MIO: microRNA target analysis system for immuno-oncology

Area of Science:

• Computational biology
• Bioinformatics
• Immunology

Background:

• MicroRNAs play a crucial role in modulating the tumor microenvironment and immune responses.
• MicroRNAs are promising biomarkers and therapeutic targets in immuno-oncology.
• A lack of dedicated analysis tools hinders microRNA research in this field.

Purpose of the Study:

• To introduce MIO, a user-friendly web platform, and miopy, a Python toolkit.
• To provide integrated methods for analyzing bulk microRNA and gene expression data.
• To facilitate the identification of prognostic and predictive microRNA and gene interaction network biomarkers.

Main Methods:

• Integration of various visualization and analysis methods for microRNA and gene expression data.
• Implementation of regularized regression and survival analysis.
• Inclusion of 40 microRNA target prediction tools, curated immune signatures, and processed TCGA data with immune cell estimations and immunophenoscore.

Main Results:

• The MIO platform and miopy toolkit offer a comprehensive solution for microRNA and gene expression analysis in immuno-oncology.
• The tools enable the selection of prognostic and predictive biomarkers through integrated machine learning methods.
• Users can analyze custom data or utilize processed TCGA data with immune cell infiltration estimations.

Conclusions:

• MIO and miopy address the need for dedicated analysis tools in immuno-oncology research.
• These platforms empower researchers to explore microRNA functions and identify novel biomarkers.
• The integrated approach facilitates a deeper understanding of the interplay between microRNAs, the tumor microenvironment, and immune responses.