Cancer Drug Targets Research Articles

Therapeutic targeting of microtubule affinity-regulating kinase 4 in cancer and neurodegenerative diseases.

Microtubule affinity-regulating kinase 4 (MARK4) is a member of the Ser/Thr protein kinase family, phosphorylates the microtubule-connected proteins and plays a vital role in causing cancers and neurodegenerative diseases. This kinase modulates multiple signaling pathways, including mammalian target of rapamycin, nuclear factor-κB, and Hippo-signaling, presumably responsible for cancer and Alzheimer's. MARK4 acts as a negative controller of the Hippo-kinase cassette for promoting YAP/TAZ action, and the loss of MARK4 detains the tumorigenic properties of cancer cells. MARK4 is involved in tau hyperphosphorylation that consequently affects neurodegeneration. MARK4 is a promising drug target for cancer, diabetes, and Alzheimer's. Developing the potent and selective inhibitors of MAKR4 are promising in the therapeutic management of associated diseases. Despite its great significance, a few reviews are available to discuss its structure, function and clinical significance. In the current review, we aimed to provide detailed information on the structural features of MARK4 targeted in drug development and its role in various signaling pathways related to cancer and neurodegenerative diseases. We further described the therapeutic potential of MARK4 inhibitors in preventing numerous diseases. Finally, the updated information on MARK4 will be helpful in the further development of effective therapeutic molecules.

Network pharmacology combined with molecular docking and in vitro verification reveals the therapeutic potential of Delphinium roylei munz constituents on breast carcinoma.

Delphinium roylei Munz is an indigenous medicinal plant to India where its activity against cancer has not been previously investigated, and its specific interactions of bioactive compounds with vulnerable breast cancer drug targets remain largely unknown. Therefore, in the current study, we aimed to evaluate the anti-breast cancer activity of different extracts of D. roylei against breast cancer and deciphering the molecular mechanism by Network Pharmacology combined with Molecular Docking and in vitro verification. The experimental plant was extracted with various organic solvents according to their polarity index. Phytocompounds were identified by High resolution-liquid chromatography-mass spectrometry (HR-LC/MS) technique, and SwissADME programme evaluated their physicochemical properties. Next, target(s) associated with the obtained bioactives or breast cancer-related targets were retrieved by public databases, and the Venn diagram selected the overlapping targets. The networks between overlapping targets and bioactive were visualized, constructed, and analyzed by STRING programme and Cytoscape software. Finally, we implemented a molecular docking test (MDT) using AutoDock Vina to explore key target(s) and compound(s). HR-LC/MS detected hundreds of phytocompounds, and few were accepted by Lipinski's rules after virtual screening and therefore classified as drug-like compounds (DLCs). A total of 464 potential target genes were attained for the nine quantitative phytocompounds and using Gene Cards, OMIM and DisGeNET platforms, 12063 disease targets linked to breast cancer were retrieved. With Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment, a total of 20 signalling pathways were manifested, and a hub signalling pathway (PI3K-Akt signalling pathway), a key target (Akt1), and a key compound (8-Hydroxycoumarin) were selected among the 20 signalling pathways via molecular docking studies. The molecular docking investigation revealed that among the nine phytoconstituents, 8-hydroxycoumarin showed the best binding energy (-9.2kcal/mol) with the Akt1 breast cancer target. 8-hydroxycoumarin followed all the ADME property prediction using SwissADME, and 100 nanoseconds (ns) MD simulations of 8-hydroxycoumarin complexes with Akt1 were found to be stable. Furthermore, D. roylei extracts also showed significant antioxidant and anticancer activity through in vitro studies. Our findings indicated for the first time that D. roylei extracts could be used in the treatment of BC.

InDEP: an interpretable machine learning approach to predict cancer driver genes from multi-omics data.

Cancer driver genes are critical in driving tumor cell growth, and precisely identifying these genes is crucial in advancing our understanding of cancer pathogenesis and developing targeted cancer drugs. Despite the current methods for discovering cancer driver genes that mainly rely on integrating multi-omics data, many existing models are overly complex, and it is difficult to interpret the results accurately. This study aims to address this issue by introducing InDEP, an interpretable machine learning framework based on cascade forests. InDEP is designed with easy-to-interpret features, cascade forests based on decision trees and a KernelSHAP module that enables fine-grained post-hoc interpretation. Integrating multi-omics data, InDEP can identify essential features of classified driver genes at both the gene and cancer-type levels. The framework accurately identifies driver genes, discovers new patterns that make genes as driver genes and refines the cancer driver gene catalog. In comparison with state-of-the-art methods, InDEP proved to be more accurate on the test set and identified reliable candidate driver genes. Mutational features were the primary drivers for InDEP's identifying driver genes, with other omics features also contributing. At the gene level, the framework concluded that substitution-type mutations were the main reason most genes were identified as driver genes. InDEP's ability to identify reliable candidate driver genes opens up new avenues for precision oncology and discovering new biomedical knowledge. This framework can help advance cancer research by providing an interpretable method for identifying cancer driver genes and their contribution to cancer pathogenesis, facilitating the development of targeted cancer drugs.

Polo-like kinase-1 mediates hepatitis C virus-induced cell migration, a drug target for liver cancer.

Polo-like kinase 1 (PLK1) is a regulator of cell mitosis and cytoskeletal dynamics. PLK1 overexpression in liver cancer is associated with tumour progression, metastasis, and vascular invasion. Hepatitis C virus (HCV) NS5A protein stimulates PLK1-mediated phosphorylation of host proteins, so we hypothesised that HCV-PLK1 interactions might be a mechanism for HCV-induced liver cancer. We used a HCV cell-culture model (Jc1) to investigate the effects of virus infection on the cytoskeleton. In HCV-infected cells, a novel posttranslational modification in β-actin was observed with phosphorylation at Ser239. Using in silico and in vitro approaches, we identified PLK1 as the mediating kinase. In functional experiments with a phosphomimetic mutant form of β-actin, Ser239 phosphorylation influences β-actin polymerization and distribution, resulting in increased cell motility. The changes were prevented by treating cells with the PLK1 inhibitor volasertib. In HCV-infected hepatocytes, increased cell motility contributes to cancer cell migration, invasion, and metastasis. PLK1 is an important mediator of these effects and early treatment with PLK1 inhibitors may prevent or reduce HCC progression, particularly in people with HCV-induced HCC.

Aberrant PI3Kδ splice isoform as a potential biomarker and novel therapeutic target for endocrine cancers.

PI3K/AKT signaling pathway is upregulated in a broad spectrum of cancers. Among the class I PI3Ks (PI3Kδ/β/δ isoforms), PI3Kδ has been implicated in hematologic cancers and solid tumors. Alternative splicing is a post-transcriptional process for acquiring proteomic diversity in eukaryotic cells. Emerging evidence has highlighted the involvement of aberrant mRNA splicing in cancer development/progression. Our previous studies revealed that PIK3CD-S is an oncogenic splice variant that promotes tumor aggressiveness and drug resistance in prostate cancer (PCa). To further evaluate the potential of utilizing PI3Kδ-S (encoded from PIK3CD-S) as a cancer biomarker and/or drug target, comprehensive analyses were performed in a series of patient samples and cell lines derived from endocrine/solid tumors. Specifically, IHC, immunofluorescence, western blot and RT-PCR assay results have demonstrated that PI3Kδ isoforms were highly expressed in endocrine/solid tumor patient specimens and cell lines. Differential PIK3CD-S/PIK3CD-L expression profiles were identified in a panel of endocrine/solid tumor cells. SiRNA knockdown of PIK3CD-L or PIK3CD-S differentially inhibits AKT/mTOR signaling in PCa, breast, colon and lung cancer cell lines. Moreover, siRNA knockdown of PTEN increased PI3Kδ levels and activated AKT/mTOR signaling, while overexpression of PTEN reduced PI3Kδ levels and inhibited AKT/mTOR signaling in cancer cells. Intriguingly, PI3Kδ-S levels remained unchanged upon either siRNA knockdown or overexpression of PTEN. Taken together, these results suggested that PTEN negatively regulates PI3Kδ-L and its downstream AKT/mTOR signaling, while PI3Kδ-S promotes AKT/mTOR signaling without regulation by PTEN. Lastly, PI3Kδ inhibitor Idelalisib and SRPK1/2 inhibitor SRPIN340 were employed to assess their efficacies on inhibiting the PI3Kδ-expressing endocrine/solid tumors. Our results have shown that Idelalisib effectively inhibited PI3Kδ-L (but not PI3Kδ-S) mediated AKT/mTOR signaling. In contrast, SRPIN340 reversed the aberrant mRNA splicing, thereby inhibiting AKT/mTOR signaling. In-vitro functional assays have further demonstrated that a combination of Idelalisib and SRPIN340 achieved a synergistic drug effect (with drastically reduced cell viabilities/growths of tumor spheroids) in inhibiting the advanced tumor cells. In summary, our study has suggested a promising potential of utilizing PI3Kδ-S (an oncogenic isoform conferring drug resistance and exempt from PTEN regulation) as a prognostic biomarker and drug target in advanced endocrine cancers.

Identification of Key Genes as Potential Drug Targets for Gastric Cancer

Gastric cancer (GC) is one of the most common cancers and ranks the third in cancer mortality all over the world. The goal of this study was to identify potential hub-genes, highlighting their functions, signaling pathways, and candidate drugs for the treatment of GC patients. We used publicly available next generation sequencing (NGS) data to identify differentially expressed (DE) genes. The top DE genes were mapped to STRING database to construct the protein-protein interaction (PPI) network and top hub genes were selected for further analysis. We found a total of 1555 DE genes with 870 upregulated and 685 downregulated genes in GC. We selected the top 400 (200 upregulated and 200 downregulated) genes to construct a PPI network and extracted the top 15 hub genes. The gene ontology (GO) term and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses of the 15 hub genes exposed some important functions and signaling pathways that were significantly associated with GC patients. The survival analysis of the hub genes disclosed that the lower expressions of the three hub genes CDH2, COL4A1, and COL5A2 were associated with better survival of GC patients. These three genes might be the candidate biomarkers for the diagnosis and treatment of GC. Then, we considered 3 key proteins (genomic biomarkers) (COL4A1, CDH2, and CO5A2) as the drug target proteins (receptors), performed their docking analysis with the 102 meta-drug agents, and found Everolimus, Docetaxel, Lanreotide, Venetoclax, Temsirolimus, and Nilotinib as the top ranked 6 candidate drugs with respect to our proposed target proteins for the treatment against GC patients. Therefore, the proposed drugs might play vital role for the treatment against GC patients.

Discovery of 2,4-diphenyl-substituted thiazole derivatives as PRMT1 inhibitors and investigation of their anti-cervical cancer effects

Cervical cancer is one of the most common cancers that affects middle-aged women and the discovery of new drugs to aid clinical management is needed. As an important member of the protein arginine methyltransferases (PRMTs) family, PRMT1 catalyzes the methylation of protein arginine, which can influence multiple biological processes of cancer cells, such as activating epithelial-mesenchymal transformation (EMT) and acquiring resistance to apoptosis. Therefore, PRMT1 can be considered as a potential drug target for cervical cancer. In the current study, a new sub-binding pocket was discovered by molecular modeling, and by introducing a third substitute on the thiazole group to occupy this pocket, a series of compounds were designed and synthesized as potential PRMT1 inhibitors. Of these, two compounds (ZJG51 and ZJG58) exhibited significant inhibitory activities against PRMT1 without significantly inhibiting PRMT5. Both ZJG51 and ZJG58 displayed potent inhibitory effects on the proliferation of four cancer-derived cell lines and ZJG51 exerted relative selectivity against the cervical cancer cell line, HeLa. Further studies showed that ZJG51 inhibited migration and induce the apoptosis of HeLa cells. Mechanistically, ZJG51 significantly regulated PRMT1 related proteins, and indicated that the induction of apoptosis and inhibition of migration by ZJG51 may involve the activation of Caspase 9 and the inhibition of EMT, respectively. Molecular dynamic simulation and free energy calculation showed that ZJG51 can bind to PRMT1 stably and the binding mode was predicted. These data indicated that introducing the third substitute on the five-membered ring could be a future direction for structure-based optimization of PRMT1 inhibitors, and ZJG51 could be an important lead compound to inform the design of more potent inhibitors.

The effect of matrices on the gene expression profile of patient-derived head and neck carcinoma cells for in vitro therapy testing

ObjectiveHead and neck squamous cell carcinoma (HNSCC) is a highly aggressive tumor with a 5-year mortality rate of ~ 50%. New in vitro methods are needed for testing patients’ cancer cell response to anti-cancer treatments. We aimed to investigate how the gene expression of fresh carcinoma tissue samples and freshly digested single cancer cells change after short-term cell culturing on plastic, Matrigel or Myogel. Additionally, we studied the effect of these changes on the cancer cells’ response to anti-cancer treatments.Materials/methodsFresh tissue samples from HNSCC patients were obtained perioperatively and single cells were enzymatically isolated and cultured on either plastic, Matrigel or Myogel. We treated the cultured cells with cisplatin, cetuximab, and irradiation; and performed cell viability measurement. RNA was isolated from fresh tissue samples, freshly isolated single cells and cultured cells, and RNA sequencing transcriptome profiling and gene set enrichment analysis were performed.ResultsCancer cells obtained from fresh tissue samples changed their gene expression regardless of the culturing conditions, which may be due to the enzymatic digestion of the tissue. Myogel was more effective than Matrigel at supporting the upregulation of pathways related to cancer cell proliferation and invasion. The impacts of anti-cancer treatments varied between culturing conditions.ConclusionsOur study showed the challenge of in vitro cancer drug testing using enzymatic cell digestion. The upregulation of many targeted pathways in the cultured cells may partially explain the common clinical failure of the targeted cancer drugs that pass the in vitro testing.

Prediction of anti-microtubular target proteins of tubulins and their interacting proteins using Gene Ontology tools

BackgroundTubulins are highly conserved globular proteins involved in stabilization of cellular cytoskeletal microtubules during cell cycle. Different isoforms of tubulins are differentially expressed in various cell types, and their protein–protein interactions (PPIs) analysis will help in identifying the anti-microtubular drug targets for cancer and neurological disorders. Numerous web-based PPIs analysis methods are recently being used, and in this paper, I used Gene Ontology (GO) tools, e.g., Stringbase, ProteomeHD, GeneMANIA, and ShinyGO, to identify anti-microtubular target proteins by selecting strongly interacting proteins of tubulins. ResultsI used 6 different human tubulin isoforms (two from each of α-, β-, and γ-tubulin) and found several thousands of node-to-node protein interactions (highest 4956 in GeneMANIA) and selected top 10 strongly interacting node-to-node interactions with highest score, which included 7 tubulin family protein and 6 non-tubulin family proteins (total 13). Functional enrichment analysis indicated a significant role of these 13 proteins in nucleation, polymerization or depolymerization of microtubules, membrane tethering and docking, dorsal root ganglion development, mitotic cycle, and cytoskeletal organization. I found γ-tubulins (TUBG1, TUBGCP4, and TUBBGCP6) were known to contribute majorly for tubulin-associated functions followed by α-tubulin (TUBA1A) and β-tubulins (TUBB AND TUBB3). In PPI results, I found several non-tubular proteins interacting with tubulins, and six of them (HTT, DPYSL2, SKI, UNC5C, NINL, and DDX41) were found closely associated with their functions. ConclusionsIncreasing number of regulatory proteins and subpopulation of tubulin proteins are being reported with poor understanding in their association with microtubule assembly and disassembly. The functional enrichment analysis of tubulin isoforms using recent GO tools resulted in identification of γ-tubulins playing a key role in microtubule functions and observed non-tubulin family of proteins HTT, DPYSL2, SKI, UNC5C, NINL, and DDX41 strongly interacting functional proteins of tubulins. The present study yields a promising model system using GO tools to narrow down tubulin-associated proteins as a drug target in cancer, Alzheimer’s, neurological disorders, etc.

Bioreducible exosomes encapsulating glycolysis inhibitors potentiate mitochondria-targeted sonodynamic cancer therapy via cancer-targeted drug release and cellular energy depletion

Nanocarrier-assisted sonodynamic therapy (SDT) has shown great potential for the effective and targeted treatment of deep-seated tumors by overcoming the critical limitations of sonosensitizers. However, in vivo SDT using nanocarriers is still constrained by their intrinsic toxicity and nonspecific cargo release. In this study, we developed bioreducible exosomes for the safe and tumor-specific delivery of mitochondria-targeting sonosensitizers [triphenylphosphonium-conjugated chlorin e6 (T-Ce6)] and glycolysis inhibitors (FX11). Redox-cleavable diselenide linker-bearing lipids were embedded into exosomes to trigger drug release in response to overexpressed glutathione in the tumor microenvironment. Bioreducible exosomes facilitate the cytoplasmic release of their payload in the reducing environment of tumor cells. They significantly enhance drug release and sonodynamic effects when irradiated with ultrasound (US). The mitochondria-targeted accumulation of T-Ce6 efficiently damaged the mitochondria of the cells under US irradiation, accelerating apoptotic cell death. FX11 substantially inhibited cellular energy metabolism, potentiating the antitumor efficacy of mitochondria-targeted SDT. Bioreducible exosomes effectively suppressed tumor growth in mice without significant systemic toxicity, via a combination of mitochondria-targeted SDT and energy metabolism-targeted therapy. This study offers new insights into the use of dual stimuli-responsive exosomes encapsulating sonosensitizers for safe and targeted sonodynamic cancer therapy.

Liposomal Encapsulation of Chemotherapeutics Agents Combined with the Use of Ultrasound in Cancer Treatment

Ultrasound (US) has numerous uses in the medical field, including imaging, tumor ablation, and lithotripsy; another interesting application of US in cancer therapy is as an external trigger in targeted drug delivery. Cancer-targeted drug delivery involves delivering chemotherapeutic drugs to tumor sites with a high degree of precision, which would minimize the adverse side effects experienced by patients. Several nanocarriers have been studied as possible nanocarriers; however, liposomes stood out from the rest because of their non-immunogenicity, amphiphilic nature, ease of functionalization, and stimuli-responsiveness. This review addresses the role of US in the synthesis of liposomes, its ability to induce localized and controlled drug release from liposomes, as well as the integration of US-induced release and US-imaging using liposomes as contrast agents utilizing thermal and/or mechanical effects.

KR4SL: knowledge graph reasoning for explainable prediction of synthetic lethality.

Synthetic lethality (SL) is a promising strategy for anticancer therapy, as inhibiting SL partners of genes with cancer-specific mutations can selectively kill the cancer cells without harming the normal cells. Wet-lab techniques for SL screening have issues like high cost and off-target effects. Computational methods can help address these issues. Previous machine learning methods leverage known SL pairs, and the use of knowledge graphs (KGs) can significantly enhance the prediction performance. However, the subgraph structures of KG have not been fully explored. Besides, most machine learning methods lack interpretability, which is an obstacle for wide applications of machine learning to SL identification. We present a model named KR4SL to predict SL partners for a given primary gene. It captures the structural semantics of a KG by efficiently constructing and learning from relational digraphs in the KG. To encode the semantic information of the relational digraphs, we fuse textual semantics of entities into propagated messages and enhance the sequential semantics of paths using a recurrent neural network. Moreover, we design an attentive aggregator to identify critical subgraph structures that contribute the most to the SL prediction as explanations. Extensive experiments under different settings show that KR4SL significantly outperforms all the baselines. The explanatory subgraphs for the predicted gene pairs can unveil prediction process and mechanisms underlying synthetic lethality. The improved predictive power and interpretability indicate that deep learning is practically useful for SL-based cancer drug target discovery. The source code is freely available at https://github.com/JieZheng-ShanghaiTech/KR4SL.

Effectively utilizing publicly available databases for cancer target evaluation.

The majority of compounds designed against cancer drug targets do not progress to become approved drugs, mainly due to lack of efficacy and/or unmanageable toxicity. Robust target evaluation is therefore required before progressing through the drug discovery process to reduce the high attrition rate. There are a wealth of publicly available databases that can be mined to generate data as part of a target evaluation. It can, however, be challenging to learn what databases are available,how and when they should be used, and to understand the associated limitations. Here, we have compiled and present key, freely accessible and easy-to-use databases that house informative datasets from in vitro, in vivo and clinical studies. We also highlight comprehensive target review databases that aim to bring together information from multiple sources into one-stop portals. In the post-genomics era, a key objective is to exploit the extensive cell, animal and patient characterization datasets in order to deliver precision medicine on a patient-specific basis. Effective utilization of the highlighted databases will go some way towards supporting the cancer research community achieve these aims.

Spatiotemporal quantitative microRNA-155 imaging reports immune-mediated changes in a triple-negative breast cancer model.

MicroRNAs are small non-coding RNAs and represent key players in physiology and disease. Aberrant microRNA expression is central to the development and progression of cancer, with various microRNAs proposed as potential cancer biomarkers and drug targets. There is a need to better understand dynamic microRNA expression changes as cancers progress and their tumor microenvironments evolve. Therefore, spatiotemporal and non-invasive in vivo microRNA quantification in tumor models would be highly beneficial. We developed an in vivo microRNA detector platform in which the obtained signals are positively correlated to microRNA presence, and which permitted stable expression in cancer cells as needed for long-term experimentation in tumor biology. It exploits a radionuclide-fluorescence dual-reporter for quantitative in vivo imaging of a microRNA of choice by radionuclide tomography and fluorescence-based downstream ex vivo tissue analyses. We generated and characterized breast cancer cells stably expressing various microRNA detectors and validated them in vitro. We found the microRNA detector platform to report on microRNA presence in cells specifically and accurately, which was independently confirmed by real-time PCR and through microRNA modulation. Moreover, we established various breast tumor models in animals with different levels of residual immune systems and observed microRNA detector read-outs by imaging. Applying the detector platform to the progression of a triple-negative breast cancer model, we found that miR-155 upregulation in corresponding tumors was dependent on macrophage presence in tumors, revealing immune-mediated phenotypic changes in these tumors as they progressed. While applied to immunooncology in this work, this multimodal in vivo microRNA detector platform will be useful whenever non-invasive quantification of spatiotemporal microRNA changes in living animals is of interest.

Structure-based drug design-guided identification of estrogen receptor binders.

Cancer is one of the life-threatening diseases and the second leading cause of death in the world. The estrogen receptor can be considered as one of the significant drug targets for cancer. A large number of clinically used anticancer drugs were identified from phytochemicals. Multiple literatures suggested that extracts of Datura sp. significantly inhibit estrogen receptors associated with human cancer. In the present study, all reported natural products present in Datura sp. were subjected to molecular docking against estrogen receptors. The top hits were shortlisted based on binding orientation and docking score and subjected to molecular dynamics simulation to explore the conformational stability followed by binding energy calculation. The ligand [(1S,5R)-8-Methyl-8-Azabicyclo [3.2.1] Octan-3-yl] (2R)-3-Hydroxy-2-Phenylpropanoate depicts highly acceptable MD simulations outcomes and drug-likeness profile. Knowledge-based de novo design and similar ligand screening were executed using the structural information. The designed ligand DL-50 exhibited satisfactory binding, drug-likeness profile, and well-accepted ADMET profile followed by easy synthetic accessibility which further requires experimental validation.

Distinctive Formation of a DNA-Protein Cross-Link during the Repair of DNA Oxidative Damage: Insights into Human Disease from MD Simulations and QM/MM Calculations.

Reactive oxygen species damage DNA and result in health issues. The major damage product, 8-oxo-7,8-dihydroguanine (8oG), is repaired by human adenine DNA glycosylase homologue (MUTYH). Although MUTYH misfunction is associated with a genetic disorder called MUTYH-associated polyposis (MAP) and MUTYH is a potential target for cancer drugs, the catalytic mechanism required to develop disease treatments is debated in the literature. This study uses molecular dynamics simulations and quantum mechanics/molecular mechanics techniques initiated from DNA-protein complexes that represent different stages of the repair pathway to map the catalytic mechanism of the wild-type MUTYH bacterial homologue (MutY). This multipronged computational approach characterizes a DNA-protein cross-linking mechanism that is consistent with all previous experimental data and is a distinct pathway across the broad class of monofunctional glycosylase repair enzymes. In addition to clarifying how the cross-link is formed, accommodated by the enzyme, and hydrolyzed for product release, our calculations rationalize why cross-link formation is favored over immediate glycosidic bond hydrolysis, the accepted mechanism for all other monofunctional DNA glycosylases to date. Calculations on the Y126F mutant MutY highlight critical roles for active site residues throughout the reaction, while investigation of the N146S mutant rationalizes the connection between the analogous N224S MUTYH mutation and MAP. In addition to furthering our knowledge of the chemistry associated with a devastating disorder, the structural information gained about the distinctive MutY mechanism compared to other repair enzymes represents an important step for the development of specific and potent small-molecule inhibitors as cancer therapeutics.

The Zinc-Binding Group Effect: Lessons from Non-Hydroxamic Acid Vorinostat Analogs.

Histone deacetylases (HDACs) are enzymes pursued as drug targets in various cancers and several non-oncological conditions, such as inflammation and neurodegenerative disorders. In the past decade, HDAC inhibitors (HDACi) have emerged as relevant pharmaceuticals, with many efforts devoted to the development of new representatives. However, the growing safety concerns regarding the established hydroxamic acid-based HDAC inhibitors tend to drive current research more toward the design of inhibitors bearing alternative zinc-binding groups (ZBGs). This Perspective presents an overview of all non-hydroxamic acid ZBGs that have been incorporated into the clinically approved prototypical HDACi, suberoylanilide hydroxamic acid (vorinostat). This provides the unique opportunity to compare the inhibition potential and biological effects of different ZBGs in a direct way, as the compounds selected for this Perspective differ only in their ZBG. To that end, different strategies used to select a ZBG, its properties, activity, and liabilities are discussed.

Abstract A037: Kinase GRK3 connects angiogenesis and neuroendocrine differentiation in prostate cancer progression by enhancing epigenetic activity of HDAC2

Abstract Background: Treatment-related neuroendocrine prostate cancer (NEPC) is an aggressive subset of castration-resistant prostate cancer (CRPC), found in ~20% of lethal CRPC. The mechanisms underlying the progression of prostate cancer to NEPC are largely unclear, and new drug targets are desperately needed. NEPC is known to be highly vascularized. Elevated expression of NE markers and increased angiogenesis are two prominent phenotypes of NEPC, and thus are expected to be linked. However, direct molecular links between these two phenotypes are still elusive, whose elucidation will substantially expand our knowledge in NEPC and enable the development of effective treatments for NEPC. Through RNAi & cDNA screening and functional validations, we previously discovered that GPCR-kinase 3 (GRK3) is essential preferentially for highly metastatic cancer cells as compared to lowly metastatic cancer cells. The mechanisms of GRK3 in prostate cancer progression were mostly unknown. Methods: We assessed GRK3’s expression in patient samples through IHC staining on TMA and data mining on public RNA-seq datasets with large cohorts. Using molecular and cell biology methods, we determined the impacts of GRK3 and HDAC2 overexpression and silencing on NE marker expression and angiogenesis in prostate cancer cells. Through biochemistry, we investigated the nature of GRK3-HDAC2 relation. By ChIP-PCR, we measured the impacts of GRK3 genetic and pharmacological modulations on HDAC2’s epigenetic activity. Through compound library screening and biochemical characterization, we searched for novel GRK3 inhibitors to study GRK3 biology and to evaluate whether GRK3 is a suitable drug target for prostate cancer. Results: GRK3 is significantly overexpressed in metastatic prostate tumors from patients, especially in NEPC. GRK3 promotes both angiogenesis and neuroendocrine differentiation in prostate cancer cells, indicating that it is a key missing link for these two phenotypes. Mechanistically, GRK3 enhances the epigenetic repressor activity of histone deacetylase 2 (HDAC2) to suppress key repressors of angiogenesis or NE phenotype. We have identified several compounds that block kinase activity of GRK3 much more potently than that of GRK2, the closest-related kinase to GRK3. Of note, our GRK3 inhibitors could substantially reduce angiogenesis and NE marker expression, as well as significantly inhibit NEPC cell growth in culture and in mouse xenografts. Conclusion: Kinase GRK3 connects angiogenesis and neuroendocrine differentiation in prostate cancer progression. Its mechanism of actions is at least in part through enhancing HDAC2’s epigenetic activity. Results based on our novel GRK3 inhibitors suggest that GRK3 is a valuable new drug target for aggressive prostate cancer. Citation Format: Samira Naderinezhad, Zheng Wang, Guoliang Zhang, Michael Ittmann, Martin Gleave, Wenliang Li. Kinase GRK3 connects angiogenesis and neuroendocrine differentiation in prostate cancer progression by enhancing epigenetic activity of HDAC2 [abstract]. In: Proceedings of the AACR Special Conference: Advances in Prostate Cancer Research; 2023 Mar 15-18; Denver, Colorado. Philadelphia (PA): AACR; Cancer Res 2023;83(11 Suppl):Abstract nr A037.

Association between targeted cancer drug net health benefit and uptake, patient out-of-pocket spending, and total spending.

6644 Background: Targeted cancer drugs (TCDs) have revolutionized oncology, but they are widely variable in their clinical benefit and are often accompanied by high patient-out-pocket (OOP) costs. The ASCO Value Framework uses published clinical trial data on survival, toxicity, and potential for symptom palliation to quantify the net health benefit (NHB) of any given cancer drug. We aimed to evaluate the association between NHB and uptake, patient OOP spending, and total spending for eight oral TCDs approved for the first line treatment of an advanced solid tumor based on one or more clinical trials comparing to a non-TCD control arm. Methods: We conducted a retrospective cohort study of incident pharmacy claims for oral TCDs prescribed to patients aged 18-64 years between 2012-2020 in the nationwide Health Care Cost Institute de-identified commercial claims dataset. NHB scores were calculated for each TCD of interest using the ASCO Value Framework and categorized as high (>60), medium (40-60), and low (<40) net health benefit. Distributions of incident 28-day TCD supplies were plotted over time by NHB category. The primary outcome was patient OOP spending (patient copay + coinsurance + deductible), whereas the secondary outcome was total spending (patient OOP spending + pharmacy reimbursement). Generalized linear models were used to evaluate the association between each outcome of interest and TCD NHB, adjusted for cancer indication. Results: We included 8,524 incident pharmacy claims for eight TCDs with nine indications in breast cancer, non-small cell lung cancer (NSCLC), melanoma, and pancreatic cancer. NHB scores ranged from 7 (erlotinib for pancreatic cancer) to 81 (crizotinib for ALK-rearranged NSCLC), with 1,145 (13%), 6,608 (78%), and 771 (9%) of pharmacy claims falling into low-, medium-, and high-NHB categories, respectively. Medium- and high-NHB TCDs accounted for the majority of incident TCD prescriptions throughout the study period. Median patient OOP spending was $18.78 for the first 28-day TCD supply (IQR $0.00-$87.57), with 45% of patients paying $0 and 8% paying >$1,000 OOP. Patient OOP spending was not significantly associated with TCD NHB category (difference $0.94, 95% CI -$49.99-$51.87 for medium vs low NHB; difference $58.86, 95% CI -$28.04-$145.75 for high vs low NHB). Median total spending was $10,118.79 (IQR $6,365.95-$10,600.37) for an incident 28-day TCD supply. There was a $1,083.56 increase in total spending for each 10-point increase in NHB score (95% CI $1,050.27-$1,116.84, p <0.01 for H0 = $0). Conclusions: Although TCDs are widely variable in their NHB, low-NHB TCDs are not prescribed as frequently as medium- and high-NHB TCDs. Total spending on TCDs is high and positively associated with NHB. Commercially insured patients are largely shielded from high OOP spending on TCDs.

RGD-engineered nanoparticles as an innovative drug delivery system in cancer therapy

The poor efficiency and drastic adverse effects of current cancer therapies entail a radical shift in treatment paradigms, which require developing cutting-edge therapeutics in laboratories and bringing them to rigorous preclinical and clinical testing. The principal drawbacks of present cancer therapies are the incapability of tumor targeting, uneven drug accumulation at the site of action, and poor tumor monitoring. Accordingly, incorporating nanoparticles (NPs) has made clinical progress in conveying conventional or candidate therapeutic molecules to the site of action, encouraging anticancer impacts. Interestingly, modern cancer therapy has lately been redefined by the functionalizing NPs with active targeting ligands like the Arginine-Glycine-Aspartic acid (RGD) peptide, remarkably strengthening the therapeutic outcomes and diminishing off-target effects. The overexpression of integrin receptors on the surface of cancerous cells brought a unique opportunity for cancer-targeted drug delivery since RGD-decorated nanocarriers precisely recognize these receptors and selectively transport their chemotherapeutic or diagnostic payloads to the cancerous cells. Subsequently, RGD-conjugated NPs have frequently been enlisted for cancer diagnosis and imaging-guided surgery, improving therapeutics strength and overwhelming drug resistance. Here, we discussed the relevance of integrin receptors in carcinogenesis and thoroughly deliberated the potential of RGD-functionalized NPs as innovative drug delivery platforms in modern cancer therapy.