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).

Project description:Glioblastoma (GBM) heterogeneity in the genomic and phenotypic properties has potentiated personalized approach against specific therapeutic targets of each GBM patient. The Cancer Genome Atlas (TCGA) Research Network has been established the comprehensive genomic abnormalities of GBM, which sub-classified GBMs into 4 different molecular subtypes. The molecular subtypes could be utilized to develop personalized treatment strategy for each subtype. We applied a classifying method, NTP (Nearest Template Prediction) method to determine molecular subtype of each GBM patient and corresponding orthotopic xenograft animal model. The models were derived from GBM cells dissociated from patient's surgical sample. Specific drug candidates for each subtype were selected using an integrated pharmacological network database (PharmDB), which link drugs with subtype specific genes. Treatment effects of the drug candidates were determined by in vitro limiting dilution assay using patient-derived GBM cells primarily cultured from orthotopic xenograft tumors. The consistent identification of molecular subtype by the NTP method was validated using TCGA database. When subtypes were determined by the NTP method, orthotopic xenograft animal models faithfully maintained the molecular subtypes of parental tumors. Subtype specific drugs not only showed significant inhibition effects on the in vitro clonogenicity of patient-derived GBM cells but also synergistically reversed temozolomide resistance of MGMT-unmethylated patient-derived GBM cells. However, inhibitory effects on the clonogenicity were not totally subtype-specific. Personalized treatment approach based on genetic characteristics of each GBM could make better treatment outcomes of GBMs, although more sophisticated classifying techniques and subtype specific drugs need to be further elucidated. Gene expression profiling experiments were conducted for 25 patient-derived xenograft glioblastoma samples using Affymetrix Human Gene 1.0 ST arrays according to manufacturer's protocol.

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Alternative classification of glioblastoma based on BUB1B-inhibition sensitivity

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