Shuhei Iwata (Tokyo / JP), Shungo Adachi (Tokyo / JP), Rei Noguchi (Tokyo / JP), Yuki Adachi (Tokyo / JP), Julia Osaki (Tokyo / JP), Koichi Ogura (Tokyo / JP), Shintaro Iwata (Tokyo / JP), Seiji Ohtori (Chiba / JP), Akira Kawai (Tokyo / JP), Tadashi Kondo (Tokyo / JP)
Backgrounds:
Sarcomas are rare mesenchymal malignant tumors. More than 100 histological subtypes have been characterized, and most of them have limited treatment options. Genomic analyses for sarcomas were reported, but proteomic analyses leading to diagnosis and treatment have not yet been conducted.
Objective:
The purpose of this study was to develop diagnostic or prognostic biomarkers and discover therapeutic targets in sarcomas.
Methods:
Proteogenomic analyses were performed on frozen tissues and cell lines derived from approximately 1,000 patients with 12 histologically different sarcomas. All materials including clinical and pathological information were obtained from the National Cancer Center Biobank, Japan. Proteins were extracted, purified with single-pot solid-phase-enhanced sample preparation (SP3), digested by Trypsin/Lys-C Mix, and subjected to the Orbitrap Astral mass spectrometer for quantitative proteomics using Data-Independent Acquisition (DIA). We integrated proteomic data and previously obtained genomic and transcriptomic data.
Results:
Sarcomas were classified into various proteomic clusters based on the expression pattern of 8000-9000 proteins. Pathway enrichment analysis revealed the specific molecular pathways unique to individual clusters. The integrated analysis showed correlations between genomic and proteomic data. Comparative analysis of proteomic and transcriptomic profiles highlighted the proteomic-specific features for optimal risk stratification. We identified proteins common to the poor prognosis group as prognostic biomarkers, and molecular pathways that could be therapeutic targets for molecular target drugs.
Conclusion:
This proteogenomic study revealed the utility of proteogenomics for identifying molecular subgroups with implications for risk stratification and therapy selection. We confirmed that this study provided a rich resource for future sarcoma research. We will conduct further analyses for the development of precision medicine for sarcomas.