RT Journal Article
SR Electronic
T1 A Library of Phosphoproteomic and Chromatin Signatures for Characterizing Cellular Responses to Drug Perturbations
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 185918
DO 10.1101/185918
A1 Lev Litichevskiy
A1 Ryan Peckner
A1 Jennifer G. Abelin
A1 Jacob K. Asiedu
A1 Amanda L. Creech
A1 John F. Davis
A1 Desiree Davison
A1 Caitlin M. Dunning
A1 Jarrett D. Egertson
A1 Shawn Egri
A1 Joshua Gould
A1 Tak Ko
A1 Sarah A. Johnson
A1 David L. Lahr
A1 Daniel Lam
A1 Zihan Liu
A1 Nicholas J. Lyons
A1 Xiaodong Lu
A1 Brendan X. MacLean
A1 Alison E. Mungenast
A1 Adam Officer
A1 Ted E. Natoli
A1 Malvina Papanastasiou
A1 Jinal Patel
A1 Vagisha Sharma
A1 Courtney Toder
A1 Andrew A. Tubelli
A1 Jennie Z. Young
A1 Steven A. Carr
A1 Todd R. Golub
A1 Aravind Subramanian
A1 Michael J. MacCoss
A1 Li-Huei Tsai
A1 Jacob D. Jaffe
YR 2017
UL http://biorxiv.org/content/early/2017/09/07/185918.abstract
AB Though the added value of proteomic measurements to gene expression profiling has been demonstrated, profiling of gene expression on its own remains the dominant means of understanding cellular responses to perturbation. Direct protein measurements are typically limited due to issues of cost and scale; however, the recent development of high-throughput, targeted sentinel mass spectrometry assays provides an opportunity for proteomics to contribute at a meaningful scale in high-value areas for drug development. To demonstrate the feasibility of a systematic and comprehensive library of perturbational proteomic signatures, we profiled 90 drugs (in triplicate) in six cell lines using two different proteomic assays — one measuring global changes of epigenetic marks on histone proteins and another measuring a set of peptides reporting on the phosphoproteome — for a total of more than 3,400 samples. This effort represents a first-of-its-kind resource for proteomics. The majority of tested drugs generated reproducible responses in both phosphosignaling and chromatin states, but we observed differences in the responses that were cell line-and assay-specific. We formalized the process of comparing response signatures within the data using a concept called connectivity, which enabled us to integrate data across cell types and assays. Furthermore, it facilitated incorporation of transcriptional signatures. Consistent connectivity among cell types revealed cellular responses that transcended cell-specific effects, while consistent connectivity among assays revealed unexpected associations between drugs that were confirmed by experimental follow-up. We further demonstrated how the resource could be leveraged against public domain external datasets to recognize therapeutic hypotheses that are consistent with ongoing clinical trials for the treatment of multiple myeloma and acute lymphocytic leukemia (ALL). These data are available for download via the Gene Expression Omnibus (accession GSE101406), and web apps for interacting with this resource are available at https://clue.io/proteomics.HighlightsFirst-of-its-kind public resource of proteomic responses to systematically administered perturbagensDirect proteomic profiling of phosphosignaling and chromatin states in cells for 90 drugs in six different cell linesExtends Connectivity Map concept to proteomic data for integration with transcriptional dataEnables recognition of unexpected, cell type-specific activities and potential translational therapeutic opportunities