TEAD4 is an Immune Regulating-Related Prognostic Biomarker for Bladder Cancer and Possesses Generalization Value in Pan-Cancer

Regulation of Tumor Microenvironment through YAP/TAZ under Tumor Hypoxia

In solid tumors such as hepatocellular carcinoma (HCC), hypoxia is one of the important mechanisms of cancer development that closely influences cancer development, survival, and metastasis. The development of treatments for cancer was temporarily revolutionized by immunotherapy but continues to be constrained by limited response rates and the resistance and high costs required for the development of new and innovative strategies. In particular, solid tumors, including HCC, a multi-vascular tumor type, are sensitive to hypoxia and generate many blood vessels for metastasis and development, making it difficult to treat HCC, not only with immunotherapy but also with drugs targeting blood vessels. Therefore, in order to develop a treatment strategy for hypoxic tumors, various mechanisms must be explored and analyzed to treat these impregnable solid tumors. To date, tumor growth mechanisms linked to hypoxia are known to be complex and coexist with various signal pathways, but recently, mechanisms related to the Hippo signal pathway are emerging. Interestingly, Hippo YAP/TAZ, which appear during early tumor and normal tumor growth, and YAP/TAZ, which appear during hypoxia, help tumor growth and proliferation in different directions. Peculiarly, YAP/TAZ, which have different phosphorylation directions in the hypoxic environment of tumors, are involved in cancer proliferation and metastasis in various carcinomas, including HCC. Analyzing the mechanisms that regulate the function and expression of YAP in addition to HIF in the complex hypoxic environment of tumors may lead to a variety of anti-cancer strategies and combining HIF and YAP/TAZ may develop the potential to change the landscape of cancer treatment.

A sialyltransferases-related gene signature serves as a potential predictor of prognosis and therapeutic response for bladder cancer

BACKGROUND

Aberrant glycosylation, catalyzed by the specific glycosyltransferase, is one of the dominant features of cancers. Among the glycosyltransferase subfamilies, sialyltransferases (SiaTs) are an essential part which has close linkages with tumor-associated events, such as tumor growth, metastasis and angiogenesis. Considering the relationship between SiaTs and cancer, the current study attempted to establish an effective prognostic model with SiaTs-related genes (SRGs) to predict patients' outcome and therapeutic responsiveness of bladder cancer.

METHODS

RNA-seq data, clinical information and genomic mutation data were downloaded (TCGA-BLCA and GSE13507 datasets). The comprehensive landscape of the 20 SiaTs was analyzed, and the differentially expressed SiaTs-related genes were screened with "DESeq2" R package. ConsensusClusterPlus was applied for clustering, following with survival analysis with Kaplan-Meier curve. The overall survival related SRGs were determined with univariate Cox proportional hazards regression analysis, and the least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate a SRGs-related prognostic model. The predictive value was estimated with Kaplan-Meier plot and the receiver operating characteristic (ROC) curve, which was further validated with the constructed nomogram and decision curve.

RESULTS

In bladder cancer tissues, 17 out of the 20 SiaTs were differentially expressed with CNV changes and somatic mutations. Two SiaTs_Clusters were determined based on the expression of the 20 SiaTs, and two gene_Clusters were identified based on the expression of differentially expressed genes between SiaTs_Clusters. The SRGs-related prognostic model was generated with 7 key genes (CD109, TEAD4, FN1, TM4SF1, CDCA7L, ATOH8 and GZMA), and the accuracy for outcome prediction was validated with ROC curve and a constructed nomogram. The SRGs-related prognostic signature could separate patients into high- and low-risk group, where the high-risk group showed poorer outcome, more abundant immune infiltration, and higher expression of immune checkpoint genes. In addition, the risk score derived from the SRGs-related prognostic model could be utilized as a predictor to evaluate the responsiveness of patients to the medical therapies.

CONCLUSIONS

The SRGs-related prognostic signature could potentially aid in the prediction of the survival outcome and therapy response for patients with bladder cancer, contributing to the development of personalized treatment and appropriate medical decisions.

Searching for Novel Biomarkers in Thymic Epithelial Tumors: Immunohistochemical Evaluation of Hippo Pathway Components in a Cohort of Thymic Epithelial Tumors

Given the pivotal role of the Hippo pathway in different facets of tumorigenesis, which has been vigorously established in multiple heterogenous malignancies, we attempted to evaluate its potential utility as a prognostic-predictive biomarker in thymic epithelial tumors (TETs). For this purpose, we performed a comprehensive immunohistochemical analysis of four Hippo cascade components (YAP, TAZ, TEAD4 and LATS1) in a sizeable cohort of TETs and attempted to identify possible correlations of their H-score with various clinicopathological parameters. TAZ and TEAD4 displayed both cytoplasmic and nuclear immunoreactivity in almost equal frequency, with their cytoplasmic H-score being strongly associated with more aggressive high-grade tumors (type B3, thymic carcinoma) and more advanced pathological stages. On the other hand, a primarily nuclear staining pattern was encountered in both YAP and LATS1, with the YAP nuclear H-score being higher in more indolent (type A) and earlier stage tumors. Interestingly, none of the four examined factors displayed any statistically significant correlation with patient overall (OS) or disease-free survival (DFS). In summary, our results provide some initial insight into the expression profile of these core Hippo pathway components in thymic neoplasms and point towards some clear associations with tumor characteristics, which are of paramount translational-clinical research with profound implications in therapeutic targeting of this pathway in the context of precision medicine.

A comparative study of COVID-19 transcriptional signatures between clinical samples and preclinical cell models in the search for disease master regulators and drug repositioning candidates

Coronavirus disease 2019 (COVID-19) is an acute viral disease with millions of cases worldwide. Although the number of daily new cases and deaths has been dropping, there is still a need for therapeutic alternatives to deal with severe cases. A promising strategy to prospect new therapeutic candidates is to investigate the regulatory mechanisms involved in COVID-19 progression using integrated transcriptomics approaches. In this work, we aimed to identify COVID-19 Master Regulators (MRs) using a series of publicly available gene expression datasets of lung tissue from patients which developed the severe form of the disease. We were able to identify a set of six potential COVID-19 MRs related to its severe form, namely TAL1, TEAD4, EPAS1, ATOH8, ERG, and ARNTL2. In addition, using the Connectivity Map drug repositioning approach, we identified 52 different drugs which could be used to revert the disease signature, thus being candidates for the design of novel clinical treatments. Furthermore, we compared the identified signature and drugs with the ones obtained from the analysis of nasopharyngeal swab samples from infected patients and preclinical cell models. This comparison showed significant similarities between them, although also revealing some limitations on the overlap between clinical and preclinical data in COVID-19, highlighting the need for careful selection of the best model for each disease stage.

A Four-Gene Prognostic Signature Based on the TEAD4 Differential Expression Predicts Overall Survival and Immune Microenvironment Estimation in Lung Adenocarcinoma

Background: TEA domain transcription factor 4 (TEAD4) is a member of the transcriptional enhancer factor (TEF) family of transcription factors, which is studied to be linked to the tumorigenesis and progression of various forms of cancers, including lung adenocarcinoma (LUAD). However, the specific function of this gene in the progression of LUAD remains to be explored.

Method: A total of 19 genes related to the Hippo pathway were analyzed to identify the significant genes involved in LUAD progression. The TCGA-LUAD data (n = 585) from public databases were mined, and the differentially expressed genes (DEGs) in patients with the differential level of TEAD4 were identified. The univariate Cox regression, zero LASSO regression coefficients, and multivariate Cox regression were performed to identify the independent prognostic signatures. The immune microenvironment estimation in the two subgroups, including immune cell infiltration, HLA family genes, and immune checkpoint genes, was assessed. The Gene Set Enrichment Analysis (GSEA) and GO were conducted to analyze the functional enrichment of DEGs between the two risk groups. The potential drugs for the high-risk subtypes were forecasted via the mode of action (moa) module of the connectivity map (CMap) database.

Results:TEAD4 was found to be significantly correlated with poor prognosis in LUAD-patients. A total of 102 DEGs in TEAD4-high vs. TEAD4-low groups were identified. Among these DEGs, four genes (CPS1, ANLN, RHOV, and KRT6A) were identified as the independent prognostic signature to conduct the Cox risk model. The immune microenvironment estimation indicated a strong relationship between the high TEAD4 expression and immunotherapeutic resistance. The GSEA and GO showed that pathways, including cell cycle regulation, were enriched in the high-risk group, while immune response-related and metabolism biological processes were enriched in the low-risk group. Several small molecular perturbagens targeting CFTR or PLA2G1B, by the mode of action (moa) modules of the glucocorticoid receptor agonist, cyclooxygenase inhibitor, and NFkB pathway inhibitor, were predicted to be suited for the high-risk subtypes based on the high TEAD4 expression.

Conclusion: The current study revealed TEAD4 is an immune regulation–related predictor of prognosis and a novel therapeutic target for LUAD.

TEAD4 as an Oncogene and a Mitochondrial Modulator

TEAD4 (TEA Domain Transcription Factor 4) is well recognized as the DNA-anchor protein of YAP transcription complex, which is modulated by Hippo, a highly conserved pathway in Metazoa that controls organ size through regulating cell proliferation and apoptosis. To acquire full transcriptional activity, TEAD4 requires co-activator, YAP (Yes-associated protein) or its homolog TAZ (transcriptional coactivator with PDZ-binding motif) the signaling hub that relays the extracellular stimuli to the transcription of target genes. Growing evidence suggests that TEAD4 also exerts its function in a YAP-independent manner through other signal pathways. Although TEAD4 plays an essential role in determining that differentiation fate of the blastocyst, it also promotes tumorigenesis by enhancing metastasis, cancer stemness, and drug resistance. Upregulation of TEAD4 has been reported in several cancers, including colon cancer, gastric cancer, breast cancer, and prostate cancer and serves as a valuable prognostic marker. Recent studies show that TEAD4, but not other members of the TEAD family, engages in regulating mitochondrial dynamics and cell metabolism by modulating the expression of mitochondrial- and nuclear-encoded electron transport chain genes. TEAD4’s functions including oncogenic activities are tightly controlled by its subcellular localization. As a predominantly nuclear protein, its cytoplasmic translocation is triggered by several signals, such as osmotic stress, cell confluency, and arginine availability. Intriguingly, TEAD4 is also localized in mitochondria, although the translocation mechanism remains unclear. In this report, we describe the current understanding of TEAD4 as an oncogene, epigenetic regulator and mitochondrial modulator. The contributing mechanisms will be discussed.