Systems-pharmacology dissection of a drug synergy in imatinib-resistant CML

Exploring affinity chromatography in proteomics: A comprehensive review

Over the past decades, the proteomics field has undergone rapid growth. Progress in mass spectrometry and bioinformatics, together with separation methods, has brought many innovative approaches to the study of the molecular biology of the cell. The potential of affinity chromatography was recognized immediately after its first application in proteomics, and since that time, it has become one of the cornerstones of many proteomic protocols. Indeed, this chromatographic technique exploiting the specific binding between two molecules has been employed for numerous purposes, from selective removal of interfering (over)abundant proteins or enrichment of scarce biomarkers in complex biological samples to mapping the post-translational modifications and protein interactions with other proteins, nucleic acids or biologically active small molecules. This review presents a comprehensive survey of this versatile analytical tool in current proteomics. To navigate the reader, the haphazard space of affinity separations is classified according to the experiment's aims and the separated molecule's nature. Different types of available ligands and experimental strategies are discussed in further detail for each of the mentioned procedures.

Small molecule inhibitor against onco-mucins disrupts Src/FosL1 axis to enhance gemcitabine efficacy in pancreatic ductal adenocarcinoma

Mucin MUC4 is an aberrantly expressed oncogene in pancreatic ductal adenocarcinoma (PDAC), yet no pharmacological inhibitors have been identified to target MUC4. Here, we adapted an in silico screening method using the Cancer Therapeutic Response Database (CTRD) to Identify Small Molecule Inhibitors against Mucins (SMIMs). We identified Bosutinib as a candidate drug to target oncogenic mucins among 126 FDA-approved drugs from CTRD screening. Functionally, Bosutinib treatment alone/and in combination with gemcitabine (Gem)/5' fluorouracil (5FU) reduced in vitro viability, migration, and colony formation in multiple PDAC cell lines as well as human PDAC organoid prolifertaion and growth and in vivo xenograft growth. Further, biochemical and molecular analyses showed that Bosutinib exhibited these functional effects by downregulating MUC4 mucin at both transcript and translation levels in a dose- and time-dependent manner. Mechanistically, global transcriptome analysis in PDAC cells upon treatment with Bosutinib revealed disruption of the Src-ERK/AKT-FosL1 pathway, leading to decreased expression of MUC4 and MUC5AC mucins. Taken together, Bosutinib is a promising, novel, and highly potent SMIMs to target MUC4/MUC5AC mucins. This mucin-targeting effect of Bosutinib can be exploited in the future with cytotoxic agents to treat mucinous tumors.

DeepIDC: A Prediction Framework of Injectable Drug Combination Based on Heterogeneous Information and Deep Learning

BACKGROUND AND OBJECTIVE

In clinical practice, injectable drug combination (IDC) usually provides good therapeutic effects for patients. Numerous clinical studies have directly indicated that inappropriate IDC generates adverse drug events (ADEs). The clinical application of injections is increasing, and many injections lack relevant combination information. It is still a significant need for experienced clinical pharmacists to participate in evidence-based drug decision making, monitor medication safety, and manage drug interactions. Meanwhile, a large number of injection pairs and dosage combinations limit exhaustive screening. Here, we present a prediction framework, called DeepIDC, that can expediently screen the feasibility of IDCs using heterogeneous information with deep learning. This is the first specific prediction framework to identify IDCs.

METHODS

Since the interaction between the injected drugs may occur in the direct physical and chemical reactions at the time of mixing or may be the indirect interaction of their drug targets and pathways, we used molecular fingerprints, drug-target associations, and drug-pathway associations to convert injections into a string of digital vectors. Then, based on these injection vectors, we combined a bidirectional long short-term memory and a feed-forward neural network to build a prediction model for accurate and instructive prediction of IDC.

RESULTS

In three realistic evaluation scenarios, DeepIDC has achieved ideal prediction results. Furthermore, compared with the other five machine-learning methods, the proposed predictor is more efficient and robust. Among the top 30 potential IDCs of each IDC class predicted by DeepIDC, we found that 9 cases were experimentally verified in the literature or available on Drug.com.

CONCLUSION

The information we extracted in vivo and in vitro can effectively characterize injectable drugs. DeepIDC developed based on deep learning algorithm provides a valuable unified framework for new IDC discovery, which can make up for the lack of IDC information and predict potential IDC events.

KOPI: Kinase inhibitOr Proteome Impact analysis

Kinase inhibitors often exert on/off-target effects, and efficient data analysis is essential for assessing these effects on the proteome. We developed a workflow for rapidly performing such a proteomic assessment, termed as kinase inhibitor proteome impact analysis (KOPI). We demonstrate KOPI’s utility with staurosporine (STS) on the leukemic K562 cell proteome. We identified systematically staurosporine’s non-kinome interactors, and showed for the first time that it caused paradoxical hyper- and biphasic phosphorylation.

BRD4 Degradation Blocks Expression of MYC and Multiple Forms of Stem Cell Resistance in Ph+ Chronic Myeloid Leukemia

In most patients with chronic myeloid leukemia (CML) clonal cells can be kept under control by BCR::ABL1 tyrosine kinase inhibitors (TKI). However, overt resistance or intolerance against these TKI may occur. We identified the epigenetic reader BRD4 and its downstream‐effector MYC as growth regulators and therapeutic targets in CML cells. BRD4 and MYC were found to be expressed in primary CML cells, CD34⁺/CD38⁻ leukemic stem cells (LSC), and in the CML cell lines KU812, K562, KCL22, and KCL22^T315I. The BRD4‐targeting drug JQ1 was found to suppress proliferation in KU812 cells and primary leukemic cells in the majority of patients with chronic phase CML. In the blast phase of CML, JQ1 was less effective. However, the BRD4 degrader dBET6 was found to block proliferation and/or survival of primary CML cells in all patients tested, including blast phase CML and CML cells exhibiting the T315I variant of BCR::ABL1. Moreover, dBET6 was found to block MYC expression and to synergize with BCR::ABL1 TKI in inhibiting the proliferation in the JQ1‐resistant cell line K562. Furthermore, BRD4 degradation was found to overcome osteoblast‐induced TKI resistance of CML LSC in a co‐culture system and to block interferon‐gamma‐induced upregulation of the checkpoint antigen PD‐L1 in LSC. Finally, dBET6 was found to suppress the in vitro survival of CML LSC and their engraftment in NSG mice. Together, targeting of BRD4 and MYC through BET degradation sensitizes CML cells against BCR::ABL1 TKI and is a potent approach to overcome multiple forms of drug resistance in CML LSC.

Kinase-targeting small-molecule inhibitors and emerging bifunctional molecules

Kinases are among the most successful drug targets. To date, 72 small-molecule kinase inhibitors (SMKIs) have been approved by the US FDA, together with ~500 SMKIs in clinical trials. Although the topic has been heavily reviewed in recent years, an overview that focused on the currently approved SMKIs in combination with the emerging kinase-targeting bifunctional molecules is absent. Herein, we first provide an updated overview of the approved SMKIs, with an emphasis on their binding modes, classified in groups of type I and II ATP-competitive inhibitors, type III and IV allosteric inhibitors, and covalent inhibitors. We then highlight the novel chemical modalities in kinase targeting by using different types of proximity-inducing bifunctional molecules for kinase degradation and modifications.

A network embedding framework based on integrating multiplex network for drug combination prediction

Drug combination is a sensible strategy for disease treatment because it improves the treatment efficacy and reduces concomitant side effects. Due to the large number of possible combinations among candidate compounds, exhaustive screening is prohibitive. Currently, a large number of studies have focused on predicting potential drug combinations. However, these methods are not entirely satisfactory in terms of performance and scalability. In this paper, we proposed a Network Embedding frameWork in MultIplex Network (NEWMIN) to predict synthetic drug combinations. Based on a multiplex drug similarity network, we offered alternative methods to integrate useful information from different aspects and to decide the quantitative importance of each network. For drug combination prediction, we found seven novel drug combinations that have been validated by external sources among the top-ranked predictions of our model. To verify the feasibility of NEWMIN, we compared NEWMIN with other five methods, for which it showed better performance than other methods in terms of the area under the precision-recall curve and receiver operating characteristic curve.

Rational discovery of molecular glue degraders via scalable chemical profiling

Targeted protein degradation is a new therapeutic modality based on drugs that destabilize proteins by inducing their proximity to E3 ubiquitin ligases. Of particular interest are molecular glues that can degrade otherwise unligandable proteins by orchestrating direct interactions between target and ligase. However, their discovery has so far been serendipitous, thus hampering broad translational efforts. Here, we describe a scalable strategy toward glue degrader discovery that is based on chemical screening in hyponeddylated cells coupled to a multi-omics target deconvolution campaign. This approach led us to identify compounds that induce ubiquitination and degradation of cyclin K by prompting an interaction of CDK12-cyclin K with a CRL4B ligase complex. Notably, this interaction is independent of a dedicated substrate receptor, thus functionally segregating this mechanism from all described degraders. Collectively, our data outline a versatile and broadly applicable strategy to identify degraders with nonobvious mechanisms and thus empower future drug discovery efforts.

HEXIM1 controls P-TEFb processing and regulates drug sensitivity in triple-negative breast cancer

The positive transcription elongation factor b (P-TEFb), composed of CDK9 and cyclin T, stimulates transcriptional elongation by RNA polymerase (Pol) II and regulates cell growth and differentiation. Recently, we demonstrated that P-TEFb also controls the expression of EMT regulators to promote breast cancer progression. In the nucleus, more than half of P-TEFb are sequestered in the inactive-state 7SK snRNP complex. Here, we show that the assembly of the 7SK snRNP is preceded by an intermediate complex between HEXIM1 and P-TEFb that allows transfer of the kinase active P-TEFb from Hsp90 to 7SK snRNP for its suppression. Down-regulation of HEXIM1 locks P-TEFb in the Hsp90 complex, keeping it in the active state to enhance breast cancer progression, but also rendering the cells highly sensitive to Hsp90 inhibition. Because HEXIM1 is often down-regulated in human triple-negative breast cancer (TNBC), these cells are particularly sensitive to Hsp90 inhibition. Our study provides a mechanistic explanation for the increased sensitivity of TNBC to Hsp90 inhibition.

Predicting drug synergy for precision medicine using network biology and machine learning

Identification of effective drug combinations for patients is an expensive and time-consuming procedure, especially for in vitro experiments. To accelerate the synergistic drug discovery process, we present a new classification model to identify more effective anti-cancer drug pairs using in silico network biology approach. Based on the hypotheses that the drug synergy comes from the collective effects on the biological network, therefore, we developed six network biology features, including overlap and distance of drug perturbation network, that were derived by using individual drug-perturbed transcriptome profiles and the relevant biological network analysis. Using publicly available drug synergy databases and three machine-learning (ML) methods, the model was trained to discriminate the positive (synergistic) and negative (nonsynergistic) drug combinations. The proposed models were evaluated on the test cases to predict the most promising network biology feature, which is the network degree activity, i.e. the synergistic effect between drug pairs is mainly accounted by the complementary signaling pathways or molecular networks from two drugs.

Bromodomain-Containing Protein BRD4 Is Hyperphosphorylated in Mitosis

The epigenetic reader BRD4 binds acetylated histones and plays a central role in controlling cellular gene transcription and proliferation. Dysregulation of BRD4's activity has been implicated in the pathogenesis of a wide variety of cancers. While blocking BRD4 interaction with acetylated histones using BET inhibitors (BETis) has been tested in clinical trials, many cancers have acquired BETi resistance. However, the underlying mechanisms are poorly understood and BETi resistance remains a pressing clinical problem. We previously showed that BRD4 phosphorylation supports stronger chromatin binding and target oncogene expression. In this study, we discovered that BRD4 is hyperphosphorylated by CDK1 during mitosis and determined the major CDK1 phosphorylation sites in BRD4. Using CRISPR/Cas9 gene editing, we replaced endogenous BRD4 with a non-phosphorylatable mutant and demonstrated that CDK1-mediated BRD4 phosphorylation contributes to BETi resistance. CDK1 over-activation frequently observed in cancers has the potential to cause aberrant BRD4 hyperphosphorylation persisting outside of mitosis to strengthen its target gene binding and confer BETi resistance. We found that dual CDK1 and BET inhibition generates a synergistic effect in killing BETi-resistant cancer cells. Our study therefore suggests that CDK1 inhibition can be employed to overcome tumor BETi resistance and improve treatments for BRD4-associated cancers.

Turning liabilities into opportunities: Off-target based drug repurposing in cancer

Targeted drugs and precision medicine have transformed the landscape of cancer therapy and significantly improved patient outcomes in many cases. However, as therapies are becoming more and more tailored to smaller patient populations and acquired resistance is limiting the duration of clinical responses, there is an ever increasing demand for new drugs, which is not easily met considering steadily rising drug attrition rates and development costs. Considering these challenges drug repurposing is an attractive complementary approach to traditional drug discovery that can satisfy some of these needs. This is facilitated by the fact that most targeted drugs, despite their implicit connotation, are not singularly specific, but rather display a wide spectrum of target selectivity. Importantly, some of the unintended drug "off-targets" are known anticancer targets in their own right. Others are becoming recognized as such in the process of elucidating off-target mechanisms that in fact are responsible for a drug's anticancer activity, thereby revealing potentially new cancer vulnerabilities. Harnessing such beneficial off-target effects can therefore lead to novel and promising precision medicine approaches. Here, we will discuss experimental and computational methods that are employed to specifically develop single target and network-based off-target repurposing strategies, for instance with drug combinations or polypharmacology drugs. By illustrating concrete examples that have led to clinical translation we will furthermore examine the various scientific and non-scientific factors that cumulatively determine the success of these efforts and thus can inform the future development of new and potentially lifesaving off-target based drug repurposing strategies for cancers that constitute important unmet medical needs.

Colorectal Cancer Growth Retardation through Induction of Apoptosis, Using an Optimized Synergistic Cocktail of Axitinib, Erlotinib, and Dasatinib

Patients with advanced colorectal cancer (CRC) still depend on chemotherapy regimens that are associated with significant limitations, including resistance and toxicity. The contribution of tyrosine kinase inhibitors (TKIs) to the prolongation of survival in these patients is limited, hampering clinical implementation. It is suggested that an optimal combination of appropriate TKIs can outperform treatment strategies that contain chemotherapy. We have previously identified a strongly synergistic drug combination (SDC), consisting of axitinib, erlotinib, and dasatinib that is active in renal cell carcinoma cells. In this study, we investigated the activity of this SDC in different CRC cell lines (SW620, HT29, and DLD-1) in more detail. SDC treatment significantly and synergistically decreased cell metabolic activity and induced apoptosis. The translation of the in-vitro-based results to in vivo conditions revealed significant CRC tumor growth inhibition, as evaluated in the chicken chorioallantoic membrane (CAM) model. Phosphoproteomics analysis of the tested cell lines revealed expression profiles that explained the observed activity. In conclusion, we demonstrate promising activity of an optimized mixture of axitinib, erlotinib, and dasatinib in CRC cells, and suggest further translational development of this drug mixture.

Tyr1 phosphorylation promotes phosphorylation of Ser2 on the C-terminal domain of eukaryotic RNA polymerase II by P-TEFb

The Positive Transcription Elongation Factor b (P-TEFb) phosphorylates Ser2 residues of the C-terminal domain (CTD) of the largest subunit (RPB1) of RNA polymerase II and is essential for the transition from transcription initiation to elongation in vivo. Surprisingly, P-TEFb exhibits Ser5 phosphorylation activity in vitro. The mechanism garnering Ser2 specificity to P-TEFb remains elusive and hinders understanding of the transition from transcription initiation to elongation. Through in vitro reconstruction of CTD phosphorylation, mass spectrometry analysis, and chromatin immunoprecipitation sequencing (ChIP-seq) analysis, we uncover a mechanism by which Tyr1 phosphorylation directs the kinase activity of P-TEFb and alters its specificity from Ser5 to Ser2. The loss of Tyr1 phosphorylation causes an accumulation of RNA polymerase II in the promoter region as detected by ChIP-seq. We demonstrate the ability of Tyr1 phosphorylation to generate a heterogeneous CTD modification landscape that expands the CTD’s coding potential. These findings provide direct experimental evidence for a combinatorial CTD phosphorylation code wherein previously installed modifications direct the identity and abundance of subsequent coding events by influencing the behavior of downstream enzymes.

DNA contains the instructions for making proteins, which build and maintain our cells. So that the information encoded in DNA can be used, a molecular machine called RNA polymerase II makes copies of specific genes. These copies, in the form of a molecule called RNA, convey the instructions for making proteins to the rest of the cell.

To ensure that RNA polymerase II copies the correct genes at the correct time, a group of regulatory proteins are needed to control its activity. Many of these proteins interact with RNA polymerase II at a region known as the C-terminal domain, or CTD for short. For example, before RNA polymerase can make a full copy of a gene, a small molecule called a phosphate group must first be added to CTD at specific units known as Ser2.

The regulatory protein P-TEFb was thought to be responsible for phosphorylating Ser2. However, it was previously not known how P-TEFb added this phosphate group, and why it did not also add phosphate groups to other positions in the CTD domain that are structurally similar to Ser2.

To investigate this, Mayfield, Irani et al. mixed the CTD domain with different regulatory proteins, and used various biochemical approaches to examine which specific positions of the domain had phosphate groups attached. These experiments revealed a previously unknown aspect of P-TEFb activity: its specificity for Ser2 increased dramatically if a different regulatory protein first added a phosphate group to a nearby location in CTD. This additional phosphate group directed P-TEFb to then add its phosphate specifically at Ser2.

To confirm the activity of this mechanism in living human cells, Mayfield, Irani et al. used a drug that prevented the first phosphate from being added. In the drug treated cells, RNA polymerase II was found more frequently ‘stalled’ at positions on the DNA just before a gene starts. This suggests that living cells needs this two-phosphate code system in order for RNA polymerase II to progress and make copies of specific genes.

These results are a step forward in understanding the complex control mechanisms cells use to make proteins from their DNA. Moreover, the model presented here – one phosphate addition priming a second specific phosphate addition – provides a template that may underlie similar regulatory processes.

Divergent Polypharmacology-Driven Cellular Activity of Structurally Similar Multi-Kinase Inhibitors through Cumulative Effects on Individual Targets

Despite recent successes of precision and immunotherapies there is a persisting need for novel targeted or multi-targeted approaches in complex diseases. Through a systems pharmacology approach, including phenotypic screening, chemical and phosphoproteomics, and RNA-seq, we elucidated the targets and mechanisms underlying the differential anticancer activity of two structurally related multi-kinase inhibitors, foretinib, and cabozantinib, in lung cancer cells. Biochemical and cellular target validation using probe molecules and RNAi revealed a polypharmacology mechanism involving MEK1/2, FER, and AURKB, which were each more potently inhibited by foretinib than cabozantinib. Based on this, we developed a synergistic combination of foretinib with barasertib, a more potent AURKB inhibitor, for MYC-amplified small-cell lung cancer. This systems pharmacology approach showed that small structural changes of drugs can cumulatively, through multiple targets, result in pronounced anticancer activity differences and that detailed mechanistic understanding of polypharmacology can enable repurposing opportunities for cancers with unmet medical need.

The Combination of the CIGB-300 Anticancer Peptide and Cisplatin Modulates Proteins Related to Cell Survival, DNA Repair and Metastasis in a Lung Cancer Cell Line Model

Background:

CIGB-300 is a pro-apoptotic peptide that abrogates CK2-mediated phosphorylation, and can elicit synergistic interaction in vitro and in vivo when combined with certain anticancer drugs.

Objective:

The combination of CIGB-300 with cisplatin is studied through data mining and expressionbased proteomics to reveal the molecular basis of this interaction. Cisplatin resistance-associated proteins, which have also been reported as CK2 substrates, were first identified by bioinformatic analyses.

Methods:

Data from these analyses suggested that the cisplatin resistance phenotype could be directly improved by inhibiting CK2 phosphorylation on specific substrates. Furthermore, 157 proteins were differentially modulated on the NCI-H125 lung cancer cell line in response to CIGB-300, cisplatin or both drugs as determined by LC-MS/MS.

Results:

The expression of 28 cisplatin resistance-associated proteins was changed when cisplatin was combined with CIGB-300. Overall, the proteins identified are also related to cell survival, cell proliferation and metastasis. Furthermore, the CIGB-300 regulated proteome revealed proteins that were initially involved in the mechanism of action of CIGB-300 and cisplatin as single agents.

Conclusion:

This is the first report describing the protein array modulated by combining CIGB-300 and cisplatin that will support the rationale for future clinical settings based on a multi-target cancer therapy.

In Silico Target Prediction for Small Molecules

Drugs modulate disease states through their actions on targets in the body. Determining these targets aids the focused development of new treatments, and helps to better characterize those already employed. One means of accomplishing this is through the deployment of in silico methodologies, harnessing computational analytical and predictive power to produce educated hypotheses for experimental verification. Here, we provide an overview of the current state of the art, describe some of the well-established methods in detail, and reflect on how they, and emerging technologies promoting the incorporation of complex and heterogeneous data-sets, can be employed to improve our understanding of (poly)pharmacology.

Interactive visual analysis of drug–target interaction networks using Drug Target Profiler, with applications to precision medicine and drug repurposing

Knowledge of the full target space of drugs (or drug-like compounds) provides important insights into the potential therapeutic use of the agents to modulate or avoid their various on- and off-targets in drug discovery and precision medicine. However, there is a lack of consolidated databases and associated data exploration tools that allow for systematic profiling of drug target-binding potencies of both approved and investigational agents using a network-centric approach. We recently initiated a community-driven platform, Drug Target Commons (DTC), which is an open-data crowdsourcing platform designed to improve the management, reproducibility and extended use of compound-target bioactivity data for drug discovery and repurposing, as well as target identification applications. In this work, we demonstrate an integrated use of the rich bioactivity data from DTC and related drug databases using Drug Target Profiler (DTP), an open-source software and web tool for interactive exploration of drug-target interaction networks. DTP was designed for network-centric modeling of mode-of-action of multi-targeting anticancer compounds, especially for precision oncology applications. DTP enables users to construct an interaction network based on integrated bioactivity data across selected chemical compounds and their protein targets, further customizable using various visualization and filtering options, as well as cross-links to several drug and protein databases to provide comprehensive information of the network nodes and interactions. We demonstrate here the operation of the DTP tool and its unique features by several use cases related to both drug discovery and drug repurposing applications, using examples of anticancer drugs with shared target profiles. DTP is freely accessible at http://drugtargetprofiler.fimm.fi/.

Development of Fangjiomics for Systems Elucidation of Synergistic Mechanism Underlying Combination Therapy

The rapid development of omics technology provides an opportunity for fulfilling the understanding of the synergistic mechanism of combination therapy. However, a systems theory to analyze synergy remains an ongoing challenge. Fangjiomics is a novel systems science based on a holistic theory integrated with reductionism which has been utilized to systematically elucidate the synergistic mechanisms underlying combination therapy using multi-target-, pathway- or network-based quantitative methods. Besides, our ability to understand the polyhierarchical structure in synergy is driven based on multi-level omics data fusion in Fangjiomics. According to the basic principle of “Jun-Chen-Zuo-Shi”, further global integration across various omics platforms and phenotype-driven quantitative multi-scale modeling would accelerate development in Fangjiomics-based dissection of synergy in multi-drug combination therapies.

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Fangjiomics is a novel systems science based on a holistic theory integrated with reductionism.

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We developed the pathway-based analysis of synergistic mechanisms in Fangjiomics.

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The theory of network-based synergistic targets is proposed in Fangjiomics.

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The hierarchical relationship of synergy in multilevel omics is dissected in Fangjiomics.

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The principle of “Jun-Chen-Zuo-Shi” is proposed to accelerate the development in Fangjiomics-based dissection of synergy.

Molecular dynamics simulations provide insights into the origin of gleevec's selectivity toward human tyrosine kinases

Protein kinases are critical drug targets against cancer. Since the discovery of Gleevec, a specific inhibitor of Abl kinase, the capability of this drug to distinguish between Abl and other tyrosine kinases, such as Src, has been intensely investigated but the origin of Gleevec's selectivity to Abl against Src is less studied. Here, we performed molecular dynamics (MD) simulations, dynamical cross-correlation matrices (DCCM), dynamical network analysis, and binding free energy calculations to explore Gleevec's selectivity based on the crystal structures of Abl, Src, and their common ancestors (ANC-AS) and the two constructed mutation systems (AS→Abl and AS→Src). MD simulations revealed that the conformation of the phosphate-binding loop (P-loop) was altered significantly in the AS→Abl system. DCCM results unraveled that mutations increased anticorrelated motions in the AS→Abl system. Community network analysis suggested that the P-loop established special contacts in the AS→Abl system that are devoid in the AS→Src system. The binding free energy calculations unveiled that the affinity of Gleevec to AS→Abl increased to near the Abl level, whereas its affinity to AS→Src decreased to near the Src level. Analysis of individual residue contributions showed that the differences were located mainly at the P-loop. This study is valuable for understanding the sensitivity of Gleevec to human tyrosine kinases. Communicated by Ramaswamy H. Sarma.

Systems Pharmacology: Defining the Interactions of Drug Combinations

The majority of diseases are associated with alterations in multiple molecular pathways and complex interactions at the cellular and organ levels. Single-target monotherapies therefore have intrinsic limitations with respect to their maximum therapeutic benefits. The potential of combination drug therapies has received interest for the treatment of many diseases and is well established in some areas, such as oncology. Combination drug treatments may allow us to identify synergistic drug effects, reduce adverse drug reactions, and address variability in disease characteristics between patients. Identification of combination therapies remains challenging. We discuss current state-of-the-art systems pharmacology approaches to enable rational identification of combination therapies. These approaches, which include characterization of mechanisms of disease and drug action at a systems level, can enable understanding of drug interactions at the molecular, cellular, physiological, and organismal levels. Such multiscale understanding can enable precision medicine by promoting the rational development of combination therapy at the level of individual patients for many diseases.

Analysis of Cellular Tyrosine Phosphorylation via Chemical Rescue of Conditionally Active Abl Kinase

Identifying direct substrates targeted by protein kinases is important in understanding cellular physiology and intracellular signal transduction. Mass spectrometry-based quantitative proteomics provides a powerful tool for comprehensively characterizing the downstream substrates of protein kinases. This approach is efficiently applied to receptor kinases that can be precisely, directly, and rapidly activated by some agent, such as a growth factor. However, nonreceptor tyrosine kinase Abl lacks the experimental advantage of extracellular growth factors as immediate and direct stimuli. To circumvent this limitation, we combine a chemical rescue approach with quantitative phosphoproteomics to identify targets of Abl and their phosphorylation sites with enhanced temporal resolution. Both known and novel putative substrates are identified, presenting opportunities for studying unanticipated functions of Abl under physiological and pathological conditions.

Identification of WEE1 as a target to make AKT inhibition more effective in melanoma

AKT3 is one of the major therapeutic targets in melanoma but clinically targeting AKT3 alone seems to be an ineffective therapeutic approach. To identify unique strategies to enhance the efficacy of targeting AKT3, a screen was undertaken where AKT3 was co-targeted with a panel of kinases important in melanoma development. The screen identified WEE1 as the most potent target that when inhibited along with AKT3 would enhance the efficacy of targeting AKT3 in melanoma. RNAi mediated inhibition of AKT3 and WEE1 synergistically inhibited the viability of melanoma cells leading to a 65-75% decrease in tumor development. This approach was effective by mechanistically modulating pathways associated with the transcription factors p53 and FOXM1. Simultaneously regulating the activity of these two transcriptionally driven pathways, cooperatively deregulated cell cycle control and DNA damage repair to synergistically kill melanoma cells. This study uniquely identifies a potential approach to improve the efficacy of targeting AKT3 in melanoma.

CAR-T cells and combination therapies: What's next in the immunotherapy revolution?

Cancer immunotherapies are dramatically reshaping the clinical management of oncologic patients. For many of these therapies, the guidelines for administration, monitoring, and management of associated toxicities are still being established. This is especially relevant for adoptively transferred, genetically-modified T cells, which have unique pharmacokinetic properties, due to their ability to replicate and persist long-term, following a single administration. Furthermore, in the case of CAR-T cells, the use of synthetic immune receptors may impact signaling pathways involved in T cell function and survival in unexpected ways. We, herein, comment on the most salient aspects of CAR-T cell design and clinical experience in the treatment of solid tumors. In addition, we discuss different possible scenarios for combinations of CAR-T cells and other treatment modalities, with a special emphasis on kinase inhibitors, elaborating on the strategies to maximize synergism. Finally, we discuss some of the technologies that are available to explore the molecular events governing the success of these therapies. The young fields of synthetic and systems biology are likely to be major players in the advancement of CAR-T cell therapies, providing the tools and the knowledge to engineer patients' T lymphocytes into intelligent cancer-fighting micromachines.

In silico-based screen synergistic drug combinations from herb medicines: a case using Cistanche tubulosa

Neuroinflammation is characterized by the elaborated inflammatory response repertoire of central nervous system tissue. The limitations of the current treatments for neuroinflammation are well-known side effects in the clinical trials of monotherapy. Drug combination therapies are promising strategies to overcome the compensatory mechanisms and off-target effects. However, discovery of synergistic drug combinations from herb medicines is rare. Encouraged by the successfully applied cases we move on to investigate the effective drug combinations based on system pharmacology among compounds from Cistanche tubulosa (SCHENK) R. WIGHT. Firstly, 63 potential bioactive compounds, the related 133 direct and indirect targets are screened out by Drug-likeness evaluation combined with drug targeting process. Secondly, Compound-Target network is built to acquire the data set for predicting drug combinations. We list the top 10 drug combinations which are employed by the algorithm Probability Ensemble Approach (PEA), and Compound-Target-Pathway network is then constructed by the 12 compounds of the combinations, targets, and pathways to unearth the corresponding pharmacological actions. Finally, an integrating pathway approach is developed to elucidate the therapeutic effects of the herb in different pathological features-relevant biological processes. Overall, the method may provide a productive avenue for developing drug combination therapeutics.

Quantitative phosphoproteomic analysis of acquired cancer drug resistance to pazopanib and dasatinib

Acquired drug resistance impacts the majority of patients being treated with tyrosine kinase inhibitors (TKIs) and remains a key challenge in modern anti-cancer therapy. The lack of clinically effective therapies to overcome resistance represents an unmet need. Understanding the signalling that drives drug resistance will facilitate the development of new salvage therapies to treat patients with secondary TKI resistance. In this study, we utilise mass spectrometry to characterise the global phosphoproteomic alterations that accompany the acquisition of resistance to two FDA-approved TKIs, pazopanib and dasatinib, in the A204 rhabdoid tumour cell line. Our analysis finds that only 6% and 9.7% of the quantified phosphoproteome is altered upon the acquisition of pazopanib and dasatinib resistance, respectively. Pazopanib resistant cells display elevated phosphorylation in cytoskeletal regulatory pathways while dasatinib resistant cells show an upregulation of the insulin receptor/IGF-1R signalling pathway. Drug response profiling rediscovers several previously reported vulnerabilities associated with pazopanib and dasatinib resistance and identifies a new dependency to the second generation HSP90 inhibitor NVP-AUY-922. This study provides a useful resource detailing the candidate signalling determinants of acquired TKI resistance; and reveals a therapeutic approach of inhibiting HSP90 function as a means of salvage therapy to overcome pazopanib and dasatinib resistance.

Significance

Pazopanib and dasatinib are tyrosine kinase inhibitors (TKIs) approved for the treatment of multiple cancer types. Patients who are treated with these drugs are prone to the development of drug resistance and consequently tumour relapse. Here we use quantitative phosphoproteomics to characterise the signalling pathways which are enriched in cells that have acquired resistance to these two drugs. Furthermore, targeted drug screens were used to identify salvage therapies capable of overcoming pazopanib and dasatinib resistance. This data advances our understanding of the mechanisms of TKI resistance and highlights candidate targets for cancer therapy.

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Pazopanib resistant cells display elevated phosphorylation in cytoskeletal regulatory pathways.

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Phosphoproteins in the insulin and IGF-1R pathways are upregulated in dasatinib resistant cells.

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Less than 10% of the phosphoproteome is altered in acquired drug-resistant A204 cells.

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Both dasatinib and pazopanib resistant A204 cells are vulnerable to HSP90 inhibition.

Defining a therapeutic window for kinase inhibitors in leukemia to avoid neutropenia

Neutropenia represents one of the major dose-limiting toxicities of many current cancer therapies. To circumvent the off-target effects of cytotoxic chemotherapeutics, kinase inhibitors are increasingly being used as an adjunct therapy to target leukemia. In this study, we conducted a screen of leukemic cell lines in parallel with primary neutrophils to identify kinase inhibitors with the capacity to induce apoptosis of myeloid and lymphoid cell lines whilst sparing primary mouse and human neutrophils. We have utilized a high-throughput live cell imaging platform to demonstrate that cytotoxic drugs have limited effects on neutrophil viability but are toxic to hematopoietic progenitor cells, with the exception of the topoisomerase I inhibitor SN-38. The parallel screening of kinase inhibitors revealed that mouse and human neutrophil viability is dependent on cyclin-dependent kinase (CDK) activity but surprisingly only partially dependent on PI3 kinase and JAK/STAT signaling, revealing dominant pathways contributing to neutrophil viability. Mcl-1 haploinsufficiency sensitized neutrophils to CDK inhibition, demonstrating that Mcl-1 is a direct target for CDK inhibitors. This study reveals a therapeutic window for the kinase inhibitors BEZ235, BMS-3, AZD7762, and (R)-BI-2536 to induce apoptosis of leukemia cell lines whilst maintaining immunocompetence and hemostasis.

Long-term outcomes of dasatinib-induced pulmonary arterial hypertension: a population-based study

This study aimed to describe the long-term outcomes of pulmonary arterial hypertension (PAH) induced by dasatinib.

21 incident, right heart catheterisation-confirmed cases of dasatinib-induced PAH were identified from the French Pulmonary Hypertension Registry. Clinical and haemodynamic variables were compared from baseline to last follow-up (median (range) 24 (1–81) months).

Median age was 52 years and 15 patients were female (71%). 19 patients received dasatinib for chronic myelogenous leukaemia for a median (range) duration of 42 (8–74) months before PAH diagnosis. No bone morphogenic protein receptor-2 (BMPR2) mutations were found in the 10 patients tested. Dasatinib was uniformly discontinued and 11 patients received PAH medications. Four patients died during follow-up. New York Heart Association functional class improved from 76% in class III/IV to 90% in class I/II (p<0.01). Median (range) 6-min walk distance improved from 306 (0–660) to 430 (165–635) m (p<0.01). Median (range) mean pulmonary arterial pressure improved from 45 (30–70) to 26 (17–50) mmHg (p<0.01) and pulmonary vascular resistance from 6.1 (3.2–27.3) to 2.6 (1.2–5.9) Wood units (p<0.01). Patients treated with PAH medications had worse baseline haemodynamics but similar long-term outcomes to untreated patients. PAH persisted in 37% of patients.

Dasatinib-induced PAH frequently improves after discontinuation but persisted in over one-third of patients, therefore systematic follow-up is essential.

Dual Targeting of WEE1 and PLK1 by AZD1775 Elicits Single Agent Cellular Anticancer Activity

Inhibition of the WEE1 tyrosine kinase enhances anticancer chemotherapy efficacy. Accordingly, the WEE1 inhibitor AZD1775 (previously MK-1775) is currently under evaluation in clinical trials for cancer in combination with chemotherapy. AZD1775 has been reported to display high selectivity and is therefore used in many studies as a probe to interrogate WEE1 biology. However, AZD1775 also exhibits anticancer activity as a single agent although the underlying mechanism is not fully understood. Using a chemical proteomics approach, we here describe a proteome-wide survey of AZD1775 targets in lung cancer cells and identify several previously unknown targets in addition to WEE1. In particular, we observed polo-like kinase 1 (PLK1) as a new target of AZD1775. Importantly, in vitro kinase assays showed PLK1 and WEE1 to be inhibited by AZD1775 with similar potency. Subsequent loss-of-function experiments using RNAi for WEE1 and PLK1 suggested that targeting PLK1 enhances the pro-apoptotic and antiproliferative effects observed with WEE1 knockdown. Combination of RNAi with AZD1775 treatment suggested WEE1 and PLK1 to be the most relevant targets for mediating AZD1775's anticancer effects. Furthermore, disruption of WEE1 by CRISPR-Cas9 sensitized H322 lung cancer cells to AZD1775 to a similar extent as the potent PLK1 inhibitor BI-2536 suggesting a complex crosstalk between PLK1 and WEE1. In summary, we show that AZD1775 is a potent dual WEE1 and PLK1 inhibitor, which limits its use as a specific molecular probe for WEE1. However, PLK1 inhibition makes important contributions to the single agent mechanism of action of AZD1775 and enhances its anticancer effects.

Improving pharmacological targeting of AKT in melanoma

Targeting AKT with pharmacological agents inhibiting this protein in the melanoma clinic is ineffective. This is a major contradiction considering the substantial preclinical data suggesting AKT as an effective target. Various approaches have been undertaken to unravel this contradiction and drug combinations sought that could resolve this concern. We have shown that genetic targeting AKT3 or WEE1 can be effective for inhibiting tumor growth in preclinical animal models. However, no one has examined whether combining pharmacological agents targeting each of these enzymes could be more effective than inhibiting each alone and enhance the efficacy of targeting AKT in melanoma. This report shows that combining the AKT inhibitors (AZD5363 or MK1775) with the WEE1 inhibitor, AZD5363, can synergistically kill cultured melanoma cells and decrease melanoma tumor growth by greater than 90%. Co-targeting AKT and WEE1 led to enhanced deregulation of the cell cycle and DNA damage repair pathways by modulating the transcription factors p53 and FOXM1, as well as the proteins whose expression is regulated by these two proteins. Thus, this study identifies a unique combination of pharmacological agents and the ratio needed for efficacy that could be used to potentially improve the therapeutic effectiveness of targeting AKT in the clinic.

Promoting active learning of graduate student by deep reading in biochemistry and microbiology pharmacy curriculum

To promote graduate students' active learning, deep reading of high quality papers was done by graduate students enrolled in biochemistry and microbiology pharmacy curriculum offered by college of life science, Jiangxi Normal University from 2013 to 2015. The number of graduate students, who participated in the course in 2013, 2014, and 2015 were eleven, thirteen and fifteen, respectively. Through deep reading of papers, presentation, and group discussion in the lecture, these graduate students have improved their academic performances effectively, such as literature search, PPT document production, presentation management, specialty document reading, academic inquiry, and analytical and comprehensive ability. The graduate students also have increased their understanding level of frontier research, scientific research methods, and experimental methods. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):305-312, 2017.

MTI-101 treatment inducing activation of Stim1 and TRPC1 expression is a determinant of response in multiple myeloma

The emergence of drug resistance continues to be a major hurdle towards improving patient outcomes for the treatment of Multiple Myeloma. MTI-101 is a first-in-class peptidomimetic that binds a CD44/ITGA4 containing complex and triggers necrotic cell death in multiple myeloma cell lines. In this report, we show that acquisition of resistance to MTI-101 correlates with changes in expression of genes predicted to attenuate Ca²⁺ flux. Consistent with the acquired resistant genotype, MTI-101 treatment induces a rapid and robust increase in intracellular Ca²⁺ levels in the parental cells; a finding that was attenuated in the acquired drug resistant cell line. Mechanistically, we show that pharmacological inhibition of store operated channels or reduction in the expression of a component of the store operated Ca²⁺ channel, TRPC1 blocks MTI-101 induced cell death. Importantly, MTI-101 is more potent in specimens obtained from relapsed myeloma patients, suggesting that relapse may occur at a cost for increased sensitivity to Ca²⁺ overload mediated cell death. Finally, we demonstrate that MTI-101 is synergistic when combined with bortezomib, using both myeloma cell lines and primary myeloma patient specimens. Together, these data continue to support the development of this novel class of compounds for the treatment of relapsed myeloma.

Global survey of the immunomodulatory potential of common drugs

Small-molecule drugs may complement antibody-based therapies in an immune-oncology setting, yet systematic methods for the identification and characterization of the immunomodulatory properties of these entities are lacking. We surveyed the immumomodulatory potential of 1,402 small chemical molecules, as defined by their ability to alter the cell-cell interactions among peripheral mononuclear leukocytes ex vivo, using automated microscopy and population-wide single-cell image analysis. Unexpectedly, ∼10% of the agents tested affected these cell-cell interactions differentially. The results accurately recapitulated known immunomodulatory drug classes and revealed several clinically approved drugs that unexpectedly harbor the ability to modulate the immune system, which could potentially contribute to their physiological mechanism of action. For instance, the kinase inhibitor crizotinib promoted T cell interactions with monocytes, as well as with cancer cells, through inhibition of the receptor tyrosine kinase MSTR1 and subsequent upregulation of the expression of major histocompatibility complex molecules. The approach offers an attractive platform for the personalized identification and characterization of immunomodulatory therapeutics.

The molecular basis for RET tyrosine-kinase inhibitors in thyroid cancer

RET receptor tyrosine kinase acts as a mutated oncogenic driver in several human malignancies and it is over-expressed in other cancers. Small molecule compounds with RET tyrosine kinase inhibitory activity are being investigated for the targeted treatment of these malignancies. Multi-targeted compounds with RET inhibitory concentration in the nanomolar range have entered clinical practice. This review summarizes mechanisms of RET oncogenic activity and properties of new compounds that, at the preclinical stage, have demonstrated promising anti-RET activity.

Huang J, Cooper MA, Li J, Velkov T. The Plasma Protein Binding Proteome of Ertapenem: A Novel Compound-Centric Proteomic Approach for Elucidating Drug-Plasma Protein Binding Interactions

Ertapenem is an important first-line carbapenem antibiotic used for the treatment of aerobic Gram-negative bacterial infections. It is the only marketed carbapenem that is highly bound to plasma proteins and displays a concentration-dependent and saturable plasma protein binding profile. To date, the plasma components responsible for sequestering ertapenems antibacterial activity remain uncharacterized. In the present study, we have employed an orthogonal, multiplatform approach, including novel compound-centric displacement proteomics and surface plasmon resonance to characterize the plasma protein binding proteome of ertapenem. In proof-of-concept, the capacity of physiological cocktails of the identified plasma proteins to inhibit the antibacterial activity of ertapenem was assessed with in vitro microbiological assays. We show that fibrinogen, complement C4, haptoglobulin, α-1-antitrypsin, fibronectin, transferrin, immunoglobulin G, hemopexin, and humans serum albumin are responsible for the majority of the sequestering activity in plasma. No binding was observed to α-1-acid-glycoprotein. The findings of this study have broad reaching implications for antibiotic drug design and for dose tailoring to suit the plasma protein levels of individual patients in order to maximize the clinical efficacy of important first-line antibiotics such as ertapenem.

Effect assessment of engineered nanoparticles in solid media - Current insight and the way forward

Engineered Nanoparticles (ENPs) present novel/added challenges to the established effect assessment modus operandi, requiring an update of used methods. ENPs are dimensionally and physically different from conventional chemicals, which imply that the metrics with which we relate effect and the type of effect responses are different from that of the conventional approach. Effects on organisms are often preceded by changes on the sub-organismal level (cell, genes), dedicated tools have vast potential to detect earlier (and link to) effects on higher levels of organization. High-throughput screening (HTS) is rapid, cost-effective and specific. One way forward is to link HTS to population outcomes, targeting a systems toxicology approach. Although the benefits of integrating various levels of information may seem obvious, this is an even more decisive aspect when rapid answers are needed for ENPs. Here we rank the available tools/methods, highlight main study gaps and list priority needs and the way forward.

7SK small nuclear RNA transcription level down-regulates in human tumors and stem cells

The small nuclear noncoding RNA (snRNA) 7SK is a highly conserved noncoding RNA of 331 nucleotides in animals, which is present in a nuclear ribonucleoprotein complex with proteins such as methylphosphate capping enzyme (MePCE), hexamethylene bisacetamide-inducible proteins 1 and 2 (HEXIM1 and HEXIM2) and La-related protein 7 (Larp7). Regulating the activity of the positive transcription elongation factor b (P-TEFb) is the key function of 7SK noncoding RNA. Recently, we have shown that 7SK snRNA over-expression reduces human embryonic kidney 293T cell line viability. Here, we attempt to monitor the expression level of 7SK snRNA in different human cell lines and cancer tissues. Examination of 7SK transcription either in cell lines or in different malignant tissues including blood (CML), breast and colon showed that 7SK expression significantly down-regulated in cancer. Similar to human cancer tissues and cell lines, 7SK transcriptional level decreased in stem cells in comparison with differentiated cell types. In this regard, over-expression of 7SK snRNA might be a powerful tool for blocking cancer progression by controlling the activity of P-TEFb.

PAXIP1 Potentiates the Combination of WEE1 Inhibitor AZD1775 and Platinum Agents in Lung Cancer

The DNA damage response (DDR) involves a complex network of signaling events mediated by modular protein domains such as the BRCA1 C-terminal (BRCT) domain. Thus, proteins that interact with BRCT domains and are a part of the DDR constitute potential targets for sensitization to DNA-damaging chemotherapy agents. We performed a pharmacologic screen to evaluate 17 kinases, identified in a BRCT-mediated interaction network as targets to enhance platinum-based chemotherapy in lung cancer. Inhibition of mitotic kinase WEE1 was found to have the most effective response in combination with platinum compounds in lung cancer cell lines. In the BRCT-mediated interaction network, WEE1 was found in complex with PAXIP1, a protein containing six BRCT domains involved in transcription and in the cellular response to DNA damage. We show that PAXIP1 BRCT domains regulate WEE1-mediated phosphorylation of CDK1. Furthermore, ectopic expression of PAXIP1 promotes enhanced caspase-3-mediated apoptosis in cells treated with WEE1 inhibitor AZD1775 (formerly, MK-1775) and cisplatin compared with cells treated with AZD1775 alone. Cell lines and patient-derived xenograft models expressing both PAXIP1 and WEE1 exhibited synergistic effects of AZD1775 and cisplatin. In summary, PAXIP1 is involved in sensitizing lung cancer cells to the WEE1 inhibitor AZD1775 in combination with platinum-based treatment. We propose that WEE1 and PAXIP1 levels may be used as mechanism-based biomarkers of response when WEE1 inhibitor AZD1775 is combined with DNA-damaging agents. Mol Cancer Ther; 15(7); 1669-81. ©2016 AACR.

Dual targeting of p53 and c-MYC selectively eliminates leukaemic stem cells

Chronic myeloid leukaemia (CML) arises after transformation of a haemopoietic stem cell (HSC) by the protein-tyrosine kinase BCR-ABL. Direct inhibition of BCR-ABL kinase has revolutionized disease management, but fails to eradicate leukaemic stem cells (LSCs), which maintain CML. LSCs are independent of BCR-ABL for survival, providing a rationale for identifying and targeting kinase-independent pathways. Here we show--using proteomics, transcriptomics and network analyses--that in human LSCs, aberrantly expressed proteins, in both imatinib-responder and non-responder patients, are modulated in concert with p53 (also known as TP53) and c-MYC regulation. Perturbation of both p53 and c-MYC, and not BCR-ABL itself, leads to synergistic cell kill, differentiation, and near elimination of transplantable human LSCs in mice, while sparing normal HSCs. This unbiased systems approach targeting connected nodes exemplifies a novel precision medicine strategy providing evidence that LSCs can be eradicated.

Polypharmacology in Precision Oncology: Current Applications and Future Prospects

Over the past decade, a more comprehensive, large-scale approach to studying cancer genetics and biology has revealed the challenges of tumor heterogeneity, adaption, evolution and drug resistance, while systems-based pharmacology and chemical biology strategies have uncovered a much more complex interaction between drugs and the human proteome than was previously anticipated. In this mini-review we assess the progress and potential of drug polypharmacology in biomarker-driven precision oncology. Polypharmacology not only provides great opportunities for drug repurposing to exploit off-target effects in a new single-target indication but through simultaneous blockade of multiple targets or pathways offers exciting opportunities to slow, overcome or even prevent inherent or adaptive drug resistance. We highlight the many challenges associated with exploiting known or desired polypharmacology in drug design and development, and assess computational and experimental methods to uncover unknown polypharmacology. A comprehensive understanding of the intricate links between polypharmacology, efficacy and safety is urgently needed if we are to tackle the enduring challenge of cancer drug resistance and to fully exploit polypharmacology for the ultimate benefit of cancer patients.

Chemoproteomics Reveals Novel Protein and Lipid Kinase Targets of Clinical CDK4/6 Inhibitors in Lung Cancer

Several selective CDK4/6 inhibitors are in clinical trials for non-small cell lung cancer (NSCLC). Palbociclib (PD0332991) is included in the phase II/III Lung-MAP trial for squamous cell lung carcinoma (LUSQ). We noted differential cellular activity between palbociclib and the structurally related ribociclib (LEE011) in LUSQ cells. Applying an unbiased mass spectrometry-based chemoproteomics approach in H157 cells and primary tumor samples, we here report distinct proteome-wide target profiles of these two drug candidates in LUSQ, which encompass novel protein and, for palbociclib only, lipid kinases. In addition to CDK4 and 6, we observed CDK9 as a potent target of both drugs. Palbociclib interacted with several kinases not targeted by ribociclib, such as casein kinase 2 and PIK3R4, which regulate autophagy. Furthermore, palbociclib engaged several lipid kinases, most notably, PIK3CD and PIP4K2A/B/C. Accordingly, we observed modulation of autophagy and inhibition of AKT signaling by palbociclib but not ribociclib.

Agent-Based Modeling in Systems Pharmacology

Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent‐based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM‐specific strengths have yielded success in the area of preclinical mechanistic modeling.

Systematic synergy modeling: understanding drug synergy from a systems biology perspective

Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose–response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and “omic”-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations.

Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives

The development of treatments involving combinations of drugs is a promising approach towards combating complex or multifactorial disorders. However, the large number of compound combinations that can be generated, even from small compound collections, means that exhaustive experimental testing is infeasible. The ability to predict the behaviour of compound combinations in biological systems, whittling down the number of combinations to be tested, is therefore crucial. Here, we review the current state-of-the-art in the field of compound combination modelling, with the aim to support the development of approaches that, as we hope, will finally lead to an integration of chemical with systems-level biological information for predicting the effect of chemical mixtures.

Do we need more drugs for chronic myeloid leukemia?

The introduction of protein tyrosine kinase inhibitors (TKIs) in 1998 transformed the management of chronic myeloid leukemia (CML), leading to significantly reduced mortality and improved 5 year survival rates. However, the CML community is faced with several clinical issues that need to be addressed. Ten to 15% of CML patients are diagnosed in advanced phase, and small numbers of chronic phase (CP) cases experience disease progression each year during treatment. For these patients, TKIs induce only transient responses and alternative treatment strategies are urgently required. Depending on choice of first line TKI, approximately 30% of CML CP cases show suboptimal responses, due to a combination of poor compliance, drug intolerance, and drug resistance, with approximately 50% of TKI-resistance caused by kinase domain mutations and the remainder due to unknown mechanisms. Finally, the chance of successful treatment discontinuation is on the order of only 10-20% related to disease persistence. Disease persistence is a poorly understood phenomenon; all CML patients have functional Philadelphia positive (Ph+) stem and progenitor cells in their bone marrows and continue to express BCR-ABL1 by DNA PCR, even when in very deep remission and following treatment discontinuation. What controls the maintenance of these persisting cells, whether it is necessary to fully eradicate the malignant clone to achieve cure, and how that might be approached therapeutically are open questions.