GeneGazer: A Toolkit Integrating Two Pipelines for Personalized Profiling and Biosignature Identification

Area of Science:

• Bioinformatics
• Genomics
• Computational Biology

Background:

• Next-generation sequencing (NGS) generates vast amounts of data (gene mutations, expression, epigenetics, etc.).
• Analyzing NGS data requires specialized bioinformatics tools, posing challenges for researchers with limited training.
• Integrating results from multiple bioinformatics tools is often tedious and complex.

Purpose of the Study:

• To develop a user-friendly toolkit, GeneGazer, for simplifying NGS data analysis and integration.
• To provide a convenient solution for researchers to analyze and integrate data from various bioinformatics tools.
• To facilitate personalized molecular profiling and disease-associated biosignature discovery from NGS data.

Main Methods:

• GeneGazer comprises two modules: Gaze_Profiler for personalized molecular profiling of paired samples and Gaze_BioSigner for discovering disease-associated biosignatures from cohort studies.
• Gaze_Profiler analyzes RNA-sequencing data to profile somatic mutations and digital gene expression.
• Gaze_BioSigner analyzes gene-expression data to identify potential therapeutic targets.

Main Results:

• Analysis of colon cancer data using Gaze_Profiler identified activated RAS/RAF/MEK/ERK and WNT signaling pathways, suggesting limited cetuximab efficacy.
• Gaze_BioSigner analysis of The Cancer Genome Atlas data revealed associations between cAMP/PKA signaling, OCT-3/4, SRF activation, and colon cancer progression.
• These findings highlight potential therapeutic targets for colon cancer.

Conclusions:

• GeneGazer is a reliable and robust toolkit for analyzing high-throughput data.
• The toolkit simplifies complex bioinformatics analyses, making them accessible to a wider range of researchers.
• GeneGazer shows potential for clinical applications and advancing biomedical research.