ArticleJournal of proteome research2016
Activity-Based Protein Profiling Shows Heterogeneous Signaling Adaptations to BRAF Inhibition.
Article in Journal of proteome research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 21 citations in OpenAlex.
- Drug-induced tolerant persisters in tumor: mechanism, vulnerability and perspective implication for clinical treatment.Molecular cancer · 2025Review
- EGFRvIII Confers Sensitivity to Saracatinib in a STAT5-Dependent Manner in Glioblastoma.International journal of molecular sciences · 2024Article
- TAOK3 Facilitates Esophageal Squamous Cell Carcinoma Progression and Cisplatin Resistance Through Augmenting Autophagy Mediated by IRGM.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Review
- Noncanonical EphA2 Signaling Is a Driver of Tumor-Endothelial Cell Interactions and Metastatic Dissemination in BRAF Inhibitor‒Resistant Melanoma.The Journal of investigative dermatology · 2021Article
- The Diverse Roles of TAO Kinases in Health and Diseases.International journal of molecular sciences · 2020Review
- Review
- HDAC Inhibition Enhances theClinical cancer research : an official journal of the American Association for Cancer Research · 2019Article
- Cell-state dynamics and therapeutic resistance in melanoma from the perspective of MITF and IFNγ pathways.Nature reviews. Clinical oncology · 2019Review
- Diverse Mechanisms of BRAF Inhibitor Resistance in Melanoma Identified in Clinical and Preclinical Studies.Frontiers in oncology · 2019Review
- Combined BRAF and HSP90 Inhibition in Patients with UnresectableClinical cancer research : an official journal of the American Association for Cancer Research · 2018Article
- Wnt/β-Catenin Pathway Activation Mediates Adaptive Resistance to BRAF Inhibition in Colorectal Cancer.Molecular cancer therapeutics · 2018Article
- Methods and approaches to disease mechanisms using systems kinomics.Synthetic and systems biotechnology · 2018Review
Corrections and comments
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Patients with BRAF V600E mutant melanoma are typically treated with targeted BRAF kinase inhibitors, such as vemurafenib and dabrafenib. Although these drugs are initially effective, they are not curative. Most of the focus to date has been upon genetic mechanisms of acquired resistance; therefore, we must better understand the global signaling adaptations that mediate escape from BRAF inhibition. In the current study, we have used activity-based protein profiling (ABPP) with ATP-analogue probes to enrich kinases and other enzyme classes that contribute to BRAF inhibitor (BRAFi) resistance in four paired isogenic BRAFi-naïve/resistant cell line models. Our analysis showed these cell line models, which also differ in their PTEN status, have considerable heterogeneity in their kinase ATP probe uptake in comparing both naïve cells and adaptations to chronic drug exposure. A number of kinases including FAK1, SLK, and TAOK2 had increased ATP probe uptake in BRAFi resistant cells, while KHS1 (M4K5) and BRAF had decreased ATP probe uptake in the BRAFi-resistant cells. Gene ontology (GO) enrichment analysis revealed BRAFi resistance is associated with a significant enhancement in ATP probe uptake in proteins implicated in cytoskeletal organization and adhesion, and decreases in ATP probe uptake in proteins associated with cell metabolic processes. The ABPP approach was able to identify key phenotypic mediators critical for each BRAFi resistant cell line. Together, these data show that common phenotypic adaptations to BRAF inhibition can be mediated through very different signaling networks, suggesting considerable redundancy within the signaling of BRAF mutant melanoma cells.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.