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

Liu, Zhendong; Zhang, Ruotian; Sun, Zhenying; Yao, Jiawei; Yao, Penglei; Chen, Xin; Wang, Xinzhuang; Gao, Ming; Wan, Jinzhao; Du, Yiqun

doi:10.7717/peerj.8670

Cited by 10 publications

(6 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, computer-aided drug design (CADD) has been used to find a varied range of prospective drug candidates utilizing a virtual screening method that combines docking, absorption, distribution, metabolism, and excretion (ADME), toxicity, and molecular dynamics (MD) simulation [ 28 ]. Trichostatin [ 29 ] A (TSA) has recently been found as a potential treatment candidate against human cancers by researchers.…”

Section: Introductionmentioning

confidence: 99%

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

Zhang

Chen

Lin

et al. 2022

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

Zhang

Chen

Lin

et al. 2022

Applied Bionics and Biomechanics

View full text Add to dashboard Cite

show abstract

“…Low expression of BRCA1 signifies worse prognosis in patients with triple negative breast cancer, while its high expression effectively inhibits invasion and metastasis [ 22 ]. Overexpression of ARG indicates poor prognosis in HCC, and is associated with the migration and invasion of cancer cells [ 23 ]. The above studies demonstrate that the six independent risk factors are closely related to the occurrence of MVI and have an impact on tumorigenesis and disease progression in the patients.…”

Section: Discussionmentioning

confidence: 99%

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

Cao

Wang

et al. 2023

BMC Gastroenterol

View full text Add to dashboard Cite

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.

show abstract

“…The Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases are the two most authoritative databases for gene function research and are the two most commonly used enrichment analysis methods ( Liu et al, 2020 ). In oncology research, the above two analysis methods can predict the biological function of target genes in the course of disease according to the overall expression level of transcriptomics.…”

Section: Methodsmentioning

confidence: 99%

“…Furthermore, the connectivity map (CMap) database can closely link the expression profile of abnormal genes of diseases with potential corrective drugs ( Lamb et al, 2006 ). For example, several drugs inhibiting the proliferation of tumor cells were found in the connectivity map database by using differentially expressed genes in medulloblastoma ( Liu et al, 2020 ). Therefore, targeted drugs to correct the disorder of gene expression can be quickly found through the CMap database, and this exploration can be used as an engine to guide more researchers to focus on tumor drug research.…”

Section: Introductionmentioning

confidence: 99%

Increased ATP2A1 Predicts Poor Prognosis in Patients With Colorectal Carcinoma

Zhang

Shang²,

Liu³

et al. 2022

Front. Genet.

View full text Add to dashboard Cite

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.

show abstract

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

Cited by 10 publications

References 36 publications

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

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

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

Increased ATP2A1 Predicts Poor Prognosis in Patients With Colorectal Carcinoma

Contact Info

Product

Resources

About