Transcriptomic analysis identifies CYP27A1 as a diagnostic marker for the prognosis and immunity in lung adenocarcinoma.

BACKGROUND: The association between lipid metabolism disorder and carcinogenesis is well-established, but there is limited research on the connection between lipid metabolism-related genes (LRGs) and lung adenocarcinoma (LUAD). The objective of our research was to identify LRGs as the potential biomarkers for prognosis and assess their impact on immune cell infiltration in LUAD. METHODS: We identified novel prognostic LRGs for LUAD patients via the bioinformatics analysis. CYP27A1 expression level was systematically evaluated via various databases, such as TCGA, UALCAN, and TIMER. Subsequently, LinkedOmics was utilized to perform the CYP27A1 co-expression network and GSEA. ssGSEA was conducted to assess the association between infiltration of immune cells and CYP27A1 expression. CYP27A1's expression level was validated by qRT-PCR analysis. RESULTS: CYP27A1 expression was decreased in LUAD. Reduced CYP27A1 expression was linked to unfavorable prognosis in LUAD. Univariate and multivariate analyses indicated that CYP27A1 was an independent prognostic biomarker for LUAD patients. GSEA results revealed a positive correlation between CYP27A1 expression and immune-related pathways. Furthermore, CYP27A1 expression was positively correlated with the infiltration levels of most immune cells. CONCLUSION: CYP27A1 is a potential biomarker for LUAD patients, and our findings provided a novel perspective to develop the prognostic marker for LUAD patients.

The identification of hub biomarkers and pathways in lung cancer and prognostic evaluation.

Background: Lung cancer is the most frequently diagnosed malignant tumor and the highest mortality worldwide, and can be divided into two differential histologic subtypes, non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). However, there are significant differences in diagnosis and prognosis between NSCLC and SCLC. We aimed to identify hub differentially expressed genes (DEGs) and pathways for diagnostic and prognostic prediction in NSCLC and SCLC. Methods: Three expression profiles (GSE43346, GSE40275 and GSE18842) were obtained through GEO2R tools from Gene Expression Omnibus (GEO) database. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to investigate functional enrichment of the DEGs. The protein-protein interaction network was constructed by the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. Kaplan-Meier analysis was performed using Kaplan-Meier plotter and Gene Expression Profiling Interactive Analysis (GEPIA). Results: We have identified 84 overlap DEGs that may play an important role in SCLC & NSCLC. However, we also found some genes were only significantly differential expressed in SCLC or NSCLC. There were 87 DEGs unique to SCLC tissues and 28 DEGs unique to NSCLC ones. Functional analysis results indicated that these DEGs had different biological functions and were significantly enriched in different pathways. Hub DEGs were identified via protein-protein interaction network and cross-validated using Kaplan-Meier plotter and GEPIA. The 14 hub DEGs were highly correlated with the overall survival of NSCLC. Kyoto Encyclopedia of Genes and Genome (KEGG) re-analysis of 14 hub DEGs showed that RRM2, CHEK1 and SERPINB5 enriched in the p53 signaling pathway, RRM2 and TYMS enriched in pyrimidine metabolism pathway maybe play a key role in SCLC&NSCLC and were significantly related to overall survival in patients with NSCLC. Conclusions: RRM2, CHEK1, TYMS and SERPINB5, which are mainly enriched in the p53 signaling pathway and pyrimidine metabolism pathway, were significantly associated with the overall survival of NSCLC patients. These genes could serve as potential prognostic markers in NSCLC and therapeutic target in lung cancer for personalized oncology.

miR-133a-5p suppresses gastric cancer through TCF4 down-regulation.

BACKGROUND: The effect of microRNAs (miRNA) on cancer regulations has received a considerable amount of attention recently. MiR-133a-5p has been identified as an anti-tumor miRNA in several types of cancers. However, the effect of miR-133a-5p on gastric cancer (GC) have not been uncovered. In this study, we sought to evaluate the regulation of TCF4 expression by miR-133-5p and the role of the miR-25-3p/TCF4 axis in the progression of GC, with the aim of identifying a potential therapeutic target for GC. METHODS: TCGA (The Cancer Genome Atlas), GTEx (The Genotype-Tissue Expression) and GEO (Gene Expression Omnibus) database were used to analyze the expression and prognosis. We performed MTT and EdU assays to elucidate the effect on cell replication. Apoptotic cells were stained with annexin V-fluorescein isothiocyanate and propidium iodide to stain, and then analyzed by flow cytometry. The effect on cell metastasis was investigated in wound healing and transwell assays. A dual-luciferase reporter assay was used to check for the direct targeting of TCF4 by miR-133a-5p. Bioinformatic analysis of the relationship of TCF4 with tumor microenvironment and the signaling cascade of TCF4 was finally performed. RESULTS: We found that the level of miR-133a-5p was decreased in both tumor tissues and GC cell lines. MiR-133a-5p inhibited cell growth and metastasis, but promoted cell apoptosis. MiR-133a-5p directly targeted TCF4 and downregulated its expression. TCF4 was highly expressed in tumor and higher level of TCF4 indicated poorer prognosis. Moreover, TCF4 overexpression reversed the aforementioned anti-tumor activity of miR-133a-5p. The expression level of TCF4 was significantly correlated with tumor-infiltrating immune cells. CONCLUSIONS: Our findings altogether reveal that miR-133a-5p can serve as a tumor suppressor in gastric cancer via the miR-133a-5p/TCF4 pathway.

Identification of Potential Biomarkers Associated with Prognosis in Gastric Cancer via Bioinformatics Analysis.

BACKGROUND Gastric cancer (GC) is one of the leading causes of cancer-related mortality worldwide. We aimed to identify differentially expressed genes (DEGs) and their potential mechanisms associated with the prognosis of GC patients. MATERIAL AND METHODS This study was based on gene profiling information for 37 paired samples of GC and adjacent normal tissues from the GSE118916, GSE79973, and GSE19826 datasets in the Gene Expression Omnibus database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to investigate the biological role of the DEGs. The protein-protein interaction (PPI) network was constructed by Cytoscape, and the Kaplan-Meier plotter was used for prognostic analysis. RESULTS We identified 119 DEGs, including 21 upregulated and 98 downregulated genes, in GC. The 21 upregulated genes were mainly enriched in extracellular matrix-receptor interaction, focal adhesion, and transforming growth factor-ß signaling, while the 98 downregulated genes were significantly associated with gastric acid secretion, retinol metabolism, and metabolism of xenobiotics by cytochrome P450. Thirty hub DEGs were obtained for further analysis. Twenty-five of the 30 hub DEGs were significantly associated with the prognosis of GC, and 21 of the 25 hub DEGs showed consistent expression trends within the 3 profile datasets. KEGG reanalysis of these 21 hub DEGs showed that COL1A1, COL1A2, COL2A1, COL11A1, THBS2, and SPP1 were mainly enriched in the extracellular matrix-receptor interaction pathways. CONCLUSIONS We identified 6 genes that were significantly related to the prognosis of GC patients. These genes and pathways could serve as potential prognostic markers and be used to develop treatments for GC patients.

Vascular Endothelial Growth Factor and Cluster of Differentiation 34 for Assessment of Perioperative Bleeding Risk in Gastric Cancer Patients.

BACKGROUND: Angiogenesis is the formation of new blood vessels to supply nutrients to tumors. Vascular endothelial growth factor (VEGF) and cluster of differentiation 34 (CD34) are important signaling proteins involved in angiogenesis. Many studies have demonstrated that VEGF and CD34 are related to tumor progression. This study focused on the relationship between VEGF, CD34, and perioperative hemorrhage in patients with gastric cancer. METHODS: To observe the relationship between VEGF and CD34, we tracked 112 patients with advanced gastric cancer for 5 years to assess factors related to hemorrhage, using immunohistochemistry. The results were subjected to statistical analysis using a 2 × 2 contingency table, logistic regression, and receiver operating characteristic (ROC) test. RESULTS: The concentrations of VEGF and CD34 were critically correlated with perioperative hemorrhage and neural invasion in patients with gastric cancer (P < 0.05). Expression of VEGF and CD34 was related (P < 0.05, χ2 = 6.834). VEGF and CD34 co-expression strongly increased the risk of preoperative bleeding (area under the ROC curve >0.7, P < 0.05). CONCLUSIONS: Expression of VEGF and CD34 was critically correlated with perioperative hemorrhage in gastric cancer patients. Co-expression of VEGF and CD34 could be an effective indicator for evaluating the risk of perioperative bleeding in gastric cancer patients.