Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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SNP profiling of pancreatic adenocarcinoma (PDAC) xenografts

ABSTRACT: Pancreatic adenocarcinoma (PDAC) is one of the most lethal human malignancies and a major health problem. Patient-derived xenografts (PDX) are appearing as a prime approach for preclinical studies despite being insufficiently characterized as a model of the human disease and its diversity. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The extensive multiomics characterization of the xenografts demonstrated that PDX is a suitable model for preclinical studies, representing the diversity of the primary cancers. We generated subcutaneous PDX from PDAC samples obtained either surgically or using diagnostic biopsies (endoscopic ultrasound guided fine needle aspirate). The variable 'MultiOmicsClassification' indicates the resulting sample's group. 'CIMPclass' is the CpG island methylator phenotype as estimated from the methylation arrays analysis. In this dataset, Illumina Infinium HumanCode-24 BeadChips SNP arrays were used to analyze the DNA xenografts samples from pancreatic ductal adenocarcinoma.

ORGANISM(S): Homo sapiens

SUBMITTER: Nabila Elarouci

PROVIDER: E-MTAB-5006 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:A major impediment to the effective treatment of patients with PDAC (Pancreatic Ductal Adenocarcinoma) is the molecular heterogeneity of the disease, which is reflected in an equally diverse pattern of clinical responses to therapy. We developed an efficient strategy in which PDAC samples from 17 consecutively patients were obtained by EUS-FNA or surgery, their cells maintained as a primary culture and tumors as breathing tumors by xenografting in immunosuppressed mice. For these patients a clinical follow up was obtained. On the breathing tumors we studied the RNA expression profile by an Affymetrix approach. We observed a significant heterogeneity in their RNA expression profile, however, the transcriptome was able to discriminate patients with long- or short-time survival which correspond to moderately- or poorly-differentiated PDAC tumors respectively. Cells allowed us the possibility to analyze their relative sensitivity to several anticancer drugs in vitro by developing a chimiogram, like an antibiogram for microorganisms, with several anticancer drugs for obtaining an individual profile of drug sensitivity and as expected, the response was patient-dependent. Interestingly, using this approach, we also found that the transcriptome analysis could predict the sensitivity to some anticancer drugs of patients with a PDAC. In conclusion, using this approach, we found that the transcriptome analysis could predict the sensitivity to some anticancer drugs and the clinical outcome of patients with a PDAC. PDAC samples from 17 consecutively patients were obtained by Endoscopic Ultrasound-Guided Fine-Needle Aspiration (EUS-FNA) or surgery. Consents of informed patients were collected, and the ethics review board of the three centers approved the study. All samples were anonymized and obtained in accordance with institutional review boards. EUS-FNA cells were maintained as a primary culture and tumors as breathing tumors by xenografting in immunosuppressed mice. We characterized 17 PDAC-derived xenografts by duplicate. Total RNA was extracted and hybridized on Human Gene 2.0 (Genechip, Affymetrix) as described previously (Hamidi et al. JCI 122: 2092-2103, 2012).

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SNP profiling of pancreatic adenocarcinoma (PDAC) xenografts

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