Proteogenomic Landscape of Breast Cancer Tumorigenesis and Targeted Therapy

The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this “proteogenomics” approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protei...

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Bibliographic Details
Published in:Cell Vol. 183; no. 5; pp. 1436 - 1456.e31
Main Authors: Krug, Karsten, Jaehnig, Eric J., Satpathy, Shankha, Blumenberg, Lili, Karpova, Alla, Anurag, Meenakshi, Miles, George, Mertins, Philipp, Geffen, Yifat, Tang, Lauren C., Heiman, David I., Cao, Song, Maruvka, Yosef E., Lei, Jonathan T., Huang, Chen, Kothadia, Ramani B., Colaprico, Antonio, Birger, Chet, Wang, Jarey, Dou, Yongchao, Wen, Bo, Shi, Zhiao, Liao, Yuxing, Wiznerowicz, Maciej, Wyczalkowski, Matthew A., Chen, Xi Steven, Kennedy, Jacob J., Paulovich, Amanda G., Thiagarajan, Mathangi, Kinsinger, Christopher R., Hiltke, Tara, Boja, Emily S., Mesri, Mehdi, Robles, Ana I., Rodriguez, Henry, Westbrook, Thomas F., Ding, Li, Getz, Gad, Clauser, Karl R., Fenyö, David, Ruggles, Kelly V., Zhang, Bing, Mani, D.R., Carr, Steven A., Ellis, Matthew J., Gillette, Michael A., Avanessian, Shayan C., Cai, Shuang, Chan, Daniel, Chen, Xian, Edwards, Nathan J., Hoofnagle, Andrew N., Kane, M. Harry, Ketchum, Karen A., Kuhn, Eric, Levine, Douglas A., Li, Shunqiang, Liebler, Daniel C., Liu, Tao, Luo, Jingqin, Madhavan, Subha, Maher, Chris, McDermott, Jason E., McGarvey, Peter B., Oberti, Mauricio, Pandey, Akhilesh, Payne, Samuel H., Ransohoff, David F., Rivers, Robert C., Rodland, Karin D., Rudnick, Paul, Sanders, Melinda E., Shaw, Kenna M., Shih, Ie-Ming, Slebos, Robbert J.C., Smith, Richard D., Snyder, Michael, Stein, Stephen E., Tabb, David L., Thangudu, Ratna R., Thomas, Stefani, Wang, Yue, White, Forest M., Whiteaker, Jeffrey R., Whiteley, Gordon A., Zhang, Hui, Zhang, Zhen, Zhao, Yingming, Zhu, Heng, Zimmerman, Lisa J.
Format: Journal Article
Language:English
Published: United States Elsevier Inc 25-11-2020
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Summary:The integration of mass spectrometry-based proteomics with next-generation DNA and RNA sequencing profiles tumors more comprehensively. Here this “proteogenomics” approach was applied to 122 treatment-naive primary breast cancers accrued to preserve post-translational modifications, including protein phosphorylation and acetylation. Proteogenomics challenged standard breast cancer diagnoses, provided detailed analysis of the ERBB2 amplicon, defined tumor subsets that could benefit from immune checkpoint therapy, and allowed more accurate assessment of Rb status for prediction of CDK4/6 inhibitor responsiveness. Phosphoproteomics profiles uncovered novel associations between tumor suppressor loss and targetable kinases. Acetylproteome analysis highlighted acetylation on key nuclear proteins involved in the DNA damage response and revealed cross-talk between cytoplasmic and mitochondrial acetylation and metabolism. Our results underscore the potential of proteogenomics for clinical investigation of breast cancer through more accurate annotation of targetable pathways and biological features of this remarkably heterogeneous malignancy. [Display omitted] •Comprehensive proteogenomics resource from prospectively collected breast tumors•Proteogenomics defines ERBB2 and Rb status with clinical implications•Acetylproteome profiling yields insights into subtype-specific cancer metabolism•Immune profiling nominates subsets of luminal tumors for immune therapy Breast cancer is a highly heterogeneous disease with variable outcomes and subtype-driven treatment approaches, making precision medicine a considerable challenge. Proteogenomic analyses of 122 primary breast cancers provide insights into clinically relevant biology, including cell cycle dysregulation, tumor immunogenicity, aberrant metabolism, and heterogeneity in therapeutic target expression.
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AUTHOR CONTRIBUTIONS
Conception and Design, K.K., S.S., P.M., L.C.T., K.R.C., D.R.M., S.A.C., M.J.E., and M.A.G.; Experiment or Data Collection, S.S., G.M., P.M., and L.C.T.; Computation and Statistical Analysis, K.K., E.J.J., S.S., L.B., A.K., M.A., Y.G., D.I.H., S.C., Y.E.M., J.T.L., C.H., R.B.K., A.C., M.A.W., K.R.C., K.V.R., and D.R.M.; Writing – Original Draft, K.K., E.J.J., S.S., L.B., A.K., M.A., S.A.C., M.J.E., and M.A.G.; Supervision, S.S., C.B., T.F.W., L.D., G.G., D.F., K.V.R., B.Z., D.R.M., S.A.C., M.J.E., and M.A.G.; Administration, C.R.K., T.H., E.S.B., M.M., A.I.R., and H.R. All authors contributed to data interpretation and review and editing of the manuscript.
ISSN:0092-8674
1097-4172
DOI:10.1016/j.cell.2020.10.036