Poster Authors:

Wanyu Tao, Kaiqiang Hu, Yunyang Zhang, Qiuyuan Yang, Pengwei Pan, Fang He

Pharmaron (Beijing) Co., Ltd, Beijing, China

This poster was presented at the AACR 2025.

This study presents PharmaRonNet, a new bioinformatics tool designed to analyze and integrate single- and multi-omics data. This tool constructs weighted networks to help researchers explore key biological pathways.

To showcase its capabilities, PharmaRonNet was tested through two case studies of bioinformatics biomarker analysis:

1. Identifying key upstream responders: Analysis of a transcriptomic dataset from liver cancer cells treated with insulin identified critical upstream molecules inducing cellular responses.
2. Revealing the drug resistance mechanisms: Whole-exome sequencing (WES) and transcriptome data examination revealed the processes driving resistance to kinase inhibitors, offering insights into overcoming treatment challenges.

PharmaRonNet bridges diverse layers of omics data and provides a platform for uncovering mechanisms often missed by traditional biomarker analyses. Integrating bioinformatics omics data deepens our understanding of intricate biological systems, paving the way for innovative therapeutic strategies.

Our poster shows how PharmaRonNet advances the field of bioinformatics, biomarkers, and omics data analysis.