Dataset Information

Comprehensive Landscape of Prognostic Significance and Immune Characteristics of Myosins in Squamous Cell Carcinoma of the Head and Neck.

ABSTRACT: Myosin superfamily, a large and diverse family of molecular motors important for cell motility and migration, has been illustrated to play contradictory roles during the development of several kinds of tumors. However, the function and prognostic values of MYOs in head and neck squamous cell carcinoma (HNSCC) still remain largely unknown. In the current manuscript, the expression levels and clinical data of MYOs in HNSCC were investigated by online databases, including Oncomine, GEPIA, GEO, TCGA, HPA, UALCAN, Kaplan-Meier plotter, and CancerSEA; we found that the expression levels of MYO1B, MYO5A, and MYO10 were significantly elevated in HNSCC tissues, which were also correlated with the unfavorable overall survival (OS) of the patients. Furthermore, MYO1B/MYO5A/MYO10 interacting genes were identified, and the protein-protein interaction (PPI) networks were constructed by STRING and GeneMANIA. The enrichment analysis revealed that MYO1B/MYO5A/MYO10 associated genes mainly participated in cell metastasis and EMT processes, which were also confirmed by cell functional experiments. At last, the ssGSEA method was conducted to investigate the extent of immune cell infiltration, and we found that both the expression of MYO1B/MYO5A/MYO10 were closely correlated with the infiltration of immune cells in HNSCC. These findings implied that MYO1B, MYO5A, and MYO10 as novel prognostic factors for HNSCC and provided new strategy for HNSCC treatment.

SUBMITTER: Zhu Y

PROVIDER: S-EPMC9038433 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Comprehensive Landscape of Prognostic Significance and Immune Characteristics of Myosins in Squamous Cell Carcinoma of the Head and Neck.

Zhu Yuying Y Zheng Shikang S Zhai Xingyou X Wang Cheng C Liu Aijun A Ju Jun J Peng Xin X Chen Liwei L Zhang Yongxia Y Ren Nan N Xie Yingli Y Fan Junda J Zhao Kai K Liu Mingbo M

Journal of immunology research 20220418

Myosin superfamily, a large and diverse family of molecular motors important for cell motility and migration, has been illustrated to play contradictory roles during the development of several kinds of tumors. However, the function and prognostic values of MYOs in head and neck squamous cell carcinoma (HNSCC) still remain largely unknown. In the current manuscript, the expression levels and clinical data of MYOs in HNSCC were investigated by online databases, including Oncomine, GEPIA, GEO, TCGA ...[more]

PMID: 35478939

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Project description:Background: There is accumulating evidence on the clinical importance of the fibroblast growth factor receptor (FGFR) signal, hypoxia, and glycolysis in the immune microenvironment of head and neck squamous cell carcinoma (HNSCC), yet reliable prognostic signatures based on the combination of the fibrosis signal, hypoxia, and glycolysis have not been systematically investigated. Herein, we are committed to establish a fibrosis-hypoxia-glycolysis-related prediction model for the prognosis and related immune infiltration of HNSCC. Methods: Fibrotic signal status was estimated with microarray data of a discovery cohort from the TCGA database using the UMAP algorithm. Hypoxia, glycolysis, and immune-cell infiltration scores were imputed using the ssGSEA algorithm. Cox regression with the LASSO method was applied to define prognostic genes and develop a fibrosis-hypoxia-glycolysis-related gene signature. Immunohistochemistry (IHC) was conducted to identify the expression of specific genes in the prognostic model. Protein expression of several signature genes was evaluated in HPA. An independent cohort from the GEO database was used for external validation. Another scRNA-seq data set was used to clarify the related immune infiltration of HNSCC. Results: Six genes, including AREG, THBS1, SEMA3C, ANO1, IGHG2, and EPHX3, were identified to construct a prognostic model for risk stratification, which was mostly validated in the independent cohort. Multivariate analysis revealed that risk score calculated by our prognostic model was identified as an independent adverse prognostic factor (p < .001). Activated B cells, immature B cells, activated CD4+ T cells, activated CD8+ T cells, effector memory CD8+ T cells, MDSCs, and mast cells were identified as key immune cells between high- and low-risk groups. IHC results showed that the expression of SEMA3C, IGHG2 were slightly higher in HNSCC tissue than normal head and neck squamous cell tissue. THBS1, ANO1, and EPHX3 were verified by IHC in HPA. By using single-cell analysis, FGFR-related genes and highly expressed DEGs in low-survival patients were more active in monocytes than in other immune cells. Conclusion: A fibrosis-hypoxia-glycolysis-related prediction model provides risk estimation for better prognoses to patients diagnosed with HNSCC.

Project description:Background: Immunotherapy has become the new standard of care for recurrent and metastatic head and neck squamous cell carcinoma (HNSCC), and PD-L1 is a widely used biomarker for immunotherapeutic response. However, PD-L1 expression in most cancer patients is low, and alternative biomarkers used to screen the population benefiting from immunotherapy are still being explored. Tumor microenvironment (TME), especially tumor immune-infiltrating cells, regulates the body's immunity, affects the tumor growth, and is expected to be a promising biomarker for immunotherapy. Purpose: This article mainly discussed how the immune-infiltrating cell patterns impacted immunity, thereby affecting HNSCC patients' prognosis. Method: The immune-infiltrating cell profile was generated by the CIBERSORT algorithm based on the transcriptomic data of HNSCC. Consensus clustering was used to divide groups with different immune cell infiltration patterns. Differentially expressed genes (DEGs) obtained from the high and low immune cell infiltration (ICI) groups were subjected to Kaplan-Meier and univariate Cox analysis. Significant prognosis-related DEGs were involved in the construction of a prognostic signature using multivariate Cox analysis. Results: In our study, 408 DEGs were obtained from high- and low-ICI groups, and 59 of them were significantly associated with overall survival (OS). Stepwise multivariate Cox analysis developed a 16-gene prognostic signature, which could distinguish favorable and poor prognosis of HNSCC patients. An ROC curve and nomogram verified the sensitivity and accuracy of the prognostic signature. The AUC values for 1 year, 2 years, and 3 years were 0.712, 0.703, and 0.700, respectively. TCGA-HNSCC cohort, GSE65858 cohort, and an independent GSE41613 cohort proved a similar prognostic significance. Notably, the prognostic signature distinguished the expression of promising immune inhibitory receptors (IRs) well and could predict the response to immunotherapy. Conclusion: We established a tumor immune cell infiltration (TICI)-based 16-gene signature, which could distinguish patients with different prognosis and help predict the response to immunotherapy.

Project description:Background: Cuproptosis has been recognized as a novel regulatory cell death, which has been confirmed to promote the occurrence and development of tumors. However, whether cuproptosis-related lncRNA has an impact on the prognosis of squamous cell carcinoma of the head and neck (HNSCC) is still unclear. Methods: In total, 501 HNSCC tumor samples and 44 normal were downloaded from the TCGA database. Cuproptosis-related lncRNAs were obtained by co-expressed analysis. We got prognostic lncRNA that was associated with cuproptosis by using univariate Cox regression analysis and LASSO Cox regression. Then we constructed and validated the prognostic signature of HNSCC and analyzed the immune landscape of the signature. Results: The Prognostic Signature is based on 10 cuproptosis-related lncRNAs including AC090587.1, AC004943.2, TTN-AS1, AL162458.1, AC106820.5, AC012313.5, AL132800.1, WDFY3-AS2, CDKN2A-DT, and AL136419.3. The results of overall survival, risk score distribution, and survival status in the low-risk group were better than those in the high-risk group. In addition, all immune checkpoint genes involved were significantly different between the two risk groups (p < 0.05). The risk score was positively correlated with Eosinophils. M0 and M2 phenotype macrophages, mast cells activated, NK cells activated, and negatively related with B cells naive, mast cells resting, plasma cells, CD8T cells, T cells follicular helper, T cells regulatory (Tregs). Consensus clustering was identified in molecular subtypes of HNSC. More high-risk samples concentrated in Cluster1, which had a higher Tumor Immune Dysfunction and Exclusion (TIDE) score and Single Nucleotide Polymorphisms (SNP) alternation than Cluster2. Conclusion: Our study elucidated the correlation between cuproptosis-related lncRNA with prognosis and immune landscape of HNSCC, which may provide references for further research on the exploration of the mechanism and functions of the prognosis for HNSCC.

Project description:BackgroundNumerous studies have shown that the aging microenvironment played a huge impact on tumor progression. However, the clinical prognostic value of aging-related risk signatures and their effects on the tumor immune microenvironment (TIME) in head and neck squamous cell carcinoma (HNSCC) remains largely unclear. This study aimed to identify novel prognostic signatures based on aging-related genes (AGs) and reveal the landscape of the TIME in HNSCC.MethodsDifferentially expressed AGs were identified using the gene set enrichment analysis (GSEA). The prognostic risk model of AGs was established by univariate and multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses. The independent prognostic value of the risk model and the correlations of the prognostic signature with immune score, tumor immune cell infiltration, and immune checkpoints were systematically analyzed.ResultsA prognostic risk model of four AGs (BAK1, DKK1, CDKN2A, and MIF) was constructed and validated in the training and testing datasets. Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curve analysis confirmed that the four-AG risk signature possessed an accurate predictive value for the prognosis of patients with HNSCC. Correlation analysis revealed that the risk score was negatively associated with immune score and immune cell infiltration level while positively correlated with immune checkpoint blockade (ICB) response score. Patients of the high-risk subtype contained higher infiltration levels of resting natural killer (NK) cells, M0 macrophages, M2 macrophages, and resting mast cells while having lower infiltration levels of memory B cells, CD8+ T cells, follicular helper T cells, regulatory T cells (Tregs), and activated mast cells than did those of the low-risk subtype. The expressions of CTLA4, PDCD1, and TIGIT were downregulated while the PDCD1LG2 expression was upregulated in the high-risk subtype compared to those in the low-risk subtype. Furthermore, the four selected AGs in the risk model were demonstrated to possess important functions in immune cell infiltration and ICB response of HNSCC.ConclusionsThe aging-related risk signature is a reliable prognostic model for predicting the survival of HNSCC patients and provides potential targets for improving outcomes of immunotherapy.

Dataset Information

Comprehensive Landscape of Prognostic Significance and Immune Characteristics of Myosins in Squamous Cell Carcinoma of the Head and Neck.

Publications

Comprehensive Landscape of Prognostic Significance and Immune Characteristics of Myosins in Squamous Cell Carcinoma of the Head and Neck.

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