Dataset Information

Identification of critical genes associated with human osteosarcoma metastasis based on integrated gene expression profiling.

ABSTRACT: Osteosarcoma is the most common type of malignant bone cancer, which often affects teenagers and young adults. The present study aimed to screen for critical genes and microRNAs (miRNAs/miRs) involved in osteosarcoma. A total of four microarray datasets (accession numbers GSE32981, GSE21257, GSE14827 and GSE14359) were downloaded from the Gene Expression Omnibus database. Following data preprocessing, module analysis was performed to identify the stable modules using the weighted gene co?expression network analysis (WGCNA) package. The differentially expressed genes (DEGs) between metastatic samples and non?metastatic samples were screened, followed by gene co?expression network construction, and Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway analyses. Subsequently, prognosis?associated genes were screened and a miRNA?target gene regulatory network was constructed. Finally, the data for critical genes were validated. WGCNA analysis identified six modules; blue and yellow modules were significantly positively associated with osteosarcoma metastasis. A total of 1,613 DEGs were screened between primary tissue samples and metastatic samples. Following comparison of the genes in the two (blue and yellow) modules, a total of 166 DEGs were identified (metastatic samples vs. non?metastatic samples). Functional enrichment analysis demonstrated that these DEGs were mainly involved in 'defense response', 'p53 signaling pathway' and 'lysosome'. By utilizing the clinical information in GSE21257, 10 critical genes associated with osteosarcoma prognosis were obtained, including CTP synthase 2 (CTPS2), tumor protein p53 inducible protein 3 (TP53I3) and solute carrier family 1 member 1 (SLC1A1). In addition, hsa?miR?422a and hsa?miR?194 were highlighted in the miRNA?target gene network. Finally, matrix metallopeptidase 3 (MMP3) and vascular endothelial growth factor B (VEGFB) were predicted as critical genes in osteosarcoma metastasis. CTPS2, TP53I3 and SLC1A1 may serve major roles in osteosarcoma development, and hsa?miR?422a, hsa?miR?194, MMP3 and VEGFB may be associated with osteosarcoma metastasis.

SUBMITTER: Fan H

PROVIDER: S-EPMC6625205 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Identification of critical genes associated with human osteosarcoma metastasis based on integrated gene expression profiling.

Fan Hongwu H Lu Shan S Wang Shengqun S Zhang Shanyong S

Molecular medicine reports 20190603 2

Osteosarcoma is the most common type of malignant bone cancer, which often affects teenagers and young adults. The present study aimed to screen for critical genes and microRNAs (miRNAs/miRs) involved in osteosarcoma. A total of four microarray datasets (accession numbers GSE32981, GSE21257, GSE14827 and GSE14359) were downloaded from the Gene Expression Omnibus database. Following data preprocessing, module analysis was performed to identify the stable modules using the weighted gene co‑express ...[more]

PMID: 31173206

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Project description:BackgroundGene expression profiling of spontaneous tumors in the dog offers a unique translational opportunity to identify prognostic biomarkers and signaling pathways that are common to both canine and human. Osteosarcoma (OS) accounts for approximately 80% of all malignant bone tumors in the dog. Canine OS are highly comparable with their human counterpart with respect to histology, high metastatic rate and poor long-term survival. This study investigates the prognostic gene profile among thirty-two primary canine OS using canine specific cDNA microarrays representing 20,313 genes to identify genes and cellular signaling pathways associated with survival. This, the first report of its kind in dogs with OS, also demonstrates the advantages of cross-species comparison with human OS.ResultsThe 32 tumors were classified into two prognostic groups based on survival time (ST). They were defined as short survivors (dogs with poor prognosis: surviving fewer than 6 months) and long survivors (dogs with better prognosis: surviving 6 months or longer). Fifty-one transcripts were found to be differentially expressed, with common upregulation of these genes in the short survivors. The overexpressed genes in short survivors are associated with possible roles in proliferation, drug resistance or metastasis. Several deregulated pathways identified in the present study, including Wnt signaling, Integrin signaling and Chemokine/cytokine signaling are comparable to the pathway analysis conducted on human OS gene profiles, emphasizing the value of the dog as an excellent model for humans.ConclusionA molecular-based method for discrimination of outcome for short and long survivors is useful for future prognostic stratification at initial diagnosis, where genes and pathways associated with cell cycle/proliferation, drug resistance and metastasis could be potential targets for diagnosis and therapy. The similarities between human and canine OS makes the dog a suitable pre-clinical model for future 'novel' therapeutic approaches where the current research has provided new insights on prognostic genes, molecular pathways and mechanisms involved in OS pathogenesis and disease progression.

Project description:BackgroundOsteosarcoma (OSA) spontaneously arises in the appendicular skeleton of large breed dogs and shares many physiological and molecular biological characteristics with human OSA. The standard treatment for OSA in both species is amputation or limb-sparing surgery, followed by chemotherapy. Unfortunately, OSA is an aggressive cancer with a high metastatic rate. Characterization of OSA with regard to its metastatic potential and chemotherapeutic resistance will improve both prognostic capabilities and treatment modalities.MethodsWe analyzed archived primary OSA tissue from dogs treated with limb amputation followed by doxorubicin or platinum-based drug chemotherapy. Samples were selected from two groups: dogs with disease free intervals (DFI) of less than 100 days (n = 8) and greater than 300 days (n = 7). Gene expression was assessed with Affymetrix Canine 2.0 microarrays and analyzed with a two-tailed t-test. A subset of genes was confirmed using qRT-PCR and used in classification analysis to predict prognosis. Systems-based gene ontology analysis was conducted on genes selected using a standard J5 metric. The genes identified using this approach were converted to their human homologues and assigned to functional pathways using the GeneGo MetaCore platform.ResultsPotential biomarkers were identified using gene expression microarray analysis and 11 differentially expressed (p < 0.05) genes were validated with qRT-PCR (n = 10/group). Statistical classification models using the qRT-PCR profiles predicted patient outcomes with 100% accuracy in the training set and up to 90% accuracy upon stratified cross validation. Pathway analysis revealed alterations in pathways associated with oxidative phosphorylation, hedgehog and parathyroid hormone signaling, cAMP/Protein Kinase A (PKA) signaling, immune responses, cytoskeletal remodeling and focal adhesion.ConclusionsThis profiling study has identified potential new biomarkers to predict patient outcome in OSA and new pathways that may be targeted for therapeutic intervention.

Dataset Information

Identification of critical genes associated with human osteosarcoma metastasis based on integrated gene expression profiling.

Publications

Identification of critical genes associated with human osteosarcoma metastasis based on integrated gene expression profiling.

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