Pan-Cancer Analyses of the Tumor Microenvironment Reveal That Ubiquitin-Conjugating Enzyme E2C Might Be a Potential Immunotherapy Target.

Increasing evidence indicated that the tumor microenvironment (TME) played a crucial role in cancer initiation and progression. Ubiquitin-conjugating enzyme E2C (UBE2C) was differentially expressed in many cancer types. However, the immunological and prognostic roles of UBE2C were unclear. Differentially expressed genes (DEGs) of 29 cancer types were downloaded from GEPIA2 and 4 cancer types failed to download owing to no DEGs. Furthermore, the gene expression profiles, mutation data, and survival data of 33 cancer types were obtained from UCSC Xena. Clinical stage relevance, tumor mutational burden (TMB), TME relevance analysis, and gene set enrichment analysis (GSEA) of DEGs in 33 cancer types were performed. And DEGs were identified in oral squamous cell carcinoma (OSCC) by biological experiments. Previous studies indicated that UBE2C was related to the prognosis of many cancers. In our study, the higher UBE2C expression level meant a terminal clinical stage in 8 cancer types and the expression level of UBE2C was related to TMB in 20 cancer types. In addition, both immune relevance analysis and GSEA showed that UBE2C might participate in immune response in many cancers. Furthermore, the UBE2C mRNA level and protein level were all identified as upregulated in OSCC cell lines and tissues. UBE2C was differentially expressed in many cancer types and related to the pathogenesis and TME of many cancers, which might be a potential diagnostic and therapeutic biomarker.

Bioinformatics Analyses Indicate That Cathepsin G (CTSG) is a Potential Immune-Related Biomarker in Oral Squamous Cell Carcinoma (OSCC).

PURPOSE: Plenty of studies showed that the immune system was associated with cancer initiation and progression. This study aimed to explore the prognostic biomarkers from immune-related genes (IRGs) in oral squamous cell carcinoma (OSCC). MATERIALS AND METHODS: RNA-seq data were downloaded from The Cancer Genome Atlas (TCGA) and IRGs and transcription factors (TFs) were extracted. Then, the co-expression network between IRGs and TFs was constructed using the "WGCNA" package in R software. Furthermore, a gene expression signature according to IRGs was constructed to predict OSCC prognosis and its accuracy was validated by survival analysis. Subsequently, correlation analyses between risk-score and immune cells level and clinical parameters were performed. Finally, immune-related biomarkers were selected and further investigated using gain-of-function assays in vitro. RESULTS: A total of 32 normal cases and 317 OSCC cases were selected in our study. Differentially-expressed analysis indicated that there were 381 differentially-expressed IRGs and 62 TFs in OSCC. Among them, 25 TFs and 21 IRGs were enrolled in the co-expression network. Furthermore, we found that gene expression signature on the basis of 10 IRGs could predict the prognosis accurately and a high-risk score based on gene expression signature meant a high T classification, terminal clinical stage, and low immune cells level in OSCC. Finally, cathepsin G (CTSG) was identified as a potential immune-related biomarker and therapeutic target in OSCC. CONCLUSION: In conclusion, IRGs were directly involved in the development and progression of OSCC. Furthermore, CTSG was identified as a potential independent biomarker and might be an immunotherapeutic target in OSCC treatment.

M6A-related bioinformatics analysis reveals that HNRNPC facilitates progression of OSCC via EMT.

Increasing evidence suggests that N6-methyladenosine(m6A) has a vital role in cancer progression. Therefore, we aimed to explore the prognostic relevance of m6A-related genes in oral squamous cell carcinoma (OSCC). First, Expression profiles were downloaded from The Cancer Genome Atlas (TCGA) and m6A-related genes were extracted afterwards. Then, cluster analysis and principal component analysis (PCA) were used to analyze m6A-related genes. And differentially-expressed analysis was performed in R software. Furthermore, a risk model was constructed, and crucial m6A genes were selected to explore its biological effects in OSCC cells. Total of 13 m6A-related genes were extracted and 8 differentially-expressed genes were identified. Subsequently, m6A-based clustering showed 2 subtypes with different clinical outcome. In addition, a risk model was successfully established. Of 13 m6A-related genes, only heterogeneous nuclear ribonucleoprotein C (HNRNPC) might be an independent biomarker and mean unfavorable overall survival in OSCC by univariate and multivariate cox regression analysis. Functional studies revealed that overexpression of HNRNPC promoted carcinogenesis of OSCC via epithelial- mesenchymal transition (EMT). In total, a risk model of m6A-related genes in OSCC was established. Subsequently, HNRNPC was proved to promote OSCC carcinogenesis and be an independent biomarker prognostic biomarker of OSCC, suggesting that it might be a new biomarker and therapeutic target of OSCC.

LncRNA AC007271.3 promotes cell proliferation, invasion, migration and inhibits cell apoptosis of OSCC via the Wnt/ß-catenin signaling pathway.

AIMS: Long noncoding RNA (lncRNA) AC007271.3 has been identified to be dysregulated in oral squamous cell carcinoma (OSCC) in our previous study. However, the precise role of AC007271.3 in OSCC remains unclear. In this study, we investigated the potential functions and the underlying mechanisms of AC007271.3 in OSCC. MATERIALS AND METHODS: The expression levels of AC007271.3 in OSCC tissues and cell lines were examined using RT-qPCR. The relationship between AC007271.3 level and clinicopathological characteristics was analyzed, and its association with patient prognosis was assessed by the Kaplan-Meier method. The biological function of AC007271.3 and its role in the development of OSCC through Wnt/ß-catenin signaling pathway were studied. KEY FINDINGS: We identified that AC007271.3 was up-regulated and positively correlated with advanced clinical stage, lymph node metastasis, poor histological differentiation and unfavorable prognosis. We explored the expression, function, and molecular mechanism of AC007271.3 in OSCC cells. Overexpression of AC007271.3 remarkably promoted cell proliferation in vitro and in vivo, induced cell migration, invasion and inhibited apoptosis in vitro, while knockdown of AC007271.3 attenuated cell proliferation, migration, invasion and induced apoptosis. Mechanistically, AC007271.3 overexpression substantially increased the expression of ß-catenin and the downstream target molecules CyclinD1, c-myc and Bcl-2, while silencing of AC007271.3 has the opposite effect. Rescued experiments showed that the ability to promote cell proliferation, migration, invasion and inhibiting apoptosis could be reversed when treated with the Wnt/ß-catenin pathway inhibitor. SIGNIFICANCE: Our data indicated that AC007271.3 could promote cell proliferation, invasion and inhibit cell apoptosis of OSCC via the Wnt/ß-catenin signaling pathway, which might provide a novel therapeutic approach for OSCC.

Identification of Candidate Biomarkers and Analysis of Prognostic Values in Oral Squamous Cell Carcinoma.

Objectives: Oral squamous cell carcinoma (OSCC) is the most common oral cancer with a poor prognosis owing to limited understanding of the disease mechanisms. The aim of this study was to explore and identify the potential biomarkers in OSCC by integrated bioinformatics analysis. Materials and Methods: Expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) were downloaded from The Cancer Genome Atlas (TCGA) and differentially expressed RNAs (DERNAs) were subsequently identified in OSCC by bioinformatics analysis. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were used to analyze DERNAs. Then, the competing endogenous RNA (ceRNA) network was constructed in Cytoscape and the protein -protein interaction (PPI) network was established in the STRING database. We established a risk model to predict the overall survival of OSCC on the basis of DElncRNAs with Kaplan-Meier analysis and combined with logrank p test. Furthermore, we identified potential biomarkers by combining univariate Cox regression with overall survival rate, which were then validated in Gene Expression Omnibus (GEO), OSCC cell lines and OSCC specimens. Results: A total of 1,919 DEmRNAs, 286 DElncRNAs and 111 DEmiRNAs were found to be dysregulated in OSCC. A ceRNA network included 46 DElncRNAs,7 DEmiRNAs and 10 DEmRNAs, and the PPI network included 712 DEmRNAs including 31 hub genes. Moreover, a 7 lncRNAs risk model was established and four genes (CMA1, GNA14, HCG22, HOTTIP) were identified as biomarkers on overall survival in patients with OSCC. Conclusions: This study successfully constructed a ceRNA network and a PPI network which play a crucial role in OSCC. A risk model was established to predict the prognosis, and four DERNAs are revealed with overall survival in patients with OSCC, suggesting that they may be potential biomarkers in tumor diagnosis and treatment.