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

Tumor cells induce neural DKK1 expression to promote MDSC infiltration and subsequent T cell suppression

Nerves are often overlooked as key components of the tumor microenvironment. However, the molecular mechanisms underlying the reciprocal interactions between tumors and nerves remain largely unknown. In this study, we analyzed data from The Cancer Genome Atlas (TCGA) and identified a significant association between DKK1 expression and poor prognosis, as well as a correlation between DKK1 expression and myeloid-derived suppressor cell (MDSC) infiltration in head and neck squamous cell carcinoma (HNSCC) and pancreatic ductal adenocarcinoma (PDAC), two cancer types characterized by pronounced tumor-nerve interactions. Based on these findings, we hypothesize that tumors may induce DKK1 expression in nerves, and that nerve-derived DKK1 may promote MDSC infiltration and immunosuppression. To test this hypothesis, we employed a combination of experimental approaches, including in vitro co-culture of trigeminal ganglia with tumor cells, multiplex immunohistochemistry, and in vivo administration of DKK1 neutralizing antibodies. Our results indicate that tumor cells significantly induce DKK1 expression in ganglia in co-culture experiments. Additionally, in vivo orthotopic tumor models revealed that DKK1 levels were markedly elevated in both the plasma and ganglia of tumor-bearing mice. Neutralization DKK1 in vivo led to a reduction in MDSC levels and impaired MDSC-mediated T cell suppression in both HNSCC and PDAC orthotopic models. Furthermore, conditional deletion of neuronal DKK1 elucidated its role in MDSC infiltration and immune suppression. Our findings establish a novel molecular axis in which tumor cells modulate the immune microenvironment by inducing the expression of secreted proteins in nerves, thereby enriching the research landscape of the tumor microenvironment.

SIRT2-dependent DKK1 deacetylation aggravates polycystic ovary syndrome by targeting the TGF-β1/Smad3 signaling pathway

BACKGROUND

Polycystic ovarian syndrome (PCOS) is a prevalent metabolic and endocrine condition in females of reproductive age. This work was to discover the underlying role of Dickkopf 1 (DKK1) and its putative regulating mechanism in P COS.

METHODS

Mice recieved dehydroepiandrosterone (DHEA) injection to establish the in vivo P COS model.Hematoxylin and eosin (H&E) staining was performed for histological analysis. RT-qP CR and Western blotting were used to detect gene and protein expression. CCK-8 and flow cytometry assays were applied to detect cell viability and apoptosis. Co-immunoprecipitation (Co-IP) and immunoprecipitation (IP) were applied to assess association between DKK1 and SIRT2.

RESULTS

In this work, DKK1 is downregulated in P COS rats. It was revealed that DKK1 knockdown induced apoptosis and suppressed proliferation in KGN cells, whereas DKK1 overexpression had exactly the opposite effects. In addition, DKK1 deactivates the T GF-β1/SMad3 signaling pathway, thereby controlling KGN cell proliferation and apoptosis. Besides, SIRT2 inhibition reversed the impact of DKK1 overexpression on KGN cell proliferation and apoptosis. Furthermore, SIRT2 downregulated DKK1 expression by deacetylating DKK1 in KGN cells.

DISCUSSION

Altogether, we concluded that SIRT2-induced deacetylation of DKK1 triggers T GF-β1/Smad3 hyperactivation, thereby inhibiting proliferation and promoting apoptosis of KGN cells. The above results indicated that DKK1 might function as a latent target for P COS treatment.

Dickkopf-related protein 1 as a biomarker of local immune status and worse prognosis of Oral squamous cell carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is an infiltrative malignancy characterized by a significantly elevated recurrence rate. Dickkopf-related protein 1 (DKK1), which plays an oncogene role in many cancers, acts as an inhibitor of the Wingless protein (Wnt) signaling pathway. Currently, there is a lack of consensus regarding the role of DKK1 in OSCC or its clinical significance.

OBJECTIVE

To examine the role and effect of DKK1 in OSCC.

METHODS

The identification of differentially expressed genes (DEGs) in OSCC was conducted by utilizing databases such as The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A comprehensive analysis of gene expression profile interactions (GEPIA) and Kaplan-Meier curve were conducted to investigate the associations among DEGs, patient survival and prognosis in individuals with OSCC. The biological function of DKK1 in OSCC was investigated by using molecular biology approaches.

RESULTS

The expression of DKK1 was found to be upregulated in OSCC tissues at various stages. High levels of DKK1 expression exhibited a positive correlation with the overall survival (OS) and progression-free survival (PFS) rates among OSCC patients. DKK1 knockdown suppressed the proliferation and induced apoptotic response in OSCC cells. Moreover, DKK1 exerted a positive regulatory effect on HMGA2 expression, thereby modulating cell growth and apoptosis in OSCC. The expression of DKK1 was found to be positively correlated with the infiltration of immune cells in patients with OSCC. Additionally, higher levels of CD4 + T cells were associated with improved 5-year survival rates.

CONCLUSION

DKK1 is a prognostic biomarker for patients with OSCC.

Seven Immune-Related Genes' Prognostic Value and Correlation with Treatment Outcome in Head and Neck Squamous Cell Carcinoma

Background

Head and neck squamous cell carcinoma (HNSCC) is a growing concern worldwide, due to its poor prognosis, low responsiveness to treatment, and drug resistance. Since immunotherapy effectively improves HNSCC patients' survival status, it is important to continuously explore new immune-related predictive factors to accurately predict the immune landscape and clinical outcomes of individuals suffering from HNSCC.

Methods

The HNSCC transcriptome profiling of RNA-sequencing data was retrieved from TCGA database, and the microarray of GSE27020 was obtained from the GEO database for validation. The differentially expressed genes (DEGs) between HNSCC and normal samples were identified by multiple test corrections in TCGA database. The univariate and multivariate Cox analyses were performed to identify proper immune-related genes (IRGs) to construct a risk model. The Cox regression coefficient was employed for calculation of the risk score (RS) of IRG signature. The median value of RS was utilized as a basis to classify individuals with HNSCC into high- and low-risk groups. The Kaplan-Meier (K-M) survival analysis and receiver operating characteristic (ROC) curves were employed for the identification of the prognostic significance and precision of the IRG signature. The signature was also evaluated based on clinical variables, predictive nomogram, mutation analysis, infiltrating immune cells, immune-related pathways, and chemotherapeutic efficacy. The protein-protein interaction (PPI) network and functional enrichment pathway investigations were utilized to explore possible potential molecular mechanisms. Finally, the hub gene's differential mRNA expression levels were evaluated by means of the Gene Expression Profiling Interactive Analysis (GEPIA), and the Human Protein Atlas (HPA) was utilized for the validation of their translational levels.

Results

Collectively, 1593 DEGs between HNSCC and normal samples were identified, of which 136 IRGs were differentially expressed. Then, the 136 immune-related DEGs were mostly enriched in the cytokine-related signaling pathways by GO and KEGG analyses. After that, a valuable signature based on seven genes (DKK1, GAST, IGHM, IL12RB2, SLURP1, STC2, and TNFRSF4) was designed. The HNSCC patients into the low-risk group and the high-risk group were divided by using the median RS; the HNSCC patients in the high-risk group had a worse survival than those in the low-risk group. The risk signature was verified to be an independent predictive marker for HNSCC patients. Meanwhile, the RS had the largest contribution to survival of these patients based on the predictive nomogram. In addition, the low-risk HNSCC patients exhibited significantly enriched immune cells, along with an association with high chemosensitivity.

Conclusion

The constructed gene signature can independently function as a predictive indicator for the clinical features of HNSCC patients. The low-risk HNSCC subjects might benefit from immunotherapy and chemotherapy.

DKK1 affects survival of patients with head and neck squamous cell carcinoma by inducing resistance to radiotherapy and immunotherapy

BACKGROUND

Immune checkpoint inhibitors (ICIs) have been approved to treat various types of tumors, including head and neck squamous cell carcinoma (HNSC). However, most HNSC patients do not respond to ICIs. Radioimmunotherapy has been proposed to enhance the immune response rate in HNSC. Dickkopf-1 (DKK1), a secreted protein, plays important roles in the Wnt signaling pathways. Herein, we aimed to explore the effect of DKK1 on radioimmunotherapy in HNSC.

METHODS

We collected the gene expression profile and clinical information of HNSC patients from TCGA and GEO databases. The immune cell infiltration and immune score were assessed using R package CIBERSORT and ESTIMATE. The level of related pathways and biological processes were analyzed by GSEA. The signature scores of gene sets of interest were calculated by GSVA. We also performed cell viability and apoptosis assay, and clonogenic assay to investigate the radiation sensitivity of HSC-3 cells and CNE-2 cells after silencing DKK1 by siRNA.

RESULTS

We found DKK1 was significantly higher expressed in HNSC, and closely correlated with patients' survival time, especially the patients who received radiotherapy. DKK1-knockdown HSC-3 cells or CNE-2 cells showed a decrease in cell viability and colony formation, and an increase in apoptotic rate after radiation. DKK1^high tumors showed a more immunosuppressive microenvironment with lower infiltration of T cells and higher infiltration of marrow-derived suppressor cells (MDSCs).

CONCLUSION

Our data show that DKK1 can affect both radiotherapy and immunotherapy in HNSC, suggesting that DKK1 can be a potential target for radioimmunology in HNSC.

Impact of tobacco smoking on oral cancer genetics-A next-generation sequencing perspective

This study identified a total of 28 genetic loci (comprising 31 genes), which were found to be altered in oral cancer patients having a habit of tobacco smoking. Three loci, that is, 17p13.1 (TP53), 9p21.3 (CDKN2A), and 9q34.3 (NOTCH1) were found to be modified and common in three records whereas one locus, that is, 3q26.32 (PIK3CA) was found to be modified and common in two records. This study suggests that oral cancer patients should be categorized into different subgroups based on (i) genetic signatures, and (ii) smoking status, then the treatment strategies for each group should be precisely defined.

The Aging-Related Prognostic Signature Reveals the Landscape of the Tumor Immune Microenvironment in Head and Neck Squamous Cell Carcinoma

Background

Numerous 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.

Methods

Differentially 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.

Results

A 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.

Conclusions

The 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.

Transcriptome analysis reveals the prognostic and immune infiltration characteristics of glycolysis and hypoxia in head and neck squamous cell carcinoma

BACKGROUND

This study aims to construct a new prognostic gene signature in survival prediction and risk stratification for patients with Head and neck squamous cell carcinoma (HNSCC).

METHOD

The transcriptome profiling data and hallmark gene sets in the Molecular Signatures Database was used to explore the cancer hallmarks most relevant to the prognosis of HNSCC patients. Differential gene expression analysis, weighted gene co-expression network analysis, univariate COX regression analysis, random forest algorithm and multiple combinatorial screening were used to construct the prognostic gene signature. The predictive ability of gene signature was verified in the TCGA HNSCC cohort as the training set and the GEO HNSCC cohorts (GSE41613 and GSE42743) as the validation sets, respectively. Moreover, the correlations between risk scores and immune infiltration patterns, as well as risk scores and genomic changes were explored.

RESULTS

A total of 3391 differentially expressed genes in HNSCC were screened. Glycolysis and hypoxia were screened as the main risk factors for OS in HNSCC. Using univariate Cox analysis, 97 prognostic candidates were identified (P < 0.05). Top 10 important genes were then screened out by random forest. Using multiple combinatorial screening, a combination with less genes and more significant P value was used to construct the prognostic gene signature (RNF144A, STC1, P4HA1, FMNL3, ANO1, BASP1, MME, PLEKHG2 and DKK1). Kaplan-Meier analysis showed that patients with higher risk scores had worse overall survival (p < 0.001). The ROC curve showed that the risk score had a good predictive efficiency (AUC > 0.66). Subsequently, the predictive ability of the risk score was verified in the validation sets. Moreover, the two-factor survival analysis combining the cancer hallmarks and risk scores suggested that HNSCC patients with the high hypoxia or glycolysis & high risk-score showed the worst prognosis. Besides, a nomogram based on the nine-gene signature was established for clinical practice. Furthermore, the risk score was significantly related to tumor immune infiltration profiles and genome changes.

CONCLUSION

This nine-gene signature associated with glycolysis and hypoxia can not only be used for prognosis prediction and risk stratification, but also may be a potential therapeutic target for patients with HNSCC.

Pan-Cancer Analyses Reveal Oncogenic and Immunological Role of Dickkopf-1 (DKK1)

WNT signaling pathway inhibitor Dickkopf-1 (DKK1) is related to cancer progression; however, its diagnostic and prognostic potential have not been investigated in a pan-cancer perspective. In this study, multiple bioinformatic analyses were conducted to evaluate therapeutic value of DKK1 in human cancers. The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project served as data resources. The Wilcoxon rank test was performed to evaluate the expression difference of DKK1 between cancer tissues and normal tissues. A Kaplan-Meier curve and Cox regression were used for prognosis evaluation. Single-sample gene set enrichment analysis (ssGSEA) was used to evaluate the association of DKK1 expression with the immune cell infiltration. The potential function of DKK1 was explored by STRING and clusterProfiler. We found that the expression level of DKK1 is significantly different in different cancer types. Importantly, we demonstrated that DKK1 is an independent risk factor in ESCA, LUAD, MESO, and STAD. Further analysis revealed that DKK1 had a large effect on the immune cell infiltration and markers of certain immune cells, such as Th1 and Th2 cells. PPI network analysis and further pathway enrichment analysis indicated that DKK1 was mainly involved in the WNT signaling pathway. Our findings suggested that DKK1 might serve as a marker of prognosis for certain cancers by affecting the WNT signaling pathway and tumor immune microenvironment.

DKK1 inhibits canonical Wnt signaling in human papillomavirus-positive penile cancer cells

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Elevated expression of Wnt pathway associated factors in HPV-positive penile cancer cells.

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lacking nuclear beta-catenin translocation indicated an actively abrogated Wnt signaling.

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elevated expression of the Wnt antagonist DKK1 in HPV-positive penile cancer cells.

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DKK1-driven autocrine Wnt pathway inhibition in penile cancer cells.

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DKK1⁺ penile cancers are with a higher frequency HPV⁺, less differentiated and grow more aggressively.

Penile squamous cell cancer (PSCC) is the most frequent penile malignant disease. Infections with human papillomaviruses (HPV) are a major etiologic driver of PSCC. However, the molecular details of the underlying carcinogenesis are understudied because of rare clinical specimens and missing cell lines. Here, we investigated if the expression of high-risk HPV16 oncogenes causes an augmentation of the Wnt pathway using unique HPV-positive penile cancer (PeCa) cell lines in monolayer and organotypic 3D raft cultures as well as tissue micro arrays containing clinical tissue specimens. The HPV oncoproteins enhanced the expression of Leucine-rich repeat-containing G-protein coupled receptor 6 (LGR6) and the HPV-positive PeCa cells expressed a signature of Wnt target and stemness-associated genes. However, the notable lack of nuclear β-catenin in vitro and in situ raised the question if the enhanced expression of Wnt pathway factors is tantamount to an active Wnt signaling. Subsequent TOP-flash reporter assays revealed Wnt signaling as absent and not inducible by respective Wnt ligands in PeCa cell lines. The HPV-positive PeCa cells and especially HPV-positive PeCa specimens of the tumor core expressed the Wnt antagonist and negative feedback-regulator Dickkopf1 (DKK1). Subsequent neutralization experiments using PeCa cell line-conditioned media demonstrated that DKK1 is capable to impair ligand-induced Wnt signaling. While gene expression analyses suggested an augmented and active canonical Wnt pathway, the respective signaling was inhibited due to the endogenous expression of the antagonist DKK1. Subsequent TMA stainings indicated Dkk1 as linked with HPV-positivity and metastatic disease progression in PeCa suggesting potential as a prognostic marker.

An Epithelial-Mesenchymal Transition Hallmark Gene-Based Risk Score System in Head and Neck Squamous-Cell Carcinoma

Background

Epithelial-to-mesenchymal transition (EMT) program plays a critical role in cancer. Thus, we attempted to generate a risk score system according to the expression pattern of different EMT hallmark genes in head and neck squamous-cell carcinoma (HNSC).

Methods

Differentially expressed EMT hallmark genes were screened to generate a risk score (RS) on TCGA HNSC dataset. The relative prognostic value of the RS compared to clinicopathological characteristics was explored using multivariable Cox analysis. Functional enrichment analysis was performed to reveal the biological characteristics. An external dataset was applied to validate the prognostic value of the RS.

Results

Nine genes constituted the EMT hallmark gene-based RS, which is significantly associated with poor prognosis and could successfully divide patients with HNSC into high- and low-risk groups. The RS was also an independent prognostic indicator compared to routine clinical factors.

Conclusion

We proposed and validated a nine-EMT hallmark gene-based risk score system in HNSC.

A Novel Immune-Related Prognostic Signature in Head and Neck Squamous Cell Carcinoma

The immune response within the tumor microenvironment plays a key role in tumorigenesis and determines the clinical outcomes of head and neck squamous cell carcinoma (HNSCC). However, to date, very limited robust and reliable immunological biomarkers have been developed that are capable of estimating prognosis in HNSCC patients. In this study, we aimed to identify the effects of novel immune-related gene signatures (IRGs) that can predict HNSCC prognosis. Based on gene expression profiles and clinical data of HNSCC patient cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, a total of 439 highly variable expressed immune-related genes (including 239 upregulated and 200 downregulated genes) were identified by using differential gene expression analysis. Pathway enrichment analysis indicated that these immune-related differentially expressed genes were enriched in inflammatory functions. After process screening in the training TCGA cohort, six immune-related genes (PLAU, STC2, TNFRSF4, PDGFA, DKK1, and CHGB) were significantly associated with overall survival (OS) based on the LASSO Cox regression model. Integrating these genes with clinicopathological features, a multivariable model was built and suggested better performance in determining patients’ OS in the testing cohort, and the independent validation cohort. In conclusion, a well-established model encompassing both immune-related gene signatures and clinicopathological factors would serve as a promising tool for the prognostic prediction of HNSCC.

Activation of the miR-371/372/373 miRNA Cluster Enhances Oncogenicity and Drug Resistance in Oral Carcinoma Cells

Oral squamous cell carcinoma (OSCC) is among the leading causes of cancer-associated deaths worldwide. Family members in miR-371/372/373 miRNA cluster, which is localized at human chromosome 19q13.4, are co-expressed in both human stem cells and malignancies. The individual miRNA in this cluster are also involved in modulating the pathogenesis of malignancies as either oncogenes or suppressors. The 19q13 region is frequently gained in head and neck cancers. High expression of miR-372 and miR-373 are survival predictors for OSCC. However, the role of the miR-371/372/373 cluster in oral carcinogenesis remains to be fully investigated. We use the clustered, regularly interspaced, short palindromic repeats (CRISPR)-Cas9 system to establish OSCC cell subclones that had the miR-371/372/373 cluster deleted. In addition, further subclones were established that had the promoter of this cluster deleted. Concordant silencing in SAS cells of miR-371/372/373 decreased oncogenic potential, increased cisplatin sensitivity, activated p53, and upregulated the expression of Bad and DKK1. We also employed the CRISPR/dCas9 synergistic activation mediator system, which allowed robust transcriptional activation of the whole miR-371/372/373 cistron. Upregulation of endogenous miR-371/372/372 expression increased both oncogenicity and drug resistance. These were accompanied by a slight activation of AKT, β-catenin, and Src. This study identifies the oncogenic role of the miR-371/372/373 cluster in OSCC. Using CRISPR based strategy can be a powerful paradigm that will provide mechanistic insights into miRNA cluster functionality, which will also likely help the development of targeting options for malignancies.

Development and validation of a three-long noncoding RNA signature for predicting prognosis of patients with gastric cancer

BACKGROUND

Gastric cancer (GC) is one of the most frequently diagnosed gastrointestinal cancers throughout the world. Novel prognostic biomarkers are required to predict the prognosis of GC.

AIM

To identify a multi-long noncoding RNA (lncRNA) prognostic model for GC.

METHODS

Transcriptome data and clinical data were downloaded from The Cancer Genome Atlas. COX and least absolute shrinkage and selection operator regression analyses were performed to screen for prognosis associated lncRNAs. Receiver operating characteristic curve and Kaplan-Meier survival analyses were applied to evaluate the effectiveness of the model.

RESULTS

The prediction model was established based on the expression of AC007991.4, AC079385.3, and AL109615.2 Based on the model, GC patients were divided into “high risk” and “low risk” groups to compare the differences in survival. The model was re-evaluated with the clinical data of our center.

CONCLUSION

The 3-lncRNA combination model is an independent prognostic factor for GC.

The Clinical Significance of Dickkopf Wnt Signaling Pathway Inhibitor Gene Family in Head and Neck Squamous Cell Carcinoma

BACKGROUND Dickkopf Wnt signaling pathway inhibitor (DKK) gene family, which is known to inhibit the Wnt regulation process, is widely found in cancers. However, the roles and functions of specific family members in head and neck squamous cell carcinoma (HNSCC) are still unclear. MATERIAL AND METHODS Online bioinformatics tools (Oncomine, UALCAN, Kaplan-Meier plotter, GEPIA, Metascape, and STRING) were used to analyze the relationships between distinct DKKs and HNSCC. The transcriptome expression, clinical association, functions, pathways, and protein-protein interaction networks of DKKs in HNSCC were explored. RESULTS The mRNA expression of DKK1, DKK3, and Dickkopf-like acrosomal protein 1 (DKKL1) in HNSCC was significantly higher than in normal tissues, while that of DKK4 was lower. The mRNA expression of DKK1, DKK3, and DKKL1 was elevated in higher-grade HNSCC. The mRNA expression of DKK1 and DKK3 was elevated in human papillomavirus (HPV)-negative HNSCC, while DKKL1 had a higher mRNA expression in HPV-positive HNSCC. In addition, DKK1 was significantly associated with unfavorable overall survival in HNSCC patients. DKK3 was more likely to be a negative factor for the 5-year survival rate, while DKK4 was the opposite. DKK1 function was mainly enriched in GTPase-mediated signal transduction. Porcupine O-acyltransferase, a key regulator of the Wnt signaling pathway, was also associated with DKK1 in the protein-protein interaction network. CONCLUSIONS With regard to improving the therapeutic strategies of HNSCC in the future, DKK1 could be an unfavorable prognostic biomarker. DKK3, DKK4, and DKKL1 might be potential biomarkers for HNSCC.

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

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 DEGs-based 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 IPS score and a higher immunoreactivity phenotype, which were correlated with better immunotherapy response.

Conclusion

Collectively, we established a reliable DEGs-based risk model with potential prognostic value and capacity to predict the immunophenotype of HNSCC patients.

Circulating osteocyte-related biomarkers (vitamin D, sclerostin, dickkopf-1), hepcidin, and oxidative stress markers in early breast cancer: Their impact in disease progression and outcome

Breast cancer (BC) is a major concern to female health worldwide. We assessed the circulating osteocyte-related biomarkers, hepcidin, and oxidative stress status among early-stage BC patients in aspects of clinical severity and impact on the outcome. The study incorporated 73 patients categorized into 57 early-stage BC and 16 benign breast diseases and 30 healthy controls. Serum 25-hydroxyvitamin D [25(OH)D], sclerostin (SOST), dickkopf-1(DKK1), and hepcidin were measured using ELISA, while, serum oxidative stress markers were assessed by spectrophotometry. Our results show that patients with BC showed significant increase in the mean levels of DKK1, SOST, hepcidin, and LPER and significant decrease in the mean levels of 25(OH)D, SOD, GPx, and Hb when compared with controls and benign breast diseases. Significantly higher DKK1, hepcidin, and SOD levels among benign breast diseases were found in comparison to control group. There were significantly lower levels of 25(OH)D, SOD, and Hb and significantly higher levels of SOST, DKK1, hepcidin, No, and LPER with advanced grade. Lower levels of 25(OH)D, SOD and higher levels of SOST, hepcidin were observed with increasing the malignant stage. Reduced levels of 25(OH)D, and SOD were significantly associated with poor prognosis and were strong predictors among BC. There were significant negative correlations between 25(OH)D with LPER, SOST, and hepicidin. We conclude that low 25(OH)D, high SOST, DKK1, and hepcidin, and dysregulated oxidative stress could be helpful in early detection and assessment of BC. 25(OH)D, and SOD were the most relevant to tumor progression and prognosis which indicate a significant role in the BC pathogenesis and could be promising targets in management. Our research paves the way to disrupt vicious circle between these biomarkers to obtain the best care of BC.

Analyzing the prognostic value of DKK1 expression in human cancers based on bioinformatics

Background

The Dickkopf1 (DKK1) gene encodes a protein that belongs to the Dickkopf family. The protein can inhibit the Wnt signaling pathway which plays a key role in the carcinogenesis and progression of various types of cancers. Based on this, we hypothesized that the differential expression of DKK1 may figure significantly in cancers by regulating Wnt signaling pathway transduction. In this study, we conducted bioinformatics analysis to evaluate the prognostic and therapeutic value of DKK1 expression level in human cancers.

Methods

The expression level was analyzed by using the Oncomine database and Gene Expression Profiling Interactive Analysis tool. The analysis of prognosis was conducted by using the UALCAN, Gene Expression Profiling Interactive Analysis (GEPIA), and DriverDBv3 databases. We also investigated using DKK1 promoter methylation to define cancer types through the UALCAN database. Meanwhile, the related functional networks of DKK1 were analyzed by using the GeneMANIA interactive tool and Cytoscape software. Furthermore, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis was conducted using the Metascape online website, and we used the cBioPotartal database to explored DKK1 expression, aberrant information, and the co-expression genes in the subgroups of lung cancer. Finally, we performed the overall survival (OS) meta-analysis of the DKK1 expression in lung squamous cell carcinoma (LUSC) via the Lung Cancer Explorer (LCE).

Results

DKK1 was differentially expressed in different types of human cancers. DKK1 was overexpressed in human cancers including head and neck squamous cell carcinoma (HNSC), LUSC, and pancreatic adenocarcinoma (PAAD). Overexpression of DKK1 indicated adverse OS in bladder urothelial carcinoma (BLCA), HNSC, and PADD, but no difference in OS was found between the LUSC and healthy groups. The high expression of DKK1 was also associated with shorter disease-free survival (DFS) in HNSC, LUSC, and PAAD. Gene regulation network analysis indicated that DKK1 was mainly involved in Wnt signaling pathways and several other signaling pathways.

Conclusions

Our findings showed that DKK1 is significantly expressed in various cancers and could be a biomarker for targeted therapy and a predictor for prognosis of these specific cancers. The bioinformatics analysis revealed a significant overexpression of DKK1 in HNSC, LUSC, and PAAD, with DKK1 overexpression being associated with adverse outcome in these patients, but how DKK1 expression levels relate to hematological malignancies and prognosis is still unclear. These new insights into the function of DKK1 may provide a basis for new targeted drug therapy and an avenue for further investigation into the mechanisms underlying carcinogenesis of DKK1 in different cancer types.

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

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.

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

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.

DKK1 inhibits breast cancer cell migration and invasion through suppression of β-catenin/MMP7 signaling pathway

Background

DKK1 has been reported to act as a tumor suppressor in breast cancer. However, the mechanism of DKK1 inhibits breast cancer migration and invasion was still unclear.

Methods

Western blot and real time PCR was used to detect the expression of DKK1, β-catenin and MMP7 in breast cancer cells. Wound scratch assay and transwell assay was employed to examine migration and invasion of breast cancer cell.

Results

DKK1 overexpression dramatically inhibits breast cancer cell migration and invasion. Knockdown of DKK1 promotes migration and invasion of breast cancer cells. DKK1 suppressed breast cancer cell migration and invasion through suppression of β-catenin and MMP7 expression. XAV-939, an inhibitor of β-catenin accumulation could reverse DKK1 silencing-induced MMP7 expression in breast cancer cells. Meanwhile, XAV-939 also could reverse the increase in the cell number invaded through Matrigel when DKK1 was knockdown. Furthermore, depletion of MMP7 also could reverse DKK1 knockdown-induced increase in the cell number invaded through Matrigel.

Conclusions

DKK1 inhibits migration and invasion of breast cancer cell through suppression of β-catenin/MMP7 pathway, our findings offered a potential alternative for breast cancer prevention and treatment.