MicroRNA expression in a chondroblastic osteosarcoma
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE98014 | GEO | 2021/08/13
REPOSITORIES: GEO
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Project description:Conventional high-grade osteosarcoma is a primary malignant bone tumor, which is most prevalent in adolescence. Survival rates of osteosarcoma patients have not improved significantly in the last 25 years. Aiming to increase this survival rate, a variety of model systems are used to study osteosarcomagenesis and to test new therapeutic agents. Such model systems are typically generated from an osteosarcoma primary tumor, but undergo many changes due to culturing or interactions with a different host species, which may result into differences in gene expression between primary tumor cells, and tumor cells from the model system. We aimed to investigate whether gene expression profiles of osteosarcoma cell lines and xenografts are still comparable to those of the primary tumor. Osteosarcoma can be subdivided into several histological subtypes, of which osteoblastic, chondroblastic, and fibroblastic osteosarcoma are the most frequent ones. Using nearest shrunken centroids classification, we have generated an expression profile that can predict these histological subtypes in both osteosarcoma biopsies (n=66), as well as in two osteosarcoma model systems, i.e. osteosarcoma cell lines (n=13) and xenografts (n=18). Based on the preservation of mRNA expression profiles that are characteristic for the histological subtype we propose that these model systems are representative to the primary tumor from which they are derived. Genome-wide expression profiling was performed on pre-treatment diagnostic biopsies of 76 resectable high-grade osteosarcoma patients from the EuroBoNet consortium (www.eurobonet.eu). Samples with a main histological subtype (n=66) were selected for subsequent subtype analyses. Out of the EuroBoNeT panel of 19 cell lines, 13 cell lines were recorded to belong to a main histological subtype. This set of 13 cell lines contained 4 cell lines derived from fibroblastic, and 9 cell lines derived from osteoblastic osteosarcomas. The 13 osteosarcoma cell lines IOR/MOS, IOR/OS10, IOR/OS14, IOR/OS15, IOR/OS18, IOR/OS9, IOR/SARG, KPD, MG-63, MHM, OHS, OSA, and ZK-58 were maintained in RPMI 1640 (Invitrogen, Carlsbad, CA, USA) supplemented with 10% fetal calf serum and 1% Penicillin/Streptomycin (Invitrogen) as previously described (PMID: 19787792). The osteosarcoma xenograft model is described in Kresse et al. (PMID: 21713766) In short, human tumors were implanted directly from patient samples and successively passaged subcutaneously in nude mice. Eighteen different xenografts were used, of which 3 were derived from chondroblastic, and 15 from osteoblastic osteosarcomas. Osteosarcoma and xenograft tissue was handled as previously described in Buddingh, Kuijjer et al. (PMID: 21372215) Osteosarcoma cell lines were prepared as in Ottaviano et al. (PMID: 19787792) RNA isolation, synthesis of cDNA, cRNA amplification, and hybridization of cRNA onto the Illumina Human-6 v2.0 Expression BeadChips were performed as described in Buddingh, Kuijjer, et al. (PMID: 21372215) Microarray data processing and quality control were performed using the statistical language R as described in Buddingh, Kuijjer, et al. (PMID: 21372215) We performed a factorial LIMMA analysis comparing 50 osteoblastic, 9 chondroblastic, and 7 fibroblastic osteosarcomas pre-chemotherapy biopsies. Probes with Benjamini and Hochberg False discovery rate-adjusted P-values < 0.05 were considered to be significantly differentially expressed. The gene expression profile was generated on the dataset of biopsies using Bioconductor package PAMR. Internal cross-validation was performed 50 times. A threshold was selected where the error rate of the prediction profile was minimal. The minimum error rate was representative of 50 independent simulations. In order to minimize optimization bias, we validated the profile on an independent dataset of osteosarcoma biopsies (n=5), containing 1 chondroblastic osteosarcoma and 4 osteoblastic osteosarcomas. We subsequently applied the validated prediction profile to two independent datasets, the first consisting of gene expression data of osteosarcoma cell lines, the second of xenografts. Expression of the probes that composed the prediction profile was verified using a factorial LIMMA analysis, comparing chondroblastic, fibroblastic, and osteoblastic osteosarcoma biopsy samples.
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Project description:Conventional high-grade osteosarcoma is a primary malignant bone tumor, which is most prevalent in adolescence. Survival rates of osteosarcoma patients have not improved significantly in the last 25 years. Aiming to increase this survival rate, a variety of model systems are used to study osteosarcomagenesis and to test new therapeutic agents. Such model systems are typically generated from an osteosarcoma primary tumor, but undergo many changes due to culturing or interactions with a different host species, which may result into differences in gene expression between primary tumor cells, and tumor cells from the model system. We aimed to investigate whether gene expression profiles of osteosarcoma cell lines and xenografts are still comparable to those of the primary tumor. Osteosarcoma can be subdivided into several histological subtypes, of which osteoblastic, chondroblastic, and fibroblastic osteosarcoma are the most frequent ones. Using nearest shrunken centroids classification, we have generated an expression profile that can predict these histological subtypes in both osteosarcoma biopsies (n=66), as well as in two osteosarcoma model systems, i.e. osteosarcoma cell lines (n=13) and xenografts (n=18). Based on the preservation of mRNA expression profiles that are characteristic for the histological subtype we propose that these model systems are representative to the primary tumor from which they are derived.
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