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Purpose:Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers.Experimental Design:Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment.Results:Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal EPHA2 expression is associated with REG resistance.Conclusions:Subtype classification systems represent canonical “termini a quo” (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors.

Supplementary Figures S1 - S8 and Table S1. Fig S1: Analysis of copy number burden in a PDX population trial of REG treated mCRC PDXs. Fig S2: Effect of REG on microvessel density and proliferation according to CNA cluster. Fig S3 - S6: BCL-2 family profiling of mCRC PDX models via quantitative Western blotting. Fig S7: RPPA protein scores indicating proteins' association with the PDX models' response to REG. Fig S8: Western blot validation of differential EPHA2 protein expression between REG post- and pre-treatment progressor and non-progressor PDX models. Table S1: List of antibodies and dilution factors used against desired targets in RPPA analysis.

Glioblastoma represents the most common primary malignancy of the central nervous system in adults and remains a largely incurable disease. The elucidation of disease subtypes based on mutational profiling, gene expression and DNA methylation has so far failed to translate into improved clinical outcomes. However, new knowledge emerging from the subtyping effort in the IDH-wild-type setting may provide directions for future precision therapies. Here, we review recent learnings in the field, and further consider how tumour microenvironment differences across subtypes may reveal novel contexts of vulnerability. We discuss recent treatment approaches and ongoing trials in the IDH-wild-type glioblastoma setting, and propose an integrated discovery stratagem incorporating multi-omics, single-cell technologies and computational approaches.

Purpose: Regorafenib (REG) is approved for the treatment of metastatic colorectal cancer, but has modest survival benefit and associated toxicities. Robust predictive/early response biomarkers to aid patient stratification are outstanding. We have exploited biological pathway analyses in a patient-derived xenograft (PDX) trial to study REG response mechanisms and elucidate putative biomarkers. Experimental Design: Molecularly subtyped PDXs were annotated for REG response. Subtyping was based on gene expression (CMS, consensus molecular subtype) and copy-number alteration (CNA). Baseline tumor vascularization, apoptosis, and proliferation signatures were studied to identify predictive biomarkers within subtypes. Phospho-proteomic analysis was used to identify novel classifiers. Supervised RNA sequencing analysis was performed on PDXs that progressed, or did not progress, following REG treatment. Results: Improved REG response was observed in CMS4, although intra-subtype response was variable. Tumor vascularity did not correlate with outcome. In CMS4 tumors, reduced proliferation and higher sensitivity to apoptosis at baseline correlated with response. Reverse phase protein array (RPPA) analysis revealed 4 phospho-proteomic clusters, one of which was enriched with non-progressor models. A classification decision tree trained on RPPA- and CMS-based assignments discriminated non-progressors from progressors with 92% overall accuracy (97% sensitivity, 67% specificity). Supervised RNA sequencing revealed that higher basal EPHA2 expression is associated with REG resistance. Conclusions: Subtype classification systems represent canonical “termini a quo” (starting points) to support REG biomarker identification, and provide a platform to identify resistance mechanisms and novel contexts of vulnerability. Incorporating functional characterization of biological systems may optimize the biomarker identification process for multitargeted kinase inhibitors.

Resistance to chemotherapy often results from dysfunctional apoptosis, however multiple proteins with overlapping functions regulate this pathway. We sought to determine whether an extensively validated, deterministic apoptosis systems model, &lsquo, DR_MOMP&rsquo, could be used as a stratification tool for the apoptosis sensitiser and BCL-2 antagonist, ABT-199 in patient-derived xenograft (PDX) models of colorectal cancer (CRC). Through quantitative profiling of BCL-2 family proteins, we identified two PDX models which were predicted by DR_MOMP to be sufficiently sensitive to 5-fluorouracil (5-FU)-based chemotherapy (CRC0344), or less responsive to chemotherapy but sensitised by ABT-199 (CRC0076). Treatment with ABT-199 significantly improved responses of CRC0076 PDXs to 5-FU-based chemotherapy, but showed no sensitisation in CRC0344 PDXs, as predicted from systems modelling. 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) scans were performed to investigate possible early biomarkers of response. In CRC0076, a significant post-treatment decrease in mean standard uptake value was indeed evident only in the combination treatment group. Radiomic CT feature analysis of pre-treatment images in CRC0076 and CRC0344 PDXs identified features which could phenotypically discriminate between models, but were not predictive of treatment responses. Collectively our data indicate that systems modelling may identify metastatic (m)CRC patients benefitting from ABT-199, and that 18F-FDG-PET could independently support such predictions.

Background: Combining bevacizumab and chemotherapy produced superior response rates compared with chemotherapy alone in metastatic breast cancer. As bevacizumab may cause hypertension (HTN) and increase the risk of cardiac failure, we performed a pilot study to evaluate the feasibility and toxicity of a non-anthracycline-containing combination of docetaxel with cyclophosphamide and bevacizumab in early stage breast cancer patients. Methods: Treatment consisted of four 3-weekly cycles of docetaxel and cyclophosphamide (75/600 mg/m2). Bevacizumab was administered 15 mg/kg intravenously on day 1, and then every 3 weeks to a total of 18 cycles of treatment. Serum biomarker concentrations of vascular endothelial growth factor (VEGF), cardiac troponin-I (cTnI), myeloperoxidase (MPO), and placental growth factor (PlGF) were quantified using enzyme-linked immunosorbent assay (ELISA) in 62 patients at baseline and whilst on treatment to determine their utility as biomarkers of cardiotoxicity, indicated by left ventricular ejection fraction (LVEF). Results: A total of 106 patients were accrued in nine sites. Median follow up was 65 months (1–72 months). Seventeen protocol-defined relapse events were observed, accounting for an overall disease-free survival (DFS) rate of 84%. The DFS rates for hormone receptor positive (HR+) and triple-negative (TN) patients were 95% versus 43%, respectively. The median time to relapse was 25 (12–54) months in TN patients versus 38 (22–71) months in HR+ patients. There have been 13 deaths related to breast cancer . The overall survival (OS) rate was 88%. The 5-year OS rate in HR+ versus TN was 95% versus 57%. None of the measured biomarkers predicted the development of cardiotoxicity. Conclusions: We observed a low relapse rate in node-positive, HR+ patients; however, results in TN breast cancer were less encouraging. Given the negative results of three large phase III trials, it is unlikely that this approach will be investigated further. Trial Registration ClinicalTrials.gov Identifier: NCT00911716.

Item does not contain fulltext PURPOSE: The tyrosine kinase inhibitor (TKI) sunitinib is a multi-targeted agent approved across multiple cancer indications. Nevertheless, since approval, data has emerged to describe a worrisome side effect profile including hypertension, hand-foot syndrome, fatigue, diarrhea, mucositis, proteinuria, and (rarely) congestive heart failure. It has been hypothesized that the observed multi-parameter toxicity profile is related to "on-target" kinase inhibition in "off-target" tissues. EXPERIMENTAL DESIGN: To interrogate off-target effects in pre-clinical studies, a reverse phase protein array (RPPA) approach is employed. Mice are treated with sunitinib (40 mg kg(-1) ) for 4 weeks, following which critical organs are removed. The Zeptosens RPPA platform is employed for protein expression analysis. RESULTS: Differentially expressed proteins associated with damage and/or stress are found in the majority of organs from treated animals. Proteins differentially expressed in the heart are associated with myocardial hypertrophy, ischaemia/reperfusion, and hypoxia. However, hypertrophy is not evidenced on histology. Mild proteinuria is observed; however, no changes in renal glomerular structure are visible via electron microscopy. In skin, proteins associated with cutaneous inflammation, keratinocyte hyper-proliferation, and increased inflammatory response are differentially expressed. CONCLUSIONS AND CLINICAL RELEVANCE: It is posited that pre-clinical implementation of a combined histopathological/RPPA approach provides a sensitive method to mechanistically elucidate the early manifestation of TKI on-target/organ off-target toxicities.

Patient-derived xenografts (PDXs) are resected human tumors engrafted into mice for preclinical studies and therapeutic testing. It has been proposed that the mouse host affects tumor evolution during PDX engraftment and propagation, affecting the accuracy of PDX modeling of human cancer. Here, we exhaustively analyze copy number alterations (CNAs) in 1,451 PDX and matched patient tumor (PT) samples from 509 PDX models. CNA inferences based on DNA sequencing and microarray data displayed substantially higher resolution and dynamic range than gene expression-based inferences, and they also showed strong CNA conservation from PTs through late-passage PDXs. CNA recurrence analysis of 130 colorectal and breast PT/PDX-early/PDX-late trios confirmed high-resolution CNA retention. We observed no significant enrichment of cancer-related genes in PDX-specific CNAs across models. Moreover, CNA differences between patient and PDX tumors were comparable to variations in multiregion samples within patients. Our study demonstrates the lack of systematic copy number evolution driven by the PDX mouse host.

Patient-Derived Xenografts (PDXs) are preclinical models largely used to study tumor biology and drug response. Recent literature highlighted the possibility that growth of human tumors in a mouse microenvironment imposes a selection driving mouse-specific genetic evolution of PDXs, which may compromise their reliability as human cancer models. Conversely, independent studies observed a conservation of the genomic landscape during PDX engraftment and passaging. We noticed that PDX genetic evolution was particularly evident in studies based on copy number aberration (CNA) inferred from gene expression data, while it was negligible when DNA-based CNA profiles were employed. Therefore, in a joint international effort of the EurOPDX and PDXNet consortia, we assembled a dataset of 37 hepatocellular and 54 gastric carcinoma tumor or PDX samples with matched RNA-based and DNA-based CNA profiles. We found that DNA-based CNA profiles invariably yield higher concordance between patient's tumor and derived PDXs than those inferred from RNA. RNA-based profiles displayed poor concordance with matched DNA-based profiles, and much lower resolution, so that they missed many focal copy number events detected by DNA-based methods. These results revealed that CNA measurements cannot be accurately estimated by expression data and that a systematic reassessment of CNA dynamics in PDXs based on DNA data is required. To this aim, we generated CNA profiles by low-pass whole genome sequencing (WGS) of 87 colorectal and 43 breast cancer triplets, each composed of matched patient's tumor (PT) and PDX at early (PDX-early) and later (PDX-late) passage. In this way, for each tumor type, we generated three perfectly matched PT, PDX-early and PDX-late cohorts and performed CNA recurrence analysis by GISTIC in each cohort. The hypothesis was that if the mouse host induces a selective pressure capable of shaping the CNA landscape during PDX engraftment and propagation, GISTIC analysis would highlight systematic and progressive changes, from the PT to the PDX-early cohort, and then to the PDX-late cohort. Notably instead, the CNA profiles of the PT and PDX-early/late cohorts were virtually indistinguishable, with no progressive accumulation or loss of CNA during PDX passage and only minor changes not functionally related or associated to cancer-driver or actionable genes. These results were not consequence of insufficient capture of the CNA repertoire, since the GISTIC profiles recapitulated those generated by TCGA for colorectal and breast cancer. In summary, our analyses highlighted that while RNA-based CNA inferences have inadequate resolution and accuracy to study genomic evolution in PDXs, DNA-based CNA profiles confirm retention of CNAs in PTs and PDXs, excluding a systematic mouse driven selection via copy number changes. Ultimately, these results support the robustness of PDXs as preclinical models for predicting drug response. Citation Format: Jessica Giordano, Xing Yi Woo, Anuj Srivastava, Zi-Ming Zhao, Michael W. Lloyd, Roebi de Bruijn, Yun-Suhk Suh, Francesco Galimi, Andrea Bertotti, Adam Lafferty, Alice C. O'Farrell, Elodie Modave, Diether Lambrechts, Petra ter Brugge, Violeta Serra, Elisabetta Marangoni, Rania El Botty, Jong-Il Kim, Han-Kwang Yang, Charles Lee, Dennis A. Dean, Brandi Davis-Dusenbery, Yvonne A. Evrard, James H. Doroshow, Alana L. Welm, Bryan E. Welm, Michael T. Lewis, Bingliang Fang, Jack Roth, Funda Meric-Bernstam, Meenhard Herlyn, Michael Davies, Li Ding, Shunqiang Li, Ramaswamy Govindan, Jeffrey A. Moscow, Carol J. Bult, Claudio Isella, Livio Trusolino, Annette T. Byrne, Jos Jonkers, Jeffrey H. Chuang, Enzo Medico, EurOPDX consortium & PDXNET consortium. Absence of mouse-specific tumor evolution in patient-derived cancer xenografts [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1118.

Glioblastoma (GBM), a highly invasive brain malignancy, remains an incurable disease. Angiogenesis, the formation of new vasculature, is a defining feature of this disease. Targeting GBM angiogenesis with Bevacizumab (Bev) is associated with improved progression free survival, but may also enhance tumour invasion into the surrounding parenchyma (Norden et al., 2008) and is not curative. Rho GTPases and their activators, guanine nucleotide exchange factors (GEFs), play central roles in the invasive process (4). Herein, we sought to identify and target GEFs of importance in mediating GBM invasion with a view to improving Bev response. We report a novel mechanism by which GBM tumours invade and proliferate via overexpression of the GEF beta-PIX gene which was shown to be increased at the invasive edge in 74% of GBM tumours assessed (n=19), compared with tumour core (Hoelzinger et al., 2005). We have further demonstrated that siRNA-mediated knockdown of beta-PIX in GBM patient-derived xenograft cell cultures and cell lines resulted in decreased cell invasion in 3D, cell proliferation and survival assays in vitro. An in vivo pilot study whereby beta-Pix knockdown was achieved using commercially available alphaV-beta3 integrin targeting nanoparticles (InVivoPlex Aparna Bio Corp), suggested that treatment with beta-PIX siRNA nanoparticles in combination with Bev could improve survival compared with Bev- alone in tumour-bearing animals. To further develop this strategy, we have recently designed and characterized a proprietary novel biodegradable, RGD-targeting and cholesterol-stabilized polyplex system for siRNA delivery in GBM. This novel nanoparticle system supports efficient gene silencing, and demonstrates a low toxicity profile in vitro and in vivo. We are currently performing advanced pre-clinical efficacy studies employing a clinically relevant GBM rodent resection model (Sweeney et al., 2014), to determine if nanoparticle mediated beta-PIX gene silencing will improve survival outcomes when combined with Bevacizumb and delivered in the adjuvant setting.

BACKGROUND: Glioblastoma (GBM) is the most frequent, aggressive and lethal of all brain tumours. 85% of patients die within two years. Thus, new treatment options are urgently required. To address this deficit, the Royal College of Surgeons in Ireland (RCSI) is leading a major new programme “GLIOTRAIN” (www.gliotrain.eu) that aims to identify new therapeutic strategies, while implementing state of the art genomics and systems medicine approaches to unravel resistance mechanisms. Here, we introduce the GLIOTRAIN initiative which received €3.8 million in September 2017 from the European Commission’s Horizon 2020 Marie Skłodowska-Curie Actions programme. MATERIAL AND METHODS: The GLIOTRAIN consortium comprises 22 organisations (RCSI, University of Stuttgart, VIB, Luxemburg Institute of Health, Erasmus Medical Centre, The ICM Institute for Brain and Spinal Cord, GeneXplain GmbH, Agilent Technologies, ITTM Solutions, The International Brain Tumour Alliance, Cancer Trials Ireland, Champions Oncology Ltd., In silico Biotechnology, YUMAB GmbH, Mimetas B.V, Pepscope B.V, Teva Nederland B.V, CarThera, Oncurious N.V, University of Luxembourg, KU Leuven, University Medical Center Göttingen) across 8 countries and includes leading academics, clinicians, private sector and not-for-profit partners across the fields of brain tumour biology, multi-omics, drug development, clinical research, bioinformatics, computational modelling and systems biology. Fifteen GLIOTRAIN sub-projects will employ systems medicine, integrative multi-’omics and translational cancer biology platforms accessing clinically relevant models and patient data-sets. RESULTS: GLIOTRAIN will identify and interrogate novel therapeutic strategies for application in GBM, while simultaneously implementing state of the art next generation sequencing to unravel disease resistance mechanisms. The programme will implement systems-based analysis of known contributors of disease progression, and will further perform unbiased molecular profiling and computational modelling. CONCLUSION: GLIOTRAIN will address currently unmet translational research and clinical needs in the neuro-oncology field by interrogating innovative therapeutic strategies and improving the mechanistic understanding of disease resistance. Funding: GLIOTRAIN (www.gliotrain.eu) has received funding from the European Commission’s Horizon 2020 Marie Skłodowska-Curie Actions programme (Grant Agreement No. 766069).

Bevacizumab (bvz) is a first choice anti-angiogenic drug in oncology and is primarily administered in combination with chemotherapy. It has been hypothesized that anti-angiogenic drugs enhance efficacy of cytotoxic drugs by “normalizing” abnormal tumor vessels and improving drug penetration. Nevertheless, the clinical relevance of this phenomenon is still unclear with several studies over recent years suggesting an opposing relationship. Herein, we sought to develop a new computational tool to interrogate anti-angiogenic drug scheduling with particular application in the setting of colorectal cancer (CRC). Specifically, we have employed a mathematical model of vascular tumour growth which interrogates the impact of anti-angiogenic treatment and chemotherapeutic treatment on tumour volume. Model predictions were validated using CRC xenografts which underwent treatment with a clinically relevant combinatorial anti-angiogenic regimen. Bayesian model selection revealed the most appropriate term for capturing the effect of treatments on the tumour size, and provided insights into a switch-like dependence of FOLFOX delivery on the tumour vasculature. Our experimental data and mathematical model suggest that delivering chemotherapy prior to bvz may be optimal in the colorectal cancer setting.

Sunitinib is a tyrosine kinase inhibitor approved for the treatment of multiple solid tumors. However, cardiotoxicity is of increasing concern, with a need to develop rational mechanism driven approaches for the early detection of cardiac dysfunction. We sought to interrogate changes in cardiac energy substrate usage during sunitinib treatment, hypothesising that these changes could represent a strategy for the early detection of cardiotoxicity. Balb/CJ mice or Sprague-Dawley rats were treated orally for 4 weeks with 40 or 20 mg/kg/day sunitinib. Cardiac positron emission tomography (PET) was implemented to investigate alterations in myocardial glucose and oxidative metabolism. Following treatment, blood pressure increased, and left ventricular ejection fraction decreased. Cardiac [18F]-fluorodeoxyglucose (FDG)-PET revealed increased glucose uptake after 48 hours. [11C]Acetate-PET showed decreased myocardial perfusion following treatment. Electron microscopy revealed significant lipid accumulation in the myocardium. Proteomic analyses indicated that oxidative metabolism, fatty acid β-oxidation and mitochondrial dysfunction were among the top myocardial signalling pathways perturbed. Sunitinib treatment results in an increased reliance on glycolysis, increased myocardial lipid deposition and perturbed mitochondrial function, indicative of a fundamental energy crisis resulting in compromised myocardial energy metabolism and function. Our findings suggest that a cardiac PET strategy may represent a rational approach to non-invasively monitor metabolic pathway remodeling following sunitinib treatment.

Molecular and non-invasive imaging are rapidly emerging fields in preclinical cancer drug discovery. This is driven by the need to develop more efficacious and safer treatments, the advent of molecular-targeted therapeutics, and the requirements to reduce and refine current preclinical in vivo models. Such bioimaging strategies include MRI, PET, single positron emission computed tomography, ultrasound, and optical approaches such as bioluminescence and fluorescence imaging. These molecular imaging modalities have several advantages over traditional screening methods, not least the ability to quantitatively monitor pharmacodynamic changes at the cellular and molecular level in living animals non-invasively in real time. This review aims to provide an overview of non-invasive molecular imaging techniques, highlighting the strengths, limitations and versatility of these approaches in preclinical cancer drug discovery and development.

Computer models allow the mechanistically detailed study of tumour proliferation and its dependency on nutrients. However, the computational study of large vascular tumours requires detailed information on the 3-dimensional vessel network and rather high computation times due to complex geometries. This study puts forward the idea of partitioning vascularised tissue into connected avascular elements that can exchange cells and nutrients between each other. Our method is able to rapidly calculate the evolution of proliferating as well as dead and quiescent cells, and hence a proliferative index, from a given amount and distribution of vascularisation of arbitrary complexity. Applying our model, we found that a heterogeneous vessel distribution provoked a higher proliferative index, suggesting increased malignancy, and increased the amount of dead cells compared to a more static tumour environment when a homogenous vessel distribution was assumed. We subsequently demonstrated that under certain amounts of vascularisation, cell proliferation may even increase when vessel density decreases, followed by a subsequent decrease of proliferation. This effect was due to a trade-off between an increase in compensatory proliferation for replacing dead cells and a decrease of cell population due to lack of oxygen supply in lowly vascularised tumours. Findings were illustrated by an ectopic colorectal cancer mouse xenograft model. Our presented approach can be in the future applied to study the effect of cytostatic, cytotoxic and anti-angiogenic chemotherapy and is ideally suited for translational systems biology, where rapid interaction between theory and experiment is essential. ispartof: Journal of Theoretical Biology vol:402 pages:129-143 ispartof: location:England status: published

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Background: Breast cancer is the leading cause of cancer in women, with 1.8 million patients diagnosed globally each year. In early stage disease, anthracycline regimens are commonly employed, but the risk of cardiotoxicity is high. Replacing anthracyclines with taxanes in combination with cyclophosphamide may improve response [1] and Bevacizumab (BVZ) may provide addtional benefit. However, as BVZ can cause hypertension and increased risk of cardiac failure, a rationale exists for studying biomarkers of cardiotoxicity in this setting. Methods: We assessed a panel of biomarkers in n = 57 early stage breast cancer patients whom underwent docetaxel/cyclophosphamide/BVZ therapy on the TC-Avastin Trial (NCT00911716). Serum was collected prior to treatment and at 3 months. Cardiotoxicity was defined as decline in left ventricular ejection fraction ≥ 10% to Results: Changes in serum MPO or cTnI were not related to cardiotoxicity when analysed in the larger cohort. However, a “cut-off” PlGF fold change of 0.99 could differentiate patients who developed cardiotoxicity from those that did not. 74% of cardiotoxicity patients, compared to only 35% of non-cardiotoxicity fell below the 0.99 cut-off. Conversely, 65% of non-cardiotoxicity patients, compared to 25% of cardiotoxicity patients fell above the cut-off (p = 0.0042). Conclusions: Our data suggest that decreased PlGF at 3 months may predict cardiotoxicity. These observations require further validation. This work was funded by AngioTox, an EC FP7 IAPP Marie Curie Award (Grant Agreement 251528). [1]Jones et al., J. Clin. Oncol.27, 1177-1183 (2009); [2] Putt et al., Clin. Chem 61, 1164-1172 (2015). Citation Format: David W. Murray, Alice C. O’Farrell, Giuseppe Gullo, Ashwini Maratha, Patrick Dicker, Mairin Rafferty, Verena Murphy, Bonnie Ky, William M. Gallagher, Norma O’Donovan, John Crown, Annette T. Byrne. Analysis of putative serum biomarker candidates for cardiotoxicity prediction in a cohort of early stage breast cancer patients treated with docetaxel, cyclophosphamide, and bevacizumab. [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 1828.

Background: Sunitinib is a multi-targeted agent approved for treatment of a number of cancers. However, since approval, data has continually emerged relating to toxicity profiles including hypertension, hand-foot syndrome and fatigue. Underlying mechanisms are unresolved. It has been hypothesised that the multi-parameter toxicity profile is related to ‘on-target’ kinase inhibition in ‘off-target’ tissues. Methods: To interrogate off-target effects, the Zeptosens Reverse Phase protein Array (RPA) platform was used to assess tissues obtained from mice treated with sunitinib (40 mg/kg) for 4 weeks. Additional tissue was collected for histological analyses and pathophysiologic changes assessed. Results: RPA data analyses on all organs collected (heart, kidney, liver, brain, intestine and skin) revealed the presence of differentially expressed proteins associated with damage and/or stress. Of note, Cyclin D1, MEK and phosphorylated-p21(CIP/WAF1) expression increased by 1.8-fold (p < 0.05), 2.2-fold (p < 0.1) and 1.7-fold (p < 0.1) respectively in the kidneys of sunitinib treated mice. These proteins are associated with kidney damage after chemotherapy, and induction of genes associated with renal immune response, inflammation and apoptosis. Mild proteinuria was observed in sunitinib treated animals, however no gross change in renal glomerular ultrastructure was visible via electron microscopy. Phosphorylated-FGFR1, cleaved Caspase-7, and phosphorylated-cMYC expression decreased by 0.45-fold (p < 0.05), 0.4-fold (p < 0.1) and 0.8-fold (p < 0.1) respectively in the skin of sunitinib treated mice. Down-regulation of these proteins has been associated with a perturbation of cutaneous wound healing (p-FGFR1/cleaved Caspase-7). Mice treated with high dose sunitinib (80 mg/kg) showed overt signs of skin toxicity. Histopathologic studies of the thyroid gland revealed decreased thyroid epithelial cell height (p < 0.05). Nevertheless, serum levels of triiodothyronine and thyroxine remained unchanged. An orthogonal validation study (Western blotting) is ongoing based on gene ontology, pathway analysis and observed fold changes in critical signalling pathway proteins involved in cellular stress. Conclusions: Implementation of a combined histopathologic/ RPA approach may provide a sensitive method to mechanistically elucidate the off-target toxicity sequelae associated with TKIs approved in the oncology setting. Work was supported by an EU funded Industry Academia Pathways and Partnerships Marie Curie Award (AngioTox) Grant Number 251528. RPAs were performed at Bayer Technology Services, Leverkusen, Germany. Citation Format: Alice C. O’Farrell, Adam Lafferty, Ian Miller, Rhys Evans, Maurice Cary, David Murray, Marina Alamanou, Girish Mallya Udupi, Liam Shiels, William M. Gallagher, Annette T. Byrne. Proteomic analysis of off-target toxicities following treatment with the tyrosine kinase inhibitor sunitinib. [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 3010.