Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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In silico nano-dissection: defining cell type specificity at transcriptional level in human disease

ABSTRACT: This SuperSeries is composed of the SubSeries listed below. Refer to individual Series

ORGANISM(S): Homo sapiens

SUBMITTER: Viji Nair

PROVIDER: E-GEOD-47185 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Engraftment of primary pancreas ductal adenocarcinomas (PDAC) in mice to generate patient derived xenograft (PDX) models is a promising platform to for biological and therapeutic studies in this disease. However, these models are still incompletely characterized. Here, we measured the impact of the murine environment on the gene expression of the engrafted human tumoral cells. We have analyzed gene expression profiles from 35 new PDX models and compared them with previously published microarray data from PDAC and hepatocellular carcinoma (HCC). Our results showed that PDX models derived from PDAC, or HCC, were clearly different to the cell lines derived from the same cancer tissues. Indeed, PDAC- and HCC-derived cell lines are indistinguishable one from the other based in their gene expression profiles. In contrast, the transcriptomes of PDAC and HCC PDX models are clearly different and more similar to their original tumor than to PDX models from the other tumor type. Interestingly, the main differences between pancreatic PDX models and human PDAC is the expression of genes involved in pathways related with extracellular matrix interactions and cell cycle regulation likely reflecting the adaptations of the tumors to the new environment. Furthermore, most of these differences are detected in the first passages after the tumor engraftment, indicating early phases of the adaptation process. In conclusion, different from conventional cancer cell lines, PDX models of PDAC retain similar gene expression profiles of PDAC. Expression changes are mainly related to genes involved in stromal pathways likely reflecting the adaptation to new environments. We also provide evidence of the stability of gene expression patterns over subsequent passages. We have analyzed gene expression profiles from 35 new PDX models and compared them with previously published in GEO microarray data. We used PDX models, primary tumors and cell lines from PDAC and hepatocellular carcinoma. All these public data were re-process in order to compare with our 35 samples

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In silico nano-dissection: defining cell type specificity at transcriptional level in human disease

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