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Gene expression profile of A549 cells from tissue of 4D model predicts poor prognosis in lung cancer patients

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE45142 | GEO | 2013/09/16

SECONDARY ACCESSION(S): PRJNA192963

REPOSITORIES: GEO

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Gene expression profile of A549 cells from tissue of 4D model predicts poor prognosis in lung cancer patients

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:To understand the global impact of PPP6C loss on gene expression, we carried out RNA-seq analysis in parental and PPP6C KO SW620 cells under 2D and 3D culture conditions. SW620 WT (sgNT) and PPP6C KO (sgPPP6C#2, sgPPP6C#3) were cultured in normal petri dish (2D culture) or U-bottom plates (3D culture) for 3 days with three independent replicates for each cell sample. A total of 4,337 genes were found to be differentially expressed in the KO cells under at least one condition (FDR < 0.05, ≥ 2-fold change). Among these, 1,123 genes were significant up- or down-regulated in PPP6C KO cells under both 2D and 3D conditions. Unsupervised clustering analysis identified three large clusters of gene expression patterns: cluster 1 were upregulated in the PPP6C KO cells primarily under 2D conditions, cluster 2 were upregulated in the PPP6C KO cells under both 2D and 3D conditions, and cluster 3 gene were downregulated genes in the PPP6C KO cells under both 2D and 2D conditions. We next carried out gene set enrichment analysis (GSEA) using the hallmark gene set database to identified pathways that were significantly altered in PPP6C KO cells. Among the pathways upregulated in the PPP6C KO cells under both 2D and 3D conditions, the “TNFA-signaling_via_NFKB” gene set scored as the top one. Both “KRAS_signaling_up” and “PI3K_AKT_mTOR_signaling” gene sets were also significantly upregulated. PPP6C KO has opposite effects on cell proliferation in 2D monolayer vs. 3D tumor spheroid culture. We noticed that 383 genes in the PPP6C KO cells showed opposite changes in 2D vs. 3D conditions. Taken together, gene expression analysis indicates that multiple signaling pathways including the KRAS, PI3K and NF-κB pathways were perturbed in the in PPP6C KO cells and they could contribute to the cell’s decreased sensitivity to MEK inhibitors.

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