Interferon-Induced Protein 44 Correlated With Immune Infiltration Serves as a Potential Prognostic Indicator in Head and Neck Squamous Cell Carcinoma.
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ABSTRACT:
SUBMITTER: Pan H
PROVIDER: S-EPMC7573551 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
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Interferon-Induced Protein 44 Correlated With Immune Infiltration Serves as a Potential Prognostic Indicator in Head and Neck Squamous Cell Carcinoma.
Pan Hua H Wang Xiaoqing X Huang Weiqiang W Dai Yongmei Y Yang Mi M Liang Huazhen H Wu Xixi X Zhang Longshan L Huang Wenqi W Yuan Lu L Wu Yuting Y Wang Yin Y Liao Liwei L Huang Jihong J Guan Jian J
Frontiers in oncology 20201006
Interferon-induced protein 44 (IFI44) containing a guanosine-5'-triphosphate (GTP) binding domain was reported to play a significant role in the immune response to autoimmune disease. However, its roles involved in cancers remain unclear. Here, we detected the expression of IFI44 in The Cancer Genome Atlas (TCGA) Pan-cancer and generally explored the effect of IFI44 on immune infiltration in the tumor microenvironment (TME). The results displayed that IFI44 was mainly located in the cytoplasm an ...[more]
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Project description:Head and neck squamous cell carcinoma (HNSC) is an aggressive type of cancer that lacks early detection, and therefore, has a low 5-year survival rate. The spermine synthase (SMS) gene has been shown to be associated with Snyder-Robinson syndrome and poor prognosis of multiple cancers; however, its regulatory role in HNSC has never been investigated. Therefore, we explored the potential predictive value of SMS in HNSC. We explored the association between SMS expression and clinicopathological parameters of HNSC patients by using data from The Cancer Genome Atlas datasets (TCGA). The prognostic value of SMS was evaluated using the Kaplan-Meier plotter, Gene Expression Profiling Interactive Analysis (GEPIA) 2 and univariate and multivariate Cox regression analyses. We further used gene set enrichment analysis (GESA) to investigate the potential roles of SMS in HNSC prognosis and Tumor Immunity Estimation Resource 2.0 (TIMER2.0) to analyze the correlation between immune cell infiltration and SMS expression. Finally, starBase was used to screen out prognosis-associated non-coding RNA genes to constructed the competing endogenous RNA (ceRNA) network. Co-expression and survival analyses were used to identify the ceRNA network's effect on HNSC prognosis. We found that SMS expression was increased in HNSC compared with normal tissues (P<0.05). In addition, SMS expression was associated with tumor grade (P=0.006), N stage (P=0.001), and prognosis. Survival analysis revealed that high expression of SMS showed worse overall survival (OS) (HR =1.4, P=0.01) and worse disease-free survival (DFS) (HR =1.5, P=0.014). Multivariate Cox analysis further supported the prognostic value of SMS in HNSC (HR =1.006636, P=0.0056). GESA showed that SMS was involved in metabolism- and immune-related pathways. The immune infiltration analyses results showed a decrease in the landscape of immune cell infiltration with high SMS expression and SMS deletion in HNSC. Finally, a ceRNA network (SMS/hsa-miR-23b-3p/KTN1-AS1 and VPS9D1-AS axis) was constructed based on the co-expression and survival analyses in HNSC. Our findings first revealed that SMS functioned as a potential prognostic biomarker and provide insights into the molecular mechanisms of its function in HNSC. The use of SMS may be powerful for determining worse prognosis HNSC patients.
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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.
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Project description:BackgroundIncreased evidence has indicated that the tumour microenvironment plays an essential in the development, treatment and prognosis of head and neck squamous cell carcinoma (HNSC). Recent studies have indicated CC chemokine receptor 4 (CCR4) plays an essential role in tumor invasion and other adverse biological behavior. This study used data from the Cancer Genome Atlas (TCGA) database to explore the role of CCR4 in HNSC and its clinical significance.MethodsThe gene expression and clinical data of HNSC patients in the TCGA database were extracted. Gene Expression Profiling Interactive Analysis (GEPIA) was used to analyze the expression of CCR4 in tumor and non-tumor tissue. Kaplan-Meier survival analysis was used to analyze the relationship between CCR4 expression and overall survival rate (OS), disease-specific survival (DSS), and progression-free interval (PFI) in HNSC. A logistic regression model was used to analyze the relationships between various clinical factors and CCR4 expression. Gene Set Enrichment Analysis (GSEA) was used to explore the potential role of CCR4 in HNSC. Additionally, we explored the relationship between CCR4 and immune infiltration.ResultsThe expression of CCR4 in HNSC was not significantly different from that in normal tissue. The expression level of CCR4 in wild-type TP53 was higher than that in mutant TP53. Cox regression analysis showed the expression level of CCR4 was related to the patient's tumor grade and Tumor-Node-Metastasis (TNM) stage. CCR4 expression level is an independent prognostic factor. CCR4 is positively correlated with immune infiltration and immune checkpoints expression levels. The results of GSEA revealed that the high CCR4 expression group genes were enriched in allograft rejection, inflammatory response, IL-6/JAK/STAT3 signaling, interferon gamma response, and KRAS signaling up. Low CCR4 expression group genes were enriched in oxidative phosphorylation, MYC targets v1, DNA repair, reactive oxygen species pathway, and P53 pathway. Further, our study indicated CCR4 can also predict the prognosis of radiotherapy patients.ConclusionsOur study found that CCR4 was a prognostic marker related to HNSC immune infiltration, and patients with high expression of CCR4 had a better prognosis.
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