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Understanding the mechanisms underlying tumour heterogeneity is key to the development of treatments that can target specific tumour subtypes. We have previously targeted CRE recombinase-dependent conditional deletion of the tumour suppressor genes Brca1, Brca2, p53 (also known as Trp53) and/or Pten to basal or luminal oestrogen receptor-negative (ER−) cells of the mouse mammary epithelium. We demonstrated that both the cell-of-origin and the tumour-initiating genetic lesions cooperate to influence mammary tumour phenotype. Here, we use a CRE-activated HER2 orthologue to specifically target HER2/ERBB2 oncogenic activity to basal or luminal ER− mammary epithelial cells and perform a detailed analysis of the tumours that develop. We find that, in contrast to our previous studies, basal epithelial cells are less sensitive to transformation by the activated NeuKI allele, with mammary epithelial tumour formation largely confined to luminal ER− cells. Histologically, most tumours that developed were classified as either adenocarcinomas of no special type or as metaplastic adenosquamous tumours. The former were typically characterized by amplification of the NeuNT/Erbb2 locus; in contrast, tumours displaying squamous metaplasia were enriched in animals that had been through at least one pregnancy and typically had lower levels of NeuNT/Erbb2 locus amplification but had activated canonical WNT signalling. Squamous changes in these tumours were associated with activation of the epidermal differentiation cluster. Thus, in this model of HER2 breast cancer, cell-of-origin, reproductive history, NeuNT/Erbb2 locus amplification and the activation of specific branches of the WNT signalling pathway all interact to drive inter-tumour heterogeneity., Summary: Using a mouse model of breast cancer, the authors show mammary epithelial cell-type sensitivity to transformation by HER2, as well as a change in tumour phenotype associated with reproductive history and driven by WNT signalling.

Understanding the mechanisms underlying tumour heterogeneity is key to development of treatments that can target specific tumour subtypes. We have previously targeted CRE recombinase-dependent conditional deletion of the tumour suppressor genes Brca1, Brca2, p53 and/or Pten to basal or luminal ER− cells of the mouse mammary epithelium. We demonstrated that both the cell-of-origin and the tumour-initiating genetic lesions co-operate to influence mammary tumour phenotype. Here, we use a CRE-activated HER2 orthologue to specifically target HER2/ERBB2 oncogenic activity to basal or luminal ER− mammary epithelial cells and carry out a detailed analysis of the tumours which develop. We find that in contrast to our previous studies, basal epithelial cells are refractory to transformation by the activated NeuKI allele, with mammary epithelial tumour formation largely confined to luminal ER− cells. Histologically, the majority of tumours that developed were classified as either adenocarcinomas of no special type or metaplastic adenosquamous tumours. Remarkably, the former were more strongly associated with virgin animals and were typically characterised by amplification of the NeuNT/ErbB2 locus and activation of non-canonical WNT signalling. In contrast, tumours characterised by squamous metaplasia were associated with animals that had been through at least one pregnancy and typically had lower levels of NeuNT/ErbB2 locus amplification but had activated canonical WNT signalling. Squamous changes in these tumours were associated with activation of the Epidermal Differentiation Cluster. Thus, in this model of HER2 breast cancer, cell-of-origin, reproductive history, NeuNT/ErbB2 locus amplification, and the activation of specific branches of the WNT signalling pathway all interact to drive inter-tumour heterogeneity.

Purpose: PTEN-null tumors become dependent on the PI3Kβ isoform and can be targeted by molecules such as the selective PI3Kβ inhibitor AZD8186. However, beyond the modulation of the canonical PI3K pathway, the consequences of inhibiting PI3Kβ are poorly defined. Experimental Design: To determine the broader impact of AZD8186 in PTEN-null tumors, we performed a genome-wide RNA-seq analysis of PTEN-null triple-negative breast tumor xenografts treated with AZD8186. Mechanistic consequences of AZD8186 treatment were examined across a number of PTEN-null cell lines and tumor models. Results: AZD8186 treatment resulted in modification of transcript and protein biomarkers associated with cell metabolism. We observed downregulation of cholesterol biosynthesis genes and upregulation of markers associated with metabolic stress. Downregulation of cholesterol biosynthesis proteins, such as HMGCS1, occurred in PTEN-null cell lines and tumor xenografts sensitive to AZD8186. Therapeutic inhibition of PI3Kβ also upregulated PDHK4 and increased PDH phosphorylation, indicative of reduced carbon flux into the TCA cycle. Consistent with this, metabolomic analysis revealed a number of changes in key carbon pathways, nucleotide, and amino acid biosynthesis. Conclusions: This study identifies novel mechanistic biomarkers of PI3Kβ inhibition in PTEN-null tumors supporting the concept that targeting PI3Kβ may exploit a metabolic dependency that contributes to therapeutic benefit in inducing cell stress. Considering these additional pathways will guide biomarker and combination strategies for this class of agents. Clin Cancer Res; 23(24); 7584–95. ©2017 AACR.

Cryptococcus neoformans is an opportunistic fungal infection that causes cryptococcal meningitis in immunocompromised individuals. Macrophages play a critical role in determining the outcome of infection, and can either phagocytose and kill the cryptococcal cells, or disseminate infection. While it is known that macrophages impact the progression of cryptococcal disease, it is not known how the macrophage intracellular niche contributes to complex infection outcomes. Clinical and experimental studies have identified potential genetic differences, in both host and pathogen, but statistical robustness has been difficult to achieve due the large variability in the outcome of infections. Therefore, in attempt to quantitatively explain this variability, we have used a zebrafish model of cryptococcal infection where we can directly relate the initial level of fungal infection with final infection outcome. We find that at low levels of initial fungal burden the outcome of infection is stochastic, while over high ranges of initial infection the outcome is linearly related to the initial burden, but with a further stochastic component that contributes to increased variability. Using these experimental data and data from clinical trials we have generated a computational simulation of in vivo cryptococcal infections which allows us to consider different infection variables and how they alter the progression of cryptococcosis. By combining such computational simulations with our experimental models we demonstrate that the macrophage intracellular niche determines the unknown stochastic component, independent of fungal burden. Using this knowledge, we can better identify the molecular, population genetic, and clinical parameters associated with the outcome of cryptococcosis.

// James R. Bradford 1 , Mark Wappett 2 , Garry Beran 2 , Armelle Logie 2 , Oona Delpuech 2 , Henry Brown 2 , Joanna Boros 2 , Nicola J. Camp 3 , Robert McEwen 2 , Anne Marie Mazzola 4 , Celina D’Cruz 4 , Simon T. Barry 2 1 Department of Oncology and Metabolism, University of Sheffield, Sheffield, South Yorkshire, UK 2 Oncology iMED, AstraZeneca Pharmaceuticals, Alderley Park, Cheshire, UK 3 Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City, Utah, USA 4 Oncology iMED, AstraZeneca Pharmaceuticals, Gatehouse Park, Massachusetts, USA Correspondence to: James R. Bradford, e-mail: J.R.Bradford@sheffield.ac.uk Keywords: patient-derived xenograft, RNA-Seq, tumor stroma, biomarker discovery, pre-clinical research Received: November 09, 2015 Accepted: February 18, 2016 Published: March 09, 2016 ABSTRACT The tumor microenvironment is emerging as a key regulator of cancer growth and progression, however the exact mechanisms of interaction with the tumor are poorly understood. Whilst the majority of genomic profiling efforts thus far have focused on the tumor, here we investigate RNA-Seq as a hypothesis-free tool to generate independent tumor and stromal biomarkers, and explore tumor-stroma interactions by exploiting the human-murine compartment specificity of patient-derived xenografts (PDX). Across a pan-cancer cohort of 79 PDX models, we determine that mouse stroma can be separated into distinct clusters, each corresponding to a specific stromal cell type. This implies heterogeneous recruitment of mouse stroma to the xenograft independent of tumor type. We then generate cross-species expression networks to recapitulate a known association between tumor epithelial cells and fibroblast activation, and propose a potentially novel relationship between two hypoxia-associated genes, human MIF and mouse Ddx6 . Assessment of disease subtype also reveals MMP12 as a putative stromal marker of triple-negative breast cancer. Finally, we establish that our ability to dissect recruited stroma from trans-differentiated tumor cells is crucial to identifying stem-like poor-prognosis signatures in the tumor compartment. In conclusion, RNA-Seq is a powerful, cost-effective solution to global analysis of human tumor and mouse stroma simultaneously, providing new insights into mouse stromal heterogeneity and compartment-specific disease markers that are otherwise overlooked by alternative technologies. The study represents the first comprehensive analysis of its kind across multiple PDX models, and supports adoption of the approach in pre-clinical drug efficacy studies, and compartment-specific biomarker discovery.

BACKGROUND A substantial number of melanoma patients develop local or metastatic recurrence, and early detection of these is vital to maximise benefit from new therapies such as inhibitors of BRAF and MEK, or immune checkpoints. This study explored the use of novel DNA copy-number profiles in circulating cell-free DNA (cfDNA) as a potential biomarker of active disease and survival. PATIENTS AND METHODS Melanoma patients were recruited from oncology and dermatology clinics in Sheffield, UK, and cfDNA was isolated from stored blood plasma. Using low-coverage whole-genome sequencing, we created copy-number profiles from cfDNA from 83 melanoma patients, 44 of whom had active disease. We used scoring algorithms to summarize copy-number aberrations and investigated their utility in multivariable logistic and Cox regression analyses. RESULTS The copy-number aberration score (CNAS) was a good discriminator of active disease (odds ratio, 3.1; 95% CI, 1.5–6.2; P = 0.002), and CNAS above or below the 75th percentile remained a significant discriminator in multivariable analysis for active disease (P = 0.019, with area under ROC curve of 0.90). Additionally, mortality was higher in those with CNASs above the 75th percentile than in those with lower scores (HR, 3.4; 95% CI, 1.5–7.9; P = 0.005), adjusting for stage of disease, disease status (active or resected), BRAF status, and cfDNA concentration. CONCLUSIONS This study demonstrates the potential of a de novo approach utilizing copy-number profiling of cfDNA as a biomarker of active disease and survival in melanoma. Longitudinal analysis of copy-number profiles as an early marker of relapsed disease is warranted.

Background The incidence of human papilloma virus positive (HPV+) oropharyngeal squamous cell carcinoma (OPSCC) has increased rapidly in recent decades. These tumours have a favourable outcome compared to HPV‐negative (HPV−) OPSCC. However, HPV+ tumours are more likely to metastasise to distant sites, suggesting a difference in how these tumour subtypes interact with the metastatic niche. Extracellular vesicles (EVs) have emerged as important players in cell‐to‐cell communication and are a potential source of biomarkers for cancer diagnosis. This study aims to characterise the microRNA cargo of small EVs released by HPV+ and HPV− OPSCC cell lines. Methods Extracellular vesicles produced by HPV+ (SCC2 and SCC90) and HPV− (SCC72 an SCC89) OPSCC cells were characterised by tunable resistive pulse sensing (TRPS) and western blotting. RNA was extracted from EVs and analysed by small RNA sequencing. A bioinformatics approach was used to identify EV miRNA signatures associated with HPV status. Results HPV− OPSCC cells produced more EVs than HPV+ OPSCC cells. EVs were positive for the common EV markers CD63, CD9 and TSG101. Unbiased hierarchical clustering analysis of EV miRNA cargo revealed that samples clustered based on HPV status. 14 miRNA were enriched in HPV+ cell‐derived EVs, whereas 19 miRNA were enriched in EVs derived from HPV− cell lines. Conclusions Here, we identify EV miRNA signatures indicative of the HPV status of the parent cell. This may provide a platform from which to validate salivary or blood‐based biomarkers with utility for early detection and stratifying risk in OPSCC patients.

Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of cellular processes in diseases such as cancer, although the functions of most remain poorly understood. To address this, here we apply a novel strategy to integrate gene expression profiles across 32 cancer types, and cluster human lncRNAs based on their pan-cancer protein-coding gene associations. By doing so, we derive 16 lncRNA modules whose unique properties allow simultaneous inference of function, disease specificity and regulation for over 800 lncRNAs. Remarkably, modules could be grouped into just four functional themes: transcription regulation, immunological, extracellular, and neurological, with module generation frequently driven by lncRNA tissue specificity. Notably, three modules associated with the extracellular matrix represented potential networks of lncRNAs regulating key events in tumour progression. These included a tumour-specific signature of 33 lncRNAs that may play a role in inducing epithelialmesenchymal transition through modulation of TGFβ signalling, and two stromal-specific modules comprising 26 lncRNAs linked to a tumour suppressive microenvironment, and 12 lncRNAs related to cancer-associated fibroblasts. At least one member of the 12-lncRNA signature was experimentally supported by siRNA knockdown, which resulted in attenuated differentiation of quiescent fibroblasts to a cancer-associated phenotype. Overall, the study provides a unique pan-cancer perspective on the lncRNA functional landscape, acting as a global source of novel hypotheses on lncRNA contribution to tumour progression.Author SummaryThe established view of protein production is that genomic DNA is transcribed into RNA, which is then translated into protein. Proteins play a critical role in shaping the function of each individual cell in the human body yet they represent less than 2% of human genomic sequence whilst up to 90% of the genome is transcribed. To explain this disparity, the existence of thousands of long non-coding RNAs (lncRNAs) has emerged that do not encode proteins but perform function as an RNA molecule. Most lncRNAs have yet to be assigned a specific biological role, so to address this we apply a novel computational approach to characterise the function of >800 lncRNAs through consistent association with protein coding genes across multiple cancer types. By doing so, we discover 16 “modules” of closely related lncRNAs that share broad functional themes, the most compelling of which consists of 12 lncRNAs that could regulate activation of specific cells neighbouring the tumour, leading to accelerated tumour progression and invasion. Overall, the study provides the most robust view of the lncRNA-protein coding gene landscape to date, adding to growing evidence that lncRNAs are key regulators of cancer, and have therapeutic potential comparable to proteins.

Prostate cancer research is hampered by the lack of in vivo preclinical models that accurately reflect patient tumour biology and the clinical heterogeneity of human prostate cancer. To overcome these limitations we propagated and characterised a new collection of patient-derived prostate cancer xenografts. Tumour fragments from 147 unsupervised, surgical prostate samples were implanted subcutaneously into immunodeficient Rag2(-/-)gamma C-/- mice within 24 hours of surgery. Histologic and molecular characterisation of xenografts was compared with patient characteristics, including androgen-deprivation therapy, and exome sequencing. Xenografts were established from 47 of 147 (32%) implanted primary prostate cancers. Only 14% passaged successfully resulting in 20 stable lines; derived from 20 independent patient samples. Surprisingly, only three of the 20 lines (15%) were confirmed as prostate cancer; one line comprised of mouse stroma, and 16 were verified as human donor-derived lymphoid neoplasms. PCR for Epstein-Barr Virus (EBV) nuclear antigen, together with exome sequencing revealed that the lymphomas were exclusively EBV-associated. Genomic analysis determined that 14 of the 16 EBV+ lines had unique monoclonal or oligoclonal immunoglobulin heavy chain gene rearrangements, confirming their B-cell origin. We conclude that the generation of xenografts from tumour fragments can commonly result in B-cell lymphoma from patients carrying latent EBV. We recommend routine screening, of primary outgrowths, for latent EBV to avoid this phenomenon.

e21045 Background: Traditionally gene expression signatures (GES) are used individually to classify patients into subgroups. Signatures targeting the same biology are often developed independently and may not classify identically. We developed the claraT software tool that uses consensus between multiple published GES categorised by the Hallmarks of Cancer (Hanahan & Weinberg, 2011) to classify cancers. As metastatic melanoma represents poor prognostic disease (5-yr survival 15-20%), we applied claraT to the TCGA melanoma dataset to identify targetable biologies, validated in a cohort of melanoma patients treated with Ipilimumab. Methods: TCGA RNA-seq data ( n= 472) was analysed using the claraT platform including GES for immune ( n= 14), angiogenesis ( n= 9) and epithelial-mesenchymal transition (EMT) ( n= 12) Hallmarks. Samples were clustered for the combined and individual Hallmarks. Median progression-free (PFS) and overall-survival (OS) differences were analysed across identified subgroups. Analysis was validated in an Ipilimumab treated melanoma dataset ( n= 42) (Van Allen, 2015). Results: Clustering the combined Hallmarks identified 4 subgroups in the TCGA cohort: 1) Immune active, 2) Immune-EMT active, 3) EMT-Angiogenesis active, 4) All inactive. Groups 1&2 had significantly improved OS compared to Groups 3&4 (HR = 0.50, p< 0.0001). Clustering using single Hallmarks revealed that immune-positive tumours had significantly improved OS (HR = 0.53, p< 0.0001) compared to immune-negative tumours. Angiogenesis-negative tumours displayed improved PFS (HR = 0.73, p= 0.03) and OS (HR = 0.53, p

Molecular profiling using low coverage whole genome sequencing of cell free DNA (cfDNA) represents a non-targeted approach to identify multiple somatic copy number alterations (SCNA) across different lung cancer subtypes. We aim to establish that SCNA can be detected in cfDNA of lung cancer cases.

Background Identification of synthetic lethal interactions in cancer cells could offer promising new therapeutic targets. Large-scale functional genomic screening presents an opportunity to test large numbers of cancer synthetic lethal hypotheses. Methods enriching for candidate synthetic lethal targets in molecularly defined cancer cell lines can steer effective design of screening efforts. Loss of one partner of a synthetic lethal gene pair creates a dependency on the other, thus synthetic lethal gene pairs should never show simultaneous loss-of-function. We have developed a computational approach to mine large multi-omic cancer data sets and identify gene pairs with mutually exclusive loss-of-function. Since loss-of-function may not always be genetic, we look for deleterious mutations, gene deletion and/or loss of mRNA expression by bimodality defined with a novel algorithm BiSEp. Results Applying this toolkit to both tumour cell line and patient data, we achieve statistically significant enrichment for experimentally validated tumour suppressor genes and synthetic lethal gene pairings. Notably non-reliance on genetic loss reveals a number of known synthetic lethal relationships otherwise missed, resulting in marked improvement over genetic-only predictions. We go on to establish biological rationale surrounding a number of novel candidate synthetic lethal gene pairs with demonstrated dependencies in published cancer cell line shRNA screens. Conclusions This work introduces a multi-omic approach to define gene loss-of-function, and enrich for candidate synthetic lethal gene pairs in cell lines testable through functional screens. In doing so, we offer an additional resource to generate new cancer drug target and combination hypotheses. Algorithms discussed are freely available in the BiSEp CRAN package at http://cran.r-project.org/web/packages/BiSEp/index.html. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2375-1) contains supplementary material, which is available to authorized users.

Although endocrine therapy is successfully used to treat patients with estrogen receptor (ER) positive breast cancer, a substantial proportion of this population will relapse. Several mechanisms of acquired resistance have been described including activation of the mTOR pathway, increased activity of CDK4 and activating mutations in ER. Using a patient derived xenograft model harboring a common activating ER ligand binding domain mutation (D538G), we evaluated several combinatorial strategies using the selective estrogen receptor degrader (SERD) fulvestrant in combination with chromatin modifying agents, and CDK4/6 and mTOR inhibitors. In this model, fulvestrant binds WT and MT ER, reduces ER protein levels, and downregulated ER target gene expression. Addition of JQ1 or vorinostat to fulvestrant resulted in tumor regression (41% and 22% regression, respectively) though no efficacy was seen when either agent was given alone. Interestingly, although the CDK4/6 inhibitor palbociclib and mTOR inhibitor everolimus were efficacious as monotherapies, long-term delayed tumor growth was only observed when co-administered with fulvestrant. This observation was consistent with a greater inhibition of compensatory signaling when palbociclib and everolimus were co-dosed with fulvestrant. The addition of fulvestrant to JQ1, vorinostat, everolimus and palbociclib also significantly reduced lung metastatic burden as compared to monotherapy. The combination potential of fulvestrant with palbociclib or everolimus were confirmed in an MCF7 CRISPR model harboring the Y537S ER activating mutation. Taken together, these data suggest that fulvestrant may have an important role in the treatment of ER positive breast cancer with acquired ER mutations.

We have carried out a thorough and systematic sequence-structure study on how the pattern of conservation at the interface differs from the noninteracting surface in seven proteases and their inhibitors. As expected, the interface of a protease could be easily distinguished from the noninteracting surface by a concentrated area of conservation. In contrast, there was less distinction to be made between the interface and the noninteracting surface of inhibitors, and in five of the seven cases, a higher proportion of the interface area was variable compared to the rest of the surface. This is likely to cause a problem for binding-site prediction methods that assume the largest cluster of highly conserved residues on the surface of a protein corresponds to the interface. We conclude that such methods would succeed when applied to our protease test cases, but complications could arise with the inhibitors. These results also impact on methods to solve the protein-protein docking problem that use conservation at the interface to provide the location of the two protein binding sites prior to application of the docking algorithm.

Pre-clinical models of tumour biology often rely on propagating human tumour cells in a mouse. In order to gain insight into the alignment of these models to human disease segments or investigate the effects of different therapeutics, approaches such as PCR or array based expression profiling are often employed despite suffering from biased transcript coverage, and a requirement for specialist experimental protocols to separate tumour and host signals. Here, we describe a computational strategy to profile transcript expression in both the tumour and host compartments of pre-clinical xenograft models from the same RNA sample using RNA-Seq. Key to this strategy is a species-specific mapping approach that removes the need for manipulation of the RNA population, customised sequencing protocols, or prior knowledge of the species component ratio. The method demonstrates comparable performance to species-specific RT-qPCR and a standard microarray platform, and allowed us to quantify gene expression changes in both the tumour and host tissue following treatment with cediranib, a potent vascular endothelial growth factor receptor tyrosine kinase inhibitor, including the reduction of multiple murine transcripts associated with endothelium or vessels, and an increase in genes associated with the inflammatory response in response to cediranib. In the human compartment, we observed a robust induction of hypoxia genes and a reduction in cell cycle associated transcripts. In conclusion, the study establishes that RNA-Seq can be applied to pre-clinical models to gain deeper understanding of model characteristics and compound mechanism of action, and to identify both tumour and host biomarkers.

The genome sequence of the malaria parasite Plasmodium falciparum was published in 2002 and revealed that approximately 60% of its genes could not be assigned a function. Eight years later the majority of P. falciparum proteins are still of unknown function. We therefore present PlasmoPredict, an easy-to-use online gene function prediction tool that integrates a wide range of functional genomics data for P. falciparum to aid in the annotation of these genes.

Olaparib is an oral inhibitor of the Poly-(ADP-ribose)-polymerases (PARP-1, -2 and -3), and has demonstrated clinical activity in trials of patients with BRCA-deficient tumors. The BRCA1 and BRCA2 proteins are both important for the repair of DNA double strand breaks (DSBs) by homologous recombination repair (HRR) and sensitivity to olaparib has further been shown preclinically to extend to other DNA DSB repair factor deficiencies, including those in the ataxia telangiectasia mutated (ATM) protein. We have demonstrated that a high proportion of gastric cancer (GC) cell lines (∼50%) are responsive (IC50 Based on these data, a Phase II GC trial has been carried out that enriches for patients with tumors having low or undetectable ATM IHC scores (H-score equivalent less than or equal to 10). Data from this clinical trial confirm activity (overall survival [OS] benefit HR=0.56, 95% CI: 0.35-0.87; P=0.010) in the overall population, which includes ATM tumor positive patients, and importantly, a substantially better OS benefit in the ATM-negative population (HR=0.35, 95% CI: 0.17-0.71; P=0.003). Together, these data provide an important example of a PARP inhibitor demonstrating both preclinical and clinical activity in a well defined but non-BRCA DNA repair deficient background. Citation Format: Darren Hodgson, Helen Mason, Lenka Oplustilova, Chris Harbron, Xiaolu Yin, Seock-Ah Im, Helen Jones, Lai Zhongwu, Brian Dougherty, Matthew McLoughlin, James Bradford, Andrew Dickinson, Anitra Fielding, Jane Robertson, Woo-Ho Kim, Chris Womack, Yi Gu, Yung-Jue Bang, Alan Lau, J. Carl Barrett, Mark J. O'Connor. Activity of the PARP inhibitor olaparib in ATM-deficient gastric cancer: from preclinical models to the clinic. [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 2398. doi:10.1158/1538-7445.AM2014-2398

Building upon the exciting precedent exemplified by olaparib in the PARP-BRCA axis, we aim to identify and exploit further synthetic lethal (SL) interactions within and beyond the DNA damage response (DDR) area. To facilitate with this search, we have developed a method implemented as an in silico algorithm that uses gene expression and mutation data to detect putative SL interactions in cell lines and cancer tissue across The Cancer Genome Atlas (TCGA). This approach has detected relatively rare signatures including those described in the literature, for example ATM and ATR. The algorithm has also revealed potentially novel in silico SL gene pairs outside of DDR involving frequently mutated tumor suppressor genes linked to targets that AstraZeneca has previously developed selective compounds against. We are validating an attractive selection of these in vitro using appropriate cell lines, siRNA and small molecule inhibitors. Citation Format: Mark Wappett, Richard Ward, Paul Fisher, James Bradford, Jonathan Dry, Mark O'Connor, Alan Lau, Steve Durant. Exploiting synthetic lethal interactions in the DNA damage response area and beyond in drug discovery. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Synthetic Lethal Approaches to Cancer Vulnerabilities; May 17-20, 2013; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(5 Suppl):Abstract nr A41.

The growth of the majority of prostate tumors is driven by androgens signaling through the androgen receptor. Most patients initially respond to androgen deprivation therapies such as LHRH analogues and anti-androgens like bicalutamide, but after a varying duration of treatment, patients generally develop resistance to these therapies and their tumor progresses to an androgen independent state. Molecular mechanisms that drive androgen independent disease include mutation and amplification of androgen receptor (AR), androgen-independent activation of AR, and AR-independent mechanisms. The aim of this project was to sequence the entire genome of pairs of cell lines, modeling the progression to androgen independent disease, to increase our understanding of these mechanisms and identify new therapeutic targets. Four ‘parental’ prostate cancer cell lines, all of which are sensitive to hormone deprivation, and an androgen independent derivative of each line, derived either by culturing in bicalutamide or growing in the absence of androgens, were subjected to whole genome sequencing. Genomic variants present in the androgen independent but not the parental lines, presumed to be acquired during the progression to androgen independence, were then identified. To find any commonality between the four different pairings, the derived variants were then mapped to functional biological pathways and their likely impact on protein function predicted. Interestingly, derived mutations in the PI3K and Notch signaling pathways were identified in multiple cell lines. In addition to the analysis of derived mutations, baseline characterization of genomic rearrangements and copy number changes in cell lines highlighted variability in the patterns and prevalence of these events as well as uncovering aberrations in genes known to impact prostate cancer development (PTEN, AR, TMPRSS2 rearrangement). This extensive genome sequencing effort has yielded a deeper understanding of potential pathways and molecular events that occur during the acquisition of resistance to anti-androgen therapy, using in vitro models of prostate cancer. These candidates now require validation in tissue samples from prostate cancer patients and functional assays. Citation Format: Gillian L. Dalgliesh, Joanne L. Hartley, Cary H. O'Donnell, James R. Bradford, Iain McKendrick, Barry R. Davies. Whole-genome sequencing of paired androgen-dependent and -independent prostate cancer cell lines: Potential role of novel targets in PI3K and Notch signaling pathways in resistance to hormonal therapy [abstract]. In: Proceedings of the AACR Special Conference on Advances in Prostate Cancer Research; 2012 Feb 6-9; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2012;72(4 Suppl):Abstract nr C38.

Neonatal rats of the Holtzman strain, 6 days of age, were fed a myo-inositol restricted liquid formula by gastric intubation for 10 days, after which they were fed a purified myo-inositol-free diet until they were 72 days old. No differences in weight gain were observed between myo-inositol/100 ml of formula or 150 mg myo-inositol/100 g diet. Most tissues examined from rats fed the myo-inositol deprived formula and diet had lower free myo-inositol levels than the controls with the exception of the liver. Despite reduced free and lipid-bound myo-inositol in the liver, there was no evidence of fatty liver in the young rats at any age. The cerebrum and cerebellum of myo-inositol deprived rats had normal myelination and mitochondriogenesis as judged by the levels of 2',3'-cyclic nucleotide-3'-phosphohydrolase (EC 3.1.4.1) and fumarase (EC 4.2.1.2) activity, respectively.