OnCorr: A pan-cancer mRNA-protein correlation tool for precision oncology

Area of Science:

• Oncology
• Genomics
• Proteomics

Background:

• Proteins determine cellular phenotypes and are primary targets for anticancer drugs.
• Precision oncology often relies on transcriptomics (mRNA levels) as a proxy for protein expression due to measurement limitations.
• Accurate protein quantification is crucial for effective personalized cancer therapy.

Purpose of the Study:

• To assess the informativeness of mRNA expression for guiding personalized cancer treatments.
• To analyze mRNA-protein correlations across diverse cancer types.
• To develop a resource for integrating protein-level insights into precision medicine.

Main Methods:

• Analysis of mRNA-protein correlations using three large pan-cancer datasets.
• Development of the Onco-Protein Correlation (OnCorr) web portal (https://oncorr.aws.procan.org.au/).
• Comparative analysis of transcriptomic and proteomic data.

Main Results:

• Quantified mRNA-protein correlations across multiple cancer types.
• Demonstrated the utility of analyzing protein expression data in oncology.
• Established a publicly accessible web portal for accessing these correlations.

Conclusions:

• mRNA levels can serve as an informative proxy for protein expression in certain contexts within precision oncology.
• The Onco-Protein Correlation (OnCorr) portal can augment transcriptomic data for personalized treatment strategies.
• Integrating proteomic data holds significant potential for advancing precision medicine in cancer care.