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Updated: Apr 19, 2026

Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
Published on: February 27, 2015
Proteomic Profiling Reveals How Physiological Media Reshape Cancer Cell Proteomes and Signaling Networks
Colin Zenge1, Brittany Q Pham2, Kihong Nam3
1Cell Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, New York, USA; Louis V. Gerstner Jr. Graduate School of Biomedical Sciences, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Abstract:
Altered metabolism is a hallmark of cancer, making metabolic enzymes attractive therapeutic targets. However, metabolic inhibitors have shown limited clinical success, partly due to differences between standard culture media and physiological nutrient conditions. Human plasma-like medium (HPLM) better recapitulates in vivo metabolite concentrations, yet its effects on cellular proteomes remain poorly characterized. We performed comprehensive TMTpro-based quantitative proteomics and phosphoproteomics across nine cancer cell lines cultured in DMEM or HPLM, consistently quantifying over 10,000 proteins and 24,000 phosphorylation sites across all three biological replicates with high reproducibility. Physiological media induced profound cell-type-specific remodeling of metabolic networks, mitochondrial proteomes, and signaling pathways. While decreased mTORC1 and CDK activity represented universal responses across all cell lines, metabolic enzyme expression exhibited striking heterogeneity. Enzymes in folate metabolism and pyrimidine salvage pathways showed consistent reductions across all cell types, indicating that drug responses may vary with media choice. Mitochondrial proteome composition and morphology displayed cell-type-specific adaptations. Phosphoproteomic analysis revealed kinase signaling networks underlying these metabolic changes. This dataset, accessible via an interactive web application, provides a resource for metabolic research using physiological media, highlighting substantial cell-type-specific variability in how media affect proteomes and signaling pathways.
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