Identification of Potential Kinase Inhibitors within the PI3K/AKT Pathway of Leishmania Species.

Leishmaniasis is a public health disease that requires the development of more effective treatments and the identification of novel molecular targets. Since blocking the PI3K/AKT pathway has been successfully studied as an effective anticancer strategy for decades, we examined whether the same approach would also be feasible in Leishmania due to their high amount and diverse set of annotated proteins. Here, we used a best reciprocal hits protocol to identify potential protein kinase homologues in an annotated human PI3K/AKT pathway. We calculated their ligandibility based on available bioactivity data of the reported homologues and modelled their 3D structures to estimate the druggability of their binding pockets. The models were used to run a virtual screening method with molecular docking. We found and studied five protein kinases in five different Leishmania species, which are AKT, CDK, AMPK, mTOR and GSK3 homologues from the studied pathways. The compounds found for different enzymes and species were analysed and suggested as starting point scaffolds for the design of inhibitors. We studied the kinases' participation in protein-protein interaction networks, and the potential deleterious effects, if inhibited, were supported with the literature. In the case of Leishmania GSK3, an inhibitor of its human counterpart, prioritized by our method, was validated in vitro to test its anti-Leishmania activity and indirectly infer the presence of the enzyme in the parasite. The analysis contributes to improving the knowledge about the presence of similar signalling pathways in Leishmania, as well as the discovery of compounds acting against any of these kinases as potential molecular targets in the parasite.

Crowdsourced mapping of unexplored target space of kinase inhibitors.

Despite decades of intensive search for compounds that modulate the activity of particular protein targets, a large proportion of the human kinome remains as yet undrugged. Effective approaches are therefore required to map the massive space of unexplored compound-kinase interactions for novel and potent activities. Here, we carry out a crowdsourced benchmarking of predictive algorithms for kinase inhibitor potencies across multiple kinase families tested on unpublished bioactivity data. We find the top-performing predictions are based on various models, including kernel learning, gradient boosting and deep learning, and their ensemble leads to a predictive accuracy exceeding that of single-dose kinase activity assays. We design experiments based on the model predictions and identify unexpected activities even for under-studied kinases, thereby accelerating experimental mapping efforts. The open-source prediction algorithms together with the bioactivities between 95 compounds and 295 kinases provide a resource for benchmarking prediction algorithms and for extending the druggable kinome.

Aggregation-related quenching of LHCII fluorescence in liposomes revealed by single-molecule spectroscopy.

Incorporation of membrane proteins into reconstituted lipid membranes is a common approach for studying their structure and function relationship in a native-like environment. In this work, we investigated fluorescence properties of liposome-reconstituted major light-harvesting complexes of plants (LHCII). By utilizing liposome labelling with the fluorescent dye molecules and single-molecule microscopy techniques, we were able to study truly liposome-reconstituted LHCII and compare them with bulk measurements and liposome-free LHCII aggregates bound to the surface. Our results showed that fluorescence lifetime obtained in bulk and in single liposome measurements were correlated. The fluorescence lifetimes of LHCII were shorter for liposome-free LHCII than for reconstituted LHCII. In the case of liposome-reconstituted LHCII, fluorescence lifetime showed dependence on the protein density reminiscent to concentration quenching. The dependence of fluorescence lifetime of LHCII on the liposome size was not significant. Our results demonstrated that fluorescence quenching can be induced by LHCII - LHCII interactions in reconstituted membranes, most likely occurring via the same mechanism as photoprotective non-photochemical quenching in vivo.

A survey of the kinome pharmacopeia reveals multiple scaffolds and targets for the development of novel anthelmintics.

Over one billion people are currently infected with a parasitic nematode. Symptoms can include anemia, malnutrition, developmental delay, and in severe cases, death. Resistance is emerging to the anthelmintics currently used to treat nematode infection, prompting the need to develop new anthelmintics. Towards this end, we identified a set of kinases that may be targeted in a nematode-selective manner. We first screened 2040 inhibitors of vertebrate kinases for those that impair the model nematode Caenorhabditis elegans. By determining whether the terminal phenotype induced by each kinase inhibitor matched that of the predicted target mutant in C. elegans, we identified 17 druggable nematode kinase targets. Of these, we found that nematode EGFR, MEK1, and PLK1 kinases have diverged from vertebrates within their drug-binding pocket. For each of these targets, we identified small molecule scaffolds that may be further modified to develop nematode-selective inhibitors. Nematode EGFR, MEK1, and PLK1 therefore represent key targets for the development of new anthelmintic medicines.

Machine learning on ligand-residue interaction profiles to significantly improve binding affinity prediction.

Structure-based virtual screenings (SBVSs) play an important role in drug discovery projects. However, it is still a challenge to accurately predict the binding affinity of an arbitrary molecule binds to a drug target and prioritize top ligands from an SBVS. In this study, we developed a novel method, using ligand-residue interaction profiles (IPs) to construct machine learning (ML)-based prediction models, to significantly improve the screening performance in SBVSs. Such a kind of the prediction model is called an IP scoring function (IP-SF). We systematically investigated how to improve the performance of IP-SFs from many perspectives, including the sampling methods before interaction energy calculation and different ML algorithms. Using six drug targets with each having hundreds of known ligands, we conducted a critical evaluation on the developed IP-SFs. The IP-SFs employing a gradient boosting decision tree (GBDT) algorithm in conjunction with the MIN + GB simulation protocol achieved the best overall performance. Its scoring power, ranking power and screening power significantly outperformed the Glide SF. First, compared with Glide, the average values of mean absolute error and root mean square error of GBDT/MIN + GB decreased about 38 and 36%, respectively. Second, the mean values of squared correlation coefficient and predictive index increased about 225 and 73%, respectively. Third, more encouragingly, the average value of the areas under the curve of receiver operating characteristic for six targets by GBDT, 0.87, is significantly better than that by Glide, which is only 0.71. Thus, we expected IP-SFs to have broad and promising applications in SBVSs.

Analyzing Kinase Similarity in Small Molecule and Protein Structural Space to Explore the Limits of Multi-Target Screening.

While selective inhibition is one of the key assets for a small molecule drug, many diseases can only be tackled by simultaneous inhibition of several proteins. An example where achieving selectivity is especially challenging are ligands targeting human kinases. This difficulty arises from the high structural conservation of the kinase ATP binding sites, the area targeted by most inhibitors. We investigated the possibility to identify novel small molecule ligands with pre-defined binding profiles for a series of kinase targets and anti-targets by in silico docking. The candidate ligands originating from these calculations were assayed to determine their experimental binding profiles. Compared to previous studies, the acquired hit rates were low in this specific setup, which aimed at not only selecting multi-target kinase ligands, but also designing out binding to anti-targets. Specifically, only a single profiled substance could be verified as a sub-micromolar, dual-specific EGFR/ErbB2 ligand that indeed avoided its selected anti-target BRAF. We subsequently re-analyzed our target choice and in silico strategy based on these findings, with a particular emphasis on the hit rates that can be expected from a given target combination. To that end, we supplemented the structure-based docking calculations with bioinformatic considerations of binding pocket sequence and structure similarity as well as ligand-centric comparisons of kinases. Taken together, our results provide a multi-faceted picture of how pocket space can determine the success of docking in multi-target drug discovery efforts.

Scutellarin ameliorates high glucose-induced vascular endothelial cells injury by activating PINK1/Parkin-mediated mitophagy.

ETHNOPHARMACOLOGICAL RELEVANCE: Scutellarin (Scu) is one of the main active ingredients of Erigeron breviscapus (Vant.) Hand.-Mazz which has been used to treat cardiovascular disease including vascular dysfunction caused by diabetes. Scu also has a protective effect on vascular endothelial cells against hyperglycemia. However, molecular mechanisms underlying this effect are not clear. AIM OF THE STUDY: This aim of this study was to investigate the effect of Scu on human umbilical vein endothelial cells (HUVECs) injury induced by high glucose (HG), especially the regulation of PTEN-induced kinase 1 (PINK1)/Parkin-mediated mitophagy. MATERIALS AND METHODS: HUVECs were exposed to HG to induce vascular endothelial cells injury in vitro. Cell viability was assessed by MTT assay. The extent of cell apoptosis was measured by Hoechst staining and flow cytometry. Mitophagy was assayed by fluorescent immunostaining, transmission electron microscope and immunoblot. Besides, virtual docking was conducted to validate the interaction of PINK1 protein and Scu. RESULTS: We found that Scu significantly increased cell viability in HG-treated HUVECs. Scu reduces the expression of Bcl-2, Bax and cytochrome C (Cyt.c) to inhibit apoptosis through a mitochondria-dependent pathway. Meanwhile, Scu improved the overload of reactive oxygen species (ROS), superoxide dismutase (SOD) activity and SOD2 protein expression, and reversed the collapse of mitochondrial membrane potential. Besides, Scu increased autophagic flux, improved the expression of microtubule-associated protein 1 light chain 3 Ⅱ (LC3 II), Beclin 1 and autophagy-related gene 5 (Atg 5) and decreased the expression of Sequestosome1/P62 in HG-treated HUVECs. Furthermore, Scu improved the expressions of PINK1, Parkin, and Mitofusin2, which revealed the enhancement of mitophagy. Moreover, the beneficial effects of Scu on HG-induced low expression of Parkin, overproduction of ROS, and over expressions of P62, Cyt.c and Cleaved caspase-3 were weakened by PINK1 gene knockdown. Molecular docking suggested good interaction of Scu and PINK1 protein. CONCLUSION: These results suggest that Scu may protect vascular endothelial cells against hyperglycemia-induced injury by up-regulating mitophagy via PINK1/Parkin signal pathway.

Functional Characterization of BRASSINAZOLE-RESISTANT 1 in Panax Ginseng (PgBZR1) and Brassinosteroid Response during Storage Root Formation.

Brassinosteroids (BRs) play crucial roles in the physiology and development of plants. In the model plant Arabidopsis, BR signaling is initiated at the level of membrane receptors, BRASSINOSTEROIDS INSENSITIVE 1 (BRI1) and BRI1-ASSOCIATED RECEPTOR KINASE 1 (BAK1) complex, thus activating the transcription factors (TFs) BRASSINAZOLE RESISTANT 1/BRI1-EMS-SUPPRESSOR 1 (BZR1/BES1) to coordinate BR responsive genes. BRASSINOSTEROIDS INSENSITIVE 2 (BIN2), glycogen synthase kinase 3 (GSK3) like-kinase, negatively regulates BZR1/BES1 transcriptional activity through phosphorylation-dependent cytosolic retention and shuttling. However, it is still unknown whether this mechanism is conserved in Panax ginseng C. A. Mayer, a member of the Araliaceae family, which is a shade-tolerant perennial root crop. Despite its pharmacological and agricultural importance, the role of BR signaling in the development of P. ginseng and characterization of BR signaling components are still elusive. In this study, by utilizing the Arabidopsisbri1 mutant, we found that ectopic expression of the gain of function form of PgBZR1 (Pgbzr1-1D) restores BR deficiency. In detail, ectopic expression of Pgbzr1-1D rescues dwarfism, defects of floral organ development, and hypocotyl elongation of bri1-5, implying the functional conservation of PgBZR1 in P. ginseng. Interestingly, brassinolide (BL) and BRs biosynthesis inhibitor treatment in two-year-old P. ginseng storage root interferes with and promotes, respectively, secondary growth in terms of xylem formation. Altogether, our results provide new insight into the functional conservation and potential diversification of BR signaling and response in P. ginseng.

A Pilot Study of Multi-Input Recurrent Neural Networks for Drug-Kinase Binding Prediction.

The use of virtual drug screening can be beneficial to research teams, enabling them to narrow down potentially useful compounds for further study. A variety of virtual screening methods have been developed, typically with machine learning classifiers at the center of their design. In the present study, we created a virtual screener for protein kinase inhibitors. Experimental compound-target interaction data were obtained from the IDG-DREAM Drug-Kinase Binding Prediction Challenge. These data were converted and fed as inputs into two multi-input recurrent neural networks (RNNs). The first network utilized data encoded in one-hot representation, while the other incorporated embedding layers. The models were developed in Python, and were designed to output the IC50 of the target compounds. The performance of the models was assessed primarily through analysis of the Q2 values produced from runs of differing sample and epoch size; recorded loss values were also reported and graphed. The performance of the models was limited, though multiple changes are proposed for potential improvement of a multi-input recurrent neural network-based screening tool.

Genome-wide analysis of proline-rich extension-like receptor protein kinase (PERK) in Brassica rapa and its association with the pollen development.

BACKGROUND: Proline-rich extension-like receptor protein kinases (PERKs) are an important class of receptor kinases located in the plasma membrane, most of which play a vital role in pollen development. RESULTS: Our study identified 25 putative PERK genes from the whole Brassica rapa genome (AA). Phylogenetic analysis of PERK protein sequences from 16 Brassicaceae species divided them into four subfamilies. The biophysical properties of the BrPERKs were investigated. Gene duplication and synteny analyses and the calculation of Ka/Ks values suggested that all 80 orthologous/paralogous gene pairs between B. rapa and A. thaliana, B. nigra and B. oleracea have experienced strong purifying selection. RNA-Seq data and qRT-PCR analyses showed that several BrPERK genes were expressed in different tissues, while some BrPERKs exhibited high expression levels only in buds. Furthermore, comparative transcriptome analyses from six male-sterile lines of B. rapa indicated that 7 BrPERK genes were downregulated in all six male-sterile lines. Meanwhile, the interaction networks of the BrPERK genes were constructed and 13 PERK coexpressed genes were identified, most of which were downregulated in the male sterile buds. CONCLUSION: Combined with interaction networks, coexpression and qRT-PCR analyses, these results demonstrated that two BrPERK genes, Bra001723.1 and Bra037558.1 (the orthologs of AtPERK6 (AT3G18810)), were downregulated beginning in the meiosis II period of male sterile lines and involved in anther development. Overall, this comprehensive analysis of some BrPERK genes elucidated their roles in male sterility.

Discovery of potential Toxoplasma gondii CDPK1 inhibitors with new scaffolds based on the combination of QSAR and scaffold-hopping method with in vitro validation.

To discover drugs for toxoplasmosis with less side-effects and less probability to get drug resistance is eagerly appealed for pregnant women, infant or immunocompromised patients. In this work, using TgCDPK1 as drug target, we design a method to discover new inhibitors for CDPK1 as potential drug lead for toxoplasmosis with novel scaffolds based on the combination of 2D/3D-QSAR and scaffold-hopping methods. All the binding sites of the potential inhibitors were checked by docking method, and only the ones that docked to the most conserved sites of TgCDPK1, which make them have less probability to get drug resistance, were remained. As a result, 10 potential inhibitors within two new scaffolds were discovered for TgCDPK1 with experimentally verified inhibitory activities in micromole level. The discovery of these inhibitors may contribute to the drug development for toxoplasmosis. Besides, the pipeline which is composed in this work as the combination of QSAR and scaffold-hopping is simple, easy to repeat for researchers without need of in-depth knowledge of pharmacology to get inhibitors with novel scaffolds, which will accelerate the procedure of drug discovery and contribute to the drug repurposing study.

Investigation of Crystal Structures in Structure-Based Virtual Screening for Protein Kinase Inhibitors.

Protein kinases are important drug targets in several therapeutic areas ,and structure-based virtual screening (SBVS) is an important strategy in discovering lead compounds for kinase targets. However, there are multiple crystal structures available for each target, and determining which one is the most favorable is a key step in molecular docking for SBVS due to the ligand induce-fit effect. This work aimed to find the most desirable crystal structures for molecular docking by a comprehensive analysis of the protein kinase database which covers 190 different kinases from all eight main kinase families. Through an integrated self-docking and cross-docking evaluation, 86 targets were eventually evaluated on a total of 2608 crystal structures. Results showed that molecular docking has great capability in reproducing conformation of crystallized ligands and for each target, the most favorable crystal structure was selected, and the AGC family outperformed the other family targets based on RMSD comparison. In addition, RMSD values, GlideScore, and corresponding bioactivity data were compared and demonstrated certain relationships. This work provides great convenience for researchers to directly select the optimal crystal structure in SBVS-based kinase drug design and further validates the effectiveness of molecular docking in drug discovery.

Unfolded protein-independent IRE1 activation contributes to multifaceted developmental processes in Arabidopsis.

In Arabidopsis, the IRE1A and IRE1B double mutant (ire1a/b) is unable to activate cytoplasmic splicing of bZIP60 mRNA and regulated IRE1-dependent decay under ER stress, whereas the mutant does not exhibit severe developmental defects under normal conditions. In this study, we focused on the Arabidopsis IRE1C gene, whose product lacks a sensor domain. We found that the ire1a/b/c triple mutant is lethal, and heterozygous IRE1C (ire1c/+) mutation in the ire1a/b mutants resulted in growth defects and reduction of the number of pollen grains. Genetic analysis revealed that IRE1C is required for male gametophyte development in the ire1a/b mutant background. Expression of a mutant form of IRE1B that lacks the luminal sensor domain (ΔLD) complemented a developmental defect in the male gametophyte in ire1a/b/c haplotype. In vivo, the ΔLD protein was activated by glycerol treatment that increases the composition of saturated lipid and was able to activate regulated IRE1-dependent decay but not bZIP60 splicing. These observations suggest that IRE1 contributes to plant development, especially male gametogenesis, using an alternative activation mechanism that bypasses the unfolded protein-sensing luminal domain.

Structure-based rational design of staurosporine-based fluorescent probe with broad-ranging kinase affinity for kinase panel application.

Selectivity profiling of compounds is important for kinase drug discovery. To this end, we aimed to develop a broad-range protein kinase assay by synthesizing a novel staurosporine-derived fluorescent probe based on staurosporine and kinase-binding related structural information. Upon structural analysis of staurosporine with kinases, a 4'-methylamine moiety of staurosporine was found to be located on the solvent side of the kinases, to which several linker units can be conjugated by either alkylation or acylation. However, such conjugation was suggested to reduce the binding affinities of the modified compound for several kinases, owing to the elimination of hydrogen bond donor moiety of NH-group from 4'-methylamine and/or steric hindrance by acyl moiety. Based on this structural information, we designed and synthesized a novel staurosporine-based probe without methyl group in order to retain the hydrogen bond donor, similar to unmodified staurosporine. The broad range of the kinase binding assay demonstrated that our novel fluorescent probe is an excellent tool for developing broad-ranging kinase binding assay.

Phytophthora infestans effector SFI3 targets potato UBK to suppress early immune transcriptional responses.

The potato blight agent Phytophthora infestans secretes a range of RXLR effectors to promote disease. Recent evidence indicates that some effectors suppress early pattern-triggered immunity (PTI) following perception of microbe-associated molecular patterns (MAMPs). Phytophthora infestans effector PiSFI3/Pi06087/PexRD16 has been previously shown to suppress MAMP-triggered pFRK1-Luciferase reporter gene activity. How PiSFI3 suppresses immunity is unknown. We employed yeast-two-hybrid (Y2H) assays, co-immunoprecipitation, transcriptional silencing by RNA interference and virus-induced gene silencing (VIGS), and X-ray crystallography for structure-guided mutagenesis, to investigate the function of PiSFI3 in targeting a plant U-box-kinase protein (StUBK) to suppress immunity. We discovered that PiSFI3 is active in the host nucleus and interacts in yeast and in planta with StUBK. UBK is a positive regulator of specific PTI pathways in both potato and Nicotiana benthamiana. Importantly, it contributes to early transcriptional responses that are suppressed by PiSFI3. PiSFI3 forms an unusual trans-homodimer. Mutation to disrupt dimerization prevents nucleolar localisation of PiSFI3 and attenuates both its interaction with StUBK and its ability to enhance P. infestans leaf colonisation. PiSFI3 is a 'WY-domain' RXLR effector that forms a novel trans-homodimer which is required for its ability to suppress PTI via interaction with the U-box-kinase protein StUBK.

Structure-Based Virtual Screening of LsrK Kinase Inhibitors to Target Quorum Sensing.

In the era of increased antibiotic resistance, targeting enzymes involved in bacterial communication (quorum sensing) represents a new strategy to fight bacterial infections. LsrK is a kinase responsible for the phosphorylation of autoinducer-2, a signaling molecule involved in quorum sensing. Inhibiting LsrK would lead to quorum sensing inactivation and interfere with the pathogenesis. In this study, we built the first LsrK 3D model and performed virtual screening of a locally available database. Selected compounds were tested against LsrK, and the analogue search conducted based on the positive hits led to the identification of low-micromolar LsrK inhibitors. These results prove the utility of the model and provide the first class of LsrK inhibitors to be further optimized as antivirulence agents.

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

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

Determination of a Focused Mini Kinase Panel for Early Identification of Selective Kinase Inhibitors.

We analyzed an extensive data set of 3000 Janssen kinase inhibitors (spanning some 40 therapeutic projects) profiled at 414 kinases in the DiscoverX KINOME scan to better understand the necessity of using such a full kinase panel versus simply profiling one's compound at a much smaller number of kinases, or mini kinase panel (MKP), to assess its selectivity. To this end, we generated a series of MKPs over a range of sizes and of varying kinase membership using Monte Carlo simulations. By defining the kinase hit index (KHI), we quantified a compound's selectivity based on the number of kinases it hits. We find that certain combinations (rather than a random selection) of kinases can result in a much lower average error. Indeed, we identified a focused MKP with a 45.1% improvement in the average error (compared to random) that yields an overall correlation of R2 = 0.786-0.826 for the KHI compared to the full kinase panel value. Unlike using a full kinase panel, which is both time and cost restrictive, a focused MKP is amenable to the triaging of all early stage compounds. In this way, promiscuous compounds are filtered out early on, leaving the most selective compounds for lead optimization.

Determination of Affinity and Residence Time of Potent Drug-Target Complexes by Label-free Biosensing.

Prolonged drug-target occupancy has become increasingly important in lead optimization, and biophysical assays that measure residence time are in high demand. Here we report a practical label-free assay methodology that provides kinetic and affinity measurements suitable for most target classes without long preincubations and over comparatively short sample contact times. The method, referred to as a "chaser" assay, has been applied to three sets of unrelated kinase/inhibitor panels in order to measure the residence times, where correlation with observed efficacy was suspected. A lower throughput chaser assay measured a residence time of 3.6 days ±3.4% (95% CI) and provided single digit pM sensitivity. A higher throughput chaser methodology enabled a maximum capacity of 108 compounds in duplicate/day with an upper residence time limit of 9 h given an assay dissociation time of 34 min.

New Perspectives, Opportunities, and Challenges in Exploring the Human Protein Kinome.

The human protein kinome comprises 535 proteins that, with the exception of approximately 50 pseudokinases, control intracellular signaling networks by catalyzing the phosphorylation of multiple protein substrates. While a major research focus of the last 30 years has been cancer-associated Tyr and Ser/Thr kinases, over 85% of the kinome has been identified to be dysregulated in at least one disease or developmental disorder. Despite this remarkable statistic, for the majority of protein kinases and pseudokinases, there are currently no inhibitors progressing toward the clinic, and in most cases, details of their physiologic and pathologic mechanisms remain at least partially obscure. By curating and annotating data from the literature and major public databases of phosphorylation sites, kinases, and disease associations, we generate an unbiased resource that highlights areas of unmet need within the kinome. We discuss strategies and challenges associated with characterizing catalytic and noncatalytic outputs in cells, and describe successes and new frontiers that will support more comprehensive cancer-targeting and therapeutic evaluation in the future. Cancer Res; 78(1); 15-29. ©2017 AACR.