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Gene Expression Profile of H1299 Cells from Tissue of 4D Model

ABSTRACT: We have developed a 4D lung cancer model that forms perfusable tumor nodules. We determined if the model could be modified to mimic metastasis. We modified the 4D lung cancer model by seeding H1299 cells via the trachea only to the left lobes of the acellular lung matrix. The model was modified so that the tumor cells can reach the right lobes of the acellular lung matrix only through the pulmonary artery as circulating tumor cells (CTC). We determined the gene expressions of the primary tumor, CTCs, and metastatic lesions using the Human OneArray chip. All cell lines formed a primary tumor in the left lobe of the ex vivo 4D lung cancer model. The CTCs were identified in the media and increased over time. The CTC gene signature predicted poor survival in lung cancer patients. A unique set of genes were significantly expressed in CTC compared to the primary tumor and metastatic lesion. The 4D lung cancer model can isolate tumor cells in three phases of tumor progression. This 4D lung cancer model may mimic the biology of lung cancer metastasis and may be used to determine its mechanism and potential therapy in the future.

ORGANISM(S): Homo sapiens

PROVIDER: GSE58355 | GEO | 2015/03/12

SECONDARY ACCESSION(S): PRJNA252097

REPOSITORIES: GEO

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Project description:Circulating tumor cells (CTCs) are critical in the development of distant organ tumor metastasis, and are associated with advanced cancer stage and poor patient outcome. Here, we present the first genome-wide nucleotide-level characterization of CTCs. Our single-nucleotide polymorphism (SNP) analysis in patients with melanoma involved: 1) global comparative genomic analysis of CTCs and matched regional metastases, 2) identification of key genomic aberrations in CTCs, 3) verification of these target genes in aggressive distant tumor metastases, and 4) evidence of selective expression and functional consequence of CTC-associated genes in melanomas. We report 131 aberrant loci in CTCs that are potentially pro-metastatic, and show that such expression of a 5-marker gene panel (CSMD2, CNTNAP5, FLJ14051, ADAM6, TRPM2) in melanomas confers prognostic utility. Successful treatment of melanoma requires understanding of the metastatic process and identification of patients with tumors most likely to develop aggressive metastatic disease. Melanomas are heterogeneous, and CTCs have long been recognized as vehicles for cancer spread, representing particularly aggressive tumor clones that can evolve into successful clinical metastases. Elucidation of genomic aberrations in CTCs will aid in the development of prognostic biomarkers and therapeutic strategies to target CTCs to prevent or control distant cancer spread. This study provides the first detailed genomic confirmation of the close relation between CTCs and tumor metastases, and illustrates how CTCs can be utilized as a novel approach and rational source for identification of pro-metastatic genes in cancer research. Three individual patient cohorts were utilized in the study. CNV and LOH loci were evaluated initially in metastatic melanoma patients (n=13) in a discovery cohort. SNP loci that harbored CNV/LOH in CTCs were then separately verified for: (a) presence in distant organ metastasis (AJCC Stage IV melanoma) (n=27), and (b) relevance to prognosis in regional melanoma metastasis (AJCC Stage III melanoma) (n=35). The first discovery patient cohort group was utilized for capture of CTCs, and consisted of peripheral blood mononuclear cell (PBMC) and tumor specimens from metastatic melanoma patients (n=13). CTC-related loci were verified in a second cohort of patients with Stage IV distant organ metastases (n=27), including 15 brain, 4 lung, and 8 gastrointestinal (bowel, liver) metastases. The third patient cohort consisted of early passage (<12) established melanoma cell lines derived from 35 regional melanoma metastases (Stage III) for evaluation of the prognostic utility of the CTC-associated aberrant loci.

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Gene Expression Profile of H1299 Cells from Tissue of 4D Model

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