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Bioinformatics Meets Biomedicine: OncoFinder, a Quantitative Approach for Interrogating Molecular Pathways Using Gene
Anton A Buzdin1,2,3,4, Vladimir Prassolov5, Alex A Zhavoronkov6,7
1Pathway Pharmaceuticals, Wan Chai, Hong Kong SAR. Buzdin@ponkc.com.
Methods in Molecular Biology (Clifton, N.J.)
|August 30, 2017
Summary
OncoFinder (OF) is a biomathematical tool for analyzing molecular pathway activation. It identifies gene roles, normalizes data, and reveals pathway signatures as superior cancer progression markers compared to individual genes.
Area of Science:
- Biomathematics
- Molecular Biology
- Bioinformatics
Background:
- Analyzing intracellular molecular pathway activation is crucial for understanding physiological and pathological conditions.
- Existing methods struggle to quantitatively and qualitatively assess pathway dynamics and gene product roles.
- There is a need for robust tools to integrate diverse molecular data (NGS, microarray, proteomics) and account for background noise.
Purpose of the Study:
- To introduce OncoFinder (OF), a novel biomathematical approach for quantitative and qualitative analysis of intracellular molecular pathway activation.
- To develop a method capable of distinguishing the activator/repressor roles of gene products within molecular pathways.
- To create a tool that can correlate pathway activation with cancer progression and therapeutic outcomes, and to extend this to analyze microRNA (miR) impacts.
Main Methods:
- Developed the OncoFinder (OF) algorithm to analyze molecular pathway activation and determine gene product roles.
- Applied OF to neutralize background noise in gene expression data from various high-throughput techniques (NGS, microarray, proteomics).
- Created MiRImpact, a variant of OF, to link miR expression data with its regulatory impact on pathways and cellular interactome.
Main Results:
- OF effectively neutralizes background variations in experimental gene expression data.
- Pathway activation signatures derived from OF proved to be more effective markers of cancer progression than individual gene products.
- MiRImpact successfully linked miR profiles to pathway regulation, revealing an orthogonal relationship to mRNA levels and highlighting the need for multi-level regulatory analysis.
Conclusions:
- OncoFinder provides a powerful framework for dissecting molecular pathway activation across various conditions.
- Pathway-level analysis offers superior insights into cancer progression and treatment response compared to gene-level analysis.
- Integrating microRNA data with pathway analysis using MiRImpact is essential for a comprehensive understanding of cellular regulation.
