Microarrays in molecular profiling of cancer - focus on head and neck squamous cell carcinoma

Microarrays have a wide range of applications in the biomedical field. From the beginning, arrays have mostly been utilized in cancer research, including classification of tumors into different subgroups and identification of clinical associations. In the microarray format, a collection of small features, such as different oligonucleotides, is attached to a solid support. The advantage of microarray technology is the ability to simultaneously measure changes in the levels of multiple biomolecules. Because many diseases, including cancer, are complex, involving an interplay between various genes and environmental factors, the detection of only a single marker molecule is usually insufficient for determining disease status. Thus, a technique that simultaneously collects information on multiple molecules allows better insights into a complex disease. Since microarrays can be custom-manufactured or obtained from a number of commercial providers, understanding data quality and comparability between different platforms is important to enable the use of the technology to areas beyond basic research. When standardized, integrated array data could ultimately help to offer a complete profile of the disease, illuminating mechanisms and genes behind disorders as well as facilitating disease diagnostics. In the first part of this work, we aimed to elucidate the comparability of gene expression measurements from different oligonucleotide and cDNA microarray platforms. We compared three different gene expression microarrays; one was a commercial oligonucleotide microarray and the others commercial and custom-made cDNA microarrays. The filtered gene expression data from the commercial platforms correlated better across experiments (r=0.78-0.86) than the expression data between the custom-made and either of the two commercial platforms (r=0.62-0.76). Although the results from different platforms correlated reasonably well, combining and comparing the measurements were not straightforward. The clone errors on the custom-made array and annotation and technical differences between the platforms introduced variability in the data. In conclusion, the different gene expression microarray platforms provided results sufficiently concordant for the research setting, but the variability represents a challenge for developing diagnostic applications for the microarrays. In the second part of the work, we performed an integrated high-resolution microarray analysis of gene copy number and expression in 38 laryngeal and oral tongue squamous cell carcinoma cell lines and primary tumors. Our aim was to pinpoint genes for which expression was impacted by changes in copy number. The data revealed that especially amplifications had a clear impact on gene expression. Across the genome, 14-32% of genes in the highly amplified regions (copy number ratio >2.5) had associated overexpression. The impact of decreased copy number on gene underexpression was less clear. Using statistical analysis across the samples, we systematically identified hundreds of genes for which an increased copy number was associated with increased expression. For example, our data implied that FADD and PPFIA1 were frequently overexpressed at the 11q13 amplicon in HNSCC. The 11q13 amplicon, including known oncogenes such as CCND1 and CTTN, is well-characterized in different type of cancers, but the roles of FADD and PPFIA1 remain obscure. Taken together, the integrated microarray analysis revealed a number of known as well as novel target genes in altered regions in HNSCC. The identified genes provide a basis for functional validation and may eventually lead to the identification of novel candidates for targeted therapy in HNSCC.

Array Comparative Genomic Hybridization in Sarcomas

Over the past years, much research on sarcomas based on low-resolution cytogenetic and molecular cytogenetic methods has been published, leading to the identification of genetic abnormalities partially underlying the tumourigenesis. Continued progress in the identification of genetic events such as copy number aberrations relies upon adapting the rapidly evolving high-resolution microarray technology, which will eventually provide novel insights into sarcoma biology, and targets for both diagnostics and drug development. The aim of this Thesis was to characterize DNA copy number changes that are involved in the pathogenesis of soft tissue leiomyosarcoma (LMS), dermatofibrosarcoma protuberans (DFSP), osteosarcoma (OS), malignant fibrous histiocytoma (MFH), and uterine leiomyosarcoma (ULMS) by applying fine resolution array comparative genomic hybridization (aCGH) technology. Both low- and high-grade LMS tumours showed distinct copy number patterns, in addition to sharing two minimal common regions of gains and losses. Small aberrations were detected by aCGH, which were beyond the resolution of chromosomal comparative genomic hybridization (cCGH). DFSP tumours analysed by aCGH showed gains in 17q, 22q, and 21 additional gained regions, but only one region (22q) with copy number loss. Recurrent amplicons identified in OS by aCGH were 12q11-q15, 8q, 6p12-p21, and 17p. Amplicons 12q and 17p were further characterized in detail. The amplicon at 17p was characterized by aCGH in low- and high-grade LMS, OS, and MFH. In all but one case this amplicon, with minimal common regions of gains at 17p11-p12, started with the distal loss of 17p13-pter. OS and high-grade LMS were grouped together as they showed a complex pattern of copy number gains and amplifications at 17p, whereas MFH and low-grade LMS showed a continuous pattern of copy number gains and amplification at 17p. In addition to the commonly gained and lost regions identified in ULMS by aCGH, various biological processes affected by these copy number changes were also indicated by pathway analysis. The three novel findings obtained in this work were: characterization of amplicon 17p in low- and high-grade LMS and MFH, profiles of DNA copy number changes in LMS, and detection of various pathways affected by copy number changes in ULMS. These studies have not been undertaken previously by aCGH technology, thus this Thesis adds new information regarding DNA copy number changes in sarcomas. In conclusion, the aCGH technique used in this Thesis has provided new insights into the genetics of sarcomas by detecting the precise regions affected by copy number changes and some potential candidate target genes within those regions, which had not been uncovered by previously applied low resolution techniques.