Combined kinome inhibition states are predictive of cancer cell line sensitivity to kinase inhibitor combination therapies.

Protein kinases are a primary focus in targeted therapy development for cancer, owing to their role as regulators in nearly all areas of cell life. Recent strategies targeting the kinome with combination therapies have shown promise, such as trametinib and dabrafenib in advanced melanoma, but empirical design for less characterized pathways remains a challenge. Computational combination screening is an attractive alternative, allowing in-silico filtering prior to experimental testing of drastically fewer leads, increasing efficiency and effectiveness of drug development pipelines. In this work, we generated combined kinome inhibition states of 40,000 kinase inhibitor combinations from kinobeads-based kinome profiling across 64 doses. We then integrated these with transcriptomics from CCLE to build machine learning models with elastic-net feature selection to predict cell line sensitivity across nine cancer types, with accuracy R2 ∼ 0.75-0.9. We then validated the model by using a PDX-derived TNBC cell line and saw good global accuracy (R2 ∼ 0.7) as well as high accuracy in predicting synergy using four popular metrics (R2 ∼ 0.9). Additionally, the model was able to predict a highly synergistic combination of trametinib and omipalisib for TNBC treatment, which incidentally was recently in phase I clinical trials. Our choice of tree-based models for greater interpretability allowed interrogation of highly predictive kinases in each cancer type, such as the MAPK, CDK, and STK kinases. Overall, these results suggest that kinome inhibition states of kinase inhibitor combinations are strongly predictive of cell line responses and have great potential for integration into computational drug screening pipelines. This approach may facilitate the identification of effective kinase inhibitor combinations and accelerate the development of novel cancer therapies, ultimately improving patient outcomes.

Combined kinome inhibition states are predictive of cancer cell line sensitivity to kinase inhibitor combination therapies.

Protein kinases are a primary focus in targeted therapy development for cancer, owing to their role as regulators in nearly all areas of cell life. Kinase inhibitors are one of the fastest growing drug classes in oncology, but resistance acquisition to kinase-targeting monotherapies is inevitable due to the dynamic and interconnected nature of the kinome in response to perturbation. Recent strategies targeting the kinome with combination therapies have shown promise, such as the approval of Trametinib and Dabrafenib in advanced melanoma, but similar empirical combination design for less characterized pathways remains a challenge. Computational combination screening is an attractive alternative, allowing in-silico screening prior to in-vitro or in-vivo testing of drastically fewer leads, increasing efficiency and effectiveness of drug development pipelines. In this work, we generate combined kinome inhibition states of 40,000 kinase inhibitor combinations from kinobeads-based kinome profiling across 64 doses. We then integrated these with baseline transcriptomics from CCLE to build robust machine learning models to predict cell line sensitivity from NCI-ALMANAC across nine cancer types, with model accuracy R2 ~ 0.75-0.9 after feature selection using elastic-net regression. We further validated the model's ability to extend to real-world examples by using the best-performing breast cancer model to generate predictions for kinase inhibitor combination sensitivity and synergy in a PDX-derived TNBC cell line and saw reasonable global accuracy in our experimental validation (R2 ~ 0.7) as well as high accuracy in predicting synergy using four popular metrics (R2 ~ 0.9). Additionally, the model was able to predict a highly synergistic combination of Trametinib (MEK inhibitor) and Omipalisib (PI3K inhibitor) for TNBC treatment, which incidentally was recently in phase I clinical trials for TNBC. Our choice of tree-based models over networks for greater interpretability also allowed us to further interrogate which specific kinases were highly predictive of cell sensitivity in each cancer type, and we saw confirmatory strong predictive power in the inhibition of MAPK, CDK, and STK kinases. Overall, these results suggest that kinome inhibition states of kinase inhibitor combinations are strongly predictive of cell line responses and have great potential for integration into computational drug screening pipelines. This approach may facilitate the identification of effective kinase inhibitor combinations and accelerate the development of novel cancer therapies, ultimately improving patient outcomes.

Lyn regulates creatine uptake in an imatinib-resistant CML cell line.

BACKGROUND: Imatinib mesylate (imatinib) is the first-line treatment for newly diagnosed chronic myeloid leukemia (CML) due to its remarkable hematologic and cytogenetic responses. We previously demonstrated that the imatinib-resistant CML cells (Myl-R) contained elevated Lyn activity and intracellular creatine pools compared to imatinib-sensitive Myl cells. METHODS: Stable isotope metabolic labeling, media creatine depletion, and Na+/K+-ATPase inhibitor experiments were performed to investigate the origin of creatine pools in Myl-R cells. Inhibition and shRNA knockdown were performed to investigate the specific role of Lyn in regulating the Na+/K+-ATPase and creatine uptake. RESULTS: Inhibition of the Na+/K+-ATPase pump (ouabain, digitoxin), depletion of extracellular creatine or inhibition of Lyn kinase (ponatinib, dasatinib), demonstrated that enhanced creatine accumulation in Myl-R cells was dependent on uptake from the growth media. Creatine uptake was independent of the Na+/creatine symporter (SLC6A8) expression or de novo synthesis. Western blot analyses showed that phosphorylation of the Na+/K+-ATPase on Tyr 10 (Y10), a known regulatory phosphorylation site, correlated with Lyn activity. Overexpression of Lyn in HEK293 cells increased Y10 phosphorylation (pY10) of the Na+/K+-ATPase, whereas Lyn inhibition or shRNA knockdown reduced Na+/K+-ATPase pY10 and decreased creatine accumulation in Myl-R cells. Consistent with enhanced uptake in Myl-R cells, cyclocreatine (Ccr), a cytotoxic creatine analog, caused significant loss of viability in Myl-R compared to Myl cells. CONCLUSIONS: These data suggest that Lyn can affect creatine uptake through Lyn-dependent phosphorylation and regulation of the Na+/K+-ATPase pump activity. GENERAL SIGNIFICANCE: These studies identify kinase regulation of the Na+/K+-ATPase as pivotal in regulating creatine uptake and energy metabolism in cells.

Application of Integrated Drug Screening/Kinome Analysis to Identify Inhibitors of Gemcitabine-Resistant Pancreatic Cancer Cell Growth.

Continuous exposure of a pancreatic cancer cell line MIA PaCa-2 (MiaS) to gemcitabine resulted in the formation of a gemcitabine-resistant subline (MiaR). In an effort to discover kinase inhibitors that inhibited MiaR growth, MiaR cells were exposed to kinase inhibitors (PKIS-1 library) in a 384-well screening format. Three compounds (UNC10112721A, UNC10112652A, and UNC10112793A) were identified that inhibited the growth of MiaR cells by more than 50% (at 50 nM). Two compounds (UNC10112721A and UNC10112652A) were classified as cyclin-dependent kinase (CDK) inhibitors, whereas UNC10112793A was reported to be a PLK inhibitor. Dose-response experiments supported the efficacy of these compounds to inhibit growth and increase apoptosis in 2D cultures of these cells. However, only UNC10112721A significantly inhibited the growth of 3D spheroids composed of MiaR cells and GFP-tagged cancer-associated fibroblasts. Multiplexed inhibitor bead (MIB)-mass spectrometry (MS) kinome competition experiments identified CDK9, CLK1-4, DYRK1A, and CSNK1 as major kinase targets for UNC10112721A in MiaR cells. Another CDK9 inhibitor (CDK-IN-2) replicated the growth inhibitory effects of UNC10112721A, whereas inhibitors against the CLK, DYRK, or CSNK1 kinases had no effect. In summary, these studies describe a coordinated approach to discover novel kinase inhibitors, evaluate their efficacy in 3D models, and define their specificity against the kinome.

BIRC6 mediates imatinib resistance independently of Mcl-1.

Baculoviral IAP repeat containing 6 (BIRC6) is a member of the inhibitors of apoptosis proteins (IAPs), a family of functionally and structurally related proteins that inhibit apoptosis. BIRC6 has been implicated in drug resistance in several different human cancers, however mechanisms regulating BIRC6 have not been extensively explored. Our phosphoproteomic analysis of an imatinib-resistant chronic myelogenous leukemia (CML) cell line (MYL-R) identified increased amounts of a BIRC6 peptide phosphorylated at S480, S482, and S486 compared to imatinib-sensitive CML cells (MYL). Thus we investigated the role of BIRC6 in mediating imatinib resistance and compared it to the well-characterized anti-apoptotic protein, Mcl-1. Both BIRC6 and Mcl-1 were elevated in MYL-R compared to MYL cells. Lentiviral shRNA knockdown of BIRC6 in MYL-R cells increased imatinib-stimulated caspase activation and resulted in a ~20-25-fold increase in imatinib sensitivity, without affecting Mcl-1. Treating MYL-R cells with CDK9 inhibitors decreased BIRC6 mRNA, but not BIRC6 protein levels. By contrast, while CDK9 inhibitors reduced Mcl-1 mRNA and protein, they did not affect imatinib sensitivity. Since the Src family kinase Lyn is highly expressed and active in MYL-R cells, we tested the effects of Lyn inhibition on BIRC6 and Mcl-1. RNAi-mediated knockdown or inhibition of Lyn (dasatinib/ponatinib) reduced BIRC6 protein stability and increased caspase activation. Inhibition of Lyn also increased formation of an N-terminal BIRC6 fragment in parallel with reduced amount of the BIRC6 phosphopeptide, suggesting that Lyn may regulate BIRC6 phosphorylation and stability. In summary, our data show that BIRC6 stability is dependent on Lyn, and that BIRC6 mediates imatinib sensitivity independently of Mcl-1 or CDK9. Hence, BIRC6 may be a novel target for the treatment of drug-resistant CML where Mcl-1 or CDK9 inhibitors have failed.