DrBioRight 2.0: an LLM-powered bioinformatics chatbot for large-scale cancer functional proteomics analysis

Area of Science:

• Proteomics
• Cancer Biology
• Bioinformatics

Background:

• Functional proteomics is key to understanding cancer mechanisms.
• Identifying novel biomarkers and therapeutic targets is crucial for cancer treatment.
• Large-scale proteomic datasets offer significant potential but require advanced analytical tools.

Purpose of the Study:

• To develop a comprehensive cancer functional proteomics resource.
• To create an intuitive bioinformatic platform (DrBioRight 2.0) for exploring and analyzing this data.
• To leverage large language models for enhanced data accessibility and analysis.

Main Methods:

• Utilized reverse phase protein arrays for proteomic profiling.
• Integrated data from The Cancer Genome Atlas (TCGA) and Cancer Cell Line Encyclopedia (CCLE).
• Developed DrBioRight 2.0, a platform incorporating large language models for natural language interaction and analysis.

Main Results:

• Created a resource with proteomic data from nearly 8000 TCGA and 900 CCLE samples.
• Included a curated panel of nearly 500 antibodies covering major cancer hallmark pathways.
• DrBioRight 2.0 enables exploration, advanced analysis, visualization, and natural language querying of proteogenomic data.

Conclusions:

• The developed resource and DrBioRight 2.0 platform significantly enhance the accessibility and analytical power of cancer functional proteomics data.
• This integrated approach accelerates the translation of complex proteogenomic findings into actionable biomedical insights.
• Facilitates the discovery of novel cancer biomarkers and therapeutic targets through streamlined data analysis.