No abstract

Osteosarcoma (OS) is a highly malignant bone neoplasm of children and young adults. It is characterized by chaotic karyotypes with complex marker chromosomes. We applied a combination of molecular cytogenetic techniques including comparative genomic hybridization (CGH), spectral karyotyping (SKY), and fluorescence in situ hybridization (FISH) to decipher the chromosomal complexity in a panel of 25 tumors. Combined SKY and G-banding analysis identified several novel recurrent breakpoint clusters and 9 nonrecurrent reciprocal translocations. CGH identified several recurrent chromosomal losses including 2q, 3p, 9, 10p, 12q, 13q, 14q, 15q, 16, 17p, and 18q, gains including Xp, Xq, 5q, 6p, 8q, 17p, and 20q, and high-level chromosomal amplifications at Xp11.2, 1q21-q22, 4p11, 4q12, 5p15, 6p12.1, 8q13, 8q23, 10q11, 10q22, 11q13, 11q23, 12q13-q14, 13q21-q34, 16q22, 17p11.2, 17q21-q22, 18q22, 20p11.2, and 20q12. Frequent amplification and rearrangement involving chromosomal bands at 6p12-p21 and 17p11.2 were found in 28% and 32% of cases, respectively. In an attempt to identify the genes involved in these amplicons, we used three nonoverlapping BAC clones contained within each amplicon as probes for FISH analysis, leading to a more detailed characterization and quantification of the 6p and 17p amplicons.

Osteosarcoma is the most common malignant bone tumor in children. After initial diagnosis is made with a biopsy, treatment consists of preoperative chemotherapy followed by definitive surgery and postoperative chemotherapy. The degree of tumor necrosis in response to preoperative chemotherapy is a reliable prognostic factor and is used to guide the choice of postoperative chemotherapy. Patients with tumors, which reveal z90% necrosis (good responders), have a much better prognosis than those with <90% necrosis (poor responders). Despite previous attempts to improve the outcome of poor responders by modifying the postoperative chemotherapy, their prognosis remains poor. Therefore, there is a need to predict at the time of diagnosis patients' response to preoperative chemotherapy. This will provide the basis for developing potentially effective therapy that can be given at the outset for those who are likely to have a poor response. Here, we report the analysis of 34 pediatric osteosarcoma samples by expression profiling. Using parametric two-sample t test, we identified 45 genes that discriminate between good and poor responders (P < 0.005) in 20 definitive surgery samples. A support vector machine classifier was built using these predictor genes and was tested for its ability to classify initial biopsy samples. Five of six initial biopsy samples that had corresponding definitive surgery samples in the training set were classified correctly (83%; confidence interval, 36%, 100%). When this classifier was used to predict eight independent initial biopsy samples, there was 100% accuracy (confidence interval, 63%, 100%). Many of the predictor genes are implicated in bone development, drug resistance, and tumorigenesis. (Cancer Res 2005; 65(18): 8142-50)