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Paediatric acute myeloid leukaemia (AML) is a heterogeneous disease characterised by the malignant transformation of myeloid precursor cells with impaired differentiation. Standard therapy for paediatric AML has remained largely unchanged for over four decades and, combined with inadequate understanding of the biology of paediatric AML, has limited the progress of targeted therapies in this cohort. In recent years, the search for novel targets for the treatment of paediatric AML has accelerated in parallel with advanced genomic technologies which explore the mutational and transcriptional landscape of this disease. Exploiting the large combinatorial space of existing drugs provides an untapped resource for the identification of potential combination therapies for the treatment of paediatric AML. We have previously designed a multiplex screening strategy known as Multiplex Screening for Interacting Compounds in AML (MuSICAL), using an algorithm designed in-house, we screened all pairings of 384 FDA-approved compounds in less than 4000 wells by pooling drugs into 10 compounds per well. This approach maximised the probability of identifying new compound combinations with therapeutic potential while minimising cost, replication and redundancy. This screening strategy identified the triple combination of glimepiride, a sulfonylurea, pancuronium dibromide, a neuromuscular blocking agent, and vinblastine sulfate, a vinca alkaloid, as a potential therapy for paediatric AML. We envision that this approach can be used for a variety of disease-relevant screens allowing the efficient repurposing of drugs that can be rapidly moved into the clinic.

Paediatric acute myeloid leukaemia (AML) is a heterogeneous disease characterised by genetics and morphology. The introduction of intensive chemotherapy treatments together with patient stratification and supportive therapy has resulted in a moderate improvement in patient prognosis. However, overall survival rates remain unacceptably poor, with only 65% of patients surviving longer than 5 years. Recently age-specific differences in AML have been identified, highlighting the need for tailored treatments for paediatric patients. Combination therapies have the potential to improve patient prognosis, while minimising harmful side-effects. In the laboratory setting, identifying key combinations from large drug libraries can be resource-intensive, prohibiting discovery and translation into the clinic. To minimise redundancy and maximise discovery, we undertook a multiplex screen of 80 apoptotic-inducing agents in paediatric AML pre-clinical models. The screen was designed using an all-pairs testing algorithm, which ensured that all pairs of compounds could be tested, while minimising the number of wells used. We identified a combination of ABT-737, a Bcl-2 family inhibitor and Purvalanol A, a CDK inhibitor, as a potential targeted therapy for AML patients with an MLL rearrangement and an FLT3-ITD. Our approach has the potential to reduce resource-intensity and time associated with the identification of novel combination therapies.

Several histone deacetylase inhibitors including Vorinostat have received FDA approval for the treatment of haematological malignancies. However, data from these trials indicate that Vorinostat has limited efficacy as a monotherapy, prompting the need for rational design of combination therapies. A number of epi-sensitised pathways, including sonic hedgehog (SHH), were identified in AML cells by integration of global patterns of histone H3 lysine 9 (H3K9) acetylation with transcriptomic analysis following Vorinostat-treatment. Direct targeting of the SHH pathway with SANT-1, following Vorinostat induced epi-sensitisation, resulted in synergistic cell death of AML cells. In addition, xenograft studies demonstrated that combination therapy induced a marked reduction in leukemic burden compared to control or single agents. Together, the data supports epi-sensitisation as a potential component of the strategy for the rational development of combination therapies in AML.

Insights distilled from integrating multiple big-data or “omic” datasets have revealed functional hierarchies of molecular networks driving tumorigenesis and modifiers of treatment response. Identifying these novel key regulatory and dysregulated elements is now informing personalized medicine. Crucially, although there are many advantages to this approach, there are several key considerations to address. Here, we examine how this big data–led approach is impacting many diverse areas of cancer research, through review of the key presentations given at the Irish Association for Cancer Research Meeting and importantly how the results may be applied to positively affect patient outcomes. Cancer Res; 76(21); 6167–70. ©2016 AACR.

It has been shown previously that cancer cells with an activated oncogenic pathway, including Met activation, require Ran for growth and survival.Here, we show that knockdown of Ran leads to a reduction of Met receptor expression in several breast and lung cancer cell lines. This, in turn suppressed HGF expression and the Met-mediated activation of the Akt pathway, as well as cell adhesion, migration, and invasion. In a cell line model where Met amplification has previously been shown to contribute to gefitinib resistance, Ran knockdown sensitized cells to gefitinib-mediated inhibition of Akt and ERK1/2 phosphorylation and consequently reduced cell proliferation. We further demonstrate that Met reduction-mediated by knockdown of Ran, occurs at the post-transcriptional level, probably via a matrix metalloproteinase. Moreover, the level of immunoreactive Ran and Met are positively associated in human breast cancer specimens, suggesting that a high level of Ran may be a pre-requisite for Met overexpression. Interestingly, a high level of immunoreactive Ran dictates the prognostic significance of Met, indicating that the co-overexpression of Met and Ran may be associated with cancer progression and could be used in combination as a prognostic indicator.

Breast cancer is one of the most prevalent malignancies worldwide. It consists of a group of tumor cells that have the ability to grow uncontrollably, overcome replicative senescence (tumor progression) and metastasize within the body. Metastases are processes that consist of an array of complex gene dysregulation events. Although these processes are still not fully understood, the dysregulation of a number of key proteins must take place if the tumor cells are to disseminate and metastasize. It is now widely accepted that future effective and innovative treatments of cancer metastasis will have to encompass all the major components of malignant transformation. For this reason, much research is now being carried out into the mechanisms that govern the malignant transformation processes. Recent research has identified key genes involved in the development of metastases, as well as their mechanisms of action. A detailed understanding of the encoded proteins and their interrelationship generates the possibility of developing novel therapeutic approaches. This review will focus on a select group of proteins, often deregulated in breast cancer metastasis, which have shown therapeutic promise, notably, EMT, E-cadherin, Osteopontin, PEA3, Transforming Growth Factor Beta (TGF-β) and Ran.

The traditional bench-to-bedside pipeline involves using model systems and patient samples to provide insights into pathways deregulated in cancer. This discovery reveals new biomarkers and therapeutic targets, ultimately stratifying patients and informing cohort-based treatment options. Precision medicine (molecular profiling of individual tumors combined with established clinical-pathological parameters) reveals, in real-time, individual patient's diagnostic and prognostic risk profile, informing tailored and tumor-specific treatment plans. Here we discuss advances in precision medicine presented at the Irish Association for Cancer Research Annual Meeting, highlighting examples where personalized medicine approaches have led to precision discovery in individual tumors, informing customized treatment programs.

Leukemia is the most frequently (30%) occurring type of pediatric cancer. Of these, approximately 80% are acute lymphoblastic leukemia (ALL) with acute myeloid leukemia (AML) cases making up the remaining 20%. Management of ALL has improved dramatically over the years with around 90% of patients surviving 5 years or more. Unfortunately, children with AML do not have such a promising prognosis with only 60% surviving 5 years or longer, plus a high risk of relapse, the side effects of the harsh chemotherapy regimen and a risk of not responding to induction therapy, provide a bleak outlook. Recently, Bolouri et al., (2017) identified the need for age-specific therapies for AML patients. To work towards age-specific treatment regimens we used the TARGET AML transcriptomic data, (https://ocg.cancer.gov/programs/target/data-matrix) and identified several therapeutically targetable pathways, in particular anomalies in apoptotic pathways amongst cytogenetically normal relapsed AML patients. Based on these apoptotic pathways we screened 80 apoptosis-inducing drugs from a compound library obtained from Selleckchem. The effect of three doses (0.01 µM, 0.1 µM and 1 µM) over 72 hrs of each drug was assayed using CellTox™ Green reagent (Promega) to investigate the cytotoxic potential of the compounds against three pediatric AML cell lines (Kasumi-1, MV4-11 and CMK) representative of a spectrum of cytogenetic and mutational anomalies. The cell lines showed varying responses in a time and dose-dependent manner with mutual and unique effects being highlighted, six compounds, including Navitoclax and TP-0903, overlapped in their effect on cell viability between the three cell lines. The cell lines also showed unique responses to many compounds, including Sunitinib and Obatoclax in the MV4-11 cell line. Based on these findings a dose of 0.1 µM was taken forward for the combination screen. To carry out the combination screen we used R to compile an algorithm, with the capability of determining all possible pairwise combinations for a given number of compounds. Several inputs were accommodated, including: the number of compounds to be used; the number of compounds in a well and the number of times the algorithm should run to get the best solution, with the best solution being the least number of wells to reduce redundant repeats of pairs. The output detailed which compounds should be in which well. With an input of 80 apoptotic-inducing compounds into the algorithm; the output was as follows: 3,160 possible pairwise combinations, 1,197 pairs used once, 827 pairs used twice, and so on with the largest number of repeats being 148 pairs used eight times. This output enabled us to cross validate our data, by analysing wells containing the successful combinations to corroborate them as 'hits' or as containing possible antagonistic pairings if they were deemed unsuccessful. Using the output of the algorithm, 160 wells were needed for all combinations to enable our Multiplex Screening for Interacting Compounds for pediatric AML (MuSICAL). CellTox™ Green was used to determine cytotoxicity up to 72 hours and the same three cell lines used as for the single agent screen. The MuSICAL screen identified some wells in common amongst the three cell lines (6.25%), although many of the positive wells (12.5%) were unique to each of the cell lines. Well 158, which included Nutlin-3, Embelin and Poziotinib, was common for the MV4-11 and the CMK cell lines, with the individual compounds in this well having no substantial effect on cell viability as single agents, but a combination of 2 or more compounds induced substantial cell death. The 10 drugs in well 158 were deconvoluted and screened, resulting in 45 pairwise combinations. Several pairwise combinations, at 0.1 µM each, induced cell death in the MV4-11 and CMK cell lines. The most effective pairwise combination was the combination of ABT-737, a Bcl-2 inhibitor and Purvalanol A, a CDK inhibitor, in the MV4-11 cell line. The effect of this combination was also a 'hit' in Well 6 validating the therapeutic potential. For the CMK cell line, the most effective combination was Poziotinib, a pan-HER inhibitor and SU9516, another CDK inhibitor. In conclusion, the MuSICAL screen has identified multiple apoptosis-inducing drug combinations across the 3 cell lines highlighting the potential for personalised treatment of pediatric AML with different cytogenetic and mutational backgrounds. Disclosures No relevant conflicts of interest to declare.

Background: Germline mutation screening of BRCA1 and BRCA2 genes is performed in suspected familial breast cancer cases, but a causative mutation is found in only 30% of patients. The development of additional methods to identify good candidates for BRCA1 and BRCA2 analysis would therefore increase the efficacy of diagnostic mutation screening. With this in mind, we developed a study to determine molecular signatures of BRCA1—or BRCA2—mutated breast cancers. Materials and Methods: Array-cgh (comparative genomic hybridization) and transcriptomic analysis were performed on a series of 103 familial breast cancers. The series included 7 breast cancers with a BRCA1 mutation and 5 breast cancers with a BRCA2 mutation. The remaining 91 cases were obtained from 73 families selected on the basis of at least 3 affected first-degree relatives or at least 2 affected first-degree relatives with breast cancer at an average age of 45 years. Array-cgh analyses were performed on a 4407 BAC-array (CIT-V8) manufactured by IntegraGen. Transcriptomic analyses were performed using an Affymetrix Human Genome U133 Plus 2.0 chip. Results: Using supervised clustering analyses we identified two transcriptomic signatures: one for BRCA1-mutated breast cancers consisting of 600 probe sets and another for BRCA2-mutated breast cancers also consisting of 600 probes sets. We also defined cgh-array signatures, based on the presence of specific genomic rearrangements, one for BRCA1-mutated breast cancers and one for BRCA2-mutated breast cancers. Conclusions: This study identified molecular signatures of breast cancers with BRCA1 or BRCA2 germline mutations. Genes present in these signatures could be exploited to find new markers for such breast cancers. We also identified specific genomic rearrangements in these breast cancers, which could be screened for in a diagnostic setting using fluorescence in situ hybridization, thus improving patient selection for BRCA1 and BRCA2 molecular genetic analysis.

A vast body of research in breast cancer prognostication has accumulated. Yet despite this, patients within current prognostic categories may have significantly different outcomes. There is a need to more accurately divide those cancer types associated with an excellent prognosis from those requiring more aggressive therapy. Gene expression array studies have revealed the numerous molecular breast cancer subtypes that are associated with differing outcomes. Furthermore, as next generation technologies evolve and further reveal the complexities of breast cancer, it is likely that existing prognostic approaches will become progressively refined. Future prognostication in breast cancer requires a morphomolecular, multifaceted approach involving the assessment of anatomical disease extent and levels of protein, DNA and RNA expression. One of the major challenges in prognostication will be the integration of potential assays into existing clinical systems and identification of appropriate patient subgroups for analysis.

Recombinant erythropoietin (Epo) is an effective anti-anemic agent in most cancer patients and improves their quality of life. Yet, concerns of disease progression and reduced survival in recombinant human Epo (rhuEpo)-treated patients have been raised by Phase III clinical trial data showing more rapid cancer progression and reduced survival in subjects randomized to Epo. Epo has pleiotropic actions and its receptor, EpoR, is expressed by many different cell types outside the erythroid compartment. It was thus proposed that a major possible mechanism for this potentially harmful effect of Epo in cancer patients is the activation of EpoRs on cancer cells. The original clinical studies have been criticized because they deployed polyclonal antibodies later shown to lack specificity for EpoR. Furthermore, multiple isoforms of EpoR caused by differential splicing have been reported, but only at the RNA level, in different cancer cell lines. Investigations into whether these spliced versions actually result in abnormal EpoR forms at the protein level, alter Epo responsiveness and have an impact on tumor progression in vivo, have been hampered by a lack of well characterized monoclonal antibodies. The ‘EpoCan’ Consortium, funded by the EU, is directed to promote improved pathological testing of EpoR in patient samples, leading to safer clinical use of rHuEpo and other Erythropoietic Stimulating Agents (ESAs). To date, 25 murine and rat monoclonal antibodies have been produced against the EpoR, using novel genetic and traditional peptide immunization protocols. Of these antibodies, several were found to specifically recognize the receptor in various assays including Western blot (WB), immunoprecipitation (IP), immunofluorescence (IF), flow cytometry (FACS) and immunohistochemistry (IHC). Table 1 lists the antibodies that were selected for further analysis, and their experimental applications. The antibodies were tested on EpoR transfected cells (HEK 293 cells and COS cells) and Epo-dependent UT7 cells which endogenously express EpoR. In addition the antibodies were tested on non-erythroid cells viz. the non-small cell lung carcinoma A549, and breast cancer MDA-MB 231 cell lines. Specificity of the antibodies towards the EpoR in these two latter cell lines was ensured by the lack of reactivity with the corresponding EpoR silenced cells.Table 1Anti EpoR Antibodies - immunizing antigens and applicationsImmunogenSubclone nameSystematic nameIsotypeEpitope locationApplicationsPeptideBCO-3H2-D3GM1201rIgG2bhEpoR cytoplasmic domainWB, IP, IF, IHCPeptideBCO-4B5-C9GM1202rIgG2ah/mEpoR cytoplasmic domainWB, IF, IHCDNAVP-2E8-B6GM1204mIgG1hEpoR extracellular domainIP, IF, FACSDNAVP-4D8-C4GM1205mIgG1hEpoR extracellular domainIP, IF, FACSDNABBQ-9C4-D8GM1206rIgG2ah/mEpoR extracellular domainFACSDNABBQ-10E10-F2GM1207rIgG2ah/mEpoR extracellular domainWB Immunohistochemical analysis was performed on a panel of human non-small cell lung carcinoma sections. Two rat monoclonal antibodies, BCO-3H2-D3 which recognizes full length EpoR and BCO-4B5-C9 which recognizes full length and truncated isoforms, have proved valuable in comparative immunohistochemical and Western blot studies in a range of human tumors and cell lines. These well characterized monoclonal antibodies will enable a careful dissection of EpoR function in cancer cells and the detection of EpoR isoforms in tumor tissue. In the longer term such studies should allow clinicians to balance the benefits and risks of ESA treatment in cancer. THIS WORK WAS SUPPORTED BY THE FP7-HEALTH EUROPEAN COMMISSION EPOCAN GRANT (282551). Disclosures: Grunert: Aldevron Freiburg GmBH: Employment. Thompson:Aldevron Freiburg GmbH: Employment.