THRESHOLD: a comprehensive transcriptomic analysis tool for evaluating gene saturation and impact in disease...

Area of Science:

• Molecular Biology
• Bioinformatics
• Genomics

Background:

• Gene expression studies are crucial for understanding biological processes and diseases.
• Analyzing large gene expression datasets requires precise and advanced tools.
• Current methods often focus on absolute or binary expression levels, missing co-regulation patterns.

Purpose of the Study:

• To introduce THRESHOLD, a novel computational tool for gene expression analysis.
• To quantify gene expression consistency across patients, introducing the concept of gene saturation.
• To reveal co-regulation patterns for improved disease mechanism understanding and patient stratification.

Main Methods:

• Development of the THRESHOLD tool for gene expression analysis.
• Quantification of gene expression consistency and saturation across patient cohorts.
• Application of THRESHOLD to TCGA cancer datasets (bladder, prostate, colon, breast).
• Utilized protein-protein interaction networks and functional analyses.

Main Results:

• Demonstrated increasing gene saturation with cancer progression in bladder urothelial carcinoma (P < .00001).
• Identified heightened gene saturation in earlier onset prostate adenocarcinoma (P < .0001).
• Discovered SLC45A2-AMACR fusion transcript linked to prostate cancer progression, recurrence, and metastasis.
• Uncovered novel biomarkers and potential drug targets in colon and breast cancers.

Conclusions:

• THRESHOLD provides a novel approach to gene expression dynamics and patient stratification.
• Gene saturation analysis offers critical insights into disease mechanisms and progression.
• The tool facilitates the discovery of biomarkers and therapeutic targets.