Knowledge on the cellular origin of HGSC may be of help in developing targeted therapies. These therapies interfere with signalling transduction pathways ...
Abstracts PO-134
RADIOSENSITIZING EFFECT OF GOLD-BASED NANOPARTICLES FOR BRAIN TUMOURTREATMENT
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P Héna*, 1A Chateau, 1P Rétif, 1J Daouk, 2S Roux, 1M Barberi-Heyob, 1S Pinel. 1CNRSUniversité de Lorraine, Centre de Recherche en Automatique de Nancy, Vandoeuvre-lèsNancy, France; 2CNRS- Université de Franche-Comté, Insitut UTINAM, Besançon, France
10.1136/esmoopen-2018-EACR25.658
Introduction Metal-based nanoparticles with radiosensitizing aim have promising prospects in the field of radiotherapy. Due to their high X-ray absorption capacity, nanomaterials with high atomic number may indeed improve radiation therapy efficacy in cancer treatment. Clinical trials are ongoing to evaluate the benefit of nanoparticle enhanced radiotherapy. The objective of the present study was to validate the potential of gold nanoparticle enhanced radiotherapy to treat glioblastoma using in silico, in vitro and in vivo approaches. Material and methods Among a panel of 5 gold nanoparticles (AuNPs), an innovative Monte Carlo simulation approach was used to rank the most promising nanoparticles according to their theoretical radiosensitizing effect. In U87-MG glioblastoma cells, the radiosensitizing effect of the selected nanoobjects was confirmed by clonogenic assays and cell death processes such as apoptosis, senescence, and mitotic catastrophes were investigated. A brain tumour window model, allowing fluorescence-based imaging was used to evaluate the tumour tissue selectivity of Cy5-labelled nanoparticles. Results and discussions A radiosensitizing effect was determined for 3 among 5 tested AuNPs with a dose modifying factor (DMF) from 0.4 to 0.5 (i.e. a DMF equal to 0.5 means the treatment is twice as efficient). Our results showed an inverse relationship between the radiosensitizing effects and the AuNPs sizes. Moreover, the nature of the coating influences the triggered cell death process. In case of PVP-coated AuNPs, the cell death was characterised by a radio-induced senescence in relation with a 1.5-fold increase of the reactive oxygen species production. In contrast, smallest PEG-coated AuNPs triggered post-RX mitotic catastrophes, leading to a delayed cell death. For in vivo experiments, a most promising AuNP (i.e. Au@DTDTPA:Gd) was selected, showing an interesting U87-tumour tissue selectivity. Conclusion After validating the in vitro radiosensitizing effect of small-sized AuNPs, an innovative design was selected for in vivo experiments. Tumour tissue accumulation and selectivity were evidenced for this innovative nanoparticle. We still have to validate the in vivo radiosensitizing effect using an orthotopic U87 model. We will suggest optimised treatment modalities.
targeting molecules in combination with adjuvant radiotherapy, or adjuvant chemotherapy following surgical resection is an important trend for GC treatment. Material and methods We compared isobaric tags for relative and absolute quantification (iTRAQ) proteomics data from 6 GC samples with those of 86 GC samples from the Chen dataset and consequently identified 122 intersecting/overlapping proteins that were highly expressed in gastric cancer tissue from both datasets followed by Kaplan-Meier survival analysis. To explore the downstream effectors of GEF-X, we analysed thousands of genes in relation to GEF-X expression from three GC datasets published in the literature. Genes displaying positive correlation with GEF-X were subsequently analysed using Metacore analysis. Results and discussions Clinical findings indicated that higher GEF-X expression is positively correlated with tumour size, depth of invasion, lymph node metastasis, vascular invasion and pathological stage. Elevated GEF-X expression was associated with significantly shorter cumulative survival of two independent cohorts of GC patients in both univariate and multivariate analyses. Depletion of GEF-X suppressed cell migration, proliferation, sphere formation, anchorage-independent growth, radioresistance and tumorigenicity as well as expression of gastric cancer stem cell (CSC) markers. GEF-X depletion was accompanied by a concomitant decrease in nuclear b-catenin and CD44 levels. Moreover, interactions between GEF-X and b-catenin were observed in the nucleus of GC cells. Conclusions Our results suggest for the first time a novel role of GEF-X in the self-renewal of CSCs, supporting its utility as an independent marker of GC progression.GEF-X depletion was accompanied by a concomitant decrease in nuclear b-catenin and CD44 levels. Moreover, interactions between GEF-X and b-catenin were observed in the nucleus of GC cells.
Poster Presentation: Signalling Pathways Computational Models of Biological Systems PO-136
STUDYING PATHWAY INTERACTIONS AND DYNAMICS TO PREDICT CELL RESPONSES TO CHEMOTHERAPEUTIC TREATMENT IN BREAST CANCER CELLS
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L Tuffery*, 2BN Kholodenko, 2W Kolch, 2M Halasz, 2D Fey. 1System Biology Irealnd, System Biology Ireland, Dublin, Ireland; 2System Biology Ireland, System Biology Ireland, Dublin, Ireland
10.1136/esmoopen-2018-EACR25.660
PO-135
GEF-X IS AN INDEPENDENT PROGNOSTIC FACTOR OF GASTRIC CANCER ASSOCIATED WITH CANCER STEM CELL DEVELOPMENT AND RADIORESISTANCE USING MULTI-OMICS DATA
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HC Chi, 2KH Lin. 1Radiological Research- Chang Gung University/Chang Gung Memorial Hospital, Radiation Biology Research Center, Taoyuan, Taiwan; 2College of MedicineChang-Gung University, Department of Biochemistry, Taoyuan, Taiwan
10.1136/esmoopen-2018-EACR25.659
Introduction Gastric cancer (GC) was recorded as the third leading cause of cancer-related deaths worldwide, and overall and recurrent survival after potentially curative gastrectomy for advanced gastric cancer remains poor. Thus, developing the GC ESMO Open 2018;3(Suppl 2):A1–A463
Introduction Breast cancer is the most common cancer among women affecting about 1 in 8 women during their lifetime. In most cases, the treatment is surgery combined with chemotherapy such as anthracyclines, including Doxorubicin. Unfortunately, the chemotherapy is only working for 25% to 50% of the patients showing a need to predict the patient’s response to the treatment. Chemotherapeutic drugs are known to activate apoptosis via the activation of JNK, p38 and p53 pathway. However, little is known about the interaction between these pathways and how the drugs activate them. My hypothesis is that dynamic behaviour and network interactions between JNK//p38 and p53 confer drug (in-)sensitivity and resistance. A279
Abstracts To address this problem, my project merges molecular and computational approaches to answer these two questions: . .
What are the activation dynamics and underlying network interactions? Can a mathematical model of this network predict drugresponses?
Material and methods To study the mechanism of action of Doxorubicin, I compared MCF10A cells, a non-cancerous cells used as a control, with five different breast cancer cell lines. The level of cell death was measured via flow cytometry after 1 mM of Doxorubicin treatment. In parallel, the cells’ molecular response to the treatment was assessed by monitoring phosphorylation of JNK and p38, and the total levels of p53 via Western blots after 1 mM of Doxorubicin treatment. Results and discussions Comparing the above pathways in MCF10A and T47D identified differences on two levels: network connectivity and activation dynamics. Currently I am constructing a mathematical model using ordinary differential equations (ODE) to test whether the identified network structures can explain network activation dynamics and drug responses. This predictive model will be validated using mammospheres and breast cancer tumour samples. Conclusion Modelling pathway interactions has already revealed correlation between the experimental data (Western blots) and the simulated outcome of Doxorubicin treatment in MCF10A cells. The next step is to explain the differential pathway connexions and dynamics in the various cell lines with different mutation pattern by using my mathematical model. By doing so, I hope to predict treatment response of other breast cancer cell lines, and ultimately patients, to develop a personalised treatment strategy.
PO-137
COMPUTATIONAL METABOLISM MODELLING PREDICTS RISK OF RELAPSE IN BREAST CANCER PATIENTS
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L Trilla-Fuertes*, 2A Gamez-Pozo, 1G Prado-Vazquez, 2A Zapater-Moros, 2M Ferrer-Gomez, M Diaz-Almiron, 2R Lopez-Vacas, 4P Zamora, 4E Espinosa, 2JA Fresno Vara. 1Biomedica Molecular Medicine SL, Research and Development, Madrid, Spain; 2Hospital Universitario La Paz, Molecular Oncology and Pathology Lab, Madrid, Spain; 3Hospital Universitario La Paz, Biostatistics Unit, Madrid, Spain; 4Hospital Universitario La Paz, Medical Oncology Service, Madrid, Spain
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10.1136/esmoopen-2018-EACR25.661
Introduction Breast cancer is one of the most prevalent cancers in the world. In previous works we observed differences in glucose metabolism between breast cancer subtypes, suggesting that metabolism plays an important role in this disease. Flux Balance Analysis (FBA) is widely used to study metabolic networks, allowing predicting growth rates or the rate of production of a given metabolite. Material and methods Proteomics data from 96 breast cancer tumours were obtained applying a high-throughput proteomics approach to routinely archive formalin-fixed, paraffinembedded tumour tissue. Proteomics tumour data were analysed using the human metabolic reconstruction Recon2 and FBA. The tumour growth rate for each tumour was calculated. In order to analyse fluxes from the different metabolic pathways, flux activities were calculated as the sum of the fluxes of each reaction in each pathway defined in the Recon2. Then, flux activities were used to build prognostic models.
A280
Results and discussions Using the results obtained from FBA in the proteomics dataset, flux activities were calculated for each pathway. Employing these flux activities, a prognostic signature was built. Flux activities of vitamin A, tetrahydrobiopterin metabolism, and beta-alanine metabolism pathways split our population into a low and a high-risk group (p=0.044). Conclusion Vitamine A, beta-alanine and tetrahydrobiopterin metabolism flux activities could be used to predict relapse risk. Flux activities is a method proposed in a previous work to study response against drugs that now also demonstrated its utility in summarising FBA data and is associated with prognosis.
PO-138
HEDGEHOG SIGNALLING PATHWAY ACTIVITY IN HIGH-GRADE SEROUS OVARIAN CARCINOMA
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P Van der Ploeg*, 2W Verhaegh, 3J De Hullu, 2A Van der Stolpe, 1J Piek. 1Catharina Hospital, Gynaecology and Obstetrics, Eindhoven, The Netherlands; 2Philips Research, Molecular Diagnostics, Eindhoven, The Netherlands; 3Radboud University Medical Center Nijmegen, Gynaecology and Obstetrics, Nijmegen, The Netherlands
10.1136/esmoopen-2018-EACR25.662
Introduction High-grade serous (ovarian) carcinoma (HGSC) is the most lethal gynaecological malignancy with a 5 year survival rate of approximately 30%. This is caused by the fact that most tumours are detected at late stage of disease and due to limited therapeutic options. Knowledge on the cellular origin of HGSC may be of help in developing targeted therapies. These therapies interfere with signalling transduction pathways (STP), which are chains of biochemical events controlling gene expression. One such STP is the hedgehog (HH) pathway. Previous research yielded contradictory results on HH activity in HGSC, possibly due to the erroneous interpretation of separate pathway components as a marker for functional pathway activity. As most HGSC are thought to arise from Fallopian tube epithelium, the aim of our study was to determine the functional HH activity in normal oviduct epithelium, HGSC and Fallopian tube stem cells (FTSC), in order to provide new insights in the HGSC cell type of origin and the potential use of HH targeted therapies. Additionally, we studied the activity of other STP. Material and methods This study used a novel computational diagnostic approach; signal transduction pathway activation analysis (STA-analysis), enabling quantitative measurements of the functional pathway activity based on inferring mRNA levels of specific target genes. STA-analysis was based on publicly available Affymetrix data (GSE69428 and GSE69453) containing microdissected HGSC (n=10), paired normal oviduct epithelium (n=10) and cultured FTSC (n=2). Results and discussions Despite the fact that samples showed some RNA degradation we demonstrated an up-regulation of HH pathway activity in HGSC (p=0.001) and FTSC (p
