Localized Osteosarcoma, Metastatic Osteosarcoma, Recurrent Osteosarcoma
Conditions
Brief summary
This research study is studying DNA biomarkers in tissue samples from patients with osteosarcoma. Studying samples of tumor tissue and blood from patients with cancer in the laboratory may help doctors learn more about changes the occur in DNA and identify biomarkers related to cancer. DNA analysis of tumor tissue may also help doctors predict how well patients will respond to treatment.
Detailed description
OBJECTIVES: I. To comprehensively detect genomic, epigenomic, and transcriptomic aberrations in tissue samples from patients with osteosarcoma that may play a role in chemoresistance and metastasis using high-resolution genome-wide technologies. II. To identify recurrent genetic mutations involved in the pathogenesis of osteosarcoma, especially for the development of chemoresistance and metastatic tumors. III. To identify and validate these biomarkers for new therapeutic targets for patients with osteosarcoma, especially those with metastatic disease and whose tumors are resistant to standard chemotherapy. OUTLINE: This is a multicenter study. Archived tumor tissue and peripheral blood DNA specimens are analyzed for DNA copy number profiling, gene expression profiling, DNA methylation profiling, microRNA profiling, and genomic resequencing. Clinical data including demographics; date of diagnosis, surgery, chemotherapy, recurrence, progression, and death; imaging; toxicity; and pathologic data elements associated with the specimens are also collected and analyzed.
Interventions
OTHERLaboratory Biomarker Analysis
Correlative studies
Sponsors
National Cancer Institute (NCI)
Children's Oncology Group
Study design
Observational model
CASE_ONLY
Time perspective
RETROSPECTIVE
Eligibility
Sex/Gender
ALL
Healthy volunteers
No
Inclusion criteria
* Diagnosis of osteosarcoma * Fresh-frozen samples collected at the time of diagnosis with matchedblood DNA (preferred) from patients enrolled on the following osteosarcoma biology protocols: * COG-P9851 * COG-AOST06B1 * Available clinical outcome data * Not specified * Not specified
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Expression of genes | Baseline | The Significance Analysis of Microarrays (SAM) algorithm will be used for analysis of differential expression. Pathway analysis and data integration will be performed on the differentially expressed genes using Ingenuity Pathway Analysis. Differentially expressed genes and miRNA targets as well as genes in the significant DNA aberrations will be mapped and integrated to identify the enriched pathways and networks. |
| Incidence of copy number abberations | Baseline | The array data will be imported to Copy Number Analyzer (CNAG) for GeneChip mapping arrays to identify copy number aberrations in the tumor samples. To identify regions with frequent CNA among different groups of patient samples, we will use the Genomic Identification of Significant Targets in Cancer (GISTIC) tool . |
| Incidence of mutations that occur at a clinically significant frequency | Baseline | — |
Countries
United States
Outcome results
None listed