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Around 12–15% of patients with locally advanced rectal cancer undergo a pathologically complete response (tumor regression grade 4) to long-course preoperative chemoradiotherapy; the remainder exhibit a spectrum of tumor regression (tumor regression grade 1–3). Understanding therapy-related transcriptional alterations may enable better prediction of response as measured by progression-free and overall survival, in addition to aiding the development of improved strategies based on the underlying biology of the disease. To this end, we performed high-throughput gene expression profiling in 40 pairs of formalin-fixed paraffin-embedded rectal cancer biopsies and matched resections following long-course preoperative chemoradiotherapy (discovery cohort). Differential gene expression analysis was performed contrasting tumor regression grades in resections. Enumeration of the tumor microenvironment cell population was undertaken using in silico analysis of the transcriptional data, and real-time PCR validation of NCR1 undertaken. Immunohistochemistry and survival analysis was used to measure CD56+ cell populations in an independent cohort (n=150). Gene expression traits observed following long-course preoperative chemoradiotherapy in the discovery cohort suggested an increased abundance of natural killer cells in tumors that displayed a clinical response to CRT in a tumor regression grade-dependent manner. CD56+ natural killer-cell populations were measured by immunohistochemistry and found to be significantly higher in tumor regression grade 3 patients compared with tumor regression grade 1–2 in the validation cohort. Furthermore, it was observed that patients positive for CD56 cells after therapy had a better overall survival (HR=0.282, 95% CI=0.109–0.729, χ2=7.854, P=0.005). In conclusion, we have identified a novel post-therapeutic natural killer-like transcription signature in patients responding to long-course preoperative chemoradiotherapy. Furthermore, patients with a higher abundance of CD56-positive natural killer cells post long-course preoperative chemoradiotherapy had better overall survival. Therefore, harnessing a natural killer-like response after therapy may improve outcomes for locally advanced rectal cancer patients. Finally, we hypothesize that future assessment of this natural killer-like response in on-treatment biopsy material may inform clinical decision-making for treatment duration.

Colorectal cancer (CRC) has one of the highest worldwide incidences and mortality rates. About 25% of stage II patients develop recurrence within 5 years. However, use of adjuvant chemotherapy yields minimal therapeutic benefit. Clinical decision-making in this population would be informed by prognostic and predictive biomarkers that help indicate more targeted interventions and/or intensified disease monitoring. Higher cMET expression has been shown to be a prognostic marker in CRC and has been evaluated as a drug target in several cancers, including CRC. cMET acts as the receptor for hepatocyte growth factor (HGF), and is associated with increased proliferation, migration and morphogenesis of epithelial cells via activation of multiple downstream pathways including PI3K/AKT, MAPK and the NF-kB pathways. Here, we investigated whether increased cellular expression of multiple markers in the cMET/adjacent pathways was correlated with clinical outcome. The study population consisted of 283 patients with stage II CRC, without neoadjuvant treatment. Using a multiplexed immunofluorescence method (MxIF) with cell-level quantification (Cell DIVETM, GE Healthcare), 41 biomarkers in the cMET, mTOR, MAPK and associated pathways, and lymphocyte markers were analyzed in an iterative sequence of staining, imaging and dye inactivation, followed by image registration, cell segmentation and biomarker intensity-quantitation. Poor quality images and cells were filtered based on poor segmentation and tissue quality following manual review. Images that did not perfectly register were also excluded. For epithelial cell analysis, all stromal cells were filtered, resulting in a total of 559,952 epithelial cells. K-means clustering was conducted on cMET and related pathways (cMET, pGSK3β, 4EBP1, p4EBP1, S6, pS6, pStat3, pp38MAPK, pNFkBp65, pNFkBp105, EGFR, pERK1/2, HER2, IGF1R, CA-IX, Glut1, SLC7A5 and Ki67). Cluster analysis identified 6 cell clusters with varying expression levels of cMET and other pathway markers. A cluster corresponding to low cMET network activation (cMETLow) was correlated with reduced risk of recurrence (cox pH model Likelihood ratio test p-value = 0.056). Furthermore, MMR proficient patients (who had a higher recurrence rate) had a significantly greater proportion of cells with elevated cMET and related pathway marker (cMETHigh) s(p= 0.007). They also had a significantly lower fraction of infiltrating helper T cells (CD3+CD4+, pvalue 0.076) and CD68+ cells in the epithelial region, compared to MMR deficient patients (p=0.005). Further research will include continuing in-depth analysis of MMR status, cMET pathway and lymphocyte response as well as the role of cellular heterogeneity. In summary, comprehensive cMET pathway analysis using a multiplexed single cell approach indicates for the first time an association between low cMET network activation and superior clinical outcomes. Citation Format: Elizabeth McDonough, Anup Sood, Fiona Ginty, Sanghee Cho, John Graf, Jochen Prehn, Philip Dunne, Andreas Lindner, Manuela Salvucci, Daniel Longley, Mark Lawler, Travis Hollmann, Jinru Shia. Lower cellular activation of cMET signaling network is associated with reduced recurrence risk in stage II colorectal cancer [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A039. doi:10.1158/1535-7163.TARG-19-A039

Apoptosis is essential for chemotherapy responses. We previously developed the mathematical models APOPTO-CELL and DR_MOMP to estimate the magnitude of tumor cells resilience to undergo and execute apoptosis in response to chemotherapy, and demonstrated that these models are prognostic markers of clinical responses in stage 3 colorectal cancer patients [Salvucci M et al., Clin Cancer Res 2017; Lindner AU et al., Gut 2018]. However, the heterogeneity of colorectal cancer tissue represents a hurdle that we have yet to overcome on our way to entirely understand differences in response and clinical outcome in patients. Quantification of protein levels as input for systems studies routinely reflects a local cell population average rather than protein levels in individual cells. In this study we aim to gain a better understanding of apoptosis resilience in tumors with respect to tumor cell heterogeneity and cell composition and local aspects of the tumor microenvironment. Two to three core slices of formalin-fixed and paraffin-embedded primary colorectal cancer tissue were collected from 165 stage II-IV patients from a previously used cohort [Salvucci M et al. 2017; Lindner AU et al. 2018]. The levels of 25 protein markers for cell type and immune status, apoptosis, metabolism and cell proliferation, as well as cell segmentation markers, were measured on TMA slides using a multiplexed tissue immunofluorescence imaging platform (Cell DIVE [Gerdes et al., Proc Natl Acad Sci USA 2013]). Batch correction between slides was performed using linear regression (using markers for regulatory T cell in patient tissues as housekeeping cells. Formalin-fixed gene deficient cells were used in parallel for antibody validation. The layout allowed us to create protein profiles for on average 13,079 (± 2,282 SD) cells per core per patient, and to categorize these as epithelial-like cells, regulatory T cells, T helper cells, cytotoxic T cells, other leukocytes and other cells. The data will be used to identify cells contributing most to the signal measured with traditional methods (such as reverse protein phase arrays) that were used to predict patients clinical response to therapy in our previous studies. Further, we will assess spatial differences in distribution and frequency of different cells and their contribution to clinical outcome in colorectal cancer patients. Specifically, we are investigating metrics to characterize the spatial features and layout found in each core in terms of textures, degree of lacunarity, neighboring cells composition and patterns of protein expression (diffuse vs. patchy) and co-expression among cell types. Further, we will characterize the degree of intra- and inter-patient spatial heterogeneity and will examine the association between the identified spatial motifs with macroscopical characteristics of the tumor and outcome. Citation Format: Andreas Urlich Lindner, Manuela Salvucci, Xanthi Stachtea, Steven Carberry, Philip D. Dunne, Anup Sood, Elizabeth McDonough, Sanghee Cho, Pierre Laurent-Puig, Sandra Van Schaeybroeck, Manuel Salto-Tellez, John F. Graf, Markus Rehm, Mark Lawler, Daniel B. Longley, Fiona Ginty Fiona, Jochen H. Prehn. Exploratory multiplex tissue image analysis of the impact of heterogeneity in the microenvironment of primary colorectal cancer on apoptosis markers in patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-088.

Background: The tumor microenvironment is a key feature to understand cancer biology and may be used clinically. Quantification of tissue composition is usually based either on visual pathological review (VPR) or deconvolution of whole genome molecular data. Although the former is a direct measurement it has modest reproducibility while the latter is an indirect measurement of unclear accuracy, expensive and not always available. Here we test digital pathology coupled with machine learning as a new tool to assess tissue composition. Methods: As part of the Stratification in COloRecTal cancer (S:CORT) programme, a set of over 500 colorectal cancer (CRC) archival paraffin blocks from resections and biopsies were sequentially sectioned for Hematoxylin and Eosin staining (H&E), RNA extraction, a second H&E and DNA extraction. RNA expression microarrays, targeted DNA sequencing and DNA methylation arrays were applied. Tissue composition from the H&Es was obtained by VPR of expert pathologists and by a deep neural net (DNN) algorithm after supervised training on >1,500 tissue areas from S:CORT, TCGA, TEM and CORGI CRC cohorts. Tumor purity estimates were obtained from RNA and methylation arrays. Results: DNN estimates including area and cell counts were obtained for tumor, desmoplastic stroma, inflamed stroma, mucin/hypocellular stroma, muscle, necrosis and white space. An average of 6.8x105 total cells (range: 1.2x104-2.8x106) and 1.2x105 (range: 7.2x104-1.8x106) were classified for resections and biopsies respectively. Analyses performed twice on the same H&Es obtained matching results (r=1.0). Comparison of the paired first and second H&E showed very high correlations (r~0.9) and total cell counts correlated with DNA and RNA extraction yields (r~0.6). Tumor purity estimates by VPR mildly correlated with DNN (r~0.5) but they were underestimated and very variable. As a result, copy number adjusted by VPR purity tended to be overestimated compared to adjustment with DNN estimates. The improved performance of DNN is reflected in an accurate capture of non-linear association between area and cell counts in invasive cancer. In contrast, tumor purity estimates derived from RNA or DNA methylation arrays showed better correlations compared with DNN (r~0.6) but both overestimated purity in cases with low cell counts by up to a three-fold difference. Conclusions: Tissue composition analysis with DNN allows analytical robustness, automatization and standardization and provides very high reproducibility at single cell resolution. DNN-based estimation of tumor purity is more accurate than VPR or extrapolation from molecular data derived from genome-wide omic platforms which tend to under and overestimate tumor purity respectively. DNN could be used to better plan and asses downstream molecular analyses and to investigate tissue-based metrics as potential clinical biomarkers in clinical trials. Citation Format: Enric Domingo, Aikaterini Chatzipli, Susan Richman, Andrew Blake, Claire Hardy, Celina Whalley, Keara Redmon, Ian Tomlinson, Philip Dunne, Steven Walker, Andrew Beggs, Ultan McDermott, Graeme I. Murray, Leslie M. Samuel, Matthew Seymour, Philip Quirke, Tim Maughan, Viktor H. Koelzer. Assessment of tissue composition with digital pathology in colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4446.

Purpose: Despite the use of 5-fluorouracil (5-FU)–based adjuvant treatments, a large proportion of patients with high-risk stage II/III colorectal cancer will relapse. Thus, novel therapeutic strategies are needed for early-stage colorectal cancer. Residual micrometastatic disease from the primary tumor is a major cause of patient relapse. Experimental Design: To model colorectal cancer tumor cell invasion/metastasis, we have generated invasive (KRASMT/KRASWT/+chr3/p53-null) colorectal cancer cell subpopulations. Receptor tyrosine kinase (RTK) screens were used to identify novel proteins that underpin the migratory/invasive phenotype. Migration/invasion was assessed using the XCELLigence system. Tumors from patients with early-stage colorectal cancer (N = 336) were examined for AXL expression. Results: Invasive colorectal cancer cell subpopulations showed a transition from an epithelial-to-mesenchymal like phenotype with significant increases in migration, invasion, colony-forming ability, and an attenuation of EGF receptor (EGFR)/HER2 autocrine signaling. RTK arrays showed significant increases in AXL levels in all invasive sublines. Importantly, 5-FU treatment resulted in significantly increased migration and invasion, and targeting AXL using pharmacologic inhibition or RNA interference (RNAi) approaches suppressed basal and 5-FU–induced migration and invasion. Significantly, high AXL mRNA and protein expression were found to be associated with poor overall survival in early-stage colorectal cancer tissues. Conclusions: We have identified AXL as a poor prognostic marker and important mediator of cell migration/invasiveness in colorectal cancer. These findings provide support for the further investigation of AXL as a novel prognostic biomarker and therapeutic target in colorectal cancer, in particular in the adjuvant disease in which EGFR/VEGF–targeted therapies have failed. Clin Cancer Res; 20(1); 164–75. ©2013 AACR.

QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath’s flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.

BACKGROUND: Combined MET and BRAF inhibition showed clinical benefit in a patient with rectal cancer carrying BRAF(V600E) and MET amplification. However after 4 months, acquired resistance emerged and the patient deceased shortly after disease progression. The mechanism of resistance to this drug combination is unknown.METHODS: We analysed plasma circulating tumour DNA obtained at progression by exome sequencing and digital PCR. MET gene and mRNA in situ hybridisation analyses in two bioptic specimens obtained at progression were used to confirm the plasma data.RESULTS: We identified in plasma MET gene hyper-amplification as a potential mechanism underlying therapy resistance. Increased MET gene copy and transcript levels were detected in liver and lymph node metastatic biopsies. Finally, transduction of MET in BRAF mutant colorectal cancer cells conferred refractoriness to BRAF and MET inhibition.CONCLUSIONS: We identified in a rectal cancer patient MET gene hyper-amplification as mechanism of resistance to dual BRAF and MET inhibition.

// Qing Wen 1 , Philip D. Dunne 1 , Paul G. O’Reilly 1 , Gerald Li 1 , Anthony J. Bjourson 2 , Darragh G. McArt 1 , Peter W. Hamilton 1, * , Shu-Dong Zhang 1, 2, * 1 Centre for Cancer Research and Cell Biology, Queen’s University Belfast, UK 2 Northern Ireland Centre for Stratified Medicine, Biomedical Sciences Research Institute, Ulster University, C-TRIC, Londonderry, UK * Joint Senior Author Correspondence to: Qing Wen, email: qwen02@qub.ac.uk Peter W. Hamilton, email: P.Hamilton@qub.ac.uk Keywords: connectivity mapping, differentially expressed genes, colorectal cancer, KRAS mutation, FDA approved drugs Received: May 15, 2016 Accepted: November 30, 2016 Published: December 10, 2016 ABSTRACT Colorectal cancer (CRC) is a life-threatening disease with high prevalence and mortality worldwide. The KRAS oncogene is mutated in approximately 40% of CRCs. While antibody based EGFR inhibitors (cetuximab and panitumumab) represent a major treatment strategy for advanced KRAS wild type (KRAS-WT) CRCs, there still remains no effective therapeutic course for advanced KRAS mutant (KRAS-MT) CRC patients. In this study, we employed a novel and comprehensive approach of gene expression connectivity mapping (GECM) to identify candidate compounds to target KRAS-MT tumors. We first created a combined KRAS-MT gene signature with 248 ranked significant genes using 677 CRC clinical samples. A series of 248 sub-signatures was then created containing an increasing number of the top ranked genes. As an input to GECM analysis, each sub-signature was translated into a statistically significant therapeutic drugs list, which was finally combined to obtain a single list of significant drugs. We identify four antihypertensive angiotensin II receptor blockers (ARBs) within the top 30 significant drugs indicating that these drugs have a mechanism of action that can alter the KRAS-MT CRC oncogenic signaling. A hypergeometric test ( p-value = 6.57 × 10 −6 ) confirmed that ARBs are significantly enriched in our results. These findings support the hypothesis that ARB antihypertensive drugs may directly block KRAS signaling resulting in improvement in patient outcome or, through a reversion to a KRAS wild-type phenotype, improve the response to anti-EGFR treatment. Antihypertensive angiotensin II receptor blockers are therefore worth further investigation as potential therapeutic candidates in this difficult category of advanced colorectal cancers.

Glioblastoma (GBM) is the most prevalent and aggressive of malignant primary brain tumours. Despite multi-modal therapy, including surgical resection, radiotherapy and chemotherapy, GBM continues to be uniformly lethal, with a median survival of 12–18 months from the time of diagnosis. The resistance to therapy and ultimate recurrence is thought to originate from a sub-population of cells residing in the initial tumour, identified as glioma-initiating or glioma-stem cells (GSC). These GSC have been shown to be intrinsically more invasive, with enhanced repair and drug-efflux pathways mediating resistance to chemo-radiation therapies. The purpose of this study was to use and validate a novel connectivity mapping procedure to identify candidate compounds targeting therapy-resistant and recurrent GBM. This procedure was developed by O’Reilly and colleagues (“QUADrATiC: A Scalable Approach to Repurposing FDA-approved therapeutics”, under review in Bioinformatics), and in this study, was performed on publicly available NCBI GEO microarray datasets. Based on the cancer stem cell theory whereby the resistant GSCs repopulate and are enriched in recurrent tumours, primary and recurrent GBM gene expression profiles were compared and the connections between the identified gene lists and drug responses were mapped. To validate that this connectivity mapping procedure is reliable at identifying effective treatments to target therapeutic resistance and recurrence, we tested one of the top ten compounds identified, rosiglitazone (rosi), a ligand of the peroxisome proliferator activated receptor gamma (PPARγ). The efficacy of rosi alone and in combination with the current standard of care therapies, temozolomide and radiation, at killing GSC was assessed in vitro using the clonogenic survival assay. Our data indicated that rosi significantly reduced survival of both non-stem glioma cells and GSC, alone and in combination with radiation and temozolomide. The p53 pathway was identified as a pathway by which rosi may induce permanent cell cycle arrest and cell death. Further work is ongoing to fully elucidate the downstream mechanisms of cell death. This work is proof-of-principle that the current connectivity mapping procedure can be instrumental in identifying more targeted therapeutic interventions for GBM resistance and prevent recurrence.

AimsBoth morphological and molecular approaches have highlighted the biological and prognostic importance of the tumour microenvironment in colorectal cancer (CRC). Despite this, microscopic assessment of tumour microenvironment has not been adopted into routine practice.Methods and ResultsBased on existing evidence, we selected specific morphological features relating to peritumoral inflammatory and stromal responses, agreed criteria for scoring, and assessed these in representative H&E-stained whole tumour sections, from a population-based cohort of 445 stage II/III colon cancer cases. Moderate/severe peritumoral diffuse lymphoid inflammation and Crohn's disease-like reaction were associated with significantly reduced risks of CRC-specific death (adjusted HR 0.48, 95% CI 0.31-0.76, and HR 0.60, 95% CI 0.42-0.84, respectively). The presence of >50% tumour stromal percentage, assessed by global evaluation of tumour area, was associated with a significantly increased risk of CRC-specific death (HR 1.60 95% CI 1.06-2.41). A composite, “fibroinflammatory score” (0-3), combining dichotomised scores of these three features, showed a highly significant association in relation to survival outcomes. Those with a score ≥2 had an almost 2.5 fold increased risk of CRC-specific death (HR 2.44, 95% CI: 1.56-3.81), compared with those scoring zero. These associations were stronger in MSI-high tumours, potentially identifying a subset of MSI-high colon cancers which lack characteristic morphological features and have an associated worse prognosis.ConclusionsIn summary, reporting on H&E staining of selected microscopic features of the tumour microenvironment, independently or in combination, offers valuable prognostic information in stage II/III colon cancer and may allow morphological correlation with developing molecular classifications of prognostic and predictive relevance.

// Conor A. Bradley 1, * , Philip D. Dunne 1, * , Victoria Bingham 1 , Stephen McQuaid 1, 2 , Hajrah Khawaja 1 , Stephanie Craig 1 , Jackie James 1, 2 , Wendy L. Moore 1 , Darragh G. McArt 1 , Mark Lawler 1 , Sonali Dasgupta 1 , Patrick G. Johnston 1 , Sandra Van Schaeybroeck 1 1 Drug Resistance Group, Centre for Cancer Research and Cell Biology, School of Medicine, Dentistry and Biomedical Science, Queen’s University Belfast, Belfast, UK 2 Tissue Pathology, Belfast Health and Social Care Trust, Belfast City Hospital, Belfast, UK * Joint first authors Correspondence to: Sandra Van Schaeybroeck, email: s.vanschaeybroeck@qub.ac.uk Keywords: c-MET, colorectal cancer (CRC), tumor budding, invasion, metastasis Received: July 06, 2016 Accepted: October 19, 2016 Published: October 26, 2016 ABSTRACT c-MET and its ligand HGF are frequently overexpressed in colorectal cancer (CRC) and increased c-MET levels are found in CRC liver metastases. This study investigated the role of the HGF/c-MET axis in regulating migration/invasion in CRC, using pre-clinical models and clinical samples. Pre-clinically, we found marked upregulation of c-MET at both protein and mRNA levels in several invasive CRC cells. Down-regulation of c-MET using RNAi suppressed migration/invasion of parental and invasive CRC cells. Stimulation of CRC cells with rh-HGF or co-culture with HGF-expressing colonic myofibroblasts, resulted in significant increases in their migratory/invasive capacity. Importantly, HGF-induced c-MET activation promoted rapid downregulation of c-MET protein levels, while the MET transcript remained unaltered. Using RNA in situ hybridization (RNA ISH), we further showed that MET mRNA, but not protein levels, were significantly upregulated in tumor budding foci at the invasive front of a cohort of stage III CRC tumors ( p < 0.001). Taken together, we show for the first time that transcriptional upregulation of MET is a key molecular event associated with CRC invasion and tumor budding. This data also indicates that RNA ISH, but not immunohistochemistry, provides a robust methodology to assess MET levels as a potential driving force of CRC tumor invasion and metastasis.

Purpose: A number of independent gene expression profiling studies have identified transcriptional subtypes in colorectal cancer with potential diagnostic utility, culminating in publication of a colorectal cancer Consensus Molecular Subtype classification. The worst prognostic subtype has been defined by genes associated with stem-like biology. Recently, it has been shown that the majority of genes associated with this poor prognostic group are stromal derived. We investigated the potential for tumor misclassification into multiple diagnostic subgroups based on tumoral region sampled. Experimental Design: We performed multiregion tissue RNA extraction/transcriptomic analysis using colorectal-specific arrays on invasive front, central tumor, and lymph node regions selected from tissue samples from 25 colorectal cancer patients. Results: We identified a consensus 30-gene list, which represents the intratumoral heterogeneity within a cohort of primary colorectal cancer tumors. Using a series of online datasets, we showed that this gene list displays prognostic potential HR = 2.914 (confidence interval 0.9286–9.162) in stage II/III colorectal cancer patients, but in addition, we demonstrated that these genes are stromal derived, challenging the assumption that poor prognosis tumors with stem-like biology have undergone a widespread epithelial–mesenchymal transition. Most importantly, we showed that patients can be simultaneously classified into multiple diagnostically relevant subgroups based purely on the tumoral region analyzed. Conclusions: Gene expression profiles derived from the nonmalignant stromal region can influence assignment of colorectal cancer transcriptional subtypes, questioning the current molecular classification dogma and highlighting the need to consider pathology sampling region and degree of stromal infiltration when employing transcription-based classifiers to underpin clinical decision making in colorectal cancer. Clin Cancer Res; 22(16); 4095–104. ©2016 AACR. See related commentary by Morris and Kopetz, p. 3989

Gremlin1 (Grem1), an antagonist of bone morphogenetic proteins, plays a key role in embryogenesis. A highly specific temporospatial gradient of Grem1 and bone morphogenetic protein signaling is critical to normal lung, kidney, and limb development. Grem1 levels are increased in renal fibrotic conditions, including acute kidney injury, diabetic nephropathy, chronic allograft nephropathy, and immune glomerulonephritis. We demonstrate that a small number of grem1−/− whole body knockout mice on a mixed genetic background (8%) are viable, with a single, enlarged left kidney and grossly normal histology. The grem1−/− mice displayed mild renal dysfunction at 4 wk, which recovered by 16 wk. Tubular epithelial cell-specific targeted deletion of Grem1 (TEC-grem1-cKO) mice displayed a milder response in the acute injury and recovery phases of the folic acid model. Increases in indexes of kidney damage were smaller in TEC-grem1-cKO than wild-type mice. In the recovery phase of the folic acid model, associated with renal fibrosis, TEC-grem1-cKO mice displayed reduced histological damage and an attenuated fibrotic gene response compared with wild-type controls. Together, these data demonstrate that Grem1 expression in the tubular epithelial compartment plays a significant role in the fibrotic response to renal injury in vivo.

Modern approaches to biomedical research and diagnostics targeted towards precision medicine are generating ‘big data’ across a range of high-throughput experimental and analytical platforms. Integrative analysis of this rich clinical, pathological, molecular and imaging data represents one of the greatest bottlenecks in biomarker discovery research in cancer and other diseases. Following on from the publication of our successful framework for multimodal data amalgamation and integrative analysis, Pathology Integromics in Cancer (PICan), this article will explore the essential elements of assembling an integromics framework from a more detailed perspective. PICan, built around a relational database storing curated multimodal data, is the research tool sitting at the heart of our interdisciplinary efforts to streamline biomarker discovery and validation. While recognizing that every institution has a unique set of priorities and challenges, we will use our experiences with PICan as a case study and starting point, rationalizing the design choices we made within the context of our local infrastructure and specific needs, but also highlighting alternative approaches that may better suit other programmes of research and discovery. Along the way, we stress that integromics is not just a set of tools, but rather a cohesive paradigm for how modern bioinformatics can be enhanced. Successful implementation of an integromics framework is a collaborative team effort that is built with an eye to the future and greatly accelerates the processes of biomarker discovery, validation and translation into clinical practice.

The topoisomerase I inhibitor irinotecan is used to treat advanced colorectal cancer and has been shown to have p53-independent anticancer activity. The aim of this study was to identify the p53-independent signaling mechanisms activated by irinotecan. Transcriptional profiling of isogenic HCT116 p53 wild-type and p53 null cells was carried out following treatment with the active metabolite of irinotecan, SN38. Unsupervised analysis methods showed that p53 status had a highly significant impact on gene expression changes in response to SN38. Pathway analysis indicated that pathways involved in cell motility [adherens junction, focal adhesion, mitogen-activated protein kinase (MAPK), and regulation of the actin cytoskeleton] were significantly activated in p53 null cells, but not p53 wild-type cells, following SN38 treatment. In functional assays, SN38 treatment increased the migratory potential of p53 null and p53-mutant colorectal cancer cell lines, but not p53 wild-type lines. Moreover, p53 null SN38-resistant cells were found to migrate at a faster rate than parental drug-sensitive p53 null cells, whereas p53 wild-type SN38-resistant cells failed to migrate. Notably, cotreatment with inhibitors of the MAPK pathway inhibited the increased migration observed following SN38 treatment in p53 null and p53-mutant cells. Thus, in the absence of wild-type p53, SN38 promotes migration of colorectal cancer cells, and inhibiting MAPK blocks this potentially prometastatic adaptive response to this anticancer drug. Mol Cancer Ther; 11(8); 1724–34. ©2012 AACR.

Available treatments for glioma have limited effectiveness rendering this a disease of poor clinical outcome. Gene expression profiling can uncover the biological mechanisms underlying disease, information that is crucial for drug development or repurposing. RNA sequencing (RNA-seq) is routinely used to assess gene expression but costs remain high. Whilst sample multiplexing reduces RNA-seq costs, the lowered cDNA sequencing depth of multiplexed samples may hinder accurate differential gene expression detection. The impact of sequencing depth alteration on RNA-seq-based downstream analyses such as gene expression connectivity mapping is not known. Connectivity mapping is a method used to identify potential therapeutic compounds for drug repurposing. In this study, published RNA-seq from brain tumour (glioma) patients were analysed and assembled into two gene signature contrasts for astrocytoma disease progression (WHO Grade II-III; III-IV). Gene signatures were subsampled to simulate sequencing depth alterations and analysed in connectivity mapping to investigate target compound robustness. Data loss to gene signatures led to the loss, gain and consistent identification of significant connections to target compounds. The most accurate gene signature contrast with consistent patient gene expression profiles was more resilient to data loss and identified robust target compounds. Target compounds lost included candidate compounds of potential clinical utility in glioma (e.g. Suramin, Dasatinib). Lost connections may have been linked to low abundance genes in the gene signature that closely characterised the disease phenotype. Consistently identified connections may have related to highly expressed abundant genes that were ever-present in gene signatures, despite data reductions. Potential noise surrounding findings included false positive connections that were gained as a result of gene signature modification with data loss. Findings highlight the necessity for gene signature accuracy for connectivity mapping, which should improve the clinical utility of future target compounds identified for drug repurposing.

BACKGROUND: Gene expression profiling can uncover biological mechanisms underlying disease and is important in drug development. RNA-seq is routinely used to assess gene expression but costs remain high. Sample multiplexing reduces RNA-seq costs, however, multiplexed samples have lower cDNA sequencing depth, which can hinder accurate differential gene expression detection. The impact of sequencing depth alteration on RNA-seq-based downstream analyses such as gene expression connectivity mapping is not known, where connectivity mapping can be used to identify potential therapeutic compounds for repurposing. MATERIAL AND METHODS: In this study, published RNA-seq profiles from brain tumour (glioma) patients were assembled into two disease progression gene signature contrasts for astrocytoma. Available treatments for glioma have limited effectiveness rendering this a disease of poor clinical outcome. Gene signatures were subsampled to simulate sequencing alterations and analysed in connectivity mapping to investigate target compound robustness. RESULTS: Data loss to gene signatures led to the loss, gain and consistent identification of significant connections. The most accurate gene signature contrast with consistent patient gene expression profiles was more resilient to data loss and identified robust target compounds. Target compounds lost included candidate compounds of potential clinical utility in glioma (e.g. Suramin, Dasatinib). Lost connections may have been linked to low abundance genes in the gene signature that closely characterised the disease phenotype. Consistently identified connections may have been related to highly expressed abundant genes that were ever-present in gene signatures, despite data reductions. Potential noise surrounding findings included false positive connections that were gained as a result of gene signature modification with data loss. CONCLUSION: Findings highlight the necessity for gene signature accuracy for connectivity mapping, which should improve the clinical utility of future target compound discoveries.

Colorectal cancer (CRC) biopsies underpin accurate diagnosis, but are also relevant for patient stratification in molecularly-guided clinical trials. The consensus molecular subtypes (CMS) and colorectal cancer intrinsic subtypes (CRIS) transcriptional signatures have potential clinical utility for improving prognostic/predictive patient assignment. However, their ability to provide robust classification, in pre-treatment biopsies from multiple regions or at different time points remains untested. In this study, we undertook a comprehensive assessment of the robustness of CRC transcriptional signatures, including CRIS and CMS, using a range of tumour sampling methodologies currently employed in clinical and translational research. These include analyses using (i) laser-capture microdissected CRC tissue, (ii) eight publically available rectal cancer biopsy data sets (n=543), (iii) serial biopsies (from AXEBeam trial, NCT00828672; n=10), (iv) multi-regional biopsies from colon tumours (n=29 biopsies, n=7 tumours) and (v) pre-treatment biopsies from the phase II rectal cancer trial COPERNCIUS (NCT01263171; n=44). Compared to previous results obtained using CRC resection material, we now demonstrate that CMS classification in biopsy tissue is significantly less capable of reliably classifying patient subtype (43% unknown in biopsy versus 13% unknown in resections, p=0.0001). In contrast, there was no significant difference in classification rate between biopsies and resections when using the CRIS classifier. Additionally, we demonstrated that CRIS provides significantly better spatially- and temporally- robust classification of molecular subtypes in CRC primary tumour tissue compared to CMS (p= 0.003 and p=0.02, respectively). These findings may have potential to inform ongoing biopsy-based patient stratification in CRC, enabling robust and stable assignment of patients into clinically-informative arms of prospective multi-arm, multi-stage clinical trials. Citation Format: Matthew Alderdice, Susan D. Richman, Simon Gollins, Peter Stewart, Chris Hurt, Richard Adams, Amy M. McCorry, Aideen Roddy, Dale Vimalachandran, Claudio Isella, Enzo Medico, Tim Maughan, Darrgh G. McArt, Mark Lawler, Philip D. Dunne. Prospective patient stratification into robust cancer-cell intrinsic subtypes from colorectal cancer biopsies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5365.

Technology advancements have enhanced our abilities to gain greater insight to the tumor environment. However, such emergent methods have brought new considerations in data storage, access and analysis. Modern large data projects and clinical trial materials could be explored to a greater degree if appropriate infrastructure could be built to support efforts. Such a scaffold would be an integrated and dynamic framework where novel hypotheses could be investigated in modern big data collections. Placing discovery back in the hands of the researcher through a reactive and supportive framework will enhance our understanding of cancer aetiology. The Cancer Integromics Research Application Framework (CIRAFm) was created to emulate current platforms that have a rigid analytical interface. We designed a robust architecture that supports a reactive user-friendly interface blended to several cross-platform coding technologies. It has been developed to accommodate an individualised framework where we can create an ‘app-store' of key software to fit research questions. In efforts to encapsulate and accelerate differing data types it sits astride of two NoSQL based database management systems, minimising data redundancy. Initial requirements have begun to create algorithms to investigate alignment-free applications on next generation sequencing (NGS) data enhancing analysis of spatial and temporal heterogeneity in cancer. Key drivers can be explored by assisting software to build correlative marker associations using Darwinian approaches such as genetic algorithms. Information requirements from external platforms are assisted through a novel domain specific language (DSL) to enable a singular interface. The modularised architecture of the platform is enabled through an Angular framework supported by interactive and dynamic data visualisation software, D3.js. Data analytics can be explored through the ‘apps' created, investigating new markers in large data and enhancing our understanding of tumor heterogeneity. Alignment-free phylogenetics of NGS data harnesses our capabilities to display fully sequence evolution in patient data. This highlights possible sub-types, markers of interest and maps to therapeutic compounds via the DSL to our externally developed drug discovery software, QUADrATiC. Future scientific endeavours further defining new tumor subtypes are paramount in efforts to help uncover treatment strategies. Unburdened by legacy pipelines and data, flexible and robust models of architecture provide an effective and efficient framework for research on our ever increasing search for precision medicine. Citation Format: Darragh G. McArt, Seedevi Senevirathne, Aideen Roddy, Jessica Black, Alan Gilmore, Suneil Jain, Philip Dunne, David Waugh. Integrative analytics: A framework for precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 290.

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths in the Western world. It is becoming increasingly clear that CRC is a diverse disease, as exemplified by the identification of subgroups of CRC tumours that are driven by distinct biology. Recently, a number of studies have begun to define panels of diagnostically relevant markers to align patients into individual subgroups in an attempt to give information on prognosis and treatment response. We examined the immunohistochemical expression profile of 18 markers, each representing a putative role in cancer development, in 493 primary colorectal carcinomas using tissue microarrays. Through unsupervised clustering in stage II cancers, we identified two cluster groups that are broadly defined by inflammatory or immune-related factors (CD3, CD8, COX-2 and FOXP3) and stem-like factors (CD44, LGR5, SOX2, OCT4). The expression of the stem-like group markers was associated with a significantly worse prognosis compared to cases with lower expression. In addition, patients classified in the stem-like subgroup displayed a trend towards a benefit from adjuvant treatment. The biologically relevant and poor prognostic stem-like group could also be identified in early stage I cancers, suggesting a potential opportunity for the identification of aggressive tumors at a very early stage of the disease. Refereed/Peer-reviewed

Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.

The application of transcriptional gene signatures to stratify tumors into prognostic and predictive subtypes has evolved rapidly since the original landmark studies demonstrated the clinical utility of this approach in breast cancer. While the number of published signatures continues to increase, the likelihood of individual signatures achieving clinical utility has remained very low, with some estimates putting this figure below 1%. Transcriptional intratumoral heterogeneity (ITH), resulting from variation in stromal components at different regions of a tumor, has been shown to undermine molecular stratification of colorectal cancer (CRC) patients into prognostic and predictive subgroups. The degree of gene expression changes associated with variation in tumor microenvironment (TME) content may even mask the relatively more subtle changes associated with genetic variability and heterogeneity within the tumor epithelium. This variation in TME content, and subsequent ITH, at different regions of the tumor has long been recognised; however, in the era of precision medicine, the implications of such microenvironmental alterations in confounding patient classification are of increased importance. To examine this issue, a panel of clinically relevant prognostic and predictive transcriptional gene signatures were selected in order to assess the potential for discordant classification of patient samples based on the tumoral region profiled. Using these clinically relevant CRC gene expression signatures, we assessed the susceptibility of each signature to the confounding effects of ITH using gene expression microarray data obtained from multiple tumor regions of a cohort of 24 patients, including central tumor, the tumor invasive front and lymph node metastasis. Consensus annotated gene lists for each of the gene signatures were used, followed by in silico analysis within our multiregional clinical dataset. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multiregion dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the recently developed CRC intrinsic signature (CRIS), which robustly clustered samples by patient rather than sample region. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of ITH. In conclusion, our data support the clinical evaluation of signatures based on intrinsic gene expression, such as CRIS, which are unaffected by the confounding variable of transcriptional ITH and therefore have the potential to be used clinically to inform precision medicine decisions, ultimately leading to improved patient outcomes. Citation Format: Philip D. Dunne, Paul O'Reilly, Aideen Roddy, Matthew Alderdice, Susan Richman, Tim Maughan, Simon McDade, Patrick Johnston, Daniel Longley, Elaine Kay, Darragh McArt, Mark Lawler. Cancer cell intrinsic gene expression signatures minimize the confounding effects of intratumoral heterogeneity in colorectal cancer patient classification [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-042. doi:10.1158/1538-7445.AM2017-LB-042

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping.

Background Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take > 2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping. Results cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance. Conclusion Emerging ‘omics’ technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.

Background: The c-MET proto-oncogene is frequently overexpressed (50-60%), amplified (1-3%), and mutated (1-3%) in colorectal cancer (CRC). Hepatocyte growth factor (HGF)-dependent and independent activation of c-MET has been associated with increased survival and resistance to targeted therapies. This study aimed to investigate the role of the HGF/c-MET axis in regulating migration/invasion in CRC, using pre-clinical models and clinical samples. Methods: In order to model CRC tumour cell invasion, we have generated invasive CRC subpopulations using Boyden Invasion chambers. To model the CRC microenvironment, we have used a range of co-culture techniques with CRC cells and colon fibroblasts. Migration/invasion was determined using xCELLigence System (Roche). c-MET expression in parental and invasive cell lines was measured using Western blotting and qRT-PCR. c-MET expression in CRC FFPE tissues was measured using IHC and RNAScope®. Results: We identified marked upregulated expression of c-MET at both the protein and transcript levels in our invasive CRC cell line models. Importantly, both parental and invasive subpopulations were found to be inherently dependent on c-MET for migration, as RNAi against c-MET abrogated migration/invasion in both parental and invasive models. We also demonstrated that stimulation of CRC cells with rh-HGF resulted in increased CRC cell migration/invasion. In addition, co-culture of CRC cells with colonic myofibroblasts, resulted in marked increases in migratory and invasive capacity, and this was dependent on HGF/c-MET signaling. Interestingly, stimulation with myofibroblast conditioned medium or HGF promotes rapid degradation of c-MET at the protein level, followed by recycling, while MET transcript remains unaltered, illustrating a dynamic expression of c-MET protein in response to activation. We further showed that MET is transcriptionally upregulated in tumour budding foci at the invasive front of a cohort of stage III CRC tumors. Intriguingly, c-MET protein levels do not correlate with the transcript, most likely due to a similar protein degradation process observed in our aforementioned in vitro models. Conclusions: We show for the first time a key role for transcriptional upregulation of MET as a molecular driver of tumour invasion, both in vitro and in stage III CRC tumours. Citation Format: Conor Bradley, Philip Dunne, Stephen McQuaid, Victoria Bingham, Mark Lawler, Manuel Salto-Tellez, Patrick Johnston, Sandra Van Schaeybroeck. Upregulation of the MET transcript is consistently associated with invasion and tumor budding in colorectal cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 924.

Glioblastoma (GBM) is the most prevalent and aggressive of malignant primary brain tumours. Despite multi-modal therapy, including surgical resection, radiotherapy and chemotherapy, GBM continues to be uniformly lethal, with a median survival of 12-18 months from the time of diagnosis. The resistance to therapy and ultimate recurrence is thought to originate from a sub-population of cells residing in the initial tumour, identified as glioma-initiating or glioma-stem cells (GSC). These GSC have been shown to be intrinsically more invasive, with enhanced repair and drug-efflux pathways mediating resistance to chemo-radiation therapies. The purpose of this study was to use and validate a novel connectivity mapping procedure to identify candidate compounds targeting therapy-resistant and recurrent GBM. This procedure was developed by O’Reilly and colleagues (“QUADrATiC: A Scalable Approach to Repurposing FDA-approved therapeutics”, under review in Bioinformatics), and in this study, was performed on publicly available NCBI GEO microarray datasets. Based on the cancer stem cell theory whereby the resistant GSCs repopulate and are enriched in recurrent tumours, primary and recurrent GBM gene expression profiles were compared and the connections between the identified gene lists and drug responses were mapped. To validate that this connectivity mapping procedure is reliable at identifying effective treatments to target therapeutic resistance and recurrence, we tested one of the top ten compounds identified, rosiglitazone (rosi), a ligand of the peroxisome proliferator activated receptor gamma (PPARγ). The efficacy of rosi alone and in combination with the current standard of care therapies, temozolomide and radiation, at killing GSC was assessed in vitro using the clonogenic survival assay. Our data indicated that rosi significantly reduced survival of both non-stem glioma cells and GSC, alone and in combination with radiation and temozolomide. The p53 pathway was identified as a pathway by which rosi may induce permanent cell cycle arrest and cell death. Further work is ongoing to fully elucidate the downstream mechanisms of cell death. This work is proof-of-principle that the current connectivity mapping procedure can be instrumental in identifying more targeted therapeutic interventions for GBM resistance and prevent recurrence. Citation Format: Shahnaz T. Al Rashid, Paul O’Reilly, Philip D. Dunne, Matthew Alderdice, Thomas J. Flannery, Kevin M. Prise, Shu-Dong Zhang, Darragh G. McArt. Therapeutic compound discovery targeting a recurrent glioblastoma (GBM) phenotype using LINCS compounds via QUADrATiC analyses. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 72.

SummaryThere are currently no approved targeted therapies for advanced KRAS mutant (KRASMT) colorectal cancer (CRC). Using a unique systems biology approach, we identified JAK1/2-dependent activation of STAT3 as the key mediator of resistance to MEK inhibitors in KRASMT CRC in vitro and in vivo. Further analyses identified acute increases in c-MET activity following treatment with MEK inhibitors in KRASMT CRC models, which was demonstrated to promote JAK1/2-STAT3-mediated resistance. Furthermore, activation of c-MET following MEK inhibition was found to be due to inhibition of the ERK-dependent metalloprotease ADAM17, which normally inhibits c-MET signaling by promoting shedding of its endogenous antagonist, soluble “decoy” MET. Most importantly, pharmacological blockade of this resistance pathway with either c-MET or JAK1/2 inhibitors synergistically increased MEK-inhibitor-induced apoptosis and growth inhibition in vitro and in vivo in KRASMT models, providing clear rationales for the clinical assessment of these combinations in KRASMT CRC patients.

DNA methyltransferase 1 (DNMT1) maintains methylation at CpG dinucleotides, important for transcriptional silencing at many loci. It is also implicated in stabilizing repeat sequences: DNMT1 deficiency causes microsatellite instability in mouse embryonic stem cells, but it is unclear how this occurs, how repeats lacking CpG become unstable and whether the effect is confined to stem cells. To address these questions, we transfected hTERT-immortalized normal human fibroblasts (hTERT-1604) with a short hairpin RNA construct targeting DNMT1 and isolated stable integrants with different levels of protein. DNMT1 expression levels agreed well with methylation levels at imprinted genes. Knockdown cells showed two key characteristics of mismatch repair (MMR) deficiency, namely resistance to the drug 6-thioguanine and up to 10-fold elevated mutation rates at a CA(17) microsatellite reporter, but had limited viability. The likely cause of MMR defects is a matching drop in steady-state protein levels for key repair components in DNMT1 knockdown cells, affecting both the MutLα and MutSα complexes. This indirect effect on MMR proteins was also seen using a different targeting method in HT29 colon cancer cells and did not involve transcriptional silencing of the respective genes. Decreased levels of MMR components follow activation of the DNA damage response and blocking this response, and in particular poly(ADP-ribose) polymerase (PARP) overactivation, rescues cell viability in DNMT1-depleted cells. These results offer an explanation for how and why unmethylated microsatellite repeats can be destabilized in cells with decreased DNMT1 levels and uncover a novel and important role for PARP in this process.

The c-MET proto-oncogene is frequently overexpressed (50-60%), amplified (5-10%), and mutated (5%) in colorectal cancer (CRC). Hepatocyte growth factor (HGF)-induced c-MET activation has been linked with migration, survival, invasion, and resistance to targeted therapy, and has been suggested as a possible prognostic biomarker for CRC. We are currently investigating the role of c-MET and microenvironment derived HGF in the acquisition of an invasive and migratory phenotype, and resistance to targeted therapy in CRC. In order to model CRC tumour cell invasion and metastasis, we have generated invasive subpopulations from CRC cells using Boyden Invasion chambers. Invasive cell lines were characterised for protein expression/activity by Western blotting, and analysed for migratory and invasive potential using the xCELLigence System (Roche). To model the CRC microenvironment, we have utilised a range of co-culture techniques with CRC cell lines and colon fibroblasts. c-MET expression in FFPE tissues was measured using IHC in a tissue microarray (TMA) derived from early stage CRC patients. HCT116 and LoVo invasive subpopulations showed an EMT-like, mesenchymal, migratory/invasive phenotype. In addition, increased expression and activation levels of c-MET were found in these sublines, which was determined to be ligand independent. Inhibition of c-MET using RNAi abrogated both basal and HGF-induced migration and invasion in CRC cell lines. Co-culture of CRC cells with HGF-expressing colon-derived fibroblasts leads to activation of c-MET, inducing CRC migration, invasion, and resistance to MEK inhibition, and this phenotype could be diminished using a HGF neutralising antibody. Significant increased expression levels of c-MET were also found in a CRC TMA compared to matched normal tissues, and also at the invasive edge of some CRC tumours, where it may be driving invasive biology. The identification of key pathways driving metastasis has a huge potential to change treatment strategies in CRC. We intend to further investigate the role of c-MET in regulation of migration, invasion, and resistance to therapy in CRC. We hypothesise that patients with high tumoural c-MET at the invasive front may benefit in particular from anti- c-MET therapies. Citation Format: Conor A. Bradley, Philip Dunne, Darragh McArt, Ken Arthur, Stephen McQuaid, Manuel Salto-Tellez, Patrick Johnston, Sandra Van Schaeybroeck. The role of c-MET/HGF signaling as a critical mediator of an invasive and resistant phenotype in colorectal cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4018. doi:10.1158/1538-7445.AM2015-4018

3573 Background: Despite the use of 5-FU-based adjuvant therapies, a large proportion of stage III (locally advanced) colorectal cancer (CRC) patients will relapse and die of metastatic disease. Re...

Background Inhibitor of Apoptosis Proteins (IAPs) are anti-apoptotic proteins which suppress the activation of caspases. IAP proteins have been shown to be overexpressed in several cancers, including colorectal cancer and correlate with poor prognosis. SMAC mimetics are a class of apoptosis inducing drugs that target IAPs by mimicking the N-terminal IAP-binding motif of SMAC. Colorectal cancer has a pro-inflammatory microenvironment with high levels of TNFα. The aims of this study were to assess the efficacy of SMAC mimetic treatment in colorectal cancer. Methods Colorectal cell lines were treated with SMAC mimetics and cell viability was determined using MTT assays. Apoptosis was assessed by Western blotting for caspase activation and PARP cleavage and Flow Cytometry using Annexin V/PI staining. Protein-protein interactions were assessed using co-immunoprecipitation experiments. The pro-inflammatory microenvironment was modelled by addition of exogenous TNFα and also media transfer from and direct co-cultures with macrophages (THP-1, monocytic cell line). Results Colorectal cell lines were resistant to SMAC mimetic treatment alone unless co-cultured with TNFα. Pretreatment of colorectal cancer cells with 5-FU and oxaliplatin sensitised the cells to SMAC mimetic treatment. THP-1 cells were found to secrete soluble TNFα and media transfer experiments and also co-culture with colorectal cell lines, sensitised the cancer cells to SMAC mimetic mediated cell death. Cell death under these conditions was found to be dependent on soluble TNFα through the utilisation of neutralising antibodies. Conclusion Our results to date suggest that the pro-inflammatory microenvironment of colorectal cancer could be exploited to target overexpressed IAP proteins leading to cell death. Citation Format: Nyree T. Crawford, Philip D. Dunne, Patrick G. Johnston, David J. Waugh, Daniel B. Longley. Rational targeting of inhibitor of apoptosis proteins (IAPs) for effective therapy of colorectal cancer. [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 2290. doi:10.1158/1538-7445.AM2014-2290

Background Colorectal cancer (CRC) is the third most common cancer worldwide. Among patients with early stage CRC, there are subsets of patients who will not benefit from adjuvant 5-FU or 5-FU/oxaliplatin treatment, highlighting the need for improved therapy options for early stage disease. In addition mutations in the KRAS proto-oncogene are found in 40%-45% of CRC patients and this mutation predicts resistance to EGFR mAb therapies. More recently it has been shown that treatments, such as bevacizumab or cetuximab, which prolong survival in the advanced disease setting, cannot be translated into successful adjuvant treatment strategies. The aim of this study was to identify therapy options which will be effective in the adjuvant setting and also whose knock-down is synthetically lethal with KRAS mutation in CRC models. Method A novel systems biology approach combined profiling of primary KRASMT/WT CRC tissues and isogenic paired KRASMT/WT CRC xenografts models. Metacore pathway analysis identified individual genes from novel KRAS-dependent pathways for incorporation into a primary RNAi screen. This screen was crossed with receptor tyrosine kinase analysis of our previously published pre-clinical adjuvant invasive cell line models. Our findings were validated by in vitro screening and expression analysis in CRC FFPE sections was measured using IHC. Results Our comprehensive approach identified 30 signalling pathways and 160 genes associated with KRASMT CRC cancer. Our siRNA screen confirmed a number of novel KRAS synthetic lethal target genes with a critical role in EMT and cell adhesion/migration. Down-regulation of members of the Eph/Ephrin family, in particular EpHA2, was found to be lethal in KRASMT but not KRASWT cells. This lethality was further synergistically enhanced in the presence of chemotherapy treatment. Overexpression of EphA2 was also identified in each of our invasive isogenic cell line models, regardless of genetic background, and EpHA2 silencing inhibited migration and invasion in a panel of CRC cells. EpHA2 expression has previously been reported as an essential component in cancer cells's ability to form tumors in vivo and in-line with this our EpHA2 overexpressing invasive subpopulations displayed an increased ability to form colonies. Importantly, high EpHA2 mRNA and protein expression were found to be associated with poor overall survival in both early stage CRC tissues and in advanced disease. Conclusion Using our novel comprehensive systems biology approach we have identified novel KRAS synthetic lethal targets and pathways. Combining these findings with targets which are effective against our pre-clinical adjuvant models we have identified EpHA2 as a key driver of invasion and migration and a synthetically lethal target in KRASMT CRC. In addition, we show that EpHA2 is a poor prognostic marker and an important novel target for KRASMT CRC tumors in both the adjuvant and advanced disease setting. Citation Format: Philip D. Dunne, Darragh G. McArt, Jaine K. Blayney, Sonali Dasgupta, Manuel Salto-Tellez, Patrick G. Johnston, Sandra Van Schaeybroeck. EpHA2 is an essential driver of invasion and a novel target in KRAS mutant colorectal cancer. [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 2079. doi:10.1158/1538-7445.AM2014-2079

3581 Background: EpHA2 is a 130 kD transmembrane glycoprotein belonging to ephrin receptor subfamily and involved in angiogenesis/tumour neovascularisation. High EpHA2 mRNA level has recently been ...

The discovery of underlying mechanisms of drug resistance, and the development of novel agents to target these pathways, is a priority for patients with advanced colorectal cancer (CRC). We previously undertook a systems biology approach to design a functional genomic screen and identified fibroblast growth factor receptor 4 (FGFR4) as a potential mediator of drug resistance. The aim of this study was to examine the role of FGFR4 in drug resistance using RNAi and the small-molecule inhibitor BGJ398 (Novartis). We found that FGFR4 is highly expressed at the RNA and protein levels in colon cancer tumour tissue compared with normal colonic mucosa and other tumours. Silencing of FGFR4 reduced cell viability in a panel of colon cancer cell lines and increased caspase-dependent apoptosis. A synergistic interaction was also observed between FGFR4 silencing and 5-fluorouracil (5-FU) and oxaliplatin chemotherapy in colon cancer cell lines. Mechanistically, FGFR4 silencing decreased activity of the pro-survival STAT3 transcription factor and expression of the anti-apoptotic protein c-FLIP. Furthermore, silencing of STAT3 resulted in downregulation of c-FLIP protein expression, suggesting that FGFR4 may regulate c-FLIP expression via STAT3. A similar phenotype and downstream pathway changes were observed following FGFR4 silencing in cell lines resistant to 5-FU, oxaliplatin and SN38 and upon exposure of parental cells to the FGFR small-molecule inhibitor BGJ398. Our results indicate that FGFR4 is a targetable regulator of chemo-resistance in CRC, and hence inhibiting FGFR4 in combination with 5-FU and oxaliplatin is a potential therapeutic strategy for this disease.

Background: Oncogenic mutations in BRAF occur in 8% of patients with advanced colorectal cancer (CRC) and have been shown to correlate with poor prognosis. In contrast to BRAF mutant (MT) melanoma, where the BRAF inhibitor PLX4032 has shown significant increases in response rates and overall survival compared to standard Dacarbazine treatment, only minor responses to PLX4032 treatment have been reported in BRAFMT CRC. Clear understanding of the vulnerabilities of BRAFMT CRC is important, and identification of druggable targets uniquely required by BRAFMT CRC tumors has the potential to fill a gap in the therapeutic armamentarium of advanced CRC. The aim of this study was to identify novel resistance mechanisms to MAPK inhibition in BRAFMT CRC. Methods: Paired BRAFMT/WT RKO and VACO432 CRC cell line models and non-isogenic BRAFMT LIM2405, WiDR and COLO205 CRC cells were used. Changes in protein expression/activity were assessed by Western Blotting. Interaction between MEK1/2 and JAK1/2 inhibition was assessed using the MTT cell viability assays and flow cytometry. Apoptosis was measured using Western blotting for PARP, cleaved caspase 3/8 and caspase 8, 3/7 activity assays. Results: Treatment with MEK1/2 inhibitors AZD6244, GSK1120212, UO126 and PD98059 resulted in acute increases in STAT3 activity in the BRAFMT RKO and VACO432 cells but not in their BRAFWT clones and this was associated with increases in JAK2 activity. Inhibition of JAK/STAT3 activation using gene specific siRNA or small molecule inhibitors TG101348 or AZD1480, abrogated this survival response and resulted in significant increases in cell death when combined with MEK1/2 inhibitors AZD6244 or GSK1120212 in BRAFMT CRC cells. In addition, combination of MEK1/2 and JAK/STAT3 inhibition resulted in strong synergy with CI values between 0.3 and 0.7 in BRAFMT CRC cells. Conclusions: We have identified JAK/STAT3 activation as an important escape mechanism for BRAFMT CRC following MEK1/2 inhibition. These data provide a strong rationale for further investigation of combination of MEK1/2 and JAK/STAT3 inhibition in BRAFMT in vivo models. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):B64. Citation Format: Robbie Carson, Basak Celtikci, Philip Dunne, Patrick Johnston, Sandra Van Schaeybroeck. The role of JAK1/2-STAT3 as acute resistance mechanism to MEK inhibition in BRAF mutant colorectal cancer. [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 B64.

Mutations in the Kras proto-oncogene are found in 40%-45% of colorectal cancer (CRC) patients and confer resistance to EGFR monoclonal antibody (mAb) therapies. The identification of druggable targets uniquely required by KrasMT CRC tumours has the potential to fill a gap in the therapeutic armamentarium of advanced CRC. We carried out microarray profiling of isogenic Kras wild type (WT) and mutant (MT) in vivo CRC models, KrasMT/WT primary colon tumours, pre-treatment metastatic CRC liver biopsies and drug resistant and sensitive CRC cell lines. We have used systems biology approach incorporating pathway analyses of the microarray data followed by siRNA screening to identify novel targets/pathways which are critical for the survival of KrasMT tumours, both basally and following chemotherapy treatment. We found that JAK1/2-STAT3 signaling was essential for the survival of KrasMT CRC cells. Moreover, suppression of JAK1/2-STAT3 activity using RNAi or small molecule inhibitors resulted in more potent increase in apoptosis in KrasMT CRC cells. In addition, treatment with chemotherapy and MEK1/2 inhibition resulted in significant increases in JAK2 and STAT3 activity and this was associated with strong increase in apoptosis when JAK1/2-STAT3 RNAi or small molecule inhibitors were combined with chemotherapy and MEK1/2 inhibition, especially in KrasMT cells. Moreover, we found that these effects were not drug- or cell line-specific. Collectively, using a systems biology approach, we have identified an essential role of JAK1/2-STAT3 signalling in survival of KrasMT CRC models. These findings support the further clinical investigation of JAK/STAT3 inhibitors in conjunction with chemotherapy or MEK inhibition in KrasMT CRC tumours. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 908. doi:1538-7445.AM2012-908

Background Colorectal cancer (CRC) is the third most common cancer in the UK with around 80% of patients undergoing surgery followed by adjuvant chemotherapy treatment. Among patients with clinicopathologically defined poor stage II and stage III CRC, there are subsets of patients who will not benefit from adjuvant 5-FU or 5-FU/oxaliplatin treatment. In fact, there is preclinical evidence to suggest that some of these patients may actually do worse when treated with adjuvant chemotherapy. The aim of this study was to develop in vitro adjuvant colon cancer models with the ultimate goal to identify novel treatment strategies for early stage CRC. Method Progressively invasive populations from parental HCT116 were generated using invasion chambers. Analysis of migration and invasion was carried out using the XCELLigence system, protein activity/expression using receptor tyrosine kinase array (RTK) and Western blotting, colony forming ability was assessed by survival assays and drug sensitivity using MTT assay and Flow cytometry. Results Six sublines of HCT116 cells were initially generated (I1-6) which displayed an increasing invasive/migratory phenotype compared to the parental cell line. At the molecular level, we found increases in basal activity of a number of RTK in the invasive sublines, such as Axl (a phenomenon which is characterized with a more aggressive nature in cancers) and also in other kinases such as ERK1/2, Akt and STAT3. Decreased activation of the EGFR and HER2 receptors was also noted in the invasive cell lines. In addition, exposure to sub-lethal 5-FU(IC20) doses resulted in significant increases in migration in these cell line models. Silencing of Axl resulted in significant decreases in migration of the invasive subpopulations even in the presence of 5-FU. Colony forming assays highlighted an increased ability to form colonies in the invasive sub-populations which also displayed drug resistance to both 5-FU and Oxaliplatin. The generation of invasive cell lines was also carried out in a number of other cell lines which confirmed that an increase in Axl expression could increase the migratory phenotype regardless of the genetic background of the cell and also that the results obtained are not an artefact of the cell line we have used. Conclusion Using our in-house developed in vitro preclinical cell line model we have begun to characterise the changes which tumour cells appear to go through during the transition to an invasive phenotype. We have highlighted Axl as a potential target for inhibition in early stage colorectal cancer as increases in total Axl protein levels correlate well with increases in invasive capacity in our models and silencing of the protein expression by siRNA results in ablation of the invasive potential in our model and also in a panel of CRC cell lines. Combination of an Axl small molecule inhibitor could potentially be a novel treatment strategy for early stage CRC. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 4324. doi:1538-7445.AM2012-4324

BACKGROUND: Methylating agents such as N-methyl-N-nitrosourea (MNU) can cause cell cycle arrest and death either via caspase-dependent apoptosis or via a poly(ADP-ribose) polymerase (PARP)-dependent form of apoptosis. We wished to investigate the possible role of MLH1 in signalling cell death through PARP. METHODS: Fibroblasts are particularly dependent on a PARP-mediated cell death response to methylating agents. We used hTERT-immortalised normal human fibroblasts (WT) to generate isogenic MLH1-depleted cells, confirmed by quantitative PCR and western blotting. Drug resistance was measured by clonogenic and cell viability assays and effects on the cell cycle by cell sorting. Damage signalling was additionally investigated using immunostaining. RESULTS: MLH1-depleted cells were more resistant to MNU, as expected. Despite having an intact G(2)/M checkpoint, the WT cells did not initially undergo cell cycle arrest but instead triggered cell death directly by PARP overactivation and nuclear translocation of apoptosis-inducing factor (AIF). The MLH1-depleted cells showed defects in this pathway, with decreased staining for phosphorylated H2AX, altered PARP activity and reduced AIF translocation. Inhibitors of PARP, but not of caspases, blocked AIF translocation and greatly decreased short-term cell death in both WT and MLH1-depleted cells. This MLH1-dependent response to MNU was not blocked by inhibitors of ATM/ATR or p53. CONCLUSION: These novel data indicate an important role for MLH1 in signalling PARP-dependent cell death in response to the methylating agent MNU. British Journal of Cancer (2009) 101, 441-451. doi:10.1038/sj.bjc.6605186 www.bjcancer.com Published online 28 July 2009 (C) 2009 Cancer Research UK

e13578 Background: Mutations in the Kras proto-oncogene are found in 40%-45% of colorectal cancer (CRC) patients and occur mainly in codon 12 and 13. Kras mutant (MT) CRC tumours are resistant to EGFR mAb therapies. Clear understanding of the biology of KrasMT CRC is important, and identification of druggable targets uniquely required by KrasMT CRC tumours has the potential to fill a gap in the therapeutic armamentarium of advanced CRC. The aim of this study was to identify novel targets whose knock-down is synthetically lethal with Kras mutation in CRC models. Methods: Transcriptional profiling (Almac Diagnostics CRC DSA) of primary KrasMT and WT CRC tissues and paired KrasMT and WT CRC xenografts models was performed and Metacore pathway analysis was used to identify individual genes from novel Kras-dependent pathways for incorporation into a primary RNAi screen. Results: Using clinical and in vivo KrasMT/WT CRC samples and public available Kras signatures, we identified 30 signalling pathways and 160 g...

BACKGROUND: While the discovery of new drugs is a complex, lengthy and costly process, identifying new uses for existing drugs is a cost-effective approach to therapeutic discovery. Connectivity mapping integrates gene expression profiling with advanced algorithms to connect genes, diseases and small molecule compounds and has been applied in a large number of studies to identify potential drugs, particularly to facilitate drug repurposing. Colorectal cancer (CRC) is a commonly diagnosed cancer with high mortality rates, presenting a worldwide health problem. With the advancement of high throughput omics technologies, a number of large scale gene expression profiling studies have been conducted on CRCs, providing multiple datasets in gene expression data repositories. In this work, we systematically apply gene expression connectivity mapping to multiple CRC datasets to identify candidate therapeutics to this disease.RESULTS: We developed a robust method to compile a combined gene signature for colorectal cancer across multiple datasets. Connectivity mapping analysis with this signature of 148 genes identified 10 candidate compounds, including irinotecan and etoposide, which are chemotherapy drugs currently used to treat CRCs. These results indicate that we have discovered high quality connections between the CRC disease state and the candidate compounds, and that the gene signature we created may be used as a potential therapeutic target in treating the disease. The method we proposed is highly effective in generating quality gene signature through multiple datasets; the publication of the combined CRC gene signature and the list of candidate compounds from this work will benefit both cancer and systems biology research communities for further development and investigations.