Functional Impact of Protein–RNA Variation in Clinical Cancer Analyses

Comprehensive molecular characterization of tumors aims to uncover cancer vulnerabilities, drug resistance mechanisms, and biomarkers. Identification of cancer drivers was suggested as the basis for patient-tailored therapy, and transcriptomic analyses were proposed to reveal the phenotypic outcome of cancer mutations. With the maturation of the proteomic field, studies of protein–RNA discrepancies suggested that RNA analyses are insufficient to predict cellular functions. In this article we discuss the importance of direct mRNA–protein comparisons in clinical cancer studies. We make use of the large amount of data generated by the Clinical Proteomic Tumor Analysis Consortium, which includes protein and mRNA expression analyses from the exact same samples. Analysis of protein–RNA correlations showed marked differences among cancer types, and highlighted the protein–RNA similarities and discrepancies among functional pathways and drug targets. Additionally, unsupervised clustering of the data based on protein or RNA showed substantial differences in tumor classification and the cellular processes that differentiate between clusters. These analyses show the difficulty to predict protein levels from mRNAs, and the critical role of protein analyses for phenotypic tumor characterization.