Glioblastoma

Glioblastoma, the most malignant brain cancer with remarkable cell migration and adaptation capabilities, contains self-renewing, stem-like cells that sustain tumor growth and therapeutic resistance. Exploring accurate molecular targets for the occurrence and progression of glioblastoma is of great value. Identifying genes promoting stem-like cell differentiation might unveil targets for novel treatments.

Bioinformatics analysis technology is widely used to find genetic changes in the process of tumorigenesis and development. It is a reliable method for finding diagnostic and therapeutic targets.  

Database

• Gene Expression Omnibus (GEO)

The GEO (http://www.ncbi.nlm.nih.gov/geo) is a public platform for the storage of gene data. Differentially expressed genes (DEGs) in datasets from the GEO can be screened by bioinformatics analysis.

• STRING

STRING (https://string-db.org) is a biological database and web resource of known and predicted protein–protein interactions.

• miRNet

miRNet (http://www.mirnet.ca) includes data on the interaction of miRNAs with target genes. Differentially expressed miRNAs (DEMs) can be screened by bioinformatics analysis.

Computational Tools and Methods

• SWIM (SWItchMiner) and Potential Therapeutic Targets Discovery

SWIM is a software able to unveil genes (named switch genes) involved in drastic changes of cell phenotype, implying crucial nodes in complex biological networks.

• GEO2R and DEGs Identification

GEO2R (https://www.ncbi.nlm.nih.gov/geo/geo2r/) is an effective online tool used to identify DEGs in datasets.

• Pathway Enrichment Analysis

The Database for Annotation, Visualization and Integrated Discovery (DAVID) is an online suite of analysis tools with an integrated discovery and annotation function. Implement DAVID to perform the GO and KEGG analysis of DEGs.

• PPI Network Analysis

Search Tool for the Retrieval of Interacting Genes (STRING) (http://string.embl.de/) is applied to construct a PPI network of the identified DEGs. Cytoscape visualization software is used to present the network.

• Coexpedia and Co-expression Analysis

Coexpedia (www.coexpedia.org) is a powerful tool applied for gene co-expression analysis and identifying hub genes.

• Metascape and GO Analysis

This is a free gene annotation and analysis resource that helps biologists make sense of one or multiple gene lists with automated meta-analysis tools to understand either common or unique pathways and protein networks within a group of orthogonal target-discovery studies.

• GEPIA and Survival Analysis

Then GEPIA is a web server for cancer and normal gene expression profiling and interactive analyses.

CD ComputaBio utilizes advanced biostatistical approaches and computational analysis methods to interpret different datasets. We can also aid in the discovery of new cancer subgroups and biomarkers. In addition, we have multiple resources including academic research and preclinical works in the identification of a suitable disease target and its corresponding hit. Contact us for more service details.

Reference

1. Xue L, Liu H, Chen Y, Wei L, Hong J. Computational analysis and verification of molecular genetic targets for glioblastoma. Biosci Rep. 2020;40(6):BSR20201401.