skip to main content

Title: Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model for protein kinase inhibitor response prediction
Abstract Background Protein kinases are a large family of druggable proteins that are genomically and proteomically altered in many human cancers. Kinase-targeted drugs are emerging as promising avenues for personalized medicine because of the differential response shown by altered kinases to drug treatment in patients and cell-based assays. However, an incomplete understanding of the relationships connecting genome, proteome and drug sensitivity profiles present a major bottleneck in targeting kinases for personalized medicine. Results In this study, we propose a multi-component Quantitative Structure–Mutation–Activity Relationship Tests (QSMART) model and neural networks framework for providing explainable models of protein kinase inhibition and drug response ( $$\hbox {IC}_{50}$$ IC 50 ) profiles in cell lines. Using non-small cell lung cancer as a case study, we show that interaction terms that capture associations between drugs, pathways, and mutant kinases quantitatively contribute to the response of two EGFR inhibitors (afatinib and lapatinib). In particular, protein–protein interactions associated with the JNK apoptotic pathway, associations between lung development and axon extension, and interaction terms connecting drug substructures and the volume/charge of mutant residues at specific structural locations contribute significantly to the observed $$\hbox {IC}_{50}$$ IC 50 values in cell-based assays. Conclusions By integrating multi-omics data in the QSMART more » model, we not only predict drug responses in cancer cell lines with high accuracy but also identify features and explainable interaction terms contributing to the accuracy. Although we have tested our multi-component explainable framework on protein kinase inhibitors, it can be extended across the proteome to investigate the complex relationships connecting genotypes and drug sensitivity profiles. « less
; ; ; ; ; ; ; ;
Award ID(s):
Publication Date:
Journal Name:
BMC Bioinformatics
Sponsoring Org:
National Science Foundation
More Like this
  1. Li Fraumeni syndrome (LFS) is a hereditary cancer predisposition syndrome caused by germline mutations in TP53. TP53 is the most common mutated gene in human cancer, occurring in 30–50% of glioblastomas (GBM). Here, we highlight a precision medicine platform to identify potential targets for a GBM patient with LFS. We used a comparative transcriptomics approach to identify genes that are uniquely overexpressed in the LFS GBM patient relative to a cancer compendium of 12,747 tumor RNA sequencing data sets, including 200 GBMs. STAT1 and STAT2 were identified as being significantly overexpressed in the LFS patient, indicating ruxolitinib, a Janus kinasemore »1 and 2 inhibitors, as a potential therapy. The LFS patient had the highest level of STAT1 and STAT2 expression in an institutional high-grade glioma cohort of 45 patients, further supporting the cancer compendium results. To empirically validate the comparative transcriptomics pipeline, we used a combination of adherent and organoid cell culture techniques, including ex vivo patient-derived organoids (PDOs) from four patient-derived cell lines, including the LFS patient. STAT1 and STAT2 expression levels in the four patient-derived cells correlated with levels identified in the respective parent tumors. In both adherent and organoid cultures, cells from the LFS patient were among the most sensitive to ruxolitinib compared to patient-derived cells with lower STAT1 and STAT2 expression levels. A spheroid-based drug screening assay (3D-PREDICT) was performed and used to identify further therapeutic targets. Two targeted therapies were selected for the patient of interest and resulted in radiographic disease stability. This manuscript supports the use of comparative transcriptomics to identify personalized therapeutic targets in a functional precision medicine platform for malignant brain tumors.« less
  2. To achieve the mission of personalized medicine, centering on delivering the right drug to the right patient at the right dose, therapeutic drug monitoring solutions are necessary. In that regard, wearable biosensing technologies, capable of tracking drug pharmacokinetics in noninvasively retrievable biofluids (e.g., sweat), play a critical role, because they can be deployed at a large scale to monitor the individuals’ drug transcourse profiles (semi)continuously and longitudinally. To this end, voltammetry-based sensing modalities are suitable, as in principle they can detect and quantify electroactive drugs on the basis of the target’s redox signature. However, the target’s redox signature in complexmore »biofluid matrices can be confounded by the immediate biofouling effects and distorted/buried by the interfering voltammetric responses of endogenous electroactive species. Here, we devise a wearable voltammetric sensor development strategy—centering on engineering the molecule–surface interactions—to simultaneously mitigate biofouling and create an “undistorted potential window” within which the target drug’s voltammetric response is dominant and interference is eliminated. To inform its clinical utility, our strategy was adopted to track the temporal profile of circulating acetaminophen (a widely used analgesic and antipyretic) in saliva and sweat, using a surface-modified boron-doped diamond sensing interface (cross-validated with laboratory-based assays,R2∼ 0.94). Through integration of the engineered sensing interface within a custom-developed smartwatch, and augmentation with a dedicated analytical framework (for redox peak extraction), we realized a wearable solution to seamlessly render drug readouts with minute-level temporal resolution. Leveraging this solution, we demonstrated the pharmacokinetic correlation and significance of sweat readings.

    « less
  3. Stomatal pore apertures are narrowing globally due to the continuing rise in atmospheric [CO2]. CO2elevation and the plant hormone abscisic acid (ABA) both induce rapid stomatal closure. However, the underlying signal transduction mechanisms for CO2/ABA interaction remain unclear. Two models have been considered: (i) CO2elevation enhances ABA concentrations and/or early ABA signaling in guard cells to induce stomatal closure and (ii) CO2signaling merges with ABA at OST1/SnRK2.6 protein kinase activation. Here we use genetics, ABA-reporter imaging, stomatal conductance, patch clamp, and biochemical analyses to investigate these models. The strong ABA biosynthesis mutantsnced3/nced5andaba2-1remain responsive to CO2elevation. Rapid CO2-triggered stomatal closure inmore »PYR/RCAR ABA receptor quadruple and hextuple mutants is not disrupted but delayed. Time-resolved ABA concentration monitoring in guard cells using a FRET-based ABA-reporter, ABAleon2.15, and ABA reporter gene assays suggest that CO2elevation does not trigger [ABA] increases in guard cells, in contrast to control ABA exposures. Moreover, CO2activates guard cell S-type anion channels innced3/nced5and ABA receptor hextuple mutants. Unexpectedly, in-gel protein kinase assays show that unlike ABA, elevated CO2does not activate OST1/SnRK2 kinases in guard cells. The present study points to a model in which rapid CO2signal transduction leading to stomatal closure occurs via an ABA-independent pathway downstream of OST1/SnRK2.6. Basal ABA signaling and OST1/SnRK2 activity are required to facilitate the stomatal response to elevated CO2. These findings provide insights into the interaction between CO2/ABA signal transduction in light of the continuing rise in atmospheric [CO2].

    « less
  4. Stomatal pores close rapidly in response to low-air-humidity-induced leaf-to-air vapor pressure difference (VPD) increases, thereby reducing excessive water loss. The hydroactive signal-transduction mechanisms mediating high VPD–induced stomatal closure remain largely unknown. The kinetics of stomatal high-VPD responses were investigated by using time-resolved gas-exchange analyses of higher-order mutants in guard-cell signal-transduction branches. We show that the slow-type anion channel SLAC1 plays a relatively more substantial role than the rapid-type anion channel ALMT12/QUAC1 in stomatal VPD signaling. VPD-induced stomatal closure is not affected in mpk12 / mpk4GC double mutants that completely disrupt stomatal CO 2 signaling, indicating that VPD signaling is independentmore »of the early CO 2 signal-transduction pathway. Calcium imaging shows that osmotic stress causes cytoplasmic Ca 2+ transients in guard cells. Nevertheless, osca1-2 / 1.3 / 2.2 / 2.3 / 3.1 Ca 2+ -permeable channel quintuple, osca1.3 / 1.7 -channel double, cngc5 / 6 -channel double, cngc20 -channel single, cngc19 / 20crispr -channel double, glr3.2 / 3.3 -channel double, cpk- kinase quintuple, cbl1 / 4 / 5 / 8 / 9 quintuple, and cbl2 / 3rf double mutants showed wild-type-like stomatal VPD responses. A B3-family Raf-like mitogen-activated protein (MAP)-kinase kinase kinase, M3Kδ5/RAF6, activates the OST1/SnRK2.6 kinase in plant cells. Interestingly, B3 Raf-kinase m3kδ5 and m3kδ1 / δ5 / δ6 / δ7 ( raf3 / 6 / 5 / 4 ) quadruple mutants, but not a 14-gene raf-kinase mutant including osmotic stress-linked B4-family Raf-kinases, exhibited slowed high-VPD responses, suggesting that B3-family Raf-kinases play an important role in stomatal VPD signaling. Moreover, high VPD–induced stomatal closure was impaired in receptor-like pseudokinase GUARD CELL HYDROGEN PEROXIDE-RESISTANT1 (GHR1) mutant alleles. Notably, the classical transient “wrong-way” VPD response was absent in ghr1 mutant alleles. These findings reveal genes and signaling mechanisms in the elusive high VPD–induced stomatal closing response pathway.« less
  5. Histidine kinases (HKs) are sensor proteins found ubiquitously in prokaryotes. They are the first protein in two-component systems (TCSs), signaling pathways that respond to a myriad of environmental stimuli. TCSs are typically comprised of a HK and its cognate response regulator (RR) which often acts as a transcription factor. RRs will bind DNA and ultimately lead to a cellular response. These cellular outputs vary widely, but HKs are particularly interesting as they are tied to antibiotic resistance and virulence pathways in pathogenic bacteria, making them promising drug targets. We anticipate that HK inhibitors could serve as either standalone antibiotics ormore »antivirulence therapies. Additionally, while the cellular response mediated by the HKs is often well-characterized, very little is known about which stimuli trigger the sensor kinase to begin the phosphorylation cascade. Studying HK activity and enrichment of active HKs through activity-based protein profiling will enable these stimuli to be elucidated, filling this fundamental gap in knowledge. Here, we describe methods to evaluate the potency of putative HK inhibitors in addition to methods to calculate kinetic parameters of various activity-based probes designed for the HKs.« less