Gene expression profile of A549 Circulating Tumor Cells from 4D Model.
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE50991 | GEO | 2015/03/12
SECONDARY ACCESSION(S): PRJNA219489
REPOSITORIES: GEO
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Project description:CTCs in cancer patients are thought to be responsible for metastasis. Currently, there is no ex vivo model that can isolate this group of cells. We have developed an ex vivo 4D lung cancer model that forms perfusable tumor nodules and form CTCs. Gene array analyses show 2504 differentially expressed genes when comparing CTCs from the 4D model seeded with A549 cells to the same cells grown on a petri dish (2D). We compared the gene expression profile (Human OneArray v5 chip) of A549 cells, human lung cancer cell line, grown on petri dish (2D) and same cells circulating as tumor cells in our ex vivo model (4D/CTC).
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Project description:Tumor microenvironment plays an important role in regulating cell growth and metastasis. Recently we developed an ex vivo lung cancer model (4D) that forms perfusable tumor nodules on a lung matrix that mimics human lung cancer histopathology and protease secretion pattern. We compared the gene expression profile (Human OneArray v5 chip) of A549 cells, a human lung cancer cell line, grown on petri dish (2D), and of the same cells grown in the matrix of our ex vivo model (4D). Furthermore, we obtained gene expression data of A549 cells grown on petri dish (2D) and matrigel (3D) from a previous study and compared the 3D expression profile with that of 4D. Expression array analysis showed 2954 genes differentially expressed between 2D and 4D. Gene Ontology (GO) analysis showed up-regulation of several genes associated with extracellular matrix, polarity, and cell fate and development. Moreover, expression array analysis of 2D versus 3D showed 269 genes that were most differentially expressed, with only 35 genes (13%) having similar expression patterns as observed between 2D and 4D. Finally, the differential gene expression signature of 4D cells (versus 2D) correlated significantly with poor survival in patients with lung cancer (n=1492), while the expression signature of 3D versus 2D correlated with better survival in lung cancer patients. Since patients with larger tumors tend to have worse survival, the ex vivo 4D model may offer additional features over the 3D model, to better mimic of natural progression of tumor growth in lung cancer patients. We compared the gene expression profile (Human OneArray v5 chip) of A549 cells, human lung cancer cell line, grown on petri dish (2D) and same cells grown in the matrix of our ex vivo model (4D).
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Project description:Tumor microenvironment plays an important role in regulating cell growth and metastasis. Recently we developed an ex vivo lung cancer model (4D) that forms perfusable tumor nodules on a lung matrix that mimics human lung cancer histopathology and protease secretion pattern. We compared the gene expression profile (Human OneArray v5 chip) of A549 cells, a human lung cancer cell line, grown on petri dish (2D), and of the same cells grown in the matrix of our ex vivo model (4D). Furthermore, we obtained gene expression data of A549 cells grown on petri dish (2D) and matrigel (3D) from a previous study and compared the 3D expression profile with that of 4D. Expression array analysis showed 2954 genes differentially expressed between 2D and 4D. Gene Ontology (GO) analysis showed up-regulation of several genes associated with extracellular matrix, polarity, and cell fate and development. Moreover, expression array analysis of 2D versus 3D showed 269 genes that were most differentially expressed, with only 35 genes (13%) having similar expression patterns as observed between 2D and 4D. Finally, the differential gene expression signature of 4D cells (versus 2D) correlated significantly with poor survival in patients with lung cancer (n=1492), while the expression signature of 3D versus 2D correlated with better survival in lung cancer patients. Since patients with larger tumors tend to have worse survival, the ex vivo 4D model may offer additional features over the 3D model, to better mimic of natural progression of tumor growth in lung cancer patients.
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