- Email: [email protected]
Validation of a model of drug-induced aggressive liver cancer: gene expression and tumor recurrence
EACR24 Poster Sessions / European Journal of Cancer 61, Suppl. 1 (2016) S9–S218 the endoglycosidase, PNGase F followed by glycan derivatization with the 2-aminobenzamide (2-AB) fluorophore. Glycans were analysed using hydrophilic interaction liquid chromatography (HILIC) coupled with Ultra low Performance Chromatography (UPLC). Exoglycosidase enzymatic digestions and comparison of pre and post enzymatic digestion chromatographic profiles were used to identify peak shifts in order to determine the presence of a specific residue(s). Weak anion exchange (WAX) Chromatography and Mass Spectrometry (MS) were used to assist in the identification of glycan structures. Results: Oral biofluids were found to contain a heavily glycosylated protein composition. All types of glycans complex, hybrid and high mannonse structures were present. The main glycans were neutral glycans with smaller levels of mono, di- and tri-sialylated glycans. Furthermore glycans were heavily fucosylated. Conclusion: Late diagnosis remains one of the major drawbacks in the treatment of oral cancer followed by chemo-resistance and recurrence. Glycosylation changes are the most frequent biochemical alterations associated with cancer, both in terms of specific hypo- and hyper-glycosylation events. Among the most frequently seen alterations in cancer cells and secreted glycoproteins is an aberrant pattern of N-linked oligosaccharide modifications. Sensitive and reliable diagnostic markers for oral cancers and recurrence of oral cancers remain unavailable. This study demonstrates the applicability of the developed methodology and its potential identification of alterations in the glycoproteome to facilitate the detection of cancers within the oral cavity. No conflict of interest. 847 Validation of a model of drug-induced aggressive liver cancer: gene expression and tumor recurrence J. Van Pelt1 , J. Dekervel2 , A. Bulle2 , H. Van Malenstein2 , P. Windmolders2 , E. Van Cutsem1 , C. Verslype1 . 1 KU Leuven, Hepatology and Digestive Oncology, Leuven, Belgium, 2 KU Leuven, Hepatology, Leuven, Belgium Background: For a long time, Epithelial-to-Mesenchymal Transition (EMT) was considered the driving mechanism of the epithelial cancer cell to metastasize to distant organs, this paradigm was very recently challenged by the finding that cells can spread without undergoing EMT. EMT has been shown to be important for drug-resistance that almost always develops during systemic cancer therapy. There has been extensive research on gene expression signatures in HCC, classifying cancer patients with the aim to predict patient survival or disease recurrence in view of treatment options. Aim: We wanted to explore the clinical importance of an EMT phenotype in liver cancer for recurrence of a tumor after resection. Methods: We present a novel translational approach using human sorafenib resistant hepatoma cell line in which we studied morphology, gene expression by microarray and invasive potential. We used gene set enrichment analysis (GSEA) and pathway analysis for the evaluation of the signature. Clinical validation was done using 5 large patient data sets submitted to Gene Expression Omnibus (GEO) against clinical outcome. Results: The resistant cells changed their appearance, lost E-cadherin and KRT19 and showed high expression of vimentin, indicating epithelial-tomesenchymal transition. Resistant cells showed reduced adherent growth, became more invasive and lost liver-specific gene expression. We determined differentially expressed genes in the drug-resistant cells. Using GSEA, resistant cells showed loss of expression of genes included in the good survival signature proposed by Lee et al. [1] and changes concordant with poor prognostic HCC such as the proliferation subclass of Chiang et al. [2] or the G3 subtype described by Boyault et al. [3]. We validated these genes in 3 large published data sets of hepatocellular carcinoma and developed a gene score. This score was applied on 2 independent patient cohorts were it could predict the recurrence risk at 3 years after resection and when applied on the surrounding liver tissue the same genes also correlated with late recurrence. Four patient classes with each different time patterns and rates of recurrence could be identified based on combining tumor and liver scores. In a multivariate Cox regression analysis our gene score was an independent risk factor for recurrence (P = 0.007). Conclusions: The in vitro sorafenib drug resistance model in HCC shows strong similarities with the more aggressive molecular subclasses identified by several groups. Using this gene expression we developed a small 7 gene risk score that is able to simultaneously predict the risk of early and late tumor recurrence demonstrating the clinical relevance of this EMT model. Reference(s) [1] Lee JS et al. Hepatology (2004) 40: 667. [2] Chiang DY et al. Cancer Res (2008) 68, 6779. [3] Boyault S et al. Hepatology (2007) 45: 42. No conflict of interest.
S195
848 A computational approach to discriminate between human and mouse reads in sequencing data from Patient Derived Tumour Xenografts M. Callari1 , A. Sati Batra1 , R.N. Batra1 , H. Clifford1 , W. Greenwood1 , S.J. Sammut1 , S.F. Chin1 , A. Bruna1 , O.M. Rueda1 , C. Caldas1 . 1 University of Cambridge, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom Background: Patient Derived Tumour Xenografts (PDTXs) are emerging pre-clinical models that better represent clinical tumours and intra-tumour heterogeneity compared with cell lines. In most of the studies involving PDTXs, their molecular characterization is central; however, the analysis of sequencing data from PDTXs is hampered by the presence of mouse stroma contamination. Due to the high homology between the two organisms, a proportion of mouse reads can still map to homologous regions of the human genome, likely with some mismatch, heavily affecting downstream analysis. Material and Methods: We carried out controlled experiments where fixed amounts of human and mouse DNA (or RNA) were mixed, ranging from a pure human sample to a pure mouse sample. Whole Exome Sequencing (WES), RNA-seq and Reduced Representation Bisulfite Sequencing (RRBS) were performed. A bioinformatic pipeline was developed to distinguish human from mouse reads by aligning raw data against both human and mouse genomes. The validity of the approach was confirmed in sequencing data from PDTXs and matched primary tumours. Results: The developed method was able to correctly classify human and mouse reads with an accuracy >99.9%. Using the controlled experiment, we also derived a calibration curve linking the percentage of human DNA in the sample and the percentage of reads classified as human. This calibration curve can then be used to estimate the percentage of mouse contamination in the sample. We verified that the alignment of PDTX WES data using the human reference genome only can generate up to thousands of false positive calls in samples with a mouse contamination as low as 10%. By applying our approach, we were able to prevent the calling of these artefacts increasing the correlation between each PDTX and the matched primary tumour. Also in RNA-seq and RRBS data, distinguishing between human and mouse reads gave more accurate estimates of the tumour transcriptome and methylome. Importantly, it also allowed analysing separately the microenvironment contribution. Conclusions: An ad-hoc bioinformatic pipeline is needed for the analysis of PDTX sequencing data. Here we present a simple and fast solution to accurately discriminate reads having human or mouse origin. No conflict of interest. 849 High throughput capture and profiling of CTCs using innovative technologies for gene expression C. Jarman1 , A. Lejeune-Dodge1 , S. Peter2 , K. Hull2 , D. Donnelly1 . 1 Labcyte, Applications, Sunnyvale, USA, 2 Angle PLC, R&D, Guildford, United Kingdom Introduction: The use of molecular diagnostics in oncology is rapidly evolving. Recent advancements have led to the production of “live” data for translational medicine and clinical guidance. Capturing intra tumoral and clonal diversity using liquid biopsies is an example of such an advancement. This precious tool enables the representation of cancer heterogeneity using molecular profiling of circulating tumour cells (CTCs) at gene expression level. Here we present a robust workflow for the capture of CTCs from patient-blood samples using Angle PLC’s Parsortix system along with CTC enrichment using the Echo Acoustic Liquid Handler from Labcyte for contactless cell transfer. Following enrichment, expression profiling reactions were set up by dispensing miniaturised volumes of reagents for high throughput qPCR read out − also using the Echo system. This approach was implemented at Angle PLC to address the need of increased throughput for molecular profiling by qPCR at the single cell level. Methods: Linearity of cell transfer: Patient blood samples were spiked with fluorescently labelled CaOV3 cells. CTCs were harvested using the Parsortix system. Harvested CTCs were transferred using the Echo system into 384-well microplates for visual inspection and counting. Gene expression profiling: Three positive controls were added to the plate, alongside three no template controls (NTC), using the Echo system. The Echo system was also used to transfer reagents from Ambion’s Single Cell-to-CT kit directly onto the CTCs and controls to perform reverse transcription, preamplification and qPCR with in a miniaturized reaction (10-fold reduction). qPCR was performed using the Roche LightCycler 480. Results: Accurate transfer of cells using the Echo system was validated. This enabled an enrichment of CTCs over white blood cells from Parsortixprocessed patient blood samples. Miniaturisation of the ‘Single Cell-to-CT’ kit for EpCAM gene expression in CaCOV3 cells & qPCR reactions using the Echo system established a robust method for flexible high throughput profiling investigations with a major impact on cost reduction. Absence of amplification in NTC & the expected differential of 3Ct between dilutions of positive controls
S195
848 A computational approach to discriminate between human and mouse reads in sequencing data from Patient Derived Tumour Xenografts M. Callari1 , A. Sati Batra1 , R.N. Batra1 , H. Clifford1 , W. Greenwood1 , S.J. Sammut1 , S.F. Chin1 , A. Bruna1 , O.M. Rueda1 , C. Caldas1 . 1 University of Cambridge, Cancer Research UK Cambridge Institute, Cambridge, United Kingdom Background: Patient Derived Tumour Xenografts (PDTXs) are emerging pre-clinical models that better represent clinical tumours and intra-tumour heterogeneity compared with cell lines. In most of the studies involving PDTXs, their molecular characterization is central; however, the analysis of sequencing data from PDTXs is hampered by the presence of mouse stroma contamination. Due to the high homology between the two organisms, a proportion of mouse reads can still map to homologous regions of the human genome, likely with some mismatch, heavily affecting downstream analysis. Material and Methods: We carried out controlled experiments where fixed amounts of human and mouse DNA (or RNA) were mixed, ranging from a pure human sample to a pure mouse sample. Whole Exome Sequencing (WES), RNA-seq and Reduced Representation Bisulfite Sequencing (RRBS) were performed. A bioinformatic pipeline was developed to distinguish human from mouse reads by aligning raw data against both human and mouse genomes. The validity of the approach was confirmed in sequencing data from PDTXs and matched primary tumours. Results: The developed method was able to correctly classify human and mouse reads with an accuracy >99.9%. Using the controlled experiment, we also derived a calibration curve linking the percentage of human DNA in the sample and the percentage of reads classified as human. This calibration curve can then be used to estimate the percentage of mouse contamination in the sample. We verified that the alignment of PDTX WES data using the human reference genome only can generate up to thousands of false positive calls in samples with a mouse contamination as low as 10%. By applying our approach, we were able to prevent the calling of these artefacts increasing the correlation between each PDTX and the matched primary tumour. Also in RNA-seq and RRBS data, distinguishing between human and mouse reads gave more accurate estimates of the tumour transcriptome and methylome. Importantly, it also allowed analysing separately the microenvironment contribution. Conclusions: An ad-hoc bioinformatic pipeline is needed for the analysis of PDTX sequencing data. Here we present a simple and fast solution to accurately discriminate reads having human or mouse origin. No conflict of interest. 849 High throughput capture and profiling of CTCs using innovative technologies for gene expression C. Jarman1 , A. Lejeune-Dodge1 , S. Peter2 , K. Hull2 , D. Donnelly1 . 1 Labcyte, Applications, Sunnyvale, USA, 2 Angle PLC, R&D, Guildford, United Kingdom Introduction: The use of molecular diagnostics in oncology is rapidly evolving. Recent advancements have led to the production of “live” data for translational medicine and clinical guidance. Capturing intra tumoral and clonal diversity using liquid biopsies is an example of such an advancement. This precious tool enables the representation of cancer heterogeneity using molecular profiling of circulating tumour cells (CTCs) at gene expression level. Here we present a robust workflow for the capture of CTCs from patient-blood samples using Angle PLC’s Parsortix system along with CTC enrichment using the Echo Acoustic Liquid Handler from Labcyte for contactless cell transfer. Following enrichment, expression profiling reactions were set up by dispensing miniaturised volumes of reagents for high throughput qPCR read out − also using the Echo system. This approach was implemented at Angle PLC to address the need of increased throughput for molecular profiling by qPCR at the single cell level. Methods: Linearity of cell transfer: Patient blood samples were spiked with fluorescently labelled CaOV3 cells. CTCs were harvested using the Parsortix system. Harvested CTCs were transferred using the Echo system into 384-well microplates for visual inspection and counting. Gene expression profiling: Three positive controls were added to the plate, alongside three no template controls (NTC), using the Echo system. The Echo system was also used to transfer reagents from Ambion’s Single Cell-to-CT kit directly onto the CTCs and controls to perform reverse transcription, preamplification and qPCR with in a miniaturized reaction (10-fold reduction). qPCR was performed using the Roche LightCycler 480. Results: Accurate transfer of cells using the Echo system was validated. This enabled an enrichment of CTCs over white blood cells from Parsortixprocessed patient blood samples. Miniaturisation of the ‘Single Cell-to-CT’ kit for EpCAM gene expression in CaCOV3 cells & qPCR reactions using the Echo system established a robust method for flexible high throughput profiling investigations with a major impact on cost reduction. Absence of amplification in NTC & the expected differential of 3Ct between dilutions of positive controls