Identification of potential key genes in esophageal adenocarcinoma using bioinformatics

The function and immune role of cuproptosis associated hub gene in Barrett's esophagus and esophageal adenocarcinoma

Barrett's esophagus (BE) is a precancerous lesion of esophageal adenocarcinoma (EAC), with approximately 3-5% of patients developing EAC. Cuproptosis is a kind of programmed cell death phenomenon discovered in recent years, which is related to the occurrence and development of many diseases. However, its role in BE and EAC is not fully understood. We used single sample Gene Set Enrichment Analysis (ssGSEA) for differential analysis of BE in the database, followed by enrichment analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO) and GSEA, Protein-Protein Interaction (PPI), Weighted Gene Co-expression Network Analysis (WGCNA), Receiver Operating Characteristic Curve (ROC) and finally Quantitative Real Time Polymerase Chain Reaction (qRT-PCR) and immunohistochemistry (IHC) of clinical tissues. Two hub genes can be obtained by intersection of the results obtained from the cuproptosis signal analysis based on BE. The ROC curves of these two genes predicted EAC, and the Area Under the Curve (AUC) values could reach 0.950 and 0.946, respectively. The mRNA and protein levels of Centrosome associated protein E (CENPE) and Shc SH2 domain binding protein 1 (SHCBP1) were significantly increased in clinical EAC tissues. When they were grouped by protein expression levels, high expression of CENPE or SHCBP1 had a poor prognosis. The CENPE and SHCBP1 associated with cuproptosis may be a factor promoting the development of BE into EAC which associated with the regulation of NK cells and T cells.

Defining the elusive oncogenic role of the methyltransferase TMT1B

Methyltransferases are enzymes fundamental to a wide range of normal biological activities that can become dysregulated during oncogenesis. For instance, the recent description of the methyltransferase-like (METTL) family of enzymes, has demonstrated the importance of the N⁶-adenosine-methyltransferase (m⁶A) modification in transcripts in the context of malignant transformation. Because of their importance, numerous METTL family members have been biochemically characterized to identify their cellular substrates, however some members such as METTL7B, recently renamed TMT1B and which is the subject of this review, remain enigmatic. First identified in the stacked Golgi, TMT1B is also localized to the endoplasmic reticulum as well as lipid droplets and has been reported as being upregulated in a wide range of cancer types including lung cancer, gliomas, and leukemia. Interestingly, despite evidence that TMT1B might act on protein substrates, it has also been shown to act on small molecule alkyl thiol substrates such as hydrogen sulfide, and its loss has been found to affect cellular proliferation and migration. Here we review the current evidence for TMT1B's activity, localization, and potential biological role in the context of both normal and cancerous cell types.

Model construction and risk analysis of the lncRNA genes associated with the prognosis of esophageal adenocarcinoma with immune infiltration

Background

Our study analyzed the immune infiltration of esophageal adenocarcinoma (EAC) tumor cells and identified long non-coding ribonucleic acid (lncRNA) genes to construct a prognostic model of EAC to evaluate the survival prognosis of patients and explore potential therapeutic targets.

Methods

The data of 89 patients with EAC, including 11 normal tissue samples and 78 EAC of tumor tissue samples, were downloaded from The Cancer Genome Atlas public database. Perl script and R software were used to run the code, conduct the statistical analysis, calculate the risk coefficients of the patients, and conduct the Cox regression analysis, immune-related lncRNA survival analysis, risk analysis, principal component analysis (PCA), and receiver operating characteristic (ROC) curve analysis.

Results

We screened and identified 19 prognostic biomarkers, including LINC01612, AC008443.2, and LINC02582, allocated the patients into high- and low-risk groups, and found significant differences in the prognosis between the high- and low-risk groups using the Kaplan-Meier survival analysis (P<0.001). A ROC curve was used to evaluate the feasibility of the prognostic model for EAC, and we found that the model had high predictability (area under the curve =0.964). A PCA analysis was performed of the complex transcriptome sequencing data and other cubes to transform the data into a 3-dimensional space constructed by feature vectors.

Conclusions

Our study effectively screened and identified the lncRNA genes related to the immune infiltration of EAC and successfully constructed a prognostic model. In total, 19 potential diagnostic and therapeutic target genes, including LINC01612, AC008443.2, and LINC02582, were identified that have certain significance in guiding the clinical treatment of EAC patients.

METTL7B contributes to the malignant progression of glioblastoma by inhibiting EGR1 expression

Glioblastoma (GBM), a predominant central nervous system (CNS) malignancy, is correlated with high mortality and severe morbidity. Mammalian methyltransferase-like 7B (METTL7B) as a methyltransferase has been identified to participate in cancer progression. However, its function in GBM is elusive. Accordingly, we aimed to explore the effect of METTL7B on GBM. The expression of METTL7B and EGR2 in GBM patients and GBM cells were detected by qPCR, western blots and immunohistochemical staining. Cell viability was assessed by CCK-8 assays. Cell proliferation was determined by EdU, colony formation, and tumor sphere formation assays. METTL7B shRNA was injected into the Balb/c nude mice. The size and weight of isolated tumor was measured. And the expression levels of Ki67, METTL7B and EGR1 were examined by immunohistochemical staining. METTL7B was significantly elevated, while EGR1 was downregulated in clinical GBM tissues. METTL7B upregulation was associated with the low overall survival of GBM patients. Moreover, METTL7B depletion remarkably attenuated GBM cell proliferation. Mechanistically, METTL7B overexpression inhibited EGR1 expression in GBM cells. EGR1 knockdown rescued the inhibitory effect of METTL7B depletion on GBM cell proliferation. Meanwhile, METTL7B depletion arrested more GBM cells at the G0/G1, but fewer cells at the S phase, which EGR1 knockdown reversed these effects. Furthermore, tumorigenicity analysis revealed that METTL7B promotes tumor growth of GBM cells in vivo. METTL7B contributes to the malignant progression of GBM by inhibiting EGR1 expression. METTL7B and EGR1 may be utilized as the treatment targets for GBM therapy.

Identification of Molecular Biomarkers and Key Pathways for Esophageal Carcinoma (EsC): A Bioinformatics Approach

Esophageal carcinoma (EsC) is a member of the cancer group that occurs in the esophagus; globally, it is known as one of the fatal malignancies. In this study, we used gene expression analysis to identify molecular biomarkers to propose therapeutic targets for the development of novel drugs. We consider EsC associated four different microarray datasets from the gene expression omnibus database. Statistical analysis is performed using R language and identified a total of 1083 differentially expressed genes (DEGs) in which 380 are overexpressed and 703 are underexpressed. The functional study is performed with the identified DEGs to screen significant Gene Ontology (GO) terms and associated pathways using the Database for Annotation, Visualization, and Integrated Discovery repository (DAVID). The analysis revealed that the overexpressed DEGs are principally connected with the protein export, axon guidance pathway, and the downexpressed DEGs are principally connected with the L13a-mediated translational silencing of ceruloplasmin expression, formation of a pool of free 40S subunits pathway. The STRING database used to collect protein-protein interaction (PPI) network information and visualize it with the Cytoscape software. We found 10 hub genes from the PPI network considering three methods in which the interleukin 6 (IL6) gene is the top in all methods. From the PPI, we found that identified clusters are associated with the complex I biogenesis, ubiquitination and proteasome degradation, signaling by interleukins, and Notch-HLH transcription pathway. The identified biomarkers and pathways may play an important role in the future for developing drugs for the EsC.

Identification and Validation of Immune- and Stemness-Related Prognostic Signature of Melanoma

Purpose: Our aim was to construct a signature that accurately predicted the prognostic and immune response of melanoma. Methods: First, the weighted co-expression network analysis (WGCNA) algorithm was used to identify the hub genes related to clinical phenotypes of melanoma in the cancer genome atlas (TCGA) database. Nest, the least absolute shrinkage and selection operator (LASSO) analysis was used to dimensionality reduction of these hub genes and constructed a prognostic signature to predict the prognosis and immunosuppressive response of melanoma. Result: Through in-depth analysis, we constructed a 5-mRNA prognostic signature and verified its prognostic value in internal (TCGA-SKCM, n = 452) and external independent datasets (GSE53118, n = 79). Based on this signature, the tumor immune microenvironment (TME) of melanoma was characterized, and the result was found that patients in the high-risk group had lower CD8 T cell infiltration and immune checkpoint expression (PD-1, PD-L1, CTLA4), as well as higher M0/M2 macrophage infiltration. Our results also found the risk score based on a 5-mRNA signature was significantly associated with tumor mutational burden (TMB) and tumor stem cell markers (CD20, CD38, ABCB5, CD44, etc.). Lastly, we built a nomogram for clinician prediction for the prognosis of patients with melanoma. Conclusion: Our findings indicated that the 5-mRNA signature has an important predictive value for the overall survival of melanoma. By analyzing the tumor immune microenvironment and tumor stem cell marker between different groups, a new method is provided for the stratified diagnosis and treatment of melanoma.

METTL7B is a novel prognostic biomarker of lower-grade glioma based on pan-cancer analysis

Methyltransferase-like 7B (METTL7B) is a member of the methyltransferase-like protein family that plays an important role in the development and progression of tumors. However, its prognostic value and the correlation of METTL7B expression and tumor immunity in some cancers remain unclear. By analyzing online data, we found that METTL7B is abnormally overexpressed in multiple human tumors and plays an important role in the overall survival (OS) of patients with 8 cancer types and disease-free survival (DFS) of patients with 5 cancer types. Remarkably, METTL7B expression was positively correlated with the OS and DFS of patients with lower-grade glioma (LGG). In addition, a positive correlation between METTL7B expression and immune cell infiltration in LGG was observed. Moreover, we identified a strong correlation between METTL7B expression and immune checkpoint gene expression in kidney chromophobe (KICH), LGG and pheochromocytoma and paraganglioma (PCPG). Furthermore, METTL7B was involved in the extracellular matrix (ECM) and immune-related pathways in LGGs. Finally, in vitro experiments showed that knockdown of METTL7B inhibited the growth, migration, invasion and the epithelial–mesenchymal transition (EMT) of LGG cells. METTL7B expression potentially represents a novel prognostic biomarker due to its significant association with immune cell infiltration in LGG.

Prognostic value of microRNA-378 in esophageal cancer and its regulatory effect on tumor progression

The incidence and mortality rates of esophageal squamous cell carcinoma (ESCC) are high in China, which has increased the clinical and economic burden. The present study aimed to investigate the role of microRNA (miRNA/miR)-378 in ESCC. Reverse transcription-quantitative polymerase chain reaction analysis was performed to detect miR-378 expression in ESCC tissues and cell lines. Survival analysis was performed using the Kaplan-Meier method, while Cox regression analysis was performed to determine the prognostic value of miR-378 in ESCC. miR-378 mimic and miR-378 inhibitor was transfected into ESCC cells to overexpress or knockdown miR-378 expression levels in ESCC cells. The Cell Counting Kit-8 assay was performed to assess the proliferative ability of ESCC cells, while the Transwell assay was conducted to assess the effect of miR-378 on the migratory and invasive abilities of ESCC cells. The results demonstrated that miR-378 displayed significantly lower expression both in ESCC cells and tissues by comparison with those in normal cells and adjacent tissues. In addition, patients with low miR-378 expression had a worse prognosis and a shorter overall survival time than those with high miR-378 expression. Furthermore, low miR-378 expression promoted ESCC cell proliferation, migration and invasion. Taken together, the results of the present study suggest that miR-378 may act as a tumor suppressor in the occurrence and development of ESCC.

Human METTL7B is an alkyl thiol methyltransferase that metabolizes hydrogen sulfide and captopril

Methylation of alkyl thiols is a biotransformation pathway designed to reduce thiol reactivity and potential toxicity, yet the gene and protein responsible for human alkyl thiol methyltransferase (TMT) activity remain unknown. Here we demonstrate with a range of experimental approaches using cell lines, in vitro systems, and recombinantly expressed enzyme, that human methyltransferase-like protein 7B (METTL7B) catalyzes the transfer of a methyl group from S-adenosyl-L-methionine (AdoMet) to hydrogen sulfide (H2S) and other exogenous thiol small molecules. METTL7B gene modulation experiments, including knockdown in HepG2 cells and overexpression in HeLa cells, directly alter the methylation of the drug captopril, a historic probe substrate for TMT activity. Furthermore, recombinantly expressed and purified wild-type METTL7B methylates several thiol compounds, including H2S, 7α-thiospironolactone, L-penicillamine, and captopril, in a time- and concentration-dependent manner. Typical for AdoMet-dependent small molecule methyltransferases, S-adenosyl-L-homocysteine (AdoHcy) inhibited METTL7B activity in a competitive fashion. Similarly, mutating a conserved aspartate residue, proposed to anchor AdoMet into the active site, to an alanine (D98A) abolished methylation activity. Endogenous thiols such as glutathione and cysteine, or classic substrates for other known small molecule S-, N-, and O-methyltransferases, were not substrates for METTL7B. Our results confirm, for the first time, that METTL7B, a gene implicated in multiple disease states including rheumatoid arthritis and breast cancer, encodes a protein that methylates small molecule alkyl thiols. Identifying the catalytic function of METTL7B will enable future pharmacological research in disease pathophysiology where altered METTL7B expression and, potentially H2S levels, can disrupt cell growth and redox state.

Study on the Selection of the Targets of Esophageal Carcinoma and Interventions of Ginsenosides Based on Network Pharmacology and Bioinformatics

Background

Esophageal carcinoma (ESCA) is not only a threat to people's health but also the sixth most common cause of cancer-related mortality worldwide.

Methods

In this study, the key targets of ESCA are screened through GeneCards and DisGeNET databases combined with the Gene Expression Omnibus (GEO) database (GSE1420 and GSE20347). Then, data associated with ESCA samples are downloaded from The Cancer Genome Atlas (TCGA) database for integrated analysis. Moreover, the effect of epithelial cell adhesion molecule (EpCAM) expression on the survival of patients with ESCA is evaluated by Kaplan–Meier and Cox analyses. The virtual screening is carried out using a Suflex-Dock molecular docking module. The chemical components, which have been well bound to EpCAM, are screened out based on a total score >5 as a threshold. Ginsenosides and EpCAM are analyzed by LigPlot + v.2.2 software to identify the binding sites.

Results

Four ESCA targets are obtained from GeneCards, DisGeNET, and GEO databases. In this study, it is found that high EpCAM expression is associated with histologic grade, stage, patient age, N classification, T classification, and radiation therapy. The Kaplan–Meier curves for overall survival also show that the higher expression of EpCAM is associated with worse outcomes in patients with ESCA. Univariate and multivariate Cox analyses indicate that EpCAM mRNA expression might be a useful biomarker for ESCA(P < 0.05). Molecular docking technology suggests that ginsenoside Rg3 and ginsenoside Rh2 can easily establish good docking modes and have a high affinity with EpCAM. The 6′-hydroxyl and 6″-hydroxyl on the 3-glycosyl of ginsenoside Rg3 are prone to form hydrogen bonds (Lys151 and Lys221) with the active sites of EpCAM ligand binding domain. The hydroxyl groups on the 12 sites of the ginsenoside Rh2 glycoside framework are found to have hydrogen bonding with Leu240. The formation of hydrogen bonds plays an important role in binding of ginsenoside Rg3 and ginsenoside Rh2 to EpCAM, as well as the stability of EpCAM conformation.

Conclusion

EpCAM may be determined as a potential biomarker for early diagnosis and prognosis of ESCA. Ginsenoside Rg3 and ginsenoside Rh2 have potential antiesophageal cancer activities. This experiment provides a reference for the study of the chemical compositions of ginsenosides in the treatment of esophageal cancer.