Oncology Drug Discovery Research Articles

Drug Discovery Goes Three-Dimensional: Goodbye to Flat High-Throughput Screening?

Immortalized cells, generated from two-dimensional cell culture techniques, are widely used in compound screening, lead optimization, and drug candidate selection. However, such cells lack many characteristics of cells in vivo. This could account for the high failure rates of lead candidates in clinical evaluation. New approaches from cell biology, materials science, and bioengineering are increasing the utility of three-dimensional (3D) culture. These approaches have become more compatible with automation and, thus, provide more physiologically relevant cells for high-throughput/high-content screening, notably in oncology drug discovery. Techniques range from simple 3D spheroids, comprising one or more cell types, to complex multitissue organoids cultured in extracellular matrix gels or microfabricated chips. Furthermore, each approach can be applied to stem cells, such as induced pluripotent stem cells, thereby providing additional phenotypic relevance and the exciting potential to enable screening in disease-specific cell types.

Abstract P2-06-07: StemScreen®, an innovative platform technology for the identification of novel cancer stem cell-directed compounds

Abstract Cancer stem cells (CSCs) are thought to play significant roles in breast cancer initiation and progression. Conventional therapeutic agents target tumor bulk but spare CSCs, leading to tumor recurrence and relapse. Therefore, drugs that eliminate both tumor bulk and CSCs may represent the most effective treatment strategy for breast cancer. We have developed a proprietary cell-based screen called StemScreen® that permits the rapid testing and identification of novel CSC-directed compounds in a high-throughput manner. StemScreen® takes advantage of a landmark discovery that many cancer cell lines harbor stable populations of CSCs. Our initial studies utilized a breast cancer cell line transfected with a unique expression vector that is only active in the 1-5% putative CSC population. The StemScreen® platform is unique because it allows for screening of compounds within the context of the CSCs’ natural microniche environment and has advantages over traditional drug discovery methods that have been designed to identify compounds that only target tumor bulk, but not CSCs. In an effort to increase the throughput and make the assay compatible with existing compound libraries, we miniaturized the platform to a 384-well format and optimized the line for high-content screening. A series of compound hits identified from screening these cells against smaller libraries of known active compounds as well as larger and more diverse compound libraries will be presented. We are also currently expanding this technology into other tumor types. We believe that this approach represents a major technological advance in oncology drug discovery and that this platform will be instrumental in the discovery of unique new therapies that have a dual effect on CSCs and non-CSC tumor bulk. Citation Format: Janice Chen, Hai Li, Marcie A Glicksman, Charles Karan, Christopher Brooks, Eric K Rowinsky. StemScreen®, an innovative platform technology for the identification of novel cancer stem cell-directed compounds [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P2-06-07.

Recent advances in cancer therapeutics.

In the past 20 years, cancer therapeutics has undergone a paradigm shift away from the traditional cytotoxic drugs towards the targeting of proteins intimately involved in driving the cancer phenotype. The poster child for this alternative approach to the treatment of cancer is imatinib, a small-molecule kinase inhibitor designed to target chronic myeloid leukaemia driven by the BCR-ABL translocation in a defined patient population. The improvement in survival achieved by treatment of this patient cohort with imatinib is impressive. Thus, the aim is to provide efficacy but with low toxicity. The role of the medicinal chemist in oncology drug discovery is now closely aligned with the role in most other therapeutic areas with high-throughput and/or fragment-based screening, structure-based design, selectivity, pharmacokinetic optimisation and pharmacodynamic biomarker modulation, all playing a familiar part in the process. In this chapter, we selected four areas in which compounds are either approved drugs or in clinical trials. These are chaperone inhibitors, kinase inhibitors, histone deacetylase inhibitors and inhibitors of protein-protein interactions. Even within these areas, we have been selective, particularly for kinase inhibitors, and our aim has been to exemplify newer approaches and novel aspects of medicinal chemistry.

Novel stem-cell-based approaches in the development of cyclin-dependent kinase inhibitors as new therapeutics in cardiology

Cardiovascular diseases (CVD) remain the leading cause of morbidity and mortality worldwide, resulting in more than 17.5 million global deaths per annum. Current therapeutic treatments are limited in effectiveness, and research in the field of cardiology is ongoing to address this alarming health issue. The lack of physiologically relevant preclinical models has been identified as the underlying cause of inefficacy where preclinical trials of therapies have often looked to animal models. As a consequence, innovative research into the use of stem cells as model systems in cardiovascular drug discovery is underway. Human embryonic stem cells (hESCs) hold great promise in bringing new and effective cardiovascular treatments to the market through providing an improved testing platform for pre-clinical drug screening. Cardiomyocytes derived from hESCs aim to overcome the lack of physiologically relevant preclinical models for toxicology testing by providing a novel system that is scalable, reproducible and from an inexhaustible source. Recent research carried out at Abertay University in Dundee, has established a novel human ‘miniheart’ cell-based assay, which involves inducing cardiac hypertrophy within hESC-derived cardiomyocyte clusters using growth factors including Angiotensin II and Endothelin-1. This allows for assessment of the therapeutic potential of novel compounds in treating the hypertrophic condition, and avoids the contentious use of animal models. The effectiveness of cyclin-dependent kinase (CDK) inhibitors as drug candidates for therapeutic intervention in cardiac hypertrophy is currently under investigation. Our data has demonstrated that the CDK inhibiting compounds are successful in preventing the induction of cardiac hypertrophy through inhibition of CDK9. Memoir: Nikolai Zhelev is Professor of Medical Biotechnology and Director of CMCBR at Abertay University, Dundee, Scotland. He is also honorary professor in eight universities in UK, China and Bulgaria. Prof. Zhelev has been involved in founding four start-up biotech companies. He is author of books, patents and papers in the field of DNA damage response, cell cycle regulation and drug discovery and development in oncology and cardiology published in reputed journals such as Nature Medicine. Prof Zhelev is currently the President of the European BioDiscovery Federation. Introduction: Industrial Biotechnology is the study of the use of enzymes and the use of microorganisms is done to make bio-based products in various sectors such as chemicals, food ingredients, paper, textiles, and many other industries. Industrial Biotechnology is one of the most important fields in working for the implications of health and medicine. Industrial biotechnology involves working with nature to maximize and optimize existing biochemical pathways that can be used in manufacturing. The industrial biotechnology revolution rides on a series of related developments in three fields of study of detailed information derived from the cell: genomics, proteomics, and bioinformatics.

AACR-NCI-EORTC - 27th International Symposium - Molecular Targets and Cancer Therapeutics (November 5-9, 2015 - Boston, Massachusetts, USA).

The 27th joint meeting of the European Organization for Research and Treatment of Cancer, National Cancer Institute and the American Association of Cancer Research (EORTC-NCI-AACR) International Conference on Molecular Targets and Cancer Therapeutics was held this year in Boston. Approximately 3,000 international academics, scientists and pharmaceutical industry representatives discussed new discoveries in the field of molecular biology of cancer and presented the latest information on drug discovery, preclinical research, clinical research and target selection in oncology. This report summarizes data on advances in cancer drug discovery.

Patient-derived xenograft models for oncology drug discovery

The success of targeted therapies for cancer patients rests on three major components: the right target(s), the right drug and drug combination, and the right patient population. Although much progress has been made in understanding the mechanism of disease and in refining pharmaceutical properties of therapeutic agents, the attrition rates between target discovery and drug marketing approval have been high, especially in oncology. One of the main reasons underlying this undesirable statistics is believed to be the lack of predictive power of the model systems used in the preclinical setting. Several strategies have been employed with the aim of improving the predictive value of the preclinical studies, such as incorporating genomic profiling and molecular segmentation into model selection, and enhancing the development and application of patient-derived xenograft models even during early stage of drug discovery. This brief review will summarize some of the recent concept and practice in incorporating patient-derived models into all stages of drug discovery process, from target to clinical development.

Abstract 323: Development of high throughput flow cytometry assays to support target therapy/personalized medicine in oncology drug discovery and development: Developing and optimizing a flow cytometry-based autophagy detection method/panel for oncology drug discovery and development

Abstract Background: Pharmacodynamics (PD) endpoint assays are important biomarker(s) for target therapy/personalized medicine in oncology drug discovery & development. Identification of the informative PD biomarkers/readouts can support dose selection in clinical trials, identify the patient subsets, explore mechanism of action, or differentiate compound(s) over others. Emerging evidence indicates that enhanced autophagy promotes tumor progression in established tumors, and inhibition of autophagy is recognized as a novel adjuvant cancer therapeutic strategy when combined with conventional chemotherapy for maximum therapeutic efficacy and overcoming chemoresistance. PI3K/mTOR inhibitors have been developed for cancer treatment and, when combined with an autophagy inhibitor, display synergistically improved efficacy. This synergy consequently has lead to multiple clinical programs to assess combination therapy regimes. Development of reliable high throughput PD readouts to measure autophagy modulation is critical for discovery of selective modulators, and/or identification of biomarkers either for patient selection or drug combination strategy for clinical development. Methods: Human U87MG glioblastoma and MCF7 breast cancer cells were treated with the PI3K/mTOR inhibitor Rapamycin with or without the autophagy inhibitor Hydroxychloroquine (HCQ). Sequestered LC3 (microtubule-associated protein1 light chain 3), which is recognized as an autophagy marker, was detected in cells by flow cytometry. 7-AAD/Annexin V staining were used for cell viability analysis. The efficacy of individual compounds and optimal combination doses were identified with a cell proliferation assay. Results: Our results indicated that autophagy was induced by Rapamycin treatment. Autophagy inhibitor Hydroxychloroquine exhibits dose dependent inhibition of in vitro proliferation of U87 MG and MCF-7 tumor cells. U87 MG cells are more sensitive to autophagy inhibition than MCF-7 breast cancer cells. Enhanced inhibition of cellular proliferation and increased cell death were observed in U87MG and MCF-7 cells in combination regime when compared to treatment with either compound alone. Conclusion: We developed a High Throughput flow cytometry based method for screening pharmacodynamics biomarker panel for supporting dose selection and/or identify optimal combinations in oncology drug discovery& development. The dynamic impacts of treatments on the activation status of autophagy at various time points are currently under investigation, and we are continuing to expand flow cytometry panels by incorporating other potential biomarkers. Studies are funded by EMD Millipore (a division of Merck KGaA, Darmstadt, Germany). Note: This abstract was not presented at the meeting. Citation Format: Zheng Feng, Theodore Baginski, Michael Donio, Diane Werth, Jacob Bode. Development of high throughput flow cytometry assays to support target therapy/personalized medicine in oncology drug discovery and development: Developing and optimizing a flow cytometry-based autophagy detection method/panel for oncology drug discovery and development. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 323. doi:10.1158/1538-7445.AM2014-323

Phenotypic screening in cancer drug discovery - past, present and future.

There has been a resurgence of interest in the use of phenotypic screens in drug discovery as an alternative to target-focused approaches. Given that oncology is currently the most active therapeutic area, and also one in which target-focused approaches have been particularly prominent in the past two decades, we investigated the contribution of phenotypic assays to oncology drug discovery by analysing the origins of all new small-molecule cancer drugs approved by the US Food and Drug Administration (FDA) over the past 15 years and those currently in clinical development. Although the majority of these drugs originated from target-based discovery, we identified a significant number whose discovery depended on phenotypic screening approaches. We postulate that the contribution of phenotypic screening to cancer drug discovery has been hampered by a reliance on 'classical' nonspecific drug effects such as cytotoxicity and mitotic arrest, exacerbated by a paucity of mechanistically defined cellular models for therapeutically translatable cancer phenotypes. However, technical and biological advances that enable such mechanistically informed phenotypic models have the potential to empower phenotypic drug discovery in oncology.

The KDM5 family of histone demethylases as targets in oncology drug discovery.

There is growing evidence for a causal role of the KDM5 family of histone demethylases in human cancer. In particular, KDM5A (JARID1A/RBP2) and KDM5B (JARID1B/PLU1) contribute to cancer cell proliferation, reduce the expression of tumor suppressor genes, promote the development of drug tolerance and maintain tumor-initiating cells. KDM5 enzymes remove tri- and di-methylations of lysine 4 of histone H3 - modifications that occur at the start site of transcription in actively transcribed genes. However, the importance of the histone demethylase activity of KDM5 proteins for cancer cells has not been resolved so far. The currently available approaches suppress or remove the targeted proteins and thereby affect their putative functions as structural components and recruitment factors for other chromatin-associated proteins. Therefore, the development of specific enzymatic inhibitors for KDM5 will promote our understanding of the biological role of their catalytic activity and yield potential novel anticancer therapeutics.

Integrative oncology drug discovery accompanied by preclinical translational research as prerequisite for clinical development.

The molecular heterogeneity of cancer calls for individualized therapies to become the standard of care. It is now generally accepted that target-specific compounds require specific new development programs. But, even for new drugs with general mode of action (i.e., chemotherapy), tailored treatment approaches, such as specific schedules or combinations, have been shown to improve the therapeutic outcome. Therefore, the preclinical development of new therapeutic agents needs, next to the "classical pharmacodynamic studies", the implementation of integrative translational research (TR) as early as possible. New TR approaches, starting already at target identification and validation (TIV) will allow to defining the optimal patient population for clinical development, to tailor individual treatment of the tumor disease and to choose a rational basis among the manifold options for treatment combinations. We will discuss several examples from TR studies, which have initially been started to evaluate the molecular mode of action and to recognize mechanisms which can lead to resistance. Research was extended later to identify predictive response biomarkers and establish a rationale for combination with different therapies. A detailed gene expression analysis of lung cancer cells and apoptotic pathway interference studies in colon cancer cells provided insight in the molecular mechanisms of action. These new findings are correlated with results from other studies performed during the preclinical development program. We discuss pros and cons, successes and failures of our integrative preclinical development program and provide recommendations for future oncology projects.

Oncology Drug Discovery: Planning a Turnaround

We have made remarkable progress in our understanding of the pathophysiology of cancer. This improved understanding has resulted in increasingly effective targeted therapies that are better tolerated than conventional cytotoxic agents and even curative in some patients. Unfortunately, the success rate of drug approval has been limited, and therapeutic improvements have been marginal, with too few exceptions. In this article, we review the current approach to oncology drug discovery and development, identify areas in need of improvement, and propose strategies to improve patient outcomes. We also suggest future directions that may improve the quality of preclinical and early clinical drug evaluation, which could lead to higher approval rates of anticancer drugs.

Systems oncology: A new paradigm in cancer research.

Systems oncology: A new paradigm in cancer research.

Recent Developments in Cancer Treatment: A Review

According to the latest cancer statistics presented worldwide, there has been a dramatic increase in the rates of occurrence of some cancers, particularly in the more developed countries. Although many therapeutic strategies to prevent and/or cure this disease have been proposed and evaluated by clinicians and researchers, there remains a need to find more effective approaches. Side effects such as toxicity and drug resistance are two of the most frequent problems faced during chemotherapy. Small - molecule drugs are being intensively pursued as new anticancer therapeutics. Oncology drug discovery has benefited significantly from progress in understanding how to target kinases with small molecules that were found to be correlated with the disease. One reason for this is that many kinases have been found to be intimately involved in the processes leading to tumor cell proliferation and survival. Monoclonal antibodies, that are produced in vitro, can be used in cancer treatment in a number of ways. They may enhance the immune system by reacting with certain types of cancer cells. They can be programmed to act against specific cell growth factors to interfere with the growth of cancer cells. Furthermore, they may be linked to anticancer drugs, radioactive substances, other biologic therapies, or other toxins (antibody – omicsonline.orgdrug conjugates). Finally, the usage of cytotoxic monoclonal antibodies during the process of bone marrow transplantation may be a key to improve the efficacy of the method. The objective of this review was to present some of the new cancer treatment modalities that have been developed. The advantages of each method including its safety and efficacy have been highlighted. The present study may support the improvement and development of new therapeutic approaches.

A matrix approach to guide IHC‐based tissue biomarker development in oncology drug discovery

Immunohistochemistry (IHC) is a core platform for the analysis of tissue samples, and there is an increasing demand for reliable and quantitative IHC-based tissue biomarkers in oncology clinical research and development (R&D) environments. Biomarker assay and drug development proceed in parallel. Furthermore, biomarker assay requirements change with each phase of drug development. We have therefore developed a matrix tool to enable researchers to evaluate whether a particular IHC biomarker assay is fit for purpose. Experience gained from the development of 130 IHC biomarkers, supporting a large number of oncology drug projects, was used to formulate a practical approach to IHC assay development. The resultant matrix grid and accompanying work flow incorporates 16 core decision points that link antibody and assay specificity and sensitivity, and assay performance in preclinical and clinical samples, with stages of drug development. The matrix provides a means to ensure that relevant information on an IHC assay in development is recorded and communicated consistently and that minimum assay validation requirements are met.

Pathology in drug discovery and development

The rapid pace of drug discovery and drug development in oncology, immunology and ophthalmology brings new challenges; the efficient and effective development of new targeted drugs will require more detailed molecular classifications of histologically homogeneous diseases that show heterogeneous clinical outcomes. To this end, single companion diagnostics for specific drugs will be replaced by multiplex diagnostics for entire therapeutic areas, preserving tissue and enabling rapid molecular taxonomy. The field will move away from the development of new molecular entities as single agents, to which resistance is common. Instead, a detailed understanding of the pathological mechanisms of resistance, in patients and in preclinical models, will be key to the validation of scientifically rational and clinically effective drug combinations. To remain at the heart of disease diagnosis and appropriate management, pathologists must evolve into translational biologists and biomarker scientists. Herein, we provide examples of where this metamorphosis has already taken place, in lung cancer and melanoma, where the transformation has yet to begin, in the use of immunotherapies for ophthalmology and oncology, and where there is fertile soil for a revolution in treatment, in efforts to classify glioblastoma and personalize treatment. The challenges of disease heterogeneity, the regulatory environment and adequate tissue are ever present, but these too are being overcome in dedicated academic centres. In summary, the tools necessary to overcome the 'whens' and 'ifs' of the molecular revolution are in the hands of pathologists today; it is a matter of standardization, training and leadership to bring these into routine practice and translate science into patient benefit. This Annual Review Issue of the Journal of Pathology highlights the central role for pathology in modern drug discovery and development.

Applications of Pathology-Assisted Image Analysis of Immunohistochemistry-Based Biomarkers in Oncology

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

Abstract B9: Tumor growth rate analysis enables cost efficient design of preclinical pharmacology studies.

Abstract Xenograft models are widely used in the oncology drug discovery and development process. However, the lack of available information regarding the xenograft models, such as growth curves, standard of care treatment results, IHC analysis of biomarkers, as well as target gene expression, mutation, and amplification, hampers the selection of suitable models for accurate evaluation of therapeutic molecules. We have created XenoBase™ that combines public cell line profiling data with our own pharmacology data on >180 xenograft models. A searching engine is also built in the database to search for models based on gene mutation, expression, amplification, as well as SOC information, types (orthotopic, subcutaneous, systemic) of the xenograft models. The XenoBase™ will enable informed decision in selecting the most relevant models for the development of targeted therapeutics. Armed with hundreds of xenograft studies available in the XenoBase™, we analyzed the tumor growth rate of each study to compare the results with traditional T/C analysis. The T/C analysis is the current standard, and a T/C value less than 0.42 is widely accepted as an indication of efficacy in evaluating a test article. However, this T/C analysis is limited in using only the data points on one day, overlooking the fact that tumor growth curves are generated over a long period of time (months) and with many days of data collection. To take advantage of the tumor growth curves, we analyzed tumor growth rate utilizing every data point, and derived growth rate based on slopes. Our analysis with the XenoBase™ data indicated that the growth rate based approach is more powerful in evaluating test articles for efficacy compared to T/C analysis or area under the curve (AUC) analysis. If adopted by the industry, this approach may save hundreds of millions of dollars spent in excess number of animals and prolonged observations that may not be necessary. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B9. Citation Format: Sheng Guo, Jun Li, Juan Zhang, Wubin Qian, Qian Shi. Tumor growth rate analysis enables cost efficient design of preclinical pharmacology studies. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr B9.

Establishing a High-Throughput and Automated Cancer Cell Proliferation Panel for Oncology Lead Optimization

Tumor cell proliferation assays are widely used for oncology drug discovery, including target validation, lead compound identification, and optimization, as well as determination of compound off-target activities. Taking advantage of robotic systems to maintain cell culture and perform cell proliferation assays would greatly increase productivity and efficiency. Here we describe the establishment of automated systems for high-throughput cell proliferation assays in a panel of 13 human tumor cell lines. These cell lines were selected from various types of human tumors containing a broad range of well-characterized mutations in multiple cellular signaling pathways. Standard procedures for cell culture and assay performance were developed and optimized in each cell line. Moreover, in-house developed software (i.e., Toolset, Curvemaster, and Biobars) was applied to analyze the data and generate data reports. Using tool compounds, we have shown that results obtained through this panel exhibit high reproducibility over a long period. Furthermore, we have demonstrated that this panel can be used to identify sensitive and insensitive cell lines for specific cancer targets, to drive cellular structure-activity relationships, and to profile compound off-target activities. All those efforts are important for cancer drug discovery lead optimization.

The Drug Annotations Series

ADVERTISEMENT RETURN TO ISSUEEditorialNEXTThe Drug Annotations SeriesJeff Zablocki* and Carlos Garcia-Echeverria*View Author Information Gilead Sciences Sanofi*For J.Z.: e-mail, [email protected] or [email protected]. J.Z. is a Senior Director at Gilead Sciences where he leads a team of scientists working on targets in multiple therapeutic areas (cardiovascular, oncology, inflammation, and antiviral). He has served as the ACS MEDI Chair and is an ACS Fellow.*For C.G.-E.: e-mail, [email protected]. C.G.-E. is Deputy Head Oncology Drug Discovery and Preclinical Development at Sanofi. He supervises the drug discovery, medicinal chemistry and in vivo pharmacology functions of the Sanofi oncology business unit. He is an ACS Fellow.Cite this: J. Med. Chem. 2013, 56, 17, 6541Publication Date (Web):September 3, 2013Publication History Published online3 September 2013Published inissue 12 September 2013https://doi.org/10.1021/jm401297rCopyright © 2013 American Chemical SocietyRIGHTS & PERMISSIONSArticle Views6566Altmetric-Citations-LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InReddit PDF (122 KB) Get e-AlertsSUBJECTS:Drug discovery,Mechanisms of action,Medicinal chemistry,Pharmaceuticals,Therapeutics Get e-Alerts

Inhibition of polo-like kinase 1 in glioblastoma multiforme induces mitotic catastrophe and enhances radiosensitisation

Glioblastoma multiforme (GBM) is the most common primary brain tumour in the United States of America (USA) with a median survival of approximately 14months. Low survival rates are attributable to the aggressiveness of GBM and a lack of understanding of the molecular mechanisms underlying GBM. The disruption of signalling pathways regulated either directly or indirectly by protein kinases is frequently observed in cancer cells and thus the development of inhibitors of specific kinases has become a major focus of drug discovery in oncology. To identify protein kinases required for the survival of GBM we performed a siRNA-based RNAi screen focused on the human kinome in GBM. Inhibition of the polo-like kinase 1 (PLK1) induced a reduction in the viability in two different GBM cell lines. To assess the potential of inhibiting PLK1 as a treatment strategy for GBM we examined the effects of a small molecule inhibitor of PLK1, GSK461364A, on the growth of GBM cells. PLK1 inhibition arrested cells in the mitotic phase of the cell cycle and induced cell kill by mitotic catastrophe. GBM engrafts treated with GSK461364A showed statistically significant inhibition of tumour growth. Further, exposure of different GBM cells to RNAi or GSK461364A prior to radiation resulted in an increase in their radiosensitivity with dose enhancement factor ranging from 1.40 to 1.53 with no effect on normal cells. As a measure of DNA double strand breaks, γH2AX levels were significantly higher in the combined modality as compared to the individual treatments. This study suggests that PLK1 is an important therapeutic target for GBM and can enhance radiosensitivity in GBM.