ECE2 is a prognostic biomarker associated with m6A modification and involved in immune infiltration of lung adenocarcinoma.

Background: The targeted therapy for lung cancer relies on prognostic genes and requires further research. No research has been conducted to determine the effect of endothelin-converting enzyme 2 (ECE2) in lung cancer. Methods: We analyzed the expression of ECE2 in lung adenocarcinoma (LUAD) and normal adjacent tissues and its relationship with clinicopathological characteristics from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus database (GEO). Immunohistochemical staining was used to further validate the findings. GO/KEGG enrichment analysis and gene set enrichment analysis (GSEA) of ECE2 co-expression were performed using R software. Data from TIMER, the GEPIA database, and TCGA were analyzed to determine the relationship between ECE2 expression and LUAD immune infiltration. To investigate the relationship between ECE2 expression levels and LUAD m6A modification, TCGA data and GEO data were analyzed. Results: ECE2 is highly expressed in various cancers including LUAD. ECE2 showed high accuracy in distinguishing tumor and normal sample results. The expression level of ECE2 in LUAD was significantly correlated with tumor stage and prognosis. GO/KEGG enrichment analysis showed that ECE2 was closely related to mitochondrial gene expression, ATPase activity and cell cycle. GSEA analysis showed that ECE2-related differential gene enrichment pathways were related to mitotic cell cycle, MYC pathway, PLK1 pathway, DNA methylation pathway, HIF1A pathway and Oxidative stress-induced cellular senescence. Analysis of the TIMER, GEPIA database, and TCGA datasets showed that ECE2 expression levels were significantly negatively correlated with B cells, CD4+ cells, M2 macrophages, neutrophils, and dendritic cells. TCGA and GEO datasets showed that ECE2 was significantly associated with m6A modification-related genes HNRNPC, IGF2BP1, IGF2BP3 and RBM1. Conclusion: ECE2 is associated with m6A modification and immune infiltration and is a prognostic biomarker in LUAD.

High expression of HNRNPR in ESCA combined with 18F-FDG PET/CT metabolic parameters are novel biomarkers for preoperative diagnosis of ESCA.

BACKGROUND: The aim of this study was to determine the expression and function of heterogeneous nuclear ribonucleoprotein R (HNRNPR) in esophageal carcinoma (ESCA), the correlation between its expression and 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computerized tomography scan (PET/CT)-related parameters. We also investigated whether 18F-FDG PET/CT can be used to predict the expression of HNRNPR in ESCA. METHODS: We analyzed patients with ESCA who underwent 18F-FDG PET/CT before surgery, and their tissues were stained with HNRNPR IHC. The associated parameters were derived using the 18F-FDG PET imaging data, and the correlation with the IHC score was evaluated. The Oncomine, TCGA, and GEO datasets were used to investigate HNRNPR expression in the pan- and esophageal cancers, as well as its relationship with N6-methyladenosine (m6A) modification and glycolysis. The R software, LinkedOmics, GeneMANIA, and StringOnline tools were used to perform GO/KEGG, GGI, and PPI analyses on the HNRNPR. RESULTS: HNRNPR is highly expressed in the majority of pan-cancers, including ESCA, and is associated with BMI, weight, and history of reflux in patients with ESCA. HNRNPR is somewhat accurate in predicting the clinical prognosis of ESCA. HNRNPR expression was positively correlated with SUVmax, SUVmean, and TLG in ESCA (p < 0.05). The combination of these three variables provides a strong predictive value for HNRNPR expression in ESCA. GO/KEGG analysis showed that HNRNPR played a role in the regulation of cell cycle, DNA replication, and the Fannie anemia pathway. The analysis of the TCGA and GEO data sets revealed a significant correlation between HNRNPR expression and m6A and glycolysis-related genes. GSEA analysis revealed that HNRNPR was involved in various m6A and glycolysis related-pathways. CONCLUSION: HNRNPR overexpression correlates with 18F-FDG uptake in ESCA and may be involved in the regulation of the cell cycle, m6A modification, and cell glycolysis. 18F-FDG PET/CT-related parameters can predict the diagnostic accuracy of HNRNPR expression in ESCA.

Comprehensive Analysis of SLC17A9 and Its Prognostic Value in Hepatocellular Carcinoma.

Background: Solute carrier family 17 member 9 (SLC17A9) encodes a member of a family of transmembrane proteins that are involved in the transport of small molecules. SLC17A9 is involved in the occurrence and development of various cancers, but its biological role in liver hepatocellular carcinoma (LIHC) is unclear. Methods: The expression level of SLC17A9 was assessed using The Cancer Genome Atlas (TCGA) database and immunohistochemistry of tumor tissues and adjacent normal liver tissues. The receiver operating characteristic (ROC) and R software package performed diagnosis and prognosis. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes functional enrichment and co-expression of SLC17A9, gene-gene interaction (GGI), and protein-protein interaction (PPI) networks were performed using R, GeneMANIA, and STRING. Western blot, real-time quantitative PCR (RT-qPCR), immunofluorescence, colony formation, wound scratch assay, ATP production assays, and high connotation were applied to determine the effect of SLC17A9 knockdown on HEPG2 (hepatocellular liver carcinoma) cells. TIMER, GEPIA, and TCGA analyzed the relationship between SLC17A9 expression and immune cells, m6A modification, and ferroptosis. Results: SLC17A9 expression in LIHC tissues was higher than in normal liver tissues (p < 0.001), and SLC17A9 was related to sex, DSS (disease-specific survival), and PFI (progression-free interval) (p = 0.015, 0.006, and 0.023). SLC17A9 expression has diagnostic (AUC: 0.812; CI: 0.770-0.854) and prognostic potential (p = 0.015) in LIHC. Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) functional enrichment analysis showed that SLC17A9 was closely related to neuronal cell body, presynapse, axonogenesis, PI3K/Akt signaling pathway. GGI showed that SLC17A9 was closely related to MYO5A. PPI showed that SLC17A9 was closely related to SLC18A3. SLC17A9 silencing inhibited HepG2 cells proliferation, migration, colony formation, and reduced their ATP level. SLC17A9 expression level was related to immune cells: B cells (r = 0.094, P = 8.06E-02), CD4+ T cells (r = 0.184, P = 5.95E-04), and macrophages (r = 0.137, P = 1.15E-02); m6A modification: HNRNPC (r = 0.220, p < 0.001), METTL3 (r = 0.180, p < 0.001), and WTAP (r = 0.130, p = 0.009); and ferroptosis: HSPA5 (r = 0.240, p < 0.001), SLC7A11 (r = 0.180, p < 0.001), and FANCD2 (r = 0.280, p < 0.001). Conclusion: Our data show that SLC17A9 may influence LIHC progression. SLC17A9 expression correlates with tumor immune infiltration, m6A modification, and ferroptosis in LIHC and may have diagnostic and prognostic value in LIHC.

Comprehensive Analysis of YTHDF1 Immune Infiltrates and ceRNA in Human Esophageal Carcinoma.

Background: YTHDF1 is highly expressed in multiple tumors and affects tumor progression. However, there are only a few comprehensive studies on the analysis of YTHDF1 in esophageal cancer. Methods: We analyzed YTHDF1 expression in pan-cancer by comparing both the GEPIA and TCGA cohorts, and further verified the differences in YTHDF1 expression between the ESCA and normal groups by the GEO ESCA cohort and in vitro experiments. The correlation of YTHDF1 expression and the clinical characteristics of ESCA patients was analyzed using the TCGA ESCA clinical data. The GO and KEGG enrichment analyses of the YTHDF1 coexpressed genes were completed by bioinformatics analysis, and the GGI and PPI were constructed for the YTHDF1, respectively. The relationship between YTHDF1 expression and the infiltration of ESCA immune cells was analyzed by using the TIMER database and the TCGA ESCA cohort. The relationships between YTHDF1 expression levels and glycolysis and ferroptosis-related genes were analyzed using the TCGA and GEPIA ESCA cohorts. Finally, the ceRNA network that may be involved in YTHDF1 in ESCA was predicted and constructed through a variety of databases. Results: YTHDF1 was overexpressed in various cancers, and in vitro experiments confirmed that YTHDF1 expression was higher in ESCA samples than in normal samples. The expression of YTHDF1 has some accuracy in predicting the tumor outcome. Expression of YTHDF1 was significantly associated with multiple clinical features in ESCA patients. GO and KEGG enrichment analyses indicated that YTHDF1 coexpressed genes involved multiple biological functions. There is a potential association between YTHDF1 expression and multiple immune cell infiltration, glycolysis, and ferroptosis-related genes in ESCA. YTHDF1 may be involved in multiple ceRNA regulatory networks in ESCA, including PAXIP1-AS1/hsa-miR-376c-3p/YTHDF1 axis, THUMPD3-AS1/hsa-miR-655-3p/YTHDF1 axis, and SNHG20/hsa-miR-655-3p/YTHDF1 axis, respectively. Conclusion: YTHDF1 can serve as a biomarker of ESCA, related to the immune cell infiltration of ESCA, regulation of glycolysis and ferroptosis, and the ceRNA regulatory network.

SLC2A1 is a Diagnostic Biomarker Involved in Immune Infiltration of Colorectal Cancer and Associated With m6A Modification and ceRNA.

Background: Overexpression of solute carrier family 2 member 1 (SLC2A1) promotes glycolysis and proliferation and migration of various tumors. However, there are few comprehensive studies on SLC2A1 in colorectal cancer (CRC). Methods: Oncomine, The Cancer Genome Atlas (TCGA), and Gene Expression Omnibus (GEO) databases were used to analyze the expression of SLC2A1 in pan-cancer and CRC and analyzed the correlation between SLC2A1 expression and clinical characteristics of TCGA CRC samples. The expression level of SLC2A1 in CRC was certified by cell experiments and immunohistochemical staining analysis. The Genome Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) analyses of SLC2A1 relative genes were completed by bioinformatics analysis. The correlation between SLC2A1 expression level and CRC immune infiltration cell was analyzed by Tumor IMmune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), and TCGA database. The correlation between SLC2A1 expression level and ferroptosis and m6A modification of CRC was analyzed by utilizing TCGA and GEO cohort. Finally, the possible competing endogenous RNA (ceRNA) networks involved in SLC2A1 in CRC are predicted and constructed through various databases. Results: SLC2A1 is highly expressed not only in CRC but also in many other tumors. ROC curve indicated that SLC2A1 had high predictive accuracy for the outcomes of tumor. The SLC2A1 expression in CRC was closely correlated with tumor stage and progression free interval (PFI). GO, KEGG, and GSEA analysis indicated that SLC2A1 relative genes were involved in multiple biological functions. The analysis of TIMER, GEPIA, and TCGA database indicated that the SLC2A1 mRNA expression was mainly positively associated with neutrophils. By the analysis of the TCGA and GEO cohort, we identified that the expression of SLC2A1 is closely associated to an m6A modification relative gene Insulin Like Growth Factor 2 MRNA Binding Protein 3 (IGF2BP3) and a ferroptosis relative gene Glutathione Peroxidase 4 (GPX4). Conclusion: SLC2A1 can be used as a biomarker of CRC, which is associated to immune infiltration, m6A modification, ferroptosis, and ceRNA regulatory network of CRC.

Corrigendum: NPM1 Is a Prognostic Biomarker Involved in Immune Infiltration of Lung Adenocarcinoma and Associated With m6A Modification and Glycolysis.

[This corrects the article DOI: 10.3389/fimmu.2021.724741.].

18F-FDG PET/CT metabolic parameters correlate with EIF2S2 expression status in colorectal cancer.

Background: We sought to investigate whether the expression of the gene EIF2S2 is related to 18F-FDG PET/CT metabolic parameters in patients with colorectal cancer (CRC). Materials and methods: The expression of EIF2S2 in CRC and its relationship with clinicopathological features were obtained through the ONCOMINE, UALCAN and GEPIA databases. EIF2S2 and GLUT1 expression were examined by immunohistochemistry in 42 CRC patients undergoing preoperative PET-CT examination. Spearman correlation analysis was used to assess the relationship between EIF2S2 and GLUT1 levels and clinical parameters. Correlation analysis between EIF2S2 and Reactome-Glycolysis signatures was performed using GEPIA2. We describe the effect of EIF2S2 knockdown on lactate production and the mRNA levels of glycolysis-related genes in human colon cancer SW480 cells. Results: Immunohistochemistry revealed an upregulation of EIF2S2 protein expression in tumor tissues of colorectal cancer patients, which is consistent with the significant upregulation of EIF2S2 transcript levels in the database. These colorectal cancer patients included 24 cases of colon cancer and 18 cases of rectal cancer, ranging in age from 31 to 78 years. The transcription was significantly related to histological subtypes and TP53 mutations (P <0.05). The value of SUVmax in CRC significantly correlated with the expression of EIF2S2 (rho = 0.462, P <0.01). Although SUVmax and SUVmean was not correlate with the expression of GLUT1 (P <0.05), a significant correlation was observed between the expression of GLUT1 and the volumetric PET parameters, such as MTV and TLG (P < 0.01). GLUT1 expression in CRC was positively correlated with EIF2S2 status (rho = 0.470, P <0.01). In SW480 cells, RNAi-mediated depletion of EIF2S2 inhibited lactic acid production (P <0.05) and SLC2A1, SLC2A3, SLC2A10, HK2, PKM2, LDHA mRNA level (P <0.01). Conclusions: Primary CRC FDG uptake is strongly associated with the overexpression of EIF2S2, and EIF2S2 may promote glycolysis in CRC by mediating GLUT1.

NPM1 Is a Prognostic Biomarker Involved in Immune Infiltration of Lung Adenocarcinoma and Associated With m6A Modification and Glycolysis.

Background: Overexpression of NPM1 can promote the growth and proliferation of various tumor cells. However, there are few studies on the comprehensive analysis of NPM1 in lung adenocarcinoma (LUAD). Methods: TCGA and GEO data sets were used to analyze the expression of NPM1 in LUAD and clinicopathological analysis. The GO/KEGG enrichment analysis of NPM1 co-expression and gene set enrichment analysis (GSEA) were performed using R software package. The relationship between NPM1 expression and LUAD immune infiltration was analyzed using TIMER, GEPIA database and TCGA data sets, and the relationship between NPM1 expression level and LUAD m6A modification and glycolysis was analyzed using TCGA and GEO data sets. Results: NPM1 was overexpressed in a variety of tumors including LUAD, and the ROC curve showed that NPM1 had a certain accuracy in predicting the outcome of tumors and normal samples. The expression level of NPM1 in LUAD is significantly related to tumor stage and prognosis. The GO/KEGG enrichment analysis indicated that NPM1 was closely related to translational initiation, ribosome, structural constituent of ribosome, ribosome, Parkinson disease, and RNA transport. GSEA showed that the main enrichment pathway of NPM1-related differential genes was mainly related to mTORC1 mediated signaling, p53 hypoxia pathway, signaling by EGFR in cancer, antigen activates B cell receptor BCR leading to generation of second messengers, aerobic glycolysis and methylation pathways. The analysis of TIMER, GEPIA database and TCGA data sets showed that the expression level of NPM1 was negatively correlated with B cells and NK cells. The TCGA and GEO data sets analysis indicated that the NPM1 expression was significantly correlated with one m6A modifier related gene (YTHDF2) and five glycolysis related genes (ENO1, HK2, LDHA, LDHB and SLC2A1). Conclusion: NPM1 is a prognostic biomarker involved in immune infiltration of LUAD and associated with m6A modification and glycolysis. NPM1 can be used as an effective target for diagnosis and treatment of LUAD.

Comprehensive Analysis of GLUT1 Immune Infiltrates and ceRNA Network in Human Esophageal Carcinoma.

BACKGROUND: Glucose transporter 1 (GLUT1) is encoded by the solute carrier family 2A1 (SLC2A1) gene and is one of the glucose transporters with the greatest affinity for glucose. Abnormal expression of GLUT1 is associated with a variety of cancers. However, the biological role of GLUT1 in esophageal carcinoma (ESCA) remains to be determined. METHODS: We analyzed the expression of GLUT1 in pan-cancer and ESCA as well as clinicopathological analysis through multiple databases. Use R and STRING to perform GO/KEGG function enrichment and PPI analysis for GLUT1 co-expression. TIMER and CIBERSORT were used to analyze the relationship between GLUT1 expression and immune infiltration in ESCA. The TCGA ESCA cohort was used to analyze the relationship between GLUT1 expression and m6A modification in ESCA, and to construct a regulatory network in line with the ceRNA hypothesis. RESULTS: GLUT1 is highly expressed in a variety of tumors including ESCA, and is closely related to histological types and histological grade. GO/KEGG functional enrichment analysis revealed that GLUT1 is closely related to structural constituent of cytoskeleton, intermediate filament binding, cell-cell adheres junction, epidermis development, and P53 signaling pathway. PPI shows that GLUT1 is closely related to TP53, GIPC1 and INS, and these three proteins all play an important role in tumor proliferation. CIBERSORT analysis showed that GLUT1 expression is related to the infiltration of multiple immune cells. When GLUT1 is highly expressed, the number of memory B cells decreases. ESCA cohort analysis found that GLUT1 expression was related to 7 m6A modifier genes. Six possible crRNA networks in ESCA were constructed by correlation analysis, and all these ceRNA networks contained GLUT1. CONCLUSION: GLUT1 can be used as a biomarker for the diagnosis and treatment of ESCA, and is related to tumor immune infiltration, m6A modification and ceRNA network.

Comprehensive Analysis of Prognostic and Immune Infiltrates for E2F Transcription Factors in Human Pancreatic Adenocarcinoma.

BACKGROUND: E2F transcription factors (E2Fs) are a group of genes encoding a family of transcription factors in higher eukaryotes. They are involved in a variety of cellular functions and are up-regulated in many tissues and organs. However, the expression level, genetic variation, molecular mechanism, and biological function of different E2Fs in PAAD and its relationship with the prognosis and immune infiltration in patients with PAAD have not been fully elucidated. METHODS: In this study, we investigated the mRNA expression level, genetic variation, prognostic value and gene-gene interaction network of E2Fs in PAAD using the Oncomine, GEPIA, Kaplan Meier plotter, cBioPortal, GeneMANIA, STRING and Metascape database. Then, the relationship between E2Fs expression and tumor immune invasion was studied by using the TIMER database. Finally, we confirmed the expression of E2Fs in PAAD by IHC. RESULTS: The transcription levels of E2F1/3/5/8 are obviously up-regulated in PAAD and the high expression of E2F2/3/6/8 was apparently associated with the tumor stage of patients with PAAD. The abnormal expression of E2F1/2/3/4/5/7/8 in PAAD patients is related to the clinical outcome of PAAD patients. We also found that PAAD tissues have higher expression levels of E2F1/3/5/8 compared with adjacent normal tissues. The function of E2Fs and its neighboring genes is mainly related to the transcription initiation of the RNA polymerase II promoter. The functions of E2Fs and its neighboring proteins are mainly related to cell cycle, virus carcinogenesis, FoxO signaling pathway, TGF-ß signaling pathway, transcriptional disorders in cancer and Wnt signaling pathway. We also found that the expression of E2Fs was significantly correlated with immune infiltrates, including B cells, CD8+ T cells, CD4+T cells, neutrophils, macrophages, and dendritic cells. CONCLUSIONS: Our study may provide new insights into the choice of immunotherapy targets and prognostic biomarkers in PAAD patients.