ArticleGenome biology2013
Phosphoproteomics data classify hematological cancer cell lines according to tumor type and sensitivity to kinase inhibitors.
Article in Genome biology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
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Who cites it
37 citing papers in PubMed, 100 citations in OpenAlex.
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- Post-Translational Modifications in Multiple Myeloma: Mechanisms of Drug Resistance and Therapeutic Opportunities.Biomolecules · 2025Review
- PNPO-Mediated Oxidation of DVL3 Promotes Multiple Myeloma Malignancy and Osteoclastogenesis by Activating the Wnt/β-Catenin Pathway.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Integrated proteogenomic characterization of ampullary adenocarcinoma.Cell discovery · 2025Article
- Phosphorylation regulates the chromatin remodeler SMARCAD1 in nucleosome binding, ATP hydrolysis, and histone exchange.The Journal of biological chemistry · 2024Article
- Smad7 palmitoylation by the S-acyltransferase zDHHC17 enhances its inhibitory effect on TGF-β/Smad signaling.The Journal of biological chemistry · 2024Article
- Evolutionary proteogenomic landscape from pre-invasive to invasive lung adenocarcinoma.Cell reports. Medicine · 2024Article
- Principles of phosphoproteomics and applications in cancer research.The Biochemical journal · 2023Article
- Comprehensive proteogenomic characterization of early duodenal cancer reveals the carcinogenesis tracks of different subtypes.Nature communications · 2023Article
- Integrative proteogenomic characterization of early esophageal cancer.Nature communications · 2023Article
- P38 kinases mediate NLRP1 inflammasome activation after ribotoxic stress response and virus infection.The Journal of experimental medicine · 2023Article
- Integrated proteogenomic characterization of urothelial carcinoma of the bladder.Journal of hematology & oncology · 2022Article
- Integrative proteomic characterization of trace FFPE samples in early-stage gastrointestinal cancer.Proteome science · 2022Article
- Targeted therapy for LIMD1-deficient non-small cell lung cancer subtypes.Cell death & disease · 2021Article
- Mitochondrial HSP70 Chaperone System-The Influence of Post-Translational Modifications and Involvement in Human Diseases.International journal of molecular sciences · 2021Review
- A lysosomal enigma CLN5 and its significance in understanding neuronal ceroid lipofuscinosis.Cellular and molecular life sciences : CMLS · 2021Review
- Drug ranking using machine learning systematically predicts the efficacy of anti-cancer drugs.Nature communications · 2021Article
- A Fresh Look at the Structure, Regulation, and Functions of Fodrin.Molecular and cellular biology · 2020Review
- Phosphotyrosine-based Phosphoproteomics for Target Identification and Drug Response Prediction in AML Cell Lines.Molecular & cellular proteomics : MCP · 2020Article
- Integrated phosphoproteomics and transcriptional classifiers reveal hidden RAS signaling dynamics in multiple myeloma.Blood advances · 2019Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundTumor classification based on their predicted responses to kinase inhibitors is a major goal for advancing targeted personalized therapies. Here, we used a phosphoproteomic approach to investigate biological heterogeneity across hematological cancer cell lines including acute myeloid leukemia, lymphoma, and multiple myeloma.
resultsMass spectrometry was used to quantify 2,000 phosphorylation sites across three acute myeloid leukemia, three lymphoma, and three multiple myeloma cell lines in six biological replicates. The intensities of the phosphorylation sites grouped these cancer cell lines according to their tumor type. In addition, a phosphoproteomic analysis of seven acute myeloid leukemia cell lines revealed a battery of phosphorylation sites whose combined intensities correlated with the growth-inhibitory responses to three kinase inhibitors with remarkable correlation coefficients and fold changes (> 100 between the most resistant and sensitive cells). Modeling based on regression analysis indicated that a subset of phosphorylation sites could be used to predict response to the tested drugs. Quantitative analysis of phosphorylation motifs indicated that resistant and sensitive cells differed in their patterns of kinase activities, but, interestingly, phosphorylations correlating with responses were not on members of the pathway being targeted; instead, these mainly were on parallel kinase pathways.
conclusionThis study reveals that the information on kinase activation encoded in phosphoproteomics data correlates remarkably well with the phenotypic responses of cancer cells to compounds that target kinase signaling and could be useful for the identification of novel markers of resistance or sensitivity to drugs that target the signaling network.
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