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Search for Master Regulators in Walking Cancer Pathways.

Alexander E Kel^1,2,3

¹Institute of Chemical Biology and Fundamental Medicine, SBRAN, Novosibirsk, Russia. alexander.kel@genexplain.com.

Methods in Molecular Biology (Clifton, N.J.)

|August 30, 2017

Summary

This study introduces an upstream analysis strategy to find master regulators in gene networks for identifying cancer drug targets. This method aids in understanding cancer development and drug resistance by analyzing multi-omics data.

Keywords:

ChIP-seq Microarray data Pathway analysis Pathway rewiring Promoter analysis RNA-seq Upstream analysis

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Area of Science:

Bioinformatics
Systems Biology
Genomics

Background:

Identifying master regulators in gene regulatory networks is crucial for understanding pathological processes.
Current methods often lack a comprehensive strategy for causal analysis of multi-omics data.

Purpose of the Study:

To present an "upstream analysis" strategy for causal analysis of multi-omics data.
To identify master regulators in gene regulatory networks as potential drug targets for pathological conditions, specifically cancer.

Main Methods:

Utilizing a state-of-the-art promoter analysis with the TRANSFAC database for transcription factor (TF)-binding sites.
Analyzing upstream signal transduction pathways controlling TF activity.
Integrating transcriptomics and epigenomics data for multi-omics analysis.

Main Results:

The approach successfully identified potential key molecules (master regulators) controlling pathological states.
Demonstrated application on multi-omics cancer data revealed insights into cancer development and drug resistance mechanisms.
Highlighted the potential for rapid and accurate identification of cancer drug targets.

Conclusions:

The upstream analysis strategy offers a powerful approach for causal analysis of multi-omics data.
This method facilitates the discovery of novel cancer drug targets by identifying master regulators.
The approach enhances understanding of molecular mechanisms underlying cancer and drug resistance.