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Buckingham M.,Institute Pasteur Paris | Rigby P.W.J.,Institute of Cancer Research
Developmental Cell | Year: 2014

We discuss the upstream regulators of myogenesis that lead to the activation of myogenic determination genes and subsequent differentiation, focusing on the mouse model. Key upstream genes, such as Pax3 and Pax7, Six1 and Six4, or Pitx2, participate in gene regulatory networks at different sites of skeletal muscle formation. MicroRNAs also intervene, with emerging evidence for the role of other noncoding RNAs. Myogenic determination and subsequent differentiation depend on members of the MyoD family. We discuss new insights into mechanisms underlying the transcriptional activity of these factors. © 2014 Elsevier Inc.

Gyrd-Hansen M.,Copenhagen University | Meier P.,Institute of Cancer Research
Nature Reviews Cancer | Year: 2010

The realization that alterations in inhibitor of apoptosis (IAP) proteins are found in many types of human cancer and are associated with chemoresistance, disease progression and poor prognosis, has sparked a worldwide frenzy in the development of small pharmacological inhibitors of IAPs. The development of such inhibitors has radically changed our knowledge of the signalling processes that are regulated by IAPs. Recent studies indicate that IAPs not only regulate caspases and apoptosis, but also modulate inflammatory signalling and immunity, mitogenic kinase signalling, proliferation and mitosis, as well as cell invasion and metastasis. © 2010 Macmillan Publishers Limited. All rights reserved.

Greaves M.,Institute of Cancer Research
Nature Reviews Cancer | Year: 2014

Around one in three individuals, if they live long enough, will have a confirmed clinical diagnosis of overt cancer, and there is increasing evidence that many of us-I contend all of us-develop covert cancer. © 2014 Macmillan Publishers Limited. All rights reserved.

Acute lymphoblastic leukemia (ALL) is the major pediatric cancer diagnosed in economically developed countries with B-cell precursor (BCP)-ALL, accounting for approximately 70% of ALL. Recent genome-wide association studies (GWAS) have provided the first unambiguous evidence for common inherited susceptibility to BCP-ALL, identifying susceptibility loci at 7p12.2, 9p21.3, 10q21.2, and 14q11.2. To identify additional BCP-ALL susceptibility loci, we conducted a GWAS and performed a meta-analysis with a published GWAS totaling 1658 cases and 4723 controls, with validation in 1449 cases and 1488 controls. Combined analysis identified novel loci mapping to 10p12.2 (rs10828317, odds ratio [OR] = 1.23; P = 2.30 × 10(-9)) and 10p14 marked by rs3824662 (OR = 1.31; P = 8.62 × 10(-12)). The single nucleotide polymorphism rs10828317 is responsible for the N215S polymorphism in exon 7 of PIP4K2A, and rs3824662 localizes to intron 3 of the transcription factor and putative tumor suppressor gene GATA3. The rs10828317 association was shown to be specifically associated with hyperdiploid ALL, whereas the rs3824662-associated risk was confined to nonhyperdiploid non-TEL-AML1 + ALL. The risk allele of rs3824662 was correlated with older age at diagnosis (P < .001) and significantly worse event-free survivorship (P < .0001). These findings provide further insights into the genetic and biological basis of inherited genetic susceptibility to BCP-ALL and the influence of constitutional genotype on disease development.

Background and purpose: Randomised trials testing 15- or 16-fraction regimens of adjuvant radiotherapy in women with early breast cancer have reported favourable outcomes compared with standard fractionation. To evaluate hypofractionation further, two 5-fraction schedules delivering 1 fraction per week have been tested against a 25-fraction regimen. Materials and methods: Women aged ≥50 years with node negative early breast cancer were randomly assigned after microscopic complete tumour resection to 50 Gy in 25 fractions versus 28.5 or 30 Gy in 5 once-weekly fractions of 5.7 or 6.0 Gy, respectively, to the whole breast. The primary endpoint was 2-year change in photographic breast appearance. Results: Nine hundred and fifteen women were recruited from 2004 to 2007. Seven hundred and twenty-nine patients had 2-year photographic assessments. Risk ratios for mild/marked change were 1.70 (95% CI 1.26-2.29, p < 0.001) for 30 Gy and 1.15 (0.82-1.60, p = 0.489) for 28.5 Gy versus 50 Gy. Three-year rates of physician-assessed moderate/marked adverse effects in the breast were 17.3% (13.3-22.3%, p < 0.001) for 30 Gy and 11.1% (7.9-15.6%, p = 0.18) for 28.5 Gy compared with 9.5% (6.5-13.7%) after 50 Gy. With a median follow-up in survivors of 37.3 months, 2 local tumour relapses and 23 deaths have occurred. Conclusions: At 3 years median follow-up, 28.5 Gy in 5 fractions is comparable to 50 Gy in 25 fractions, and significantly milder than 30 Gy in 5 fractions, in terms of adverse effects in the breast. © 2011 Elsevier Ltd. All rights reserved.

Agency: GTR | Branch: MRC | Program: | Phase: Research Grant | Award Amount: 10.12M | Year: 2015

Radiation therapy involves delivering high-energy X-ray beams to tumours in order to kill cancer cells. For many people with cancer, radiation therapy is very effective and frequently cures their disease. Unfortunately, when treating tumours, nearby normal tissues will inevitably receive some of the radiation and this is associated with side effects. These side effects can vary from mild, temporary changes that disappear completely to severe, life-threatening, permanent effects that chronically affect a patients quality of life. Therefore, when treating patients with radiotherapy, there is a clear need to ensure that the treatment is delivered as accurately as possible in order to avoid unnecessary treatment of normal tissues. In most cases, radiotherapy is planned using a CT scan to show the position of the tumour, but this is usually only done once before the treatment starts. One of the major problems with accurate delivery of radiation lies in the fact that it can be very difficult to determine precisely where the tumour is, because it can be difficult to see on standard CT scans. The problem is compounded by the fact that radiation therapy is usually given as a series of doses (called fractions) divided over a period of weeks and the tumour may be in a slightly different position each day or may shrink during the course of treatment. To make matters even more difficult, tumours often occur in tissues that move. For example, lung tumours can move quite significantly as a patient breathes in and out. Therefore, when planning a course of radiation therapy, it is necessary to include a large margin around the tumour to make sure that the radiation beams do not miss their target. As a result, large volumes of normal tissues may receive unnecessarily high radiation doses. In this research project, we aim to revolutionise the technique for delivering radiation therapy by developing a new type of machine called an MR Linac (or magnetic resonance imaging-guided linear accelerator). This machine combines a state-of-the-art radiation machine (called a linear accelerator) with a magnetic resonance imaging (MRI) scanner. MRI scanning is better than CT scanning at being able to tell the difference between tumour and normal tissues and does not expose patients to additional radiation doses. Therefore, such a machine will allow us to see very accurately where the tumour is at the time of each fraction of radiation therapy and it will also be able to track the movements of a tumour as they occur in real-time within a patient during a dose of radiation. With these improvements, we aim to be able to reduce the margins we place around tumours before we start a course of radiation therapy and yet still be confident that we are hitting the tumour target all of the time. For patients, this will have a number of benefits including greater confidence that the treatment will be effective against their disease with fewer side effects. The greater level of accuracy and the avoidance of normal tissues also means that we may be able to prescribe higher radiation doses to the tumour. For clinicians and scientists, the diagnostic power of MRI scanning will allow them to use the MR Linac to develop new approaches to modify the pattern of radiation delivery such that extra dose can be deposited in tumour areas that pose the greatest threat to the patient. Such areas can be identified using so-called functional imaging techniques on an MRI scanner. Before MR-guided radiation therapy can become a reality, there are a number of challenges that need to be met to ensure that treatment can be delivered accurately and safely. The programme of research described in this proposal will enable us to use the MRI scanner to acquire accurate images of tumour and normal tissues while delivering precise radiation doses, even to moving tumour targets.

Agency: GTR | Branch: MRC | Program: | Phase: Research Grant | Award Amount: 495.10K | Year: 2016

Tumours of the adrenal cortex are relatively common with a prevalence of 1-10%. Most of these are benign, however, in rare case adrenocortical carcinoma (ACC) can develop which is aggressive and has a poor 5 year prognosis. Understanding pathways that drive ACC progression is essential to the development of more effective treatments and for the prediction of individual outcomes. Next generation sequencing studies have revealed recurrent alterations present in human disease. These studies have identified mutations in the WNT signalling pathway, including activating mutations in CTNNB1, to be one of the most frequent alterations. Studies in mice have shown that activating mutations in Ctnnb1 can give rise to tumour formation in the adrenal cortex, highlighting the value of this model to study adrenal tumourigenesis. We have identified HOXB9 as a gene expressed in the early stages of adrenal cortex development and upregulated in adrenal tumours driven by activating Ctnnb1 mutations in mice. Human ACC tumours also show upregulation of HOXB9 expression that correlates with WNT signalling dysregulation and decreased survival frequency suggesting a role for this gene in carcinogenesis. In preliminary studies, we have generated transgenic mice with elevated Hoxb9 expression in developing and adult adrenal cortical cells. Mice that contain this transgene and an activating Ctnnb1 mutation showed acceleration of tumourigenesis characterised by increased cell proliferation and tumour weight and in the appearance of cells with a neoplastic undifferentiated spindle shaped phenotype. These studies indicate that HOXB9 can cooperate with the WNT signalling pathway to drive adrenal tumour progression. The aim of this project is to investigate the cellular and molecular mechanisms and pathways by which HOXB9 drives tumour progression. Using in vitro and in vivo approaches we will determine the role of this gene in adrenocortical tumour cell proliferation and survival, cell fate and differentiation. We will identify the molecular pathways associated with HOXB9, including its interaction with the WNT signalling pathway. An additional aim of this project is to characterise the drug sensitivities associated with the WNT signalling pathway in adrenocortical carcinoma. Using various ACC models with dysregulated WNT signalling we will investigate the effect of drugs targeting this pathway on cell survival in vivo and in vitro. Using high throughput drug library screens we will identify combinations therapies that will increase the effectiveness of these targeted compounds. In a complementary approach, we will use RNA interference screens to identify the key nodal points in the WNT signalling pathway that when inhibited achieve a therapeutic response in ACC. The ultimate goal of the studies proposed is to identify novel pathways and drug sensitivities in adrenocortical carcinogenesis that will provide important information that will aid in the development of clinical therapies to treat this rare and aggressive disease.

Agency: GTR | Branch: MRC | Program: | Phase: Fellowship | Award Amount: 323.69K | Year: 2016

Scientific/medical context of research? Prostate cancer is the commonest male cancer (41,000 diagnosed in 2010) and the second commonest (10,700 died in 2010) cause of male cancer death in the UK. One man dies of prostate cancer every hour in the UK. The growth of the prostate is dependent on hormones (androgens). Hormones are the bodys chemical messengers that stimulate cell growth through binding their receptors (androgen receptor). Prostate cancer develops when prostate cells grow uncontrollably. This is initially dependent on androgens. If diagnosed early prostate cancer can be cured by surgery and/or radiotherapy. However, 30% of cases will relapse and more than 20% of cases will present with widespread (metastatic) disease that is incurable. Initial treatment strategies to lower androgen levels provide robust responses in 90% of cases (hormone naive prostate cancer). Unfortunately, in time, nearly all cases progress to fatal disease that no longer responds to such therapies (castrate resistant prostate cancer). One mechanism driving castrate resistance is the identification of structurally altered androgen receptors (splice variants). These are permanently active and do not bind androgens rendering current therapies ineffective. There are currently no clinically available treatment strategies that target the androgen receptor splice variants and this is a critical area of unmet research and clinical need. BAG-1 is a protein found at increased levels in castrate resistant prostate cancer compared to hormone naive prostate cancer. BAG-1 activates both the androgen receptor and androgen receptor splice variants in prostate cancer. Techniques lowering BAG-1 protein levels inhibit the growth of prostate cancer cells. BAG-1 provides a novel therapeutic target to inhibit the androgen receptor splice variants and impact on the survival of patients with castrate resistant prostate cancer. What is the research trying to achieve? This fellowship will determine BAG-1 protein levels in patient biopsies and correlate this with patient survival and treatment responses to identify BAG-1 as a prognostic biomarker (predictor of survival and treatment response) in castrate resistant prostate cancer. It will identify BAG-1 as a critical regulator of androgen receptor and androgen receptor splice variant signalling driving castrate resistance and therapeutic resistance in prostate cancer. The fellowship will identify BAG-1 as a novel therapeutic target for anticancer drug discovery efforts in castrate resistant prostate cancer. Why is this important? There are no clinically available therapies that target androgen receptor splice variants in castrate resistant prostate cancer. Targeting BAG-1 provides a strategy to overcome castrate resistance and therapeutic resistance improving patient survival in this common disease. Who is carrying out the research? Dr Adam Sharp is a specialist registrar in medical oncology at the Royal Marsden Hospital in London. He completed his Bachelor of Science (Biochemistry and Pharmacology) and Doctor of Philosophy (Cancer Sciences) before undertaking his medical training. His career ambition is to be an academic medical oncologist with a laboratory focused on translational research within the field of cancer therapeutics. This fellowship will be carried out under the supervision of Professors Johann de Bono and Paul Workman who are key opinion leaders within the fields of drug discovery, drug development, chaperone proteins and prostate cancer medicine. Dr Sharp will be based in the Cancer Therapeutics Unit at the Institute of Cancer Research, the top rated academic drug discovery unit worldwide. The fellowship will initiate a consortium (sponsors and collaborators) of international leaders within the fields of BAG-1, androgen receptor, chaperone proteins, drug discovery and prostate cancer medicine to ensure the greatest scientific and clinical impact of this fellowship.

Agency: GTR | Branch: EPSRC | Program: | Phase: Research Grant | Award Amount: 675.86K | Year: 2016

Therapeutic ultrasound (ThUS) has enormous potential as a minimally invasive treatment modality with applications ranging from the treatment of cancer and stroke, to fracture healing and neuromodulation. It is uniquely versatile, offering a non-invasive technique with the ability to thermally ablate tissue, to mechanically fragment tissue or to enhance drug delivery, depending on the way in which the acoustic energy is delivered. However, despite highly promising initial trials and its considerable advantages in terms of cost and patient safety, widespread clinical adoption has been hindered by a combination of factors. These include: poor understanding of the mechanisms of action, lack of effective treatment monitoring, absence of standardised treatment protocols and poor communication between basic scientists, engineers and clinicians. The main focus of the Therapeutic Ultrasound for Drug Delivery and Ablation Research (ThUNDDAR) Network is to address these factors by stimulating translational research that will enable the potential of therapeutic ultrasound to be fully realised. The Network brings together engineers, physicists, mathematicians, chemists, biologists, industry and clinicians as well as patient groups and regulatory bodies to identify and break down existing, and future, barriers to the use of therapeutic ultrasound in the UK and throughout the world. ThUNDDARs activities will include the organisation of specialist meetings, seed funding for pilot studies that cross disciplinary and institutional boundaries, and the production of web based information about therapy ultrasound for the benefit of industry, clinical users, health commissioners and patient groups.

Agency: GTR | Branch: MRC | Program: | Phase: Research Grant | Award Amount: 940.53K | Year: 2016

The changes in the DNA that give rise to a tumour are not the same changes that make the tumour progress further and become metastatic. This is because a cancer evolves, and hence continuously changes over time, shaped by selective forces that favour more and more aggressive cancer cells. Late but clinically relevant changes may not be detectable everywhere in the cancer because of the so-called intra-tumour heterogeneity, or variation of cells within the same malignancy. This is critical because those late changes may be the most clinically relevant ones for the progression of the disease and therefore focusing on this would maximise the benefit to the patient. Current genomic studies have limited power in detecting late but clinically relevant genomic alterations because they are either based on a single sample per patient (not informing on intra-tumour heterogeneity), or because they employed a small number of patients and therefore the statistics is poor. A major problem is that each tumour is different, and the large variation between patients makes the genomic analysis very challenging. To date, the most common strategy to handle this complexity is using statistics on large groups of patients, thus loosing the personalised focus and requiring huge costs. I argue that a radically different strategy, based on a new type of sampling and analysis, is necessary if we want to reliably identify those newly emerging subpopulations in cancers that need prioritised treatment. Moreover, we need to do this patient by patient to maximise clinical impact. Every cancer is the result of a unique and extremely complex evolutionary process. This is the crucial yet overlooked reason why the inter-patient variation in cancer is so large and consequently the statistics in cancer genomic studies is often poor. Whereas a few usual suspects driver alterations have been identified, the long tail of many yet rare putative drivers is a major obstacle to personalised medicine. Here I propose to refocus the analysis on individual evolutionary processes in each patient. Although this seems extremely challenging, I argue that this can be achieved using the paradigm of cancer evolution. Indeed also in evolutionary biology we only have a single instance of the evolutionary process: the evolution of life on earth happened only once. Other scientific fields, such as cosmology, are based on observations from unique processes (our universe, the only one we can observe), but despite this limitation, they can attain extraordinary predictive power. This is achieved through the integration of data and theory, to obtain a mechanistic understanding of a phenomenon, rather than for example measuring statistical correlations on a group, which does not necessarily imply understanding of the system. Here I propose a novel approach based on integrating a new strategy to collect samples from human tumours, with novel and powerful analysis methods that are based on the physics and mathematics of how tumours grow. Together, this multi-disciplinary approach allows identifying and characterising newly emerging and potentially aggressive subpopulations in an individual human tumour, one patient at a time. This personalises the analysis of patient data and allows tailoring the treatment not only to a specific patient, but also to a specific cancer cell subpopulation, the most clinically relevant.

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