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Gene signatures of m5C regulators may predict prognoses of patients with head and neck squamous cell carcinoma.

ABSTRACT: BACKGROUND:Head and neck squamous cell carcinoma (HNSCC) is the fifth most common malignancy in the world. The 5-methylcytosine (m5C) plays vital roles in pathological conditions, such as cancer. METHODS:This study investigated The Cancer Genome Atlas (TCGA) database for patients with HNSCC. We characterized the mutations and copy number variations (CNVs) in m5C-regulatory genes, in addition to analyzing their mRNA expressions. Gene set enrichment analysis (GSEA) and protein-protein interaction (PPI) analyses were used to explore relevant functional annotations of m5C-regulatory genes. RESULTS:Alterations in m5C-regulatory genes were closely associated with patient clinicopathological characteristics. The expression of ten m5C-regulatory genes was significantly correlated with CNV patterns, indicating that m5C-regulatory genes have important regulatory effects. There was increased expression of m5C-regulatory genes, particularly ALYREF and NSUN5, during the tumor, node, and metastasis stages. Cox regression analysis revealed that the expression of DNMT1, TET2, and NSUN6 correlated with HNSCC prognoses. Furthermore, the expression of DNMT1 and ALYREF could effectively predict HNSCC risk in patients. In addition, the high expression levels of ALYREF correlated with mitochondrial function, and the elevated DNMT1 expression was associated with peptide cross-linking and humoral immunity. These results provide promising insight into the roles of m5C genes in tumor energy-metabolism and protein synthesis. CONCLUSIONS:Collectively, the results indicate that m5C plays critical roles in HNSCC progression, and is also a potential HNSCC prognostic marker.

SUBMITTER: Xue M

PROVIDER: S-EPMC7653571 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Gene signatures of m5C regulators may predict prognoses of patients with head and neck squamous cell carcinoma.

Xue Miaomiao M Shi Qingmiao Q Zheng Lian L Li Qingbin Q Yang Liya L Zhang Yuanyuan Y

American journal of translational research 20201015 10

<h4>Background</h4>Head and neck squamous cell carcinoma (HNSCC) is the fifth most common malignancy in the world. The 5-methylcytosine (m5C) plays vital roles in pathological conditions, such as cancer.<h4>Methods</h4>This study investigated The Cancer Genome Atlas (TCGA) database for patients with HNSCC. We characterized the mutations and copy number variations (CNVs) in m5C-regulatory genes, in addition to analyzing their mRNA expressions. Gene set enrichment analysis (GSEA) and protein-prote ...[more]

PMID: 33194076

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Project description:The role of 5-methylcytosine (m5C) in tumor initiation and progression has been increasingly recognized. However, the precise association between the regulation of m5C and the progression, metastasis, and prognosis of head and neck squamous cell carcinoma (HNSCC) has not yet been fully explored. Data from 545 HNSCC patients obtained from The Cancer Genome Atlas (TCGA) database were analyzed. Unsupervised cluster analysis was conducted using the expression levels of m5C regulatory genes. Additionally, gene set variation analysis (GSVA), single-sample gene set enrichment analysis (ssGSEA), and Cox regression analysis were utilized. Quantitative reverse transcription polymerase chain reaction (RT-qPCR), colony formation assay, transwell experiments and western blots were performed in the HNSCC cell line UM-SCC-17B to assess the expression and functional role of one of the novel signatures, CNFN. Significant expression differences were found in m5C regulatory genes between tumor and normal tissues in HNSCC. Two distinct m5C modification patterns, characterized by substantial prognostic differences, were identified. Cluster-2, which exhibited a strong association with epithelial-mesenchymal transition (EMT), was found to be associated with a poorer prognosis. Based on the m5C clusters and EMT status, differentially expressed genes (DEGs) were identified. Using DEGs, an 8-gene signature (CAMK2N1, WNT7A, F2RL1, AREG, DEFB1, CNFN, TGFBI, and CAV1) was established to develop a prognostic model. The performance of this signature was validated in both the training and external validation datasets, demonstrating its promising efficacy. Furthermore, additional investigations using RT-qPCR on clinical specimens and experimental assays in cell lines provided compelling evidence suggesting that CNFN, one of the genes in the signature, could play a role in HNSCC progression and metastasis through the EMT pathway. This study highlighted the role of m5C in HNSCC progression and metastasis. The relationship between m5C and EMT has been elucidated for the first time. A robust prognostic model was developed for accurately predicting HNSCC patients' survival outcomes. Potential molecular mechanisms underlying these associations have been illuminated through this research.

Project description:BackgroundHead and neck squamous cell carcinoma (HNSCC) is a common malignancy that emanates from the lips, mouth, paranasal sinuses, oropharynx, larynx, nasopharynx, and from other pharyngeal cancers. The availability of high-throughput expression data has made it possible to use global gene expression data to analyze the relationship between metabolic-related gene expression and clinical outcomes in HNSCC patients.MethodIn this study, we used RNA sequencing (RNA-seq) data from the cancer genome atlas (TCGA), with validation in the GEO dataset to profile the metabolic microenvironment and define potential biomarkers for metabolic therapy.ResultsWe extracted data for 529 patients and 327 metabolic genes (198 upregulated and 129 downregulated genes) in the TCGA database. Carbonic anhydrase 9 (CA9) and CA6 had the largest logFCs in the upregulated and downregulated genes, respectively. Our Cox regression model data showed 51 prognostic-related genes with lysocardiolipin acyltransferase 1 (LCLAT1) and choline dehydrogenase (CHDH) being associated with the highest risk (HR = 1.144, 95% CI = 1.044 ~ 1.251) and the lowest risk (HR = 0.580, 95% CI = 0.400 ~ 0.839) in HNSCC, respectively. We next used the ROC curve to evaluate whether the differentially expressed metabolic-related genes could serve as early predictors of HNSCC. The findings showed an AUC of 0.745 and 0.618 in the TCGA and GEO analysis, respectively. Besides, the ability for the genes to predict clinicopathological HNSCC status was analyzed and the data showed that the AUC for age, gender, grade, stage, T, M, and N was 0.520, 0.495, 0.568, 0.606, 0.577, 0.476, and 0.673, respectively, in the TCGA dataset. On the other hand, the AUC for age, gender, stage, T, M, N, smoking, and HPV16-pos was 0.599, 0.531, 0.622, 0.606, 0.616, 0.550, 0.614, 0.519, and 0.397, respectively, in the GEO dataset.ConclusionTaken together, our study unearths a novel metabolic gene signature for the prediction of HNSCC prognosis based on the TCGA dataset. Our signature might point out the metabolic microenvironment disorders and provides potential treatment targets and prognostic biomarkers.

Project description:OBJECTIVES:Head and neck squamous cell carcinoma (HNSCC) shows a remarkable heterogeneity between tumors, which may be captured by a variety of quantitative features extracted from diagnostic images, termed radiomics. The aim of this study was to develop and validate MRI-based radiomic prognostic models in oral and oropharyngeal cancer. MATERIALS AND METHODS:Native T1-weighted images of four independent, retrospective (2005-2013), patient cohorts (n = 102, n = 76, n = 89, and n = 56) were used to delineate primary tumors, and to extract 545 quantitative features from. Subsequently, redundancy filtering and factor analysis were performed to handle collinearity in the data. Next, radiomic prognostic models were trained and validated to predict overall survival (OS) and relapse-free survival (RFS). Radiomic features were compared to and combined with prognostic models based on standard clinical parameters. Performance was assessed by integrated area under the curve (iAUC). RESULTS:In oral cancer, the radiomic model showed an iAUC of 0.69 (OS) and 0.70 (RFS) in the validation cohort, whereas the iAUC in the oropharyngeal cancer validation cohort was 0.71 (OS) and 0.74 (RFS). By integration of radiomic and clinical variables, the most accurate models were defined (iAUC oral cavity, 0.72 (OS) and 0.74 (RFS); iAUC oropharynx, 0.81 (OS) and 0.78 (RFS)), and these combined models outperformed prognostic models based on standard clinical variables only (p < 0.001). CONCLUSIONS:MRI radiomics is feasible in HNSCC despite the known variability in MRI vendors and acquisition protocols, and radiomic features added information to prognostic models based on clinical parameters. KEY POINTS:• MRI radiomics can predict overall survival and relapse-free survival in oral and HPV-negative oropharyngeal cancer. • MRI radiomics provides additional prognostic information to known clinical variables, with the best performance of the combined models. • Variation in MRI vendors and acquisition protocols did not influence performance of radiomic prognostic models.

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Gene signatures of m5C regulators may predict prognoses of patients with head and neck squamous cell carcinoma.

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Gene signatures of m5C regulators may predict prognoses of patients with head and neck squamous cell carcinoma.

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