Application of Cancer Cell Line Encyclopedia for Measuring Correlation Between Transcriptomics and Proteomics as a Guide for System-level Insights

Blake Williams, Darryl Perry, PJ Aspesi, Jefferson Parker, Ted Johnson, Wendy Su, Eduardo Tabacman, Kirk Delisle, Kayvon Avishan, Vic Myer, Felipa Mapa, Michael Hinterberg, Alan Williams,Lori Jennings, Nebojsa Janjic,Joseph Loureiro

biorxiv(2024)

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摘要
Robust and reliable proteome measurements provide mechanistic insights in biomedical research. SOMAmer (Slow Off-rate Modified Aptamer) reagents are modified, DNA-based, affinity reagents that measure defined target proteins with reproducibility and accuracy similar to monoclonal antibodies. Applying SOMAmer reagent technology, we developed SomaScan, a clinical proteome profiling platform with capability to measure 7,523 proteoforms for 6,594 human proteins by Uni-protID in small sample volumes (e.g., 55 microliters of plasma or serum). We evaluated the platform by profiling the proteome of a panel of well characterized Cell Line Encyclopedia (CCLE) cancer models. Unsupervised machine learning analyses demonstrate the SomaScan assay distinguishing cell lines on the basis of their proteome signatures and identifying both tissue-specific and oncogenic pathways. The proteome measured by SomaScan correlates with published CCLE transcriptome at a level comparable to other published transcript to proteome studies. Taken together, we demonstrate that the SomaScan platform is a technically reproducible system suitable for biomedical and clinical applications that reliably illuminates underlying biomolecular mechanisms. ### Competing Interest Statement Funding and Conflict of Interest: This research was resourced as part of a Novartis-Somalogic multiyear collaboration and all authors were employees of Novartis or Somalogic at the time of their contribution to this work.
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