consistent with TCGA. Furthermore, the risk score was significantly higher in tumor tissues. The high-risk group had poorer overall survival (OS) in each subgroup.

CONCLUSIONS

Our study constructed a new risk score model for STAD prognosis, which may provide a new perspective to explore the tumor immune microenvironment mechanism in STAD.