Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression analysis of osteosarcoma tumor-initiating cells (High) vs bulk tumor cells (Low)

ABSTRACT: In the cancer stem cell model a cell hierarchy has been suggested as an explanation for intratumoral heterogeneity, and tumor formation is thought to be driven by this tumor cell subpopulation. The identification of cancer stem cells in osteosarcoma (OS) and the biological processes dysregulated in this cell subpopulation, also known as tumor-initiating cells (TICs), may provide new therapeutic targets. The goal of this study, therefore, was to identify and characterize the gene expression profiles of TICs isolated from human OS cell lines. We analyzed the self-renewal capacity of OS cell lines and primary OS tumors based upon their ability to form sphere-like structures (sarcospheres) under serum-starving conditions. TICs were identify from OS cell lines using the long-term label retention dye PKH26. OS TICs and the bulk of tumor cells were isolated and used to assess their ability to initiate tumor in NOD/SCID mice. Gene expression profiles of OS TICs were obtained from fresh orthotopic tumor samples. We observed that increased sarcosphere efficiency correlated with an enhanced tumorigenic potential in OS. PKH26High cells were shown to constitute OS TICs based upon their capacity to form more sarcospheres, as well as to generate both primary bone tumors and lung metastases efficiently in NOD/SCID mice. Genomic profiling of OS TICs revealed that both bone development and cell migration processes were dysregulated in this tumor cell subpopulation. PKH26 labeling represents a valuable tool to identify OS TICs and gene expression analysis of this tumor cell compartment evidences potential therapeutic targets. Gene expression analysis was performed in PKH26Hi cells (TICs) and PKH26Lo cells (non-TICs) obtained from five orthotopic bone tumors generated by each MNNG/HOS and 143B cell lines.The soft tissue component from each bone tumor was dissected, minced and processed. Immediately after FACS, 1.5x10^5 PKH26Hi cells and 7x10^5 PKH26Lo cells from each bone tumor sample were snap frozen and stored at -80°C until RNA processing. The microarray data were first evaluated for quality control using the AffyQCReport library of BioConductor 50.Two 143B PKH26Hi tumor samples were processed together due to insufficient RNA material.

ORGANISM(S): Homo sapiens

SUBMITTER: Alexander Yu

PROVIDER: E-GEOD-33458 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Publications

Identification and gene expression profiling of tumor-initiating cells isolated from human osteosarcoma cell lines in an orthotopic mouse model.

Rainusso Nino N Man Tsz-Kwong TK Lau Ching C CC Hicks John J Shen Jianhe J JJ Yu Alexander A Wang Lisa L LL Rosen Jeffrey M JM

Cancer biology & therapy 20110815 4

In the cancer stem cell model a cell hierarchy has been suggested as an explanation for intratumoral heterogeneity and tumor formation is thought to be driven by this tumor cell subpopulation. The identification of cancer stem cells in osteosarcoma (OS) and the biological processes dysregulated in this cell subpopulation, also known as tumor-initiating cells (TICs), may provide new therapeutic targets. The goal of this study, therefore, was to identify and characterize the gene expression profil ...[more]

PMID: 21617384

Similar Datasets

Project description:Background Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models. Results mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a “shortest path” algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including “Cytoskeleton remodeling/TGF/WNT”, “Cytoskeleton remodeling/Cytoskeleton remodeling”, and “Cell adhesion/Chemokines and adhesion”. Of these, the “Cytoskeleton remodeling/TGF/WNT” was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the “Cytoskeleton remodeling/TGF/WNT” pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform. Conclusions In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS. In this study we analyzed two human metastatic OS cell lines and their parental non-metastatic lines. The two human metastatic OS cell line models were HOS/143B and SaOS-2/LM7. The HOS cell line, originally known as M.T. and later as TE-85, was derived from an OS of a 13 year-old girl. The 143B metastatic subline was generated from HOS by a Ki-RAS oncogene transformation [Rhim, J.S., et al., Characterization of human cells transformed in vitro by N-methyl-N'-nitro-N-nitrosoguanidine. Int J Cancer, 1977. 19(4): p. 505-10.]. The SaOS-2 cell was derived from an OS of an 11 year-old girl, and its metastatic subline LM7, was developed by multiple in vivo selection of SaOS-2 cells in mice with pulmonary metastases [Jia, S.F., L.L. Worth, and E.S. Kleinerman, A nude mouse model of human osteosarcoma lung metastases for evaluating new therapeutic strategies. Clin Exp Metastasis, 1999. 17(6): p. 501-6.]. No replicates were included.

Dataset Information

Gene expression analysis of osteosarcoma tumor-initiating cells (High) vs bulk tumor cells (Low)

Publications

Identification and gene expression profiling of tumor-initiating cells isolated from human osteosarcoma cell lines in an orthotopic mouse model.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets