Abstract LB-C12: Functional proteomics elucidates signaling adaptation driven by combination therapy in BRAF mutant melanoma cell line models

Targeted kinase inhibition is a promising treatment modality for melanoma, which has significantly increased available clinical strategies and improved survival outcomes for patients, whose tumors harbor the BRAF V600E mutation. However, responses are transient and multiple mechanisms for drug resistance can contribute to therapeutic escape. Therefore, a novel multiplexed proteomics approach provides an optimal choice for comprehensively dissecting multiple mechanisms of resistance to BRAFi and combination therapy within one experiment. A large-scale quantitative expression proteomics and phosphoproteomics analysis (SysQuant) was carried out on BRAF V600E mutant melanoma cell lines treated with two different clinically relevant kinase inhibitor combinations: 1) BRAFi/MEKi and 2) BRAFi/PI3Ki. Changes in protein expression and phosphorylation in response to each treatment are determined by comparison to vehicle controls. Cell line models all harbor BRAF V600E mutations, but differ in PTEN status (A375 is WT, while WM793 is PTEN null). Briefly, cells were treated with either drug combination (as above) and harvested at 1hr, 6hrs, 24hrs and 48hrs post-treatment. Control cells were treated with DMSO. Samples were lysed, reduced, alkylated and digested with trypsin. Tryptic peptides from each sample were chemically labeled or “barcoded” with TMT-10plex reagents (4 BRAFi/MEKi time points, 4 BRAFi/PI3Ki time points, 1 DMSO control and a pooled reference sample) and combined for LC-MS/MS. After peptide fractionation with strong cation exchange chromatography and phosphopeptide enrichment, LC-MS/MS peptide sequencing and relative quantification was performed using an Orbitrap Fusion mass spectrometer (Thermo). Raw MS data was searched by Proteome Discoverer and analyzed by in-house R-scripts and Perseus statistical software package. Pathway analysis was done in GeneGO (Metacore). The SysQuant workflow identified >9,000 protein groups and >17,000 unique phosphosites per cell line across different treatments. Principal component analysis of the phosphoproteomics data revealed signaling differences across different treatment conditions and drug combinations are mainly driven by BRAFi and the time post-treatment. K-means clustering was also used to examine trends in the data; as an example, this technique could be used to track signaling changes that correlate with reduction and recovery in ERK signaling. The SysQuant approach provides a systems view of global signaling changes occurring in response to drug treatment. The ability to multiplex samples with TMT allows quantitative deduction of protein expression and phosphorylation patterns that are common or unique in different cell lines, time post-treatment and the effect of combination treatments. This proteomics approach ties protein expression and phosphorylation status in response to combination therapy and generates several hypotheses for further testing with the goal of developing novel combination therapy strategies. Citation Format: Ritin Sharma, Inna Fedorenko, Sasa Koncarevic, Vikram Mitra, Stefan Selzer, Gitte Boehm, Ian Pike, Keiran Smalley, John M. Koomen. Functional proteomics elucidates signaling adaptation driven by combination therapy in BRAF mutant melanoma cell line models. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr LB-C12.