TTK (threonine tyrosine kinase) regulates the malignant behaviors of cancer cells and is regulated by microRNA-582-5p in ovarian cancer

Expression of circular RNA has-circ-0009158 and identification of associated miRNA-mRNA network in hepatocellular carcinoma

Primary hepatocellular carcinoma (HCC) affects people all over the world. Circular RNAs are involved in the growth and development of several malignancies and regulate a number of biological processes. However, the roles of has-circ-0009158 in HCC remain unknown. This study explored the expression and associated miRNA-mRNA network of has-circ-0009158 in HCC. Quantitative real-time polymerase chain reaction was used to measure the expression of hsa-circ-0009158 in the HCC tissues of 143 patients and four human HCC cell lines. Then, the potential relationship of hsa-circ-0009158 expression with clinical characteristics and prognosis of patients was analyzed using the GO and KEGG databases. Correlated miRNA-mRNA networks were forecasted using the TCGA database and Cytoscape software. The hsa-circ-0009158 expression was significantly upregulated in HCC tissues and cell lines (P<0.001). The multivariate Cox analysis revealed that HCC patients were associated with high hsa-circ-0009158 expression. The bioinformatics analysis screened 1 miRNA, and 248 mRNAs associated with the circRNA in HCC. A pathway analysis suggested that the differentially expressed genes (DEGs) may be linked to the development and growth of HCC tumors. Ten hub genes (MELK, NCAPG, BUB1B, BIRC5, CDCA8, CENPF, BUB1, CDK1, TTK, TPX2) were identified from the PPI network based on the 248 genes. Additionally, the 10 hub genes that were verified had an association between high expression levels and low overall survival rates. As a result, the high expression of hsa-circ-0009158 was found to be a separate risk factor for recurrence and a poor prognosis in HCC patients.

CWH43 Is a Novel Tumor Suppressor Gene with Negative Regulation of TTK in Colorectal Cancer

Colorectal cancer (CRC) ranks among the most prevalent forms of cancer globally, and its late-stage survival outcomes are less than optimal. A more nuanced understanding of the underlying mechanisms behind CRC's development is crucial for enhancing patient survival rates. Existing research suggests that the expression of Cell Wall Biogenesis 43 C-Terminal Homolog (CWH43) is reduced in CRC. However, the specific role that CWH43 plays in cancer progression remains ambiguous. Our research seeks to elucidate the influence of CWH43 on CRC's biological behavior and to shed light on its potential as a therapeutic target in CRC management. Utilizing publicly available databases, we examined the expression levels of CWH43 in CRC tissue samples and their adjacent non-cancerous tissues. Our findings indicated lower levels of both mRNA and protein expressions of CWH43 in cancerous tissues. Moreover, we found that a decrease in CWH43 expression correlates with poorer prognoses for CRC patients. In vitro experiments demonstrated that the suppression of CWH43 led to increased cell proliferation, migration, and invasiveness, while its overexpression had inhibitory effects. Further evidence from xenograft models showed enhanced tumor growth upon CWH43 silencing. Leveraging data from The Cancer Genome Atlas (TCGA), our Gene Set Enrichment Analysis (GSEA) indicated a positive relationship between low CWH43 expression and the activation of the epithelial-mesenchymal Transition (EMT) pathway. We conducted RNA sequencing to analyze gene expression changes under both silenced and overexpressed CWH43 conditions. By identifying core genes and executing KEGG pathway analysis, we discovered that CWH43 appears to have regulatory influence over the TTK-mediated cell cycle. Importantly, inhibition of TTK counteracted the tumor-promoting effects caused by CWH43 downregulation. Our findings propose that the decreased expression of CWH43 amplifies TTK-mediated cell cycle activities, thus encouraging tumor growth. This newly identified mechanism offers promising avenues for targeted CRC treatment strategies.

TTK is a potential regulator of tumor progression correlated with dedifferentiation and immune cell infiltration in papillary thyroid cancer

OBJECTIVE

To investigate the role and clinical significance of threonine tyrosine kinase (TTK) in papillary thyroid cancer (PTC).

METHODS

TTK expression in PTC and normal groups were compared using TCGA data and in vitro experiments. The prognostic value of TTK and its possible role in PTC dedifferentiation was evaluated. Next, TTK involvement in PTC occurrence and progression was analyzed via in vitro experiments. Subsequently, analyses of enrichment and immune cell infiltration were conducted to reveal the possible mechanism. Finally, we predicted the target miRNAs followed by performing a luciferase reporter experiment.

RESULTS

TTK upregulation was observed in PTC, and its elevated level was significantly related to an unfavorable prognosis (P < 0.05). Interestingly, TTK negatively correlated with thyroid differentiation score (TDS), and patients with higher TDS showed longer survival (all P < 0.05). PTC cell growth, migration, and invasion were inhibited upon TTK knockdown. Besides, TTK was involved in metabolic processes and regulated cell adhesion molecules pathway. Its overexpression was positively associated with immune cell infiltrates (P < 0.05). Moreover, miR-582-5p was an upstream target of TTK.

CONCLUSION

TTK serves as a potential biomarker for tumorigenesis and prognosis in PTC, especially for those that may differentiate into more aggressive thyroid cancers.

Inhibition of apoptosis through AKT-mTOR pathway in ovarian cancer and renal cancer

OBJECTIVE

Ovarian cancer and renal cancer are malignant tumors; however, the relationship between TTK Protein Kinase (TTK), AKT-mTOR pathway and ovarian cancer, renal cancer remains unclear.

METHODS

Download GSE36668 and GSE69428 from Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was performed. Created protein-protein interaction (PPI) network. Used Gene Ontology analysis (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for functional enrichment analysis. Gene Set Enrichment Analysis (GSEA) analysis and survival analysis were performed. Created animal model for western blot analysis. Gene Expression Profiling Interactive Analysis (GEPIA) was performed to explore the role of TTK on the overall survival of renal cancer.

RESULTS

GO showed that DEGs were enriched in anion and small molecule binding, and DNA methylation. KEGG analysis presented that they mostly enriched in cholesterol metabolism, type 1 diabetes, sphingolipid metabolism, ABC transporters, etc., TTK, mTOR, p-mTOR, AKT, p-AKT, 4EBP1, p-4EBP1 and Bcl-2 are highly expressed in ovarian cancer, Bax, Caspase3 are lowly expressed in ovarian cancer, cell apoptosis is inhibited, leading to deterioration of ovarian cancer. Furthermore, the TTK was not only the hub biomarker of ovarian cancer, but also one significant hub gene of renal cancer, and its expression was up-regulated in the renal cancer. Compared with the renal cancer patients with low expression of TTK, the patients with high expression of TTK have the poor overall survival (P = 0.0021).

CONCLUSION

TTK inhibits apoptosis through AKT-mTOR pathway, worsening ovarian cancer. And TTK was also one significant hub biomarker of renal cancer.

Integrated multi-omics analyses and functional validation reveal TTK as a novel EMT activator for endometrial cancer

BACKGROUND

Cancer-testis antigens (CTAs) are often expressed in tumor and testicular tissues but not in other normal tissues. To date, there has been no comprehensive study of the expression and clinical significance of CTA genes associated with endometrial cancer (EC) development. Additionally, the clinical relevance, biological role, and molecular mechanisms of the CTA gene TTK protein kinase (TTK) in EC are yet to be fully understood.

METHODS

Using bioinformatics methods, we comprehensively investigated the genomic, transcriptomic, and epigenetic changes associated with aberrant TTK overexpression in EC samples from the TCGA database. We further investigated the mechanisms of the lower survival associated with TTK dysregulation using single-cell data of EC samples from the GEO database. Cell functional assays were used to confirm the biological roles of TTK in EC cells.

RESULTS

We identified 80 CTA genes that were more abundant in EC than in normal tissues, and high expression of TTK was significantly linked with lower survival in EC patients. Furthermore, ROC analysis revealed that TTK could accurately distinguish stage I EC tissues from benign endometrial samples, suggesting that TTK has the potential to be a biomarker for early EC detection. We found TTK overexpression was more prevalent in EC patients with high-grade, advanced tumors, serous carcinoma, and TP53 alterations. Furthermore, in EC tissue, TTK expression showed a strong positive correlation with EMT-related genes. With single-cell transcriptome data, we identified a proliferative cell subpopulation with high expression of TTK and known epithelial-mesenchymal transition (EMT)-related genes and transcription factors. When proliferative cells were grouped according to TTK expression levels, the overexpressed genes in the TTK^high group were shown to be functionally involved in the control of chemoresistance. Utilizing shRNA to repress TTK expression in EC cells resulted in substantial decreases in cell proliferation, invasion, EMT, and chemoresistance. Further research identified microRNA-21 (miR-21) as a key downstream regulator of TTK-induced EMT and chemoresistance. Finally, the TTK inhibitor AZ3146 was effective in reducing EC cell growth and invasion and enhancing the apoptosis of EC cells generated by paclitaxel.

CONCLUSION

Our findings establish the clinical significance of TTK as a new biomarker for EC and an as-yet-unknown carcinogenic function. This present study proposes that the therapeutic targeting of TTK might provide a viable approach for the treatment of EC.

Combined 3D-QSAR, molecular docking and dynamics simulations studies to model and design TTK inhibitors

Tyrosine threonine kinase (TTK) is the key component of the spindle assembly checkpoint (SAC) that ensures correct attachment of chromosomes to the mitotic spindle and thereby their precise segregation into daughter cells by phosphorylating specific substrate proteins. The overexpression of TTK has been associated with various human malignancies, including breast, colorectal and thyroid carcinomas. TTK has been validated as a target for drug development, and several TTK inhibitors have been discovered. In this study, ligand and structure-based alignment as well as various partial charge models were used to perform 3D-QSAR modelling on 1H-Pyrrolo[3,2-c] pyridine core containing reported inhibitors of TTK protein using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) approaches to design better active compounds. Different statistical methods i.e., correlation coefficient of non-cross validation (r2), correlation coefficient of leave-one-out cross-validation (q2), Fisher's test (F) and bootstrapping were used to validate the developed models. Out of several charge models and alignment-based approaches, Merck Molecular Force Field (MMFF94) charges using structure-based alignment yielded highly predictive CoMFA (q2 = 0.583, Predr2 = 0.751) and CoMSIA (q2 = 0.690, Predr2 = 0.767) models. The models exhibited that electrostatic, steric, HBA, HBD, and hydrophobic fields play a key role in structure activity relationship of these compounds. Using the contour maps information of the best predictive model, new compounds were designed and docked at the TTK active site to predict their plausible binding modes. The structural stability of the TTK complexes with new compounds was confirmed using MD simulations. The simulation studies revealed that all compounds formed stable complexes. Similarly, MM/PBSA method based free energy calculations showed that these compounds bind with reasonably good affinity to the TTK protein. Overall molecular modelling results suggest that newly designed compounds can act as lead compounds for the optimization of TTK inhibitors.

Comprehensive Molecular Analyses of a Macrophage-Related Gene Signature With Regard to Prognosis, Immune Features, and Biomarkers for Immunotherapy in Hepatocellular Carcinoma Based on WGCNA and the LASSO Algorithm

Macrophages have been reported to exert a crucial role in hepatocellular carcinoma (HCC). This study aimed to explore the macrophage-related genes and establish a macrophage-related signature (MRS) model to predict the overall survival (OS) of patients with HCC based on these genes’ expression. We screened the macrophage-related gene module by weighted gene coexpression network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO) Cox regression analysis was utilized for further selection, and the selected genes were entered into stepwise regression to develop the MRS model, which was further validated in the Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC) datasets. We analyzed the biological phenotypes associated with macrophages in terms of functional enrichment, tumor immune signature, and tumor mutational signature. The patient’s response to immunotherapy was inferred by the tumor immune dysfunction and exclusion (TIDE) score, the immunophenotype score (IPS), and the IMvigor210 dataset. A novel MRS model was established based on the LASSO regression coefficients of the genes PON1, IL15RA, NEIL3, HILPDA, PFN2, HAVCR1, ANXA10, CDCA8, EPO, S100A9, TTK, KLRB1, SPP1, STC2, CYP26B1, GPC1, G6PD, and CBX2. In either dataset, MRS was identified as an independent risk factor for OS in HCC patients. Additionally, our research indicated that a high-risk score in the MRS model was significantly correlated with tumor staging, pathological grade, tumor–node–metastasis (TNM) stage, and survival. Several genes of the human leukocyte antigen (HLA) family and immune checkpoints were highly expressed in the high-risk group. In addition, the frequency of tumor mutations was also higher in the high-risk group. According to our analyses, a higher risk score in the MRS model may predict a better response to immunotherapy.