Prognostic values and clinical relationship of TYK2 in laryngeal squamous cell cancer

Molecular Characteristics of TYK2 Gene Expressions in Patients with Colorectal Cancer

Background

TYK2 is a member of the JAK family and is known to mediate signals of multiple cytokines that play a crucial role in immune and inflammatory signaling. Activation of TYK2 in tumor cells has been linked to promote cell survival, growth, and invasion. This study aimed to investigate the expression of tyrosine kinase 2 (TYK2) in colorectal cancer (CRC) and adjacent control tissues.

Materials and Methods

Quantitative Real-Time PCR (qRT-PCR) method was elaborated to examine the expression levels of TYK2 in 100 colorectal tumor tissues and adjacent tissues as a control. Furthermore, we analyzed the diagnostic power of the mentioned TYK2 by plotting the receiver operating characteristic (ROC) curve.

Results

Our results revealed that the expression level of TYK2 was significantly up-regulated in CRC patients sample compared to the adjacent sample of the control group. Analysis of patient's clinic pathological features shows that expressions TYK2 were differently associated with lymph vascular invasion and TMN stage (P < 0.0001, P < 0.0006).

Conclusion

These results indicated that TYK2 levels potential biomarkers for diagnosing colorectal cancer may be identified.

8-Gene signature related to CD8+ T cell infiltration by integrating single-cell and bulk RNA-sequencing in head and neck squamous cell carcinoma

Background: CD8⁺ T cells, a critical component of the tumor immune microenvironment, have become a key target of cancer immunotherapy. Considering the deficiency of robust biomarkers for head and neck squamous cell carcinoma (HNSCC), this study aimed at establishing a molecular signature associated with CD8+T cells infiltration.

Methods: Single-cell RNA sequencing data retrieved from the Gene Expression Omnibus (GEO) database was analyzed to obtain the different cell types. Next, the cell proportions were investigated through deconvolution of RNA sequencing in the Cancer Genome Atlas (TCGA) database, and then the immune-related genes (IRGs) were identified by weighted gene co-expression network analysis (WGCNA). LASSO-Cox analysis was employed to establish a gene signature, followed by validation using a GEO dataset. Finally, the molecular and immunological properties, and drug responses between two subgroups were explored by applying “CIBERSORT”, “ESTIMATE”, and single sample gene set enrichment analysis (ssGSEA) methods.

Results: A total of 215 differentially expressed IRGs were identified, of which 45 were associated with the overall survival of HNSCC. A risk model was then established based on eight genes, including DEFB1, AICDA, TYK2, CCR7, SCARB1, ULBP2, STC2, and LGR5. The low-risk group presented higher infiltration of memory activated CD4⁺ T cells, CD8⁺ T cells, and plasma cells, as well as a higher immune score, suggesting that they could benefit more from immunotherapy. On the other hand, the high-risk group showed higher abundance of activated mast cells and M2 macrophages, as well as a lower immune score.

Conclusion: It was evident that the 8-gene signature could accurately predict HNSCC prognosis and thus it may serve as an index for clinical treatment.

Identification of Gene-Tyrosine Kinase 2 (TYK2) in Head and Neck Squamous Cell Carcinoma Patients-An Integrated Bioinformatics Approach

Background

The human tyrosine kinase 2 (TYK2) has been found to be associated with at least 20 autoimmune diseases; however, its tumor-regulating role in head and neck squamous cell carcinoma (HNSC) has not been researched by using an integrative bioinformatics approach, yet.

Objective

To investigate the regulating mechanisms of the TYK2 gene in HNSC in terms of its expression pattern, prognostic values, involved biological functions, and implication of tumor immunity.

Methods

The TYK2 gene expression pattern and regulatory involvement in HNSC were investigated using publically accessible data from TCGA database. R software tools and public web servers were utilized to conduct statistical analysis on cancer and noncancerous samples.

Results

TYK2 was found to be significantly upregulated in HNSC samples compared with healthy control samples. The expression of TYK2 gene was shown to be associated with the prognosis of HNSC by showing its upregulation represented better survival outcome. The regulating role of TYK2 in HNSC was found mainly in several pathways including DNA replication, base excision repair, apoptosis, p53 signaling pathway, and NF-kappa B signaling pathway. The gene set enrichment analysis (GSEA) results showed that TYK2-significantly correlated genes were mainly enriched in several biological functional terms including cell cycle, DNA replication, PLK1 pathway, ATR pathway, and Rho GTPase pathway. In addition, TYK2 was found to be involved in tumor immunity, showing positive correlation with the majority of tumor infiltrating immune cells, immune checkpoint genes, and significant representative components of tumor microenvironment, according to the ESTIMATE-Stromal-Immune score.

Conclusions

Given the dysregulation, prognostic values, regulating tumor progression-related pathways, and the tumor immune-modulatory role of TYK2 in HNSC, the TYK2 gene should be regarded as a potential therapeutic target in treating head and neck cancer.

Development and Validation of a Necroptosis-Related Prognostic Model in Head and Neck Squamous Cell Carcinoma

Necroptosis is a new regulated cell-death mechanism that plays a critical role in various cancers. However, few studies have considered necroptosis-related genes (NRGs) as prognostic indexes for cancer. As one of the most common cancers in the world, head and neck squamous cell carcinoma (HNSCC) lacks effective diagnostic strategies at present. Hence, a series of novel prognostic indexes are required to support clinical diagnosis. Recently, many studies have confirmed that necroptosis was a key regulated mechanism in HNSCC, but no systematic study has ever studied the correlation between necroptosis-related signatures and the prognosis of HNSCC. Thus, in the current study, we aimed to construct a risk model of necroptosis-related signatures for HNSCC. We acquired 159 NRGs from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and compared them with samples of normal tissue downloaded from The Cancer Genome Atlas (TCGA), ultimately screening 38 differentially expressed NRGs (DE-NRGs). Then, by Cox regression analysis, we successfully identified 7 NRGs as prognostic factors. We next separated patients into high- and low-risk groups via the prognostic model consisting of 7 NRGs. Individuals in the high-risk group had much shorter overall survival (OS) times than their counterparts. Furthermore, using Cox regression analysis, we confirmed the necroptosis-related prognostic model to be an independent prognostic factor for HNSCC. Receiver operating characteristic (ROC) curve analysis proved the predictive ability of this model. Finally, Gene Expression Omnibus (GEO) data sets (GSE65858, GSE4163) were used as independent databases to verify the model’s predictive ability, and similar results obtained from two data sets confirmed our conclusion. Collectively, in this study, we first referred to necroptosis-related signatures as an independent prognostic model for cancer via bioinformatics measures, and the necroptosis-related prognostic model we constructed could precisely forecast the OS time of patients with HNSCC. Utilizing the model may significantly improve the diagnostic rate and provide a series of new targets for treatment in the future.