Elevated &lt;em&gt;DKK1&lt;/em&gt; expression is an independent unfavorable prognostic indicator of survival in head and neck squamous cell carcinoma

Gao, Haihe; Li, Lisha; Xiao, Mang; Guo, Yongwei; Shen, Yi; Cheng, Lixin; Tang, Ming

doi:10.2147/cmar.s177043

Cited by 23 publications

(24 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Among these 27 genes enrolled in IRGS, six genes (ULBP1, CCR6, CCL22, ROBO1, DKK1 and PDGFA) have previously shown to correlate with the tumorigenesis of HNSCC [20][21][22][23][24][25]. As reported, CCR6 Fig.…”

Section: Discussionmentioning

confidence: 78%

“…Reliable prognostic biomarkers are needed to identify patients with the highest risk of unfavorable survival outcomes. Numerous studies have highlighted the biomarkers associated with the pathogenesis and biology of HNSCC [14,[20][21][22][23][24][25]. Unfortunately, the accuracy of their survival evaluations remains limited and they have not yet been applied in routine clinical practice.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma

She

Kong

et al. 2020

Cancer Cell Int

View full text Add to dashboard Cite

Background: Immune-related genes (IRGs) were linked to the prognosis of head and neck squamous cell carcinoma (HNSCC). This study aimed to identify the effects of an immune-related gene signature (IRGS) that can predict the of HNSCC prognosis. Methods: The expression data of 770 HNSCC patients from the TCGA database and the GEO database were used. To explore a predictive model, the Cox proportional hazards model was applied. The Kaplan-Meier survival analysis, as well as univariate and multivariate analyses were performed to evaluate the independent predictive value of IRGS. To explore biological functions of IRGS, enrichment analyses and pathway annotation for differentially expressed genes (DEGs) in different immune groups were applied, as well as the immune infiltration. Results: A prognostic signature comprising 27 IRGs was generated. IRGS significantly stratified HNSCC patients into high and low immune risk groups in regard to overall survival in the training cohort (HR = 3.69, 95% CI 2.73-4.98, P < 0.001). Likewise, IRGS could be linked to the prognosis of HNSCC in patients of the validation cohort (HR = 1.84, 95% CI 1.21-2.81, P < 0.01). Even after adjusting for TNM stage, IRGS was maintained as an independent predictor in the multivariate analysis (HR = 3.62, 95% CI 2.58-5.09, P < 0.001), and in the validation cohort (HR = 1.73, 95% CI 1.12-2.67, P = 0.014). The IFN-α response, the IFN-γ response, IL-2/STAT5 signaling, and IL-6/JAK/STAT3 signaling were all negatively correlated with the immune risk (P < 0.01). Immune infiltration of the high-risk group was significantly lower than that of the low-risk group (P < 0.01). Most notably, the infiltration of CD8 T cells, memory-activated CD4 T cells, and regulatory T cells was strongly upregulated in the low immune risk groups, while memory resting CD4 T cell infiltration was downregulated (P < 0.01). Conclusion: Our analysis provides a comprehensive prognosis of the immune microenvironments and outcomes for different individuals. Further studies are needed to evaluate the clinical application of this signature.

show abstract

Section: Discussionmentioning

confidence: 78%

Section: Discussionmentioning

confidence: 99%

Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma

She

Kong

et al. 2020

Cancer Cell Int

View full text Add to dashboard Cite

show abstract

“…Most of these genes hold a decisive place in expression of cytokine and its receptors. Overexpression of DKK1, an identified proinflammatory cytokine in quite a number of cancers (Chae and Bothwell, 2019), could boost malignant cell proliferation, migration, and invasiveness and give rise to unfavorable clinical outcomes in HNSCC (Shi et al, 2014;Gao et al, 2018). HBEGF serves as a crucial component of EGFR, mediating tumor cell proliferation and bringing about cetuximab resistance (Hatakeyama et al, 2010;Huang et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Systematic Profiling of Immune Risk Model to Predict Survival and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma

Liu

Chen

et al. 2020

Front. Genet.

View full text Add to dashboard Cite

Background and Purpose: Head and neck squamous carcinoma (HNSCC), characterized by immunosuppression, is a group of highly heterogeneous cancers. Although immunotherapy exerts a promising influence on HNSCC, the response rate remains low and varies in assorted primary sites. Immunological mechanisms underlying HNSCC pathogenesis and treatment response are not fully understood. This study aimed to develop a differentially expressed genes (DEGs)-based risk model to predict immunotherapy efficacy and stratify prognosis of HNSCC patients. Materials and Methods: The expression profiles of HNSCC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The tumor microenvironment and immune response were estimated by cell type identification via estimating relative subset of known RNA transcripts (CIBERSORT) and immunophenoscore (IPS). The differential expression pattern based on human papillomavirus status was identified. A DEGsbased prognostic risk model was developed and validated. All statistical analyses were performed with R software (version 3.6.3). Results: By using the TCGA database, we identified DKK1, HBEGF, RNASE7, TNFRSF12A, INHBA, and IPIK3R3 as DEGs that were associated with patients' overall survival (OS). Patients were stratified into the high-and low-risk subgroups according to a DEGs-based prognostic risk model. Significant difference in OS was found between the high-and low-risk patients (1.64 vs. 2.18 years, P = 0.0017). In multivariate Cox analysis, the risk model was an independent prognostic factor for OS (hazard radio = 1.06, 95% confidence interval [1.02-1.10], P = 0.004). More CD8 + T cells and regulatory T cells were observed in the low-risk group and associated with a favorable prognosis. The IPS analysis suggested that the low-risk patients possessed a higher

show abstract

“…In the present study, univariate CPH analysis was performed to analyze the relations between the expression of genes and the OS of patients with LUAD, and the results exhibited that 99 genes were associated with the OS of LUAD patients. LASSO (34) was introduced in order to improve the prediction accuracy and interpretability of regression models by forcing certain coefficients to be set to zero, and effectively to choose a simpler model that did not include those coefficients. Based on this, the above 99 genes were included into a LASSO penalized CPH model, and as a result 4 genes with none-zero coefficients in this model were obtained.…”

Section: Discussionmentioning

confidence: 99%

“…This gene played a role in embryonic development and might be important in bone formation in adults [32]. Elevated expression of this gene had been observed in numerous human cancers and it corresponding protein promoted proliferation, invasion and growth in several kinds of cancer cell lines [33,34]. Aufderklamm S et al demonstrated that DKK-1 could inhibit osteoblast activity by blocking the Wnt pathway, which led to progression of metastatic prostate cancer [35].…”

Section: Discussionmentioning

confidence: 99%

Development and validation of a 4-gene combination for the prognostication in lung adenocarcinoma patients

Yin

Zhao

et al. 2020

J. Cancer

View full text Add to dashboard Cite

Objective: To identify a multi-gene prognostic factor in patients with lung adenocarcinoma (LUAD). Materials and methods Prognosis-related genes were screened in the TCGA-LUAD cohort. Then, patients in this cohort were randomly separated into training set and test set. Least absolute shrinkage and selection operator (LASSO) regression was performed to the penalized the Cox proportional hazards regression (CPH) model on the training set, and a prognostication combination based on the result of LASSO analysis was developed. By performing Kaplan-Meier curve analysis, univariate and multivariable CPH model on the overall survival (OS) as well as recurrence free survival (RFS), the prognostication performance of the multigene combination were evaluated. Moreover, we constructed a nomogram and performed decision curve analysis to evaluate the clinical application of the multigene combination. Results We obtained 99 prognosis-related genes and screened out a 4-gene combination (including CIDEC, ZFP3, DKK1, and USP4) according to the LASSO analysis. The results of survival analyses suggested that patients in the 4-gene combination low-risk group had better OS and RFS than those in the 4-gene combination high-risk group. The 4-gene mentioned was demonstrated to be independent prognostic factor of patients with LUAD in the training set(OS, HR=11.962, P<0.001; RFS, HR=9.281, P<0.001) and test set (OS, HR=5.377, P=0.003; RFS, HR=2.949, P=0.104). More importantly, its prognosis performance was well in the validation set (OS, HR=0.955, P=0.002; RFS, HR=1.042, P<0.001). Conclusions We introduced a 4-gene combination which could predict the survival of LUAD patients and might be an independent prognostic factor in LUAD.

show abstract

Elevated <em>DKK1</em> expression is an independent unfavorable prognostic indicator of survival in head and neck squamous cell carcinoma

Cited by 23 publications

References 35 publications

Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma

Immune-related gene signature for predicting the prognosis of head and neck squamous cell carcinoma

Systematic Profiling of Immune Risk Model to Predict Survival and Immunotherapy Response in Head and Neck Squamous Cell Carcinoma

Development and validation of a 4-gene combination for the prognostication in lung adenocarcinoma patients

Contact Info

Product

Resources

About