Integrating proteomics into precision oncology. Issue 6 (25th September 2020) - Wahjudi, Leonie W.; Bernhardt, Stephan; Abnaof, Khalid; Horak, Peter; Kreutzfeldt, Simon; Heining, Christoph; Borgoni, Simone; Becki, Corinna; Berg, Daniela; Richter, Daniela; Hutter, Barbara; Uhrig, Sebastian; et al.
Abstract: DNA sequencing and RNA sequencing are increasingly applied in precision oncology, where molecular tumor boards evaluate the actionability of genetic events in individual tumors to guide targeted treatment. To work toward an additional level of patient characterization, we assessed the abundance and activity of 27 proteins in 134 patients whose tumors had previously undergone whole‐exome and RNA sequencing within the Molecularly Aided Stratification for Tumor Eradication Research (MASTER) program of National Center for Tumor Diseases, Heidelberg. Proteomic and phosphoproteomic targets were selected to reflect the most relevant therapeutic baskets in MASTER. Among six different therapeutic baskets, the proteomic data supported treatment recommendations that were based on DNA and RNA analyses in 10% to 57% and frequently suggested alternative treatment options. In several cases, protein activities explained the patients' clinical course and provided potential explanations for treatment failure. Our study indicates that the integrative analysis of DNA, RNA and protein data may refine therapeutic stratification of individual patients and, thus, holds potential to increase the success rate of precision cancer therapy. Prospective validation studies are needed to advance the integration of proteomic analysis into precision oncology. What's new?: Molecular tumor boards increasingly use DNA and RNA sequence information to identify genetic events in tumors to guide treatment for individual patients. Here, tumor samples from patients with advanced or rare cancers enrolled in the NCT MASTER precision oncology program in Heidelberg, Germany, were retrospectively assessed for expression and phosphorylation of proteins relevant to signaling pathways in six interventional categories applied in the program. Depending on interventional category, proteomic data supported prior therapeutic proposals based on DNA/RNA analysis in 10 to 57 percent and was suggestive of alternative treatment options in most other cases. The findings suggest that proteomic information could help refine therapeutic decisions for advanced‐stage cancer patients.