Identification of novel biomarkers and candidate small-molecule drugs in cutaneous melanoma by comprehensive gene microarrays analysis

Effect of 23‑hydroxybetulinic acid on lung adenocarcinoma and its mechanism of action

The present study aimed to investigate the effect and mechanism of Pulsatilla compounds on lung adenocarcinoma. The representative drug chosen was the compound 23-HBA. GeneCards, Swiss target prediction, DisGeNET and TCMSP were used to screen out related genes, and MTT and flow cytometry assays were used to verify the inhibitory effect of Pulsatilla compounds on the proliferation of lung adenocarcinoma cells. Subsequently, the optimal target, peroxisome proliferator-activated receptor (PPAR)-γ, was selected using bioinformatics analysis, and its properties of low expression in lung adenocarcinoma cells and its role as a tumor suppressor gene were verified by western blot assay. The pathways related to immunity and inflammation, vascular function, cell proliferation, differentiation, development and apoptosis with the highest degree of enrichment and the mechanisms were explored through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Finally, the clinical prognosis in terms of the survival rate of patients in whom the drug is acting on the target was analyzed using the GEPIA database. The results indicated that Pulsatilla compounds can inhibit the proliferation of lung adenocarcinoma cells by blocking the cell cycle at the G1 phase. Subsequently, the related PPAR-γ gene was verified as a tumor suppressor gene. Further analysis demonstrated that this finding was related to the PPAR signaling pathway and mitochondrial reactive oxygen species (ROS) production. Finally, the clinical prognosis was found to be improved, as the survival rate of patients was increased. In conclusion, Pulsatilla compounds were indicated to inhibit the viability and proliferation of lung adenocarcinoma H1299 cells, and the mechanism of action was related to PPAR-γ, the PPAR signaling pathway and mitochondrial ROS. The present study provides novel insight to further explore the treatment of lung adenocarcinoma.

The Clinical Impact of Death Domain-Associated Protein and Holliday Junction Recognition Protein Expression in Cancer: Unmasking the Driving Forces of Neoplasia

Death domain-associated protein (DAXX) and Holliday junction recognition protein (HJURP) act as chaperones of H3 histone variants H3.3 and centromere protein A (CENPA), respectively, and are implicated in many physiological processes, including aging and epigenetic regulation, by controlling various genes' transcription and subsequently protein expression. Research has highlighted both these biomolecules as participants in key procedures of tumorigenesis, including cell proliferation, chromosome instability, and oncogene expression. As cancer continues to exert a heavy impact on patients' well-being and bears substantial socioeconomic ramifications, the discovery of novel biomarkers for timely disease detection, estimation of prognosis, and therapy monitoring remains of utmost importance. In the present review, we present data reported from studies investigating DAXX and HJURP expression, either on mRNA or protein level, in human tissue samples from various types of neoplasia. Of note, the expression of DAXX and HJURP has been associated with a multitude of clinicopathological parameters, including disease stage, tumor grade, patients' overall and disease-free survival, as well as lymphovascular invasion. The data reveal the tumor-promoting properties of DAXX and HJURP in a number of organs as well as their potential use as diagnostic biomarkers and underline the important association between aberrations in their expression and patients' prognosis, rendering them as possible targets of future, personalized and precise therapeutic interventions.

TRIP13/FLNA Complex Promotes Tumor Progression and Is Associated with Unfavorable Outcomes in Melanoma

Cutaneous melanoma is a high-grade malignant tumor originating from skin melanocytes with high risk of recurrence and metastasis. Further study on the mechanism of melanoma development is urgently needed. Here, we performed a bioinformatic analysis to identify critical genes in melanoma using public datasets in the Gene Expression Omnibus database. Among these differentially expressed genes, thyroid hormone receptor interactor 13 (TRIP13) has been reported to exert an important role in the development of various tumors, while its role in melanoma remains unclear. We selected TRIP13 as a candidate gene for further study. TRIP13 expression in clinical specimens was evaluated by immunohistochemistry, and its association with patient prognosis was analyzed by the Kaplan-Meier method and log-rank test. MV3 and A2058 melanoma cells were transfected with lentiviral vector to overexpress or knockdown TRIP13 expression level, and then, its biological function was studied using a series of in vitro and in vivo assays. RNA sequencing, co-immunoprecipitation, and mass spectrometry were used to identify the underlying mechanism of TRIP13. The results of this study exhibited that TRIP13 expression was upregulated in melanoma tissue compared with normal tissues, and high levels of TRIP13 were closely correlated with poor prognoses of melanoma patients. Elevated TRIP13 promoted the invasion and migration of melanoma cells in vitro and enhanced lung metastasis in vivo, without an influence on tumor growth. Importantly, elevated TRIP13 promoted the epithelial-mesenchymal transition (EMT) of melanoma cells, indicating a higher metastatic potential of these cells. Mechanically, TRIP13 physically interacted with filamin A (FLNA) and then activated the PI3K/AKT pathway to transcriptional activation of EMT-related genes. The present study revealed that TRIP13 is a novel prognostic biomarker and potential therapeutic target for melanoma treatment.

DTL Is a Prognostic Biomarker and Promotes Bladder Cancer Progression through Regulating the AKT/mTOR axis

Background

Denticleless E3 ubiquitin protein ligase homolog (DTL) has been reported to be an important regulator for tumorigenesis and progression. Nonetheless, the biological functions and molecular mechanisms of DTL in BCa remain elusive.

Methods

We implemented integrative bioinformatics analysis to explore the diagnostic and prognostic values of DTL based on The Cancer Genome Atlas (TCGA), ArrayExpress, and Gene Expression Omnibus (GEO) databases. Then, we utilized qRT-PCR and immunohistochemistry to verify the clinical significance of DTL expression according to clinical specimens and tissue microarray (TMA). Moreover, the biological functions and underlying mechanisms of DTL in BCa were investigated through in vitro and in vivo experiments.

Results

Integrative bioinformatics analysis revealed that DTL was a key gene associated with BCa progression, and increased DTL expression was correlated with malignant biological behavior and poor prognosis. Experiments on clinical specimens and tissue microarray (TMA) further confirmed our findings. Bioinformatics analysis demonstrated that DTL could be associated with cell cycle- and DNA replication-associated pathways in BCa. The suppression of DTL inhibited BCa cell proliferation, migration, and invasion in vivo and in vitro. Mechanistically, DTL may promote BCa progression through the AKT/mTOR pathway.

Conclusions

Increased DTL expression was correlated with malignant biological behavior and poor prognosis of BCa patients, and it may promote BCa progression through the AKT/mTOR pathway. Our research provided a potential predictor and therapeutic target for BCa.

Development of an Interferon Gamma Response-Related Signature for Prediction of Survival in Clear Cell Renal Cell Carcinoma

Background

Interferon plays a crucial role in the pathogenesis and progression of tumors. Clear cell renal cell carcinoma (ccRCC) represents a prevalent malignant urinary system tumor. An effective predictive model is required to evaluate the prognosis of patients to optimize treatment.

Materials and Methods

RNA-sequencing data and clinicopathological data from TCGA were involved in this retrospective study. The IFN-γ response genes with significantly different gene expression were screened out. Univariate Cox regression, LASSO regression and multivariate Cox regression were used to establish a new prognostic scoring model for the training group. Survival curves and ROC curves were drawn, and nomogram was constructed. At the same time, we conducted subgroup analysis and experimental verification using our own samples. Finally, we evaluated the relatedness between the prognostic signature and immune infiltration landscapes. In addition, the sensitivity of different risk groups to six drugs and immune checkpoint inhibitors was calculated.

Results

The IFN-γ response-related signature included 7 genes: C1S, IFI44, ST3GAL5, NUP93, TDRD7, DDX60, and ST8SIA4. The survival curves of the training and testing groups showed the model's effectiveness (P = 4.372e-11 and P = 1.08e-08, respectively), the ROC curves showed that the signature was stable, and subgroup analyses showed the wide applicability of the model (P<0.001). Multivariate Cox regression analysis showed that the risk model was an independent prognostic factor of ccRCC. A high-risk score may represent an immunosuppressive microenvironment, while the high-risk group exhibited poor sensitivity to drugs.

Conclusion

Our findings strongly indicate that the IFN-γ response-related signature can be used as an effective prognostic indicator of ccRCC.

A Robust Prognostic Gene Signature Based on eRNAs-Driven Genes in Prostate Cancer

Prostate cancer (PCa) is the second most common malignancy in men, but its exact pathogenetic mechanisms remain unclear. This study explores the effect of enhancer RNAs (eRNAs) in PCa. Firstly, we screened eRNAs and eRNA -driven genes from The Cancer Genome Atlas (TCGA) database, which are related to the disease-free survival (DFS) of PCa patients;. screening methods included bootstrapping, Kaplan–Meier (KM) survival analysis, and Pearson correlation analysis. Then, a risk score model was established using multivariate Cox analysis, and the results were validated in three independent cohorts. Finally, we explored the function of eRNA-driven genes through enrichment analysis and analyzed drug sensitivity on datasets from the Genomics of Drug Sensitivity in Cancer database. We constructed and validated a robust prognostic gene signature involving three eRNA-driven genes namely MAPK15, ZNF467, and MC1R. Moreover, we evaluated the function of eRNA-driven genes associated with tumor microenvironment (TME) and tumor mutational burden (TMB), and identified remarkable differences in drug sensitivity between high- and low-risk groups. This study identified a prognostic gene signature, which provides new insights into the role of eRNAs and eRNA-driven genes while assisting clinicians to determine the prognosis and appropriate treatment options for patients with PCa.