Identification of hub genes and small-molecule compounds in medulloblastoma by integrated bioinformatic analyses

FAIM2 is correlated with metastasis of medulloblastoma through bioinformatics analysis

Medulloblastoma (MB) is one of the most frequent malignant brain tumors in children. The metastasis of MB outside the nervous system is associated with a poor prognosis. Our study aimed to explore the genes correlated with metastasis in MB. Using the data downloaded from the gene expression omnibus database, the differentially expressed genes were identified between the metastatic and nonmetastatic samples in MB, which were undergone functional enrichment. Prognosis related genes were identified using univariate Cox regression analysis. The gene set enrichment analysis was conducted to find MB metastasis related pathways. A total of 196 differentially expressed genes were identified between metastatic and nonmetastatic samples in MB patients, and these genes were significantly enriched in 483 gene ontology terms and 29 Kyoto encyclopedia of genes and genomes pathways. In addition, univariate Cox regression analysis screened the top 10 genes (CEMIP, GLCE, ART3, GABRA5, COLEC12, LIN28B, ZNF521, IL17RB, Fas apoptotic inhibitory molecule 2 (FAIM2), RCBTB2) that were significantly associated with survival of MB, among which FAIM2 was prominently expressed in cerebral cortex, cerebellum and hippocampus. The expression of FAIM2 was decreased in metastatic MB samples, and FAIM2 harbored missense mutations, amplifications and deep deletions in metastatic samples of MB. Moreover, a total of 25 pathways were significantly activated and 41 pathways were significantly inhibited in FAIM2 high expression group compared to FAIM2 low expression group in MB patients. FAIM2 was tightly correlated with metastasis in MB patients, and the low expression of FAIM2 was associated with poor prognosis.

A novel predictive model of microvascular invasion in hepatocellular carcinoma based on differential protein expression

BACKGROUND

This study aims to construct and verify a nomogram model for microvascular invasion (MVI) based on hepatocellular carcinoma (HCC) tumor characteristics and differential protein expressions, and explore the clinical application value of the prediction model.

METHODS

The clinicopathological data of 200 HCC patients were collected and randomly divided into training set and validation set according to the ratio of 7:3. The correlation between MVI occurrence and primary disease, age, gender, tumor size, tumor stage, and immunohistochemical characteristics of 13 proteins, including GPC3, CK19 and vimentin, were statistically analyzed. Univariate and multivariate analyzes identified risk factors and independent risk factors, respectively. A nomogram model that can be used to predict the presence of MVI was subsequently constructed. Then, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA) were conducted to assess the performance of the model.

RESULTS

Multivariate logistic regression analysis indicated that tumor size, GPC3, P53, RRM1, BRCA1, and ARG were independent risk factors for MVI. A nomogram was constructed based on the above six predictors. ROC curve, calibration, and DCA analysis demonstrated the good performance and the clinical application potential of the nomogram model.

CONCLUSIONS

The predictive model constructed based on the clinical characteristics of HCC tumors and differential protein expression patterns could be helpful to improve the accuracy of MVI diagnosis in HCC patients.

High-Throughput Screening and Molecular Dynamics Simulation of Natural Products for the Identification of Anticancer Agents against MCM7 Protein

Minichromosome maintenance complex component 7 (MCM7) belongs to the minichromosome maintenance family that is necessary for the initiation of eukaryotic DNA replication. Overexpression of the MCM7 protein is linked to cellular proliferation and is accountable for critical malignancy in many cancers. Mechanistically, the suppression of MCM7 greatly lowers the cellular proliferation associated with cancer. Advances in immunotherapy have revolutionized treatments for many types of cancer. To date, no effective small molecular candidate has been found that can stop the advancement of cancer produced by the MCM7 protein. Here, we present the findings of methods that used a combination of structure-assisted drug design, high-throughput virtual screening, and simulations studies to swiftly generate lead compounds against MCM7 protein. In the current study, we designed efficient compounds that may combat all emerging cancer targeting the common MCM7 protein. For this objective, a molecular docking and molecular dynamics (MD) simulation-based virtual screening of 29,000 NPASS library was carried out. As a consequence of using specific pharmacological, physiological, and ADMET criteria, four new prevailing compounds, NPA000018, NPA000111, NPA00305, and NPA014826, were successfully selected. The MD simulations were also used for a time period of 50 ns to evaluate for stability and dynamics behavior of the compounds. Eventually, compounds NPA000111 and NPA014826 were found to be highly potent against MCM7 protein. According to our results, the selected compounds may be effective in treating certain cancer subtypes, for which additional follow-up experimental validation is recommended.

CLSPN is a potential biomarker associated with poor prognosis in low-grade gliomas based on a multi-database analysis

BACKGROUND

The oncogene CLSPN, also known as claspin, has regulatory effects in a variety of tumours; however, it is not clear whether CLSPN is a therapeutic target in low-grade gliomas (LGG). In this study, the prognostic value of CLSPN in LGG and its role as an immunotherapeutic target were evaluated.

METHODS

Transcriptome and methylation data for thousands of patients with glioma were collected from various databases, including The Cancer Genome Atlas, Chinese Glioma Genome Atlas, and Gene Expression Omnibus. Subsequently, a series of bioinformatics methods were used to evaluate the relationships between CLSPN and prognosis, clinical features, methylation status, immune cells, and molecular signaling pathways in LGG.

RESULTS

CLSPN expression levels were positively correlated with major malignant characteristics of LGG, and low expression of CLSPN was associated with a better prognosis. The methylation sites cg04263115 and cg06100291 negatively regulated the expression of CLSPN, and increased methylation levels at these sites were related to a longer survival time in patients with LGG. CLSPN was positively correlated with tumour-infiltrating immune cells and showed high copy number variation in these cells. There was a positive regulatory relationship between CLSPN expression and programmed death-1 (PD-1) and programmed cell death ligand 1 (PD-L1). A gene set enrichment analysis revealed that CLSPN activates a variety of cancer signaling pathways.

CONCLUSION

CLSPN was identified as an independent risk factor for LGG with excellent prognostic value.

Increased ATP2A1 Predicts Poor Prognosis in Patients With Colorectal Carcinoma

Colorectal cancer is one of the most common malignant tumors in the digestive system. Traditional diagnosis and treatment methods have not significantly improved the overall survival of patients. In this study, we explored the value of ATP2A1 as a biomarker in predicting the prognosis of colorectal cancer patients. We used the TCGA database to reveal the relationship between ATP2A1 mRNA level and prognosis, methylation, and immune invasion in colorectal cancer. The results showed that the expression of ATP2A1 was increased in colorectal cancer. The overall survival of patients with high expression of ATP2A1 was significantly lower than patients with low expression of ATP2A1. Cox regression analysis showed that high expression of ATP2A1 was an independent risk factor for poor prognosis in colorectal cancer patients. In addition, we used three datasets to perform a meta-analysis, which further confirmed the reliability of the results. Furthermore, we revealed that ATP2A1 could significantly inhibit the proliferation of colorectal cancer cells by inhibiting the autophagy process and was associated with several immune cells, especially CD8 + T cells. Finally, four small molecule drugs with potential inhibition of ATP2A1 expression were found by CMap analysis. This study demonstrates for the first time that ATP2A1 is a potential pathogenic factor, which may play a significant role in colorectal cancer.

Bioinformatics approaches identified dasatinib and bortezomib inhibit the activity of MCM7 protein as a potential treatment against human cancer

Minichromosome Maintenance Complex Component 7 (MCM7) is a key component of the DNA replication licensing factor and hexamer MCM (MCM2–7) complex that regulates the DNA replication process. The MCM7 protein is associated with tumor cell proliferation that plays an important role in different human cancer progression. As the protein is highly expressed during the cancer development process, therefore, inhibition of the protein can be utilized as a treatment option for different human cancer. However, the study aimed to identify potential small molecular drug candidates against the MCM7 protein that can utilize treatment options for human cancer. Initially, the compounds identified from protein-drugs network analysis have been retrieved from NetworkAnalyst v3.0 server and screened through molecular docking, MM-GBSA, DFT, pharmacokinetics, toxicity, and molecular dynamics (MD) simulation approach. Two compounds namely Dasatinib (CID_3062316) and Bortezomib (CID_387447) have been identified throughout the screening process, which have the highest negative binding affinity (Kcal/mol) and binding free energy (Kcal/mol). The pharmacokinetics and toxicity analysis identified drug-like properties and no toxicity properties of the compounds, where 500 ns MD simulation confirmed structural stability of the two compounds to the targeted proteins. Therefore, we can conclude that the compounds dasatinib and bortezomib can inhibit the activity of the MCM7 and can be developed as a treatment option against human cancer.

NRXN2 Possesses a Tumor Suppressor Potential via Inhibiting the Growth of Thyroid Cancer Cells

Thyroid cancer (THCA) is a common endocrine malignant tumor, and its global incidence of THCA has increased significantly. Neurexin 2 (NRXN2) is involved in the progression of some diseases. Nevertheless, it is still elusive towards the clinical implication and function of NRXN2 in THCA. As The Cancer Genome Atlas (TCGA) data demonstrated, we conducted a study to explore the links between NRXN2 expression and clinical features. Additionally, our data exhibited that, compared to normal thyroid tissues, NRXN2 showed low expression in THCA tissues. 20 important genes associated with NRXN2 were screened and identified. KEGG analysis data displayed that NRXN2 exhibited a link to the neuronal system, insulin secretion modulation, energy metabolism integration, muscle contraction, cardiac conduction, and neural adhesion molecule 1 (NCAM1) interactions. Our results in depth affirmed that NRXN2 was decreased in the tissues and cell lines of THCA patients. Functionally, we proved that overexpressing NRXN2 resulted in an inhibition of THCA cell proliferation, migration, and invasion in vitro. Collectively, our study demonstrated that, for the first time, NRXN2 behaved as an inhibitor of neoplasm and a promising biomarker in THCA.