Measuring Kinase Activity-A Global Challenge

Multiplexed Profiling of CDK Kinase Activities in Tumor Biopsies with Fluorescent Peptide Biosensors

Detection of disease biomarkers constitutes a major challenge for the development of personalized and predictive diagnostics as well as companion assays. Protein kinases (PKs) involved in the coordination of cell cycle progression and proliferation that are hyperactivated in human cancers constitute attractive pharmacological targets and relevant biomarkers. Although it is relatively straightforward to assess the relative abundance of PKs in a biological sample, there is not always a direct correlation with enzymatic activity, which is regulated by several posttranslational mechanisms. Studies of relative abundance therefore convey limited information, and the lack of selective, sensitive, and standardized tools together with the inherent complexity of biological samples makes it difficult to quantify PK activities in physio-pathological tissues. To address this challenge, we have developed a toolbox of fluorescent biosensors that report on CDK activities in a sensitive, selective, dose-dependent, and quantitative fashion, which we have implemented to profile CDK activity signatures in cancer cell lines and biopsies from human tumors. In this study, we report on a standardized and calibrated biosensing approach to quantify CDK1,2,4, and 6 activities simultaneously through a combination of four different biosensors in a panel of 40 lung adenocarcinoma and 40 follicular lymphoma samples. CDK activity profiling highlighted two major patterns which were further correlated with age, sex of patients, tumor size, grade, and genetic and immunohistochemical features of the biopsies. Multiplex CDKACT biosensing technology provides new and complementary information relative to current genetic and immunohistochemical characterization of tumor biopsies, which will be useful for diagnostic purposes, potentially guiding therapeutic decision. These fluorescent peptide biosensors offer promise for personalized diagnostics based on kinase activity profiling.

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.

Tracking mutation and drug-driven alterations of oncokinase conformations

Numerous kinases act as central nodes of cellular signaling networks. As such, many of these enzymes function as molecular switches for coordinating spatiotemporal signal transmission. Typically, it is the compartmentalized phosphorylation of protein substrates which relays the transient input signal to determine decisive physiological cell responses. Genomic alterations affect kinase abundance and/or their activities which contribute to the malignant transformation, progression, and metastasis of human cancers. Thus, major drug discovery efforts have been made to identify lead molecules targeting clinically relevant oncokinases. The concept of personalized medicine aims to apply the therapeutic agent with the highest efficacy towards a patient-specific mutation. Here, we discuss the implementation of a cell-based reporter system which may foster the decision-making process to identify the most promising lead-molecules. We present a modular kinase conformation (KinCon) biosensor platform for live-cell analyses of kinase activity states. This biosensor facilitates the recording of kinase activity conformations of the wild-type and the respective mutated kinase upon lead molecule exposure. We reflect proof-of-principle studies demonstrating how this technology has been extended to profile drug properties of the full-length kinases BRAF and MEK1 in intact cells. Further, we pinpoint how this technology may open new avenues for systematic and patient-tailored drug discovery efforts. Overall, this precision-medicineoriented biosensor concept aims to determine kinase inhibitor specificity and anticipate their drug efficacies.

Recent Progress in Fluorescent Chemosensors for Protein Kinases

Protein kinases are involved in almost all biological activities. The activities of different kinases reflect the normal or abnormal status of the human body. Therefore, detecting the activities of different kinases is important for disease diagnosis and drug discovery. Fluorescent probes offer opportunities for studying kinase behaviors at different times and spatial locations. In this review, we summarize different kinds of fluorescent chemosensors that have been used to detect the activities of many different kinases.

Shining Light on Protein Kinase Biomarkers with Fluorescent Peptide Biosensors

Protein kinases (PKs) are established gameplayers in biological signalling pathways, and a large body of evidence points to their dysregulation in diseases, in particular cancer, where rewiring of PK networks occurs frequently. Fluorescent biosensors constitute attractive tools for probing biomolecules and monitoring dynamic processes in complex samples. A wide variety of genetically encoded and synthetic biosensors have been tailored to report on PK activities over the last decade, enabling interrogation of their function and insight into their behaviour in physiopathological settings. These optical tools can further be used to highlight enzymatic alterations associated with the disease, thereby providing precious functional information which cannot be obtained through conventional genetic, transcriptomic or proteomic approaches. This review focuses on fluorescent peptide biosensors, recent developments and strategies that make them attractive tools to profile PK activities for biomedical and diagnostic purposes, as well as insights into the challenges and opportunities brought by this unique toolbox of chemical probes.

Discerning Tyrosine Phosphorylation from Multiple Phosphorylations Using a Nanofluidic Logic Platform

Discerning tyrosine phosphorylation (pTyr) catalyzed by Tyr kinase is central to the revelation of oncogenic mechanisms and the development of targeted anticancer drugs. Despite some techniques, this goal remains challenging, especially when faced with the interference of multiple phosphorylation events, including serine (pSer) and threonine phosphorylation (pThr). We describe here a functional polymer-modified artificial ion nanochannel, which enables the sensitive and selective recognition of phosphotyrosine (pY) peptide by the distinct ionic current change. Such a recognition effect allows for the nanochannel to work in a complex protein digest condition. Further, the implementation of nanofluidic logic functions with the addition of Ca²⁺ dramatically improves the selectivity of the nanochannel to pY peptide and thus can discern pTyr by the Tyr kinase from pSer by the Ser/Thr kinase through simultaneously monitoring multisite phosphorylation at the same or different peptide substrates in one-pot. This logic sensing platform displays the potential in differentiating Tyr kinase and Ser/Thr kinase and assessing multi-kinase activities in multi-targeted drug design.

Phosphoproteomics Meets Chemical Genetics: Approaches for Global Mapping and Deciphering the Phosphoproteome

Protein kinases are important enzymes involved in the regulation of various cellular processes. To function properly, each protein kinase phosphorylates only a limited number of proteins among the thousands present in the cell. This provides a rapid and dynamic regulatory mechanism that controls biological functions of the proteins. Despite the importance of protein kinases, most of their substrates remain unknown. Recently, the advances in the fields of protein engineering, chemical genetics, and mass spectrometry have boosted studies on identification of bona fide substrates of protein kinases. Among the various methods in protein kinase specific substrate identification, genetically engineered protein kinases and quantitative phosphoproteomics have become promising tools. Herein, we review the current advances in the field of chemical genetics in analog-sensitive protein kinase mutants and highlight selected strategies for identifying protein kinase substrates and studying the dynamic nature of protein phosphorylation.

KinCon: Cell-based recording of full-length kinase conformations

The spectrum of kinase alterations displays distinct functional characteristics and requires kinase mutation-oriented strategies for therapeutic interference. Besides phosphotransferase activity, protein abundance, and intermolecular interactions, particular patient-mutations promote pathological kinase conformations. Despite major advances in identifying lead molecules targeting clinically relevant oncokinase functions, still many kinases are neglected and not part of drug discovery efforts. One explanation is attributed to challenges in tracking kinase activities. Chemical probes are needed to functionally annotate kinase functions, whose activities may not always depend on catalyzing phospho-transfer. Such non-catalytic kinase functions are related to transitions of full-length kinase conformations. Recent findings underline that cell-based reporter systems can be adapted to record conformation changes of kinases. Here, we discuss the possible applications of an extendable kinase conformation (KinCon) reporter toolbox for live-cell recording of kinase states. KinCon is a genetically encoded bioluminescence-based biosensor platform, which can be subjected for measurements of conformation dynamics of mutated kinases upon small molecule inhibitor exposure. We hypothesize that such biosensors can be utilized to delineate the molecular modus operandi for kinase and pseudokinase regulation. This should pave the path for full-length kinase-targeted drug discovery efforts aiming to identify single and combinatory kinase inhibitor therapies with increased specificity and efficacy.

Dynamic regulatory features of the protein tyrosine kinases

The SRC, Abelson murine leukemia viral oncogene homolog 1, TEC and C-terminal SRC Kinase families of non-receptor tyrosine kinases (collectively the Src module kinases) mediate an array of cellular signaling processes and are therapeutic targets in many disease states. Crystal structures of Src modules kinases provide valuable insights into the regulatory mechanisms that control activation and generate a framework from which drug discovery can advance. The conformational ensembles visited by these multidomain kinases in solution are also key features of the regulatory machinery controlling catalytic activity. Measurement of dynamic motions within kinases substantially augments information derived from crystal structures. In this review, we focus on a body of work that has transformed our understanding of non-receptor tyrosine kinase regulation from a static view to one that incorporates how fluctuations in conformational ensembles and dynamic motions influence activation status. Regulatory dynamic networks are often shared across and between kinase families while specific dynamic behavior distinguishes unique regulatory mechanisms for select kinases. Moreover, intrinsically dynamic regions of kinases likely play important regulatory roles that have only been partially explored. Since there is clear precedence that kinase inhibitors can exploit specific dynamic features, continued efforts to define conformational ensembles and dynamic allostery will be key to combating drug resistance and devising alternate treatments for kinase-associated diseases.

Relevance of neuroendocrine tumours models assessed by kinomic profiling

Although there is evidence of a significant rise of neuroendocrine tumours (NETs) incidence, current treatments are largely insufficient due to somewhat poor knowledge of these tumours. Despite many efforts achieved to expose driver oncogene mutations in NETs, the genetic landscape of NETs is characterized by relatively few mutations and chromosomal aberrations per tumour compared with other tumour types. In addition, NETs display few actionable mutations providing compelling rationale for targeted therapies. Recent works aiming at characterizing currently used NETs in vitro models at the genomic level raised concerns on their reliability as bona fide tools to study NETs biology. However, the lack of actionable mutation in NETs implies that sole use of genomic is not sufficient to describe these models and establish appropriate therapeutic strategies. Several kinases and kinase-involving signalling pathways have been demonstrated as abnormally regulated in NETs. Yet, kinases have only been investigated regardless of their involvement in large intracellular signalling networks. In order to assess the validity of in vitro NETs models to study NETs biology, "next-generation" high throughput functional technologies based on "kinome-wide activity" will demonstrate the similarities between signalling pathways in NETs models and patients' samples. These approaches will significantly assist in identifying actionable alterations in NETs signalling pathways and guide patient stratification into early-phase clinical trials based on kinase inhibition targeted therapies.

Dasatinib Is Preferentially Active in the Activated B-Cell Subtype of Diffuse Large B-Cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease, and at least one-third of its patients relapse after treatment with the current chemotherapy regimen, R-CHOP. By gene-expression profiling, patients with DLBCL can be categorized into two clinically relevant subtypes: activated B-cell (ABC) and germinal center B-cell (GCB) DLBCL. Patients with the ABC subtype have a worse prognosis than those with GCB, and the subtype is defined by chronic, over-active signaling through the B-cell receptor and NF-κB pathways. We examined the effects of the Src family kinase (SFK) inhibitor dasatinib in a panel of ABC and GCB DLBCL cell lines and found that the former are much more sensitive to dasatinib than the latter. However, using multiplexed inhibitor bead coupled to mass spectrometry (MIB/MS) kinome profiling and Western blot analysis, we found that both subtypes display inhibition of the SFKs in response to dasatinib after both short- and long-term treatment. The MIB/MS analyses revealed that several cell-cycle kinases, including CDK4, CDK6, and the Aurora kinases, are down-regulated by dasatinib treatment in the ABC, but not in the GCB, subtype. The present findings have potential implications for the clinical use of dasatinib for the treatment of ABC DLBCL, either alone or in combination with other agents.