DNA Biomarkers in Tissue Samples From Patients With Osteosarcoma

Therapeutically Applicable Research to Generate Effective Treatments (TARGET) for Osteosarcoma

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.

Study Overview

• Status: Completed
• Conditions: Recurrent Osteosarcoma; Metastatic Osteosarcoma; Localized Osteosarcoma
• Intervention / Treatment: Other: Laboratory Biomarker Analysis

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.

• Study Type: Observational
• Enrollment (Actual): 125

Contacts and Locations

Study Locations

• United States
  • Pennsylvania
    • Philadelphia, Pennsylvania, United States, 19104
      • Childrens Oncology Group

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Child; Adult; Older Adult
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

PATIENTS WITH OSTEOSARCOMA WITH SPECIMENS COLLECTED AND BANKED ON THE OS BIOLOGY PROTOCOL (P9851) OR THE REPLACEMENT AOST06B1

Description

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

Study Plan

How is the study designed?

Design Details

• Observational Models: Case-Only
• Time Perspectives: Retrospective

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Ancillary-Correlative (biomarker sampling and analysis); 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.

Other: Laboratory Biomarker Analysis; Correlative studies

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Expression of genes	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.	Baseline
Incidence of copy number abberations	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 .	Baseline
Incidence of mutations that occur at a clinically significant frequency		Baseline

Collaborators and Investigators

• Sponsor: Children's Oncology Group
• Collaborators: National Cancer Institute (NCI)
• Investigators: Principal Investigator: Ching C Lau, Children's Oncology Group

Study record dates

Study Major Dates

• Study Start (Actual): August 6, 2010
• Primary Completion (Actual): October 1, 2010

Study Registration Dates

• First Submitted: August 27, 2010
• First Submitted That Met QC Criteria: August 27, 2010
• First Posted (Estimate): August 30, 2010

Study Record Updates

• Last Update Posted (Actual): March 28, 2022
• Last Update Submitted That Met QC Criteria: March 11, 2022
• Last Verified: March 1, 2022

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Neoplasms, Connective and Soft Tissue; Neoplasms by Histologic Type; Neoplasms; Neoplasms, Bone Tissue; Neoplasms, Connective Tissue; Sarcoma; Osteosarcoma
• Other Study ID Numbers: AOST10B5 (Other Identifier: CTEP); U10CA098543 (U.S. NIH Grant/Contract); NCI-2011-02840 (Registry Identifier: CTRP (Clinical Trial Reporting Program)); CDR0000683276; COG-AOST10B5

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No