Chromosomal imbalances are of major significance in cancer initiation and progression. Gains of chromosome 8 in human cancer have been described by a number of authors and are amongst the most common cytogenetic events that occur. However in childhood solid tumours, few studies have examined copy number changes of specific genes on chromosome 8. Somatic genomic events have been for many years an important component of diagnosis, prognosis and therapy selection in paediatric oncology. Different techniques have been designed to identify gene dosage or copy number changes in a quantitative fashion. In this project we used Multiplex Ligation dependent Probe Amplification (MLPA), array Comparative Genomic Hybridization (aCGH) and quantitative PCR (qPCR). MLPA was used as a screening tool to assess chromosome 8 copy number changes in a cohort of 31 paediatric solid tumours - osteosarcoma n=5, Ewing sarcoma n=8, rhabdomyosarcoma n=8, and neuroblastoma n=10, and 6 breast cell lines (5 breast cancer and a non-tumorigenic cell line MCF-10A), some of which were expected to show defined copy number changes on chromosome 8. The SALSA MLPA KIT P014-A1 Chromosome 8 kit has 32 probes mapping to 30 chromosome 8 genes, and 9 reference probes mapping to other chromosomes. Using MLPA, osteosarcomas and neuroblastoma showed the greatest number of copy number changes at chromosome 8 loci with copy number gain/loss at 21/30 loci and 29/30 loci, respectively. Ewing sarcoma and rhabdomyosarcomas showed fewer chromosome 8 copy number changes at 9/30 loci and 11/30 loci, respectively. In the breast cell lines, MLPA results confirmed as expected copy number loss at 8p loci in 5/6 breast cell lines, and copy number gains at MYC in 5/6 cell lines, followed by TPD52 in 4/6 cell lines. As an additional finding, we obtained some discrepant results within the 4 MLPA experiments conducted for both cell lines and the solid tumour cohort. MLPA results could not be consistently reproduced for EIF3E and EXT1. To obtain a broader view of copy number changes in this tumour cohort, we analysed genomic DNA samples using array Comparative Genomic Hybridization (aCGH). We used a customized 60-mer-oligonucleotide high density Agilent eArray SurePrint G3 2x400K with 52,639 probes along chromosome 8, 39,654 probes in 95 genes known to be important in cancer, and evenly spaced whole-genome coverage (253,502 probes) for the remainder of the human genome. aCGH chromosome 8 results showed that osteosarcoma samples had the most frequent copy number changes, between 9 and 21 per sample, congruent with the hallmarks of osteosarcoma that include an unusually high frequency of genome rearrangements. In Ewing sarcoma, a gain of whole chromosome 8 was detected in 37% (3/8) of samples, consistent with this being one of the most prominent features of this solid tumour. Rhabdomyosarcomas and neuroblastoma showed infrequent gain or loss at chromosome 8 loci. From the list of cancer genes with lower oligonucleotide probe spacing, 5/5 osteosarcoma samples showed copy number loss at RB1, TP53 and APC, and 8/10 neuroblastoma samples showed copy number gain at MYCN, findings that are in agreement with the literature. From results generated from genome-wide probes, a chromosomal region located at chromosome 22 band q11.22 showed copy number gain in all 4 solid tumour types, and in 21/31 samples analysed. This region contained the PRAME gene or preferentially expressed antigen in melanoma, which has been proposed as a promising target for immunotherapy in some hematologic malignancies, but has not specifically been studied in osteosarcoma, rhabdomyosarcoma or Ewing sarcoma. In addition, the aCGH data presented in this thesis revealed some genes that had not previously been linked in literature with paediatric solid tumours, including KCNK9, that showed copy number gain in all osteosarcoma samples, and RECQL4 that showed copy number gain in most rhabdomyosarcomas. Further studies in these genes may prove to be beneficial for the understanding of tumourigenesis and progress in paediatric solid tumours. Comparison of MLPA versus aCGH copy number results was made based on the results for the 30 genes included in the chromosome 8 MLPA kit. Clear discrepancies in copy number measured by MLPA and aCGH were obtained. To quantify differences and propose genes to be used for copy number validation using a third technique, MLPA and aCGH results were compared. A list of genes was generated, from the ones that presented results with the greatest degree of disagreement to genes with least disagreement. From this list, 6 genes were chosen to be validated with a third technique namely qPCR, including MYC that was selected as a control because it presented the least disagreement between MLPA and aCGH results. Due to the small amount of DNA remaining for many samples after having applied both MLPA and aCGH techniques, 7 tumour samples (one osteosarcoma, 2 Ewing sarcomas, 2 rhabdomyosarcomas, and 2 neuroblastomas) and 2 cell lines were selected to perform qPCR analyses. Copy number results obtained using MLPA versus qPCR showed agreement percentages ranging from 11.1-67%, and 78% of agreement for MYC. In contrast, qPCR versus aCGH showed 100% agreement for all but one gene, EXT1, which showed 89% agreement (in 8/9 samples). These results demonstrate that aCGH copy number results could be more frequently validated by qPCR than could MLPA results. In summary, copy number results produced by aCGH were more consistently in agreement with those produced by qPCR, making qPCR a more reliable technique for diagnostic purposes than MLPA. To the best of our knowledge, this is the first time that such a technical comparison has been performed for any MLPA kit targeting human chromosome 8
