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Vaughan L.,The Institute of Cancer Research | Vaughan L.,University of Manchester | Clarke P.A.,Cancer Research UK Research Institute | Barker K.,The Institute of Cancer Research | And 18 more authors.
Oncotarget | Year: 2016

MYC oncoproteins deliver a potent oncogenic stimulus in several human cancers, making them major targets for drug development, but efforts to deliver clinically practical therapeutics have not yet been realized. In childhood cancer, aberrant expression of MYC and MYCN genes delineates a group of aggressive tumours responsible for a major proportion of pediatric cancer deaths. We designed a chemical-genetic screen that identifies compounds capable of enhancing proteasomal elimination of MYCN oncoprotein. We isolated several classes of compound that selectively kill MYCN expressing cells and we focus on inhibitors of PI3K/mTOR pathway in this study. We show that PI3K/mTOR inhibitors selectively killed MYCNexpressing neuroblastoma tumor cells, and induced significant apoptosis of transgenic MYCN-driven neuroblastoma tumors concomitant with elimination of MYCN protein in vivo. Mechanistically, the ability of these compounds to degrade MYCN requires complete blockade of mTOR but not PI3 kinase activity and we highlight NVP-BEZ235 as a PI3K/mTOR inhibitor with an ideal activity profile. These data establish that MYCN expression is a marker indicative of likely clinical sensitivity to mTOR inhibition, and provide a rationale for the selection of clinical candidate MYCN-destabilizers likely to be useful for the treatment of MYCN-driven cancers.


PubMed | Cancer Research UK Research Institute, Novartis, University of California at San Francisco and Cancer Research UK Cancer Therapeutics Unit
Type: Journal Article | Journal: Oncotarget | Year: 2016

MYC oncoproteins deliver a potent oncogenic stimulus in several human cancers, making them major targets for drug development, but efforts to deliver clinically practical therapeutics have not yet been realized. In childhood cancer, aberrant expression of MYC and MYCN genes delineates a group of aggressive tumours responsible for a major proportion of pediatric cancer deaths. We designed a chemical-genetic screen that identifies compounds capable of enhancing proteasomal elimination of MYCN oncoprotein. We isolated several classes of compound that selectively kill MYCN expressing cells and we focus on inhibitors of PI3K/mTOR pathway in this study. We show that PI3K/mTOR inhibitors selectively killed MYCN-expressing neuroblastoma tumor cells, and induced significant apoptosis of transgenic MYCN-driven neuroblastoma tumors concomitant with elimination of MYCN protein in vivo. Mechanistically, the ability of these compounds to degrade MYCN requires complete blockade of mTOR but not PI3 kinase activity and we highlight NVP-BEZ235 as a PI3K/mTOR inhibitor with an ideal activity profile. These data establish that MYCN expression is a marker indicative of likely clinical sensitivity to mTOR inhibition, and provide a rationale for the selection of clinical candidate MYCN-destabilizers likely to be useful for the treatment of MYCN-driven cancers.


News Article | January 6, 2016
Site: www.scientificcomputing.com

The world’s largest database for cancer drug discovery has been revolutionized by adding 3-D structures of faulty proteins and maps of cancer’s communication networks, according to Cancer Research UK-funded research published in Nucleic Acid Research on January 4, 2016.1 The updated canSAR database, developed at The Institute of Cancer Research, London, will allow scientists working in the UK and across the globe to design new cancer treatments more effectively. The canSAR database2 was launched in 2011 by researchers in the Cancer Research UK Cancer Therapeutics Unit at The Institute of Cancer Research (ICR) — with the ambitious goal of using Big Data approaches to build a detailed picture of how the majority of known human molecules behave. canSAR has already collated billions of experimental measurements mapping the actions of one million drugs and chemicals on human proteins, and has combined these data with genetic information and results from clinical trials. The new version of canSAR uses artificial intelligence to identify nooks and crannies on the surface of faulty cancer-causing molecules, as a key step in designing new drugs to block them. It also allows scientists to identify communication lines that can be intercepted within tumor cells, opening up potential new approaches for cancer treatment. The growing database now holds the 3-D structures of almost three million cavities on the surface of nearly 110,000 molecules. Cancer Research UK and the ICR together ensure that this resource is free to use for researchers around the world, giving them speedy access to key information. Dr. Bissan Al-Lazikani, team leader in computational biology at The Institute of Cancer Research, London, who led the Cancer Research UK-funded team that developed canSAR, said: “Our database is constantly growing with information and is the largest of its kind — with more than 140,000 users from over 175 countries. And we regularly develop new artificial intelligence technologies that help scientists make predictions and design experiments. Our aim is that cancer scientists will be armed with the data they need to carry out life-saving research into the most exciting drugs of the future. “Scientists need to find all the information there is about a faulty gene or protein to understand whether a new drug might work. These data are vast and scattered, but the canSAR database brings them together and adds value by identifying hidden links and presenting the key information easily.” Professor Paul Workman, chief executive of The Institute of Cancer Research, London, and a Cancer Research UK Life Fellow, said: “The canSAR database is an important part of the overall drive to use Big Data approaches to understand and treat cancer more effectively. canSAR is a massively powerful resource that’s used globally by researchers to gain rapid and easy-to-use access to a huge wealth of integrated knowledge in biology, chemistry and cancer medicine. This latest research has greatly enhanced the power of canSAR to enable scientists to select the best possible targets for future cancer drug discovery and also to help them develop really innovative drugs much more rapidly and effectively than ever before for the benefit of cancer patients worldwide.” Dr. Kat Arney, Cancer Research UK’s science information manager, said: “This database  makes masses of detailed scientific information about cancer available to scientists all over the world, and will speed up crucial advances in drug discovery — ultimately saving more lives. Finding new treatments for cancer can be a long and expensive process, so anything that cuts times and costs will help to bring the next generation of therapies to patients even sooner.”


News Article | January 4, 2016
Site: www.rdmag.com

The world's largest database for cancer drug discovery has been revolutionized by adding 3-D structures of faulty proteins and maps of cancer's communication networks, according to Cancer Research UK-funded research published in Nucleic Acid Research Monday. The updated canSAR database, developed at The Institute of Cancer Research, London, will allow scientists working in the UK and across the globe to design new cancer treatments more effectively. The canSAR database was launched in 2011 by researchers in the Cancer Research UK Cancer Therapeutics Unit at The Institute of Cancer Research (ICR) - with the ambitious goal of using Big Data approaches to build a detailed picture of how the majority of known human molecules behave. canSAR has already collated billions of experimental measurements mapping the actions of one million drugs and chemicals on human proteins, and has combined these data with genetic information and results from clinical trials. The new version of canSAR uses artificial intelligence to identify nooks and crannies on the surface of faulty cancer-causing molecules, as a key step in designing new drugs to block them. It also allows scientists to identify communication lines that can be intercepted within tumour cells, opening up potential new approaches for cancer treatment. The growing database now holds the 3-D structures of almost three million cavities on the surface of nearly 110,000 molecules. Cancer Research UK and the ICR together ensure that this resource is free to use for researchers around the world, giving them speedy access to key information. Dr Bissan Al-Lazikani, team leader in computational biology at The Institute of Cancer Research, London, who led the Cancer Research UK-funded team that developed canSAR, said: "Our database is constantly growing with information and is the largest of its kind - with more than 140,000 users from over 175 countries. And we regularly develop new artificial intelligence technologies that help scientists make predictions and design experiments. Our aim is that cancer scientists will be armed with the data they need to carry out life-saving research into the most exciting drugs of the future. "Scientists need to find all the information there is about a faulty gene or protein to understand whether a new drug might work. These data are vast and scattered, but the canSAR database brings them together and adds value by identifying hidden links and presenting the key information easily." Professor Paul Workman, chief executive of The Institute of Cancer Research, London, and a Cancer Research UK Life Fellow, said: "The canSAR database is an important part of the overall drive to use Big Data approaches to understand and treat cancer more effectively. canSAR is a massively powerful resource that's used globally by researchers to gain rapid and easy to use access to a huge wealth of integrated knowledge in biology, chemistry and cancer medicine. This latest research has greatly enhanced the power of canSAR to enable scientists to select the best possible targets for future cancer drug discovery and also to help them develop really innovative drugs much more rapidly and effectively than ever before for the benefit of cancer patients worldwide." Dr Kat Arney, Cancer Research UK's science information manager, said: "This database makes masses of detailed scientific information about cancer available to scientists all over the world, and will speed up crucial advances in drug discovery - ultimately saving more lives. Finding new treatments for cancer can be a long and expensive process, so anything that cuts times and costs will help to bring the next generation of therapies to patients even sooner."


Reader J.C.,Sareum Ltd. | Matthews T.P.,Cancer Research UK Cancer Therapeutics Unit | Klair S.,Sareum Ltd. | Cheung K.-M.J.,Cancer Research UK Cancer Therapeutics Unit | And 26 more authors.
Journal of Medicinal Chemistry | Year: 2011

Pyrazolopyridine inhibitors with low micromolar potency for CHK1 and good selectivity against CHK2 were previously identified by fragment-based screening. The optimization of the pyrazolopyridines to a series of potent and CHK1-selective isoquinolines demonstrates how fragment-growing and scaffold morphing strategies arising from a structure-based understanding of CHK1 inhibitor binding can be combined to successfully progress fragment-derived hit matter to compounds with activity in vivo. The challenges of improving CHK1 potency and selectivity, addressing synthetic tractability, and achieving novelty in the crowded kinase inhibitor chemical space were tackled by multiple scaffold morphing steps, which progressed through tricyclic pyrimido[2,3-b] azaindoles to N-(pyrazin-2-yl)pyrimidin-4-amines and ultimately to imidazo[4,5-c]pyridines and isoquinolines. A potent and highly selective isoquinoline CHK1 inhibitor (SAR-020106) was identified, which potentiated the efficacies of irinotecan and gemcitabine in SW620 human colon carcinoma xenografts in nude mice. (Figure presented) © 2011 American Chemical Society.

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