|Publication Type||Journal Article|
|Year of Publication||2018|
|Authors||Litichevskiy, L, Peckner, R, Abelin, JG, Asiedu, JK, Creech, AL, Davis, JF, Davison, D, Dunning, CM, Egertson, JD, Egri, S, Gould, J, Ko, T, Johnson, SA, Lahr, DL, Lam, D, Liu, Z, Lyons, NJ, Lu, X, MacLean, BX, Mungenast, AE, Officer, A, Natoli, TE, Papanastasiou, M, Patel, J, Sharma, V, Toder, C, Tubelli, AA, Young, JZ, Carr, SA, Golub, TR, Subramanian, A, MacCoss, MJ, Tsai, L-H, Jaffe, JD|
|Date Published||2018 Apr 25|
Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP). A majority of these drugs elicited reproducible signatures, but notable cell line- and assay-specific differences were observed. Using the "connectivity" framework, we compared signatures across cell types and integrated data across assays, including a transcriptional assay (L1000). Consistent connectivity among cell types revealed cellular responses that transcended lineage, and consistent connectivity among assays revealed unexpected associations between drugs. We further leveraged the resource against public data to formulate hypotheses for treatment of multiple myeloma and acute lymphocytic leukemia. This resource is publicly available at https://clue.io/proteomics.
|Alternate Journal||Cell Syst|
|Grant List||U54 HG008097 / HG / NHGRI NIH HHS / United States |
U54 HL127366 / HL / NHLBI NIH HHS / United States