Activity-Based Protein Profiling Shows Heterogeneous Signaling Adaptations to BRAF Inhibition

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.

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.

Abstract 809: BRAF wild-type melanoma survival hinges upon AKT activity and adaptive autophagic reprogramming in response to chemotherapy

Strategies for patients whose melanomas are BRAF wild-type are completely lacking. We here report on the mechanisms underlying the long-term responses (>12 months) of 2 BRAF wild-type (WT) melanoma patients to the AKT inhibitor MK-2206 in combination with paclitaxel and carboplatin. A panel of 7 BRAF/NRAS-WT cell lines was leveraged to investigate strategies to overcome chemoresistance. Electron microscopy, western blotting and flow cytometry assays were integrated to simultaneously follow fluctuations in autophagic flux, reactive oxygen species levels and cytotoxicity caused from chronic treatment of cells with chemotherapy, MK-2206, lysomotropic agents and/or anti-oxidants. MK-2206 potently inhibited phospho-AKT signaling, but did not impact melanoma growth or survival. The combination of MK-2206 with paclitaxel and carboplatin induced little apoptosis following 3-day treatment, but led to cytotoxicity in long-term colony formation and 3D spheroid assays. Mechanistically the combination was noted to induce autophagy and disrupt reactive oxygen species homeostasis, as shown by increased LC3-II expression, the formation of LC3 punctae, acridine orange protonation, the accumulation of autophagosomes and increased ROS detection using DHR-123. At earlier time points, autophagy was protective with cytotoxicity enhanced following chloroquine and bafilomycin treatment as well as the increased cytotoxic effects seen in ATG5-/- MEFs. Although prolonged MK-2206/chemotherapy treatment (6-9 days) led to high levels of autophagy induction and a switch to caspase-dependent apoptosis, drug resistant clones still eventually emerged. The importance of autophagy for the escape process was suggested by the lack of ATG5-/- MEF colonies seen following combination therapy treatment. Autophagy inhibition enhanced the cell death response through increased generation of ROS and could be reversed by anti-oxidants. In summary, we demonstrate for the first time that AKT inhibition in combination with chemotherapy may have clinical activity in BRAF WT melanoma. We further show that the administration of an autophagy inhibitor may prevent resistance from emerging to this drug combination.

Citation Format: Vito W. Rebecca, Renato Massaro, Inna Fedorenko, Geoffrey T. Gibney, Vernon K. Sondak, Ravi K. Amaravadi, Shengkan Jin, Silvya S. Maria-Engler, Ragini Kudchadkar, Keiran S. M. Smalley. BRAF wild-type melanoma survival hinges upon AKT activity and adaptive autophagic reprogramming in response to chemotherapy. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 809. doi:10.1158/1538-7445.AM2014-809

Abstract 5237: Systems level modeling following BRAF inhibition reveals an essential role for Ephrin A2 receptor in therapeutic escape

Although initially striking, the therapeutic efficacy of BRAF inhibition is eventually undermined by adaptive cellular signaling that leads to progressive disease. To date, several mechanisms of BRAF inhibitor resistance have been reported focusing primarily on single alterations. To address how global rewiring of melanoma signaling promotes resistance, we utilized mass spectrometry based phosphoproteomic and network analyses to identify signaling changes in tyrosine, threonine and serine that occur prior to and following acquired BRAF inhibitor resistance. This comprehensive bioinformatics approach uncovered a “resistance interactome” consisting of ∼150 nodes that was marked by significant alterations and the emergence of signaling nodes such as ITGB1, EphA2, EphB4, FAK1, STAT3 and PXN. GeneGo pathway enrichment analysis revealed enhanced cytoskeletal rearrangement, adhesion, integrin signaling, cell migration and extracellular matrix remodeling. Consistent with our bioinformatic predictions, melanoma cell lines with acquired vemurafenib resistance were considerably more invasive than their drug naïve counterparts and showed increased trans-endothelial cell migration. Confirmatory Western blot studies showed increased expression and phosphorylation of EphA2 receptor at Ser897, FAK1 at Ser397 and paxillin at Y118. Knockdown of EphA2 in the resistant cultures inhibited ERK signaling and completely prevented cell invasion and trans-endothelial cell migration. Functionally, EphA2 expression appeared to be regulated by an epigenetic mechanism involving promoter methylation and HDAC1. The clinical relevance of these findings was demonstrated in matched pairs of biopsies from patients receiving either BRAF or BRAF+MEK inhibitors, with significant Ephrin A2 receptor expression being observed in a subset of those on therapy. In summary, chronic MAPK pathway inhibition leads to major remodeling of the melanoma signaling network with EphA2 emerging as a key driver of the resistance phenotype.

Citation Format: Kim H. T. Paraiso, Bin Fang, Dale Han, Inna Fedorenko, Jobin John, John Koomen, Jennifer Wargo, Keith Flaherty, Friedegund Meier, Kerian S. M. Smalley. Systems level modeling following BRAF inhibition reveals an essential role for Ephrin A2 receptor in therapeutic escape. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 5237. doi:10.1158/1538-7445.AM2013-5237

Abstract 692: Drug treatment causes evolution

A targeted drug treatment, PLX40720, eliminates the bulk of melanoma tumours, but there is always regression. We assert that the tumour population is heterogenous. Then the drug treatment is a selection process, targeting specific subpopulations. When the treatment ends, phenotypic drift causes reversion towards the original wild-type population.

Our model is a discrete population of cells. The cells each have a distinct phenotype. This phenotype determines their fitness. The fitness changes under drug conditions: we define a fitness landscape for both drug and drug-free conditions. We validate the model using population experiments on four melanoma cell lines (1205Lu, WM164, WM793, WM983A). We find initial growth curves, death rates and regrowth curves under drug treatment.

Matching the clinical approach, we treat the cell lines chronically with drug for six months. We then stop treatment and examine the reversion of the resistant cell lines to wild-type over a period of several weeks. There is only partial reversion to wild-type. We return to the model to incorporate this experimental data. We extend the complexity of the fitness landscape to multiple fitness “wells". Reversion after drug treatment only populates one of these wells. This more complex landscape reproduces the experimental observations.

The model concept extends naturally to considering combination therapies. We also discuss the effect of modifying the local environment of the tumour: the drug treatment may become more effective. This approach gives a quantitative assessment of treatment strategies.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 692. doi:10.1158/1538-7445.AM2011-692

Quantificational and statistical analysis of the differences in centrosomal features of untreated lung cancer cells and normal cells

OBJECTIVE

To distinguish untreated lung cancer cells from normal cells through quantitative analysis and statistical inference of centrosomal features extracted from cell images.

STUDY DESIGN

Recent research indicates that human cancer cell development is accompanied by centrosomal abnormalities. For quantitative analysis of centrosome abnormalities, high-resolution images of normal and untreated cancer lung cells were acquired. After the images were preprocessed and segmented, 11 features were extracted. Correlations among the features were calculated to remove redundant features. Ten nonredundant features were selected for further analysis. The mean values of 10 centrosome features were compared between cancer and normal cells by the two-sample t-test; distributions of the 10 features of cancer and normal centrosomes were compared by the two-sample Kolmogorov-Smirnov test.

RESULTS

Both tests reject the null hypothesis; the means and distributions of features coincide for normal and cancer cells. The 10 centrosome features separate normal from cancer cells at the 5% significance level and show strong evidence that all 10 features exhibit major differences between normal and cancer cells.

CONCLUSION

Centrosomes from untreated cancer and normal bronchial epithelial cells can be distinguished through objective measurement and quantitative analysis, suggesting a new approach for lung cancer detection, early diagnosis and prognosis.