Prognostic Value of CD200R1 mRNA Expression in Head and Neck Squamous Cell Carcinoma.
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ABSTRACT:
SUBMITTER: Chang H
PROVIDER: S-EPMC7408128 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:FOXD1 has been reported to function as an oncogene in several types of cancer. This study evaluated the expression of FOXD1 and its role in head and neck squamous cell carcinoma (HNSCC). We mined the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases for expression profiles, clinical significance, and potential mechanisms of FOXD1in HNSCC. Our validation cohort consisted of FOXD1 mRNA expression in 162 paired HNSCC and adjacent normal tissues, as determined using quantitative real-time polymerase chain reaction. FOXD1 expression was upregulated in HNSCC in the public databases and in the validation cohort. The expression level of FOXD1 was associated with DNA amplification and methylation level. The areas under the curves (AUC) of TCGA cohort and the validation cohort were 0.855 and 0.843, respectively. Furthermore, higher FOXD1 expression was significantly associated with worse overall survival (hazard ratio [HR]: 1.849, 95% confidence interval [CI]: 1.280-2.670, P = 0.001) and a lower rate of recurrence-free survival (HR: 1.650, 95% CI: 1.058-2.575, P = 0.027) in patients with HNSCC. Moreover, gene set enrichment analysis showed that cases of HNSCC with FOXD1 overexpression were enriched in bladder cancer, cell cycle, DNA replication, glycosaminoglycan biosynthesis chondroitin sulfate, homologous recombination, glycan biosynthesis, nucleotide excision repair, p53 signaling pathway, pyrimidine metabolism, and spliceosome pathways. In summary, FOXD1 was significantly upregulated in HNSCC and was a good diagnostic biomarker and an independent predictor of poor survival and low rate of recurrence-free survival in patients with HNSCC.
| S-EPMC7778536 | biostudies-literature
Project description:BackgroundThe CAV family, especially CAV1 and CAV2, is significantly associated with tumor development. In this study, we aimed to explore the pathogenic and prognostic roles of CAV1 and CAV2 in head and neck squamous cell carcinoma (HNSCC) through bioinformatic analysis and verified in human tissue.MethodsWe analyzed expression profiles of CAV1 and CAV2 in HNSCC and in normal tissues via data from The Cancer Genome Altas. Prognostic significance was examined by Kaplan-Meier survival curve obtained from the Xena browser together with Cox regression analysis. Co-expressed genes were uploaded to GeneMANIA and applied to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, showing interaction networks. Signaling pathways of CAV1 and CAV2 in HNSCC were analyzed by Gene Set Enrichment Analysis to elucidate potential regulatory mechanisms. Gene-drug interaction network was explored via Comparative Toxicogenomics Database. Immunohistochemistry was performed to verify theoretical results.ResultsCompared with normal tissues, expression levels of CAV1 and CAV2 were remarkably higher in HNSCC (p < 0.0001), which independently implies poor OS (CAV1: HR: 1.146, p = 0.027; CAV2: HR: 1.408, p = 0.002). Co-expressed genes (PXN, ITGA3, TES, and MET) were identified and analyzed by FunRich with CAV1 and CAV2, revealing a significant correlation with focal adhesion (p < 0.001), which has a vital influence on cancer progression. GSEA also showed cellular protein catabolic process (ES = 0.42) and proteasome complex (ES = 0.72), which is a key degradation system for proteins involved in oxidatively damaging and cell cycle and transcription, closely correlated with high expression of CAV2 in HNSCC. More importantly, we found the relationship between different immune cell infiltration degrees in the immune micro-environment in HNSCC and expression levels of CAV1/CAV2 (p < 0.0001). Gene-drug interaction network was checked via CTD. Moreover, tissue microarrays verified higher expression levels of CAV1/CAV2 in HNSCC (p < 0.0001), and the high expression subgroup indicated significantly poorer clinical outcomes (p < 0.05).ConclusionsThe results revealed that CAV1 and CAV2 are typically upregulated in HNSCC and might predict poor prognosis.
| S-EPMC9952890 | biostudies-literature
Project description:BackgroundCircular RNAs (circRNAs) have been found to have potential biological applications against tumors in humans. This study aimed to evaluate the diagnostic, prognostic, and clinicopathological value of circRNAs in head and neck squamous cell carcinoma (HNSCC).MethodsThe PubMed, Web of Science, EMBASE, and the Cochrane Library were comprehensively searched for the relevant studies before October 20, 2021. Statistical analysis was performed based on STATA 15.0, Meta-DiSc 1.4, and RevMan 5.3 software.ResultsA total of 55 reports regarding 56 kinds of circRNA were studied in this meta-analysis, including 23, 38, and 26 articles on diagnosis, prognosis, and clinicopathological features, respectively. The pooled sensitivity, specificity, and area under the curve (AUC) of the summary receiver-operating characteristic curve (SROC) were 0.78, 0.84, and 0.87, respectively. Besides, the upregulation of oncogenic circRNAs was significantly associated with poorer overall survival (OS) (HR=2.25, p < 0.05) and disease-free interval (DFS) (HR=1.92, p < 0.05). In contrast, the elevated expression of tumor suppressor circRNAs was associated with a favorable prognosis (HR=0.50, p < 0.05). In addition, the high expression of oncogenic circRNAs was associated with the tumor size (OR=3.59, p < 0.05), degree of differentiation (OR=1.89, p < 0.05), TNM stage (OR=2.35, p < 0.05), lymph node metastasis (OR=1.85, p < 0.05), and distant metastasis (OR=3.42, p < 0.05). Moreover, the expression of tumor suppressor circRNAs was associated with improved clinicopathological features (lymph node metastasis: OR=0.25, p < 0.05).ConclusionsCircRNAs could serve as potential predictive indicators and be useful for the diagnosis, prognosis, and identification of clinicopathological features in HNSCC.
| S-EPMC9280010 | biostudies-literature
Project description:The MET pathway plays a key role in various cancers, and its inhibition represents a potential treatment target. However, appropriate biomarkers are needed to facilitate the selection of patients who would benefit from MET inhibiting therapy. We herein conducted a robust confirmatory evaluation of the MET copy number alteration status and prognostic significance of c-Met expression in a large series of patients (n = 396) who underwent standard surgical resection and adjuvant chemoradiotherapy for head and neck squamous cell carcinoma (HNSCC). Surgically resected HNSCC samples were subjected to immunohistochemical and H-score analysis of c-Met expression and silver in situ hybridization analysis of MET amplification and copy number gains. c-Met expression varied, with mean and median H-scores (scale: 0-300 scale) of 61.2 and 60.0, respectively. The lowest and highest expression levels were observed in SCC of the larynx and oral cavity, respectively. MET copy number gains were observed in 16.9% of cases (67/339) and were associated with c-Met protein expression. High c-Met expression, determined according to MET gain status, was associated with an inferior overall survival rate, especially among completely resected cases. In conclusion, our robust analysis revealed that c-Met expression in HNSCCs varied according to anatomical site, correlated with MET copy number gains, and was associated with poor prognosis. This c-Met expression analysis method, which is based on the MET gain status, appears to appropriately predict high-risk HNSCC patients in the context of anti-MET therapeutic decisions.
| S-EPMC5166528 | biostudies-literature
Project description:BackgroundMetastasis is a major event for survival and prognosis in patients with head and neck squamous cell carcinomas (HNSCC). A primary cause of metastasis is the proteolytic degradation of the extracellular matrix (ECM). The plasminogen activator urokinase (PLAU) is involved in the transformation of plasminogen to plasmin leading to hydrolyzation of ECM-related proteins. However, the role of PLAU expression in HNSCC is unclear and the worth being investigated.MethodsPLAU expression profiles and clinical parameters from multiple HNSCC datasets were used to investigate the relationship of PLAU expression and HNSCC survival. GO and PPI network were established on PLAU-related downstream molecular. The stroma score was deconvoluted for analysis of PLAU's association with the immune environment. ROC analysis was applied to show the performance of PLAU in predicting HNSCC prognosis.ResultsPLAU mRNA was significantly elevated, as opposed to its methylation, in HNSCC tumor samples over normal specimens (all p < 0.01). Univariate and multivariate cox analysis showed PLAU could be an independent indicator for HNSCC prognosis. Combining with neck lymph node status, the AUC of PLAU in predicting 5-years overall survival reached to 0.862. GO enrichment analysis showed the major biological process (extracellular matrix organization and the P13K-Akt signaling pathway) may involve to the possible mechanism of PLAU's function on HNSCC prognosis. Furthermore, PLAU expression was positively correlated with stroma cell score, M1 type macrophages, and negatively associated with CD4 + T cell, Tregs cell, and follicular helper T cell.ConclusionsPLAU might be an independent biomarker for predicting outcomes of HNSCC patients. The elevated expression of PLAU was associated with HPV positivity and neck node status. The PI3K-Akt pathway and aberrant proportions of immune cells might underly the mechanism of PLAU's oncogene role in HNSCC.
| S-EPMC7812932 | biostudies-literature
Project description:Glycolysis markers including glucose transporter 1 (GLUT1), monocarboxylate transporter 4 (MCT4), hexokinase 2 (HK2), pyruvate kinase M2 (PKM2) and glucose transporter 4 (GLUT4) play vital roles in head and neck squamous cell carcinoma (HNSCC). However, their prognostic value in HNSCC is still controversial. In this meta-analysis, we searched the PubMed, Web of Science and Cochrane Library databases and included thirty-seven studies (3272 patients) that met the inclusion criteria. Higher expression levels of the glycolysis markers in tumor tissues correlated with poorer overall survival (OS; P < 0.001), disease-free survival (DFS; P = 0.03) and recurrence-free survival (RFS; P < 0.001) of HNSCC patients. Subgroup and sensitivity analyses demonstrated that higher expression levels of GLUT1 (P < 0.001), MCT4 (P = 0.002), HK2 (P = 0.002) and PKM2 (P < 0.001) correlated with poorer OS among HNSCC patients. Higher expression of MCT4 (P < 0.001) and PKM2 (P = 0.008) predicted poorer DFS among HNSCC patients. However, GLUT4 expression levels did not associate with clinical outcomes in HNSCC patients. These results demonstrate that glycolysis markers, such as GLUT1, MCT4, HK2 and PKM2, are potential prognostic predictors and therapeutic targets in HNSCC.
| S-EPMC7993722 | biostudies-literature
Project description:Head and neck cancer (HNC) is the fifth most common cancer worldwide. In this study, we performed an integrative analysis of the discovery set and established an eight-gene signature for the prediction of prognosis in patients with head and neck squamous cell carcinoma (HNSCC). Univariate Cox analysis was used to identify prognosis-related genes (with P < 0.05) in the GSE41613, GSE65858, and TCGA-HNSC RNA-Seq datasets after data collection. We performed LASSO Cox regression analysis and identified eight genes (CBX3, GNA12, P4HA1, PLAU, PPL, RAB25, EPHX3, and HLF) with non-zero regression coefficients in TCGA-HNSC datasets. Survival analysis revealed that the overall survival (OS) of GSE41613 and GSE65858 datasets and the progression-free survival(DFS)of GSE27020 and GSE42743 datasets in the low-risk group exhibited better survival outcomes compared with the high-risk group. To verify that the eight-mRNA prognostic model was independent of other clinical features, KM survival analysis of the specific subtypes with different clinical characteristics was performed. Univariate and multivariate Cox regression analyses were used to identify three independent prognostic factors to construct a prognostic nomogram. Finally, the GSVA algorithm identified six pathways that were activated in the intersection of the TCGA-HNSC, GSE65858, and GSE41613 datasets, including early estrogen response, cholesterol homeostasis, oxidative phosphorylation, fatty acid metabolism, bile acid metabolism, and Kras signaling. However, the epithelial-mesenchymal transition pathway was inhibited at the intersection of the three datasets. In conclusion, the eight-gene prognostic signature proved to be a useful tool in the prognostic evaluation and facilitate personalized treatment of HNSCC patients.
| S-EPMC8252784 | biostudies-literature
Project description:BackgroundTranscriptional dysregulation is one of the most important features of cancer genesis and progression. Applying gene expression dysregulation information to predict the development of cancers is useful for cancer diagnosis. However, previous studies mainly focused on the relationship between a single gene and cancer. Prognostic prediction using combined gene models remains limited.Materials and methodsGene expression profiles were downloaded from The Cancer Genome Atlas and the data sets were randomly divided into training data sets and test data sets. A six-gene signature associated with head and neck squamous cell carcinoma (HNSCC) and overall survival (OS) was identified according to a training cohort by using weighted gene correlation network analysis and least absolute shrinkage and selection operator Cox regression. The test data set and gene expression omnibus (GEO) data set were used to validate this signature.ResultsWe identified six candidate genes, namely, FOXL2NB, PCOLCE2, SPINK6, ULBP2, KCNJ18, and RFPL1, and, using a six-gene model, predicted the risk of death of head and neck squamous cell carcinoma in The Cancer Genome Atlas. At a selected cutoff, patients were clustered into low- and high-risk groups. The OS curves of the two groups of patients had significant differences, and the time-dependent receiver operating characteristics of OS, disease-specific survival (DSS), and progression-free survival (PFS) were as high as 0.766, 0.731, and 0.623, respectively. Then, the test data set and the GEO data set were used to evaluate our model, and we found that the OS time in the high-risk group was significantly shorter than in the low-risk group in both data sets, and the receiver operating characteristics of test data set were 0.669, 0.675, and 0.614, respectively. Furthermore, univariate and multivariate Cox regression analyses showed that the risk score was independent of clinicopathological features.ConclusionThe six-gene model could predict the OS of HNSCC patients and improve therapeutic decision-making.
| S-EPMC6305138 | biostudies-literature
Project description:BACKGROUND:Long non-coding RNA (lncRNA) has emerged as a new avenue of interest due to its various biological functions in cancer. Abnormal expression of lncRNA has been reported in other malignancies but has been understudied in head and neck squamous cell carcinoma (HNSCC). METHODS:The lncRNA expression was interrogated via quantitative real-time polymerase chain reaction (qRT-PCR) array for 19 human papillomavirus (HPV)-negative HNSCC tumor-normal pairs. The Cancer Genome Atlas (TCGA) was used to validate these results. The association between differentially expressed lncRNA and survival outcomes was analyzed. RESULTS:Differential expression was validated for 5 lncRNA (SPRY4-IT1, HEIH, LUCAT1, LINC00152, and HAND2-AS1). There was also an inverse association between MEG3 expression (not significantly differentially expressed in TCGA tumors but highly variable expression) and 3-year recurrence-free survival (RFS). CONCLUSION:We identified and validated differential expression of 5 lncRNA in HPV-negative HNSCC. Low MEG3 expression was associated with favorable 3-year RFS, although the significance of this finding remains unclear.
| S-EPMC6037541 | biostudies-literature
Project description:Head and neck squamous cell carcinoma (HNSCC) is a common malignant cancer that accounts for 5-10% of all cancers. This study aimed to identify essential genes associated with the prognosis of HNSCC and construct a powerful prognostic model for the risk assessment of HNSCC. RNAseq expression profile data for the patients with HNSCC were obtained from the TCGA database (GEO). A total of 500 samples with full clinical following-up were randomly divided into a training set and a validation set. The training set was used to screen for differentially expressed lncRNAs. Single-factor survival analysis was performed to obtain lncRNAs that associated with prognosis. A robust likelihood-based survival model was constructed to identify the lncRNAs that are essential for the prognosis of HNSCC. A co-expression network between genes and lncRNAs was also constructed to identify lncRNAs co-expressed with genes to serve as the final signature lncRNAs for prognosis. Finally, the prognostic effect of the signature lncRNAs was tested by multi-factor survival analysis and a scoring model for the prognosis of HNSCC was constructed. Moreover, the results of the validation set and the relative expression levels of the signature lncRNAs in the tumour and the adjacent tissue were consistent with the results of the training set. The 5 lncRNAs were distributed among 3 expression modules. Further KEGG pathway enrichment analysis showed that these 3 co-expressed modules participate in different pathways, and many of these pathways are associated with the development and progression of disease. Therefore, we proposed that the 5 validated lncRNAs can be used to predict the prognosis of HNSCC patients and can be applied in postoperative treatment and follow-up.
| S-EPMC6189101 | biostudies-literature