Microarrays in Molecular Profiling of Ewing Sarcoma Family of Tumors and CDKN2A Aberrations

Background: The Ewing sarcoma family of tumors (ESFT) are rare but highly malignant neoplasms that occur mainly in bone or but also in soft tissue. ESFT affects patients typically in their second decade of life, whereby children and adolescents bear the heaviest incidence burden. Despite recent advances in the clinical management of ESFT patients, their prognosis and survival are still disappointingly poor, especially in cases with metastasis. No targeted therapy for ESFT patients is currently available. Moreover, based merely on current clinical and biological characteristics, accurate classification of ESFT patients often fails at the time of diagnosis. Therefore, there is a constant need for novel molecular biomarkers to be applied in tandem with conventional parameters to further intensify ESFT risk-stratification and treatment selection, and ultimately to develop novel targeted therapies. In this context, a greater understanding of the genetics and immune characteristics of ESFT is needed. Aims: This study sought to open novel insights into gene copy number changes and gene expression in ESFT and, further, to enlighten the role of inflammation in ESFT. For this purpose, microarrays were used to provide gene-level information on a genomewide scale. In addition, this study focused on screening of 9p21.3 deletion sizes and frequencies in ESFT and, in another pediatric cancer, acute lymphocytic leukemia (ALL), in order to define more exact criteria for highrisk patient selection and to provide data for developing a more reliable diagnostic method to detect CDKN2A deletions. Results: In study I, 20 novel ESFT-associated suppressor genes and oncogenes were pinpointed using combined array CGH and expression analysis. In addition, interesting chromosomal rearrangements were identified: (1) Duplication of derivative chromosome der(22)(11;22) was detected in three ESFT patients. This duplication included the EWSR1-FLI1 fusion gene leading to increase in its copy number; (2) Cryptic amplifications on chromosomes 20 and 22 were detected, suggesting a novel translocation between chromosomes 20 and 22, which most probably produces a fusion between EWSR1 and NFATC2. In study II, bioinformatic analysis of ESFT expression profiles showed that inflammatory gene activation is detectable in ESFT patient samples and that the activation is characterized by macrophage gene expression. Most interestingly, ESFT patient samples were shown to express certain inflammatory genes that were prognostically significant. High local expression of C5 and JAK1 at the tumor site was shown to associate with favorable clinical outcome, whereas high local expression of IL8 was shown to be detrimental. Studies III and IV showed that the smallest overlapping region of deletion in 9p21.3 includes CDKN2A in all cases and that the length of this region is 12.2 kb in both Ewing sarcoma and ALL. Furthermore, our results showed that the most widely used commercial CDKN2A FISH probe creates false negative results in the narrowest microdeletion cases (<190 kb). Therefore, more accurate methods should be developed for the detection of deletions in the CDKN2A locus. Conclusions: This study provides novel insights into the genetic changes involved in the biology of ESFT, in the interaction between ESFT cells and immune system, and in the inactivation of CDKN2A. Novel ESFT biomarker genes identified in this study serve as a useful resource for future studies and in developing novel therapeutic strategies to improve the survival of patients with ESFT.

A New Rare-Gas Compound: HXeOXeH

Rare-gas chemistry is of growing interest, and the recent advances include the "insertion" of a Xe atom into OH and water in the rare-gas hydrides HXeO and HXeOH. The insertion of Xe atoms into the H-C bonds of hydrocarbons was also demonstrated for HXeCC, HXeCCH and HXeCCXeH, the last of which was the first rare-gas hydride containing two rare-gas atoms. We describe the preparation and characterization of a new rare-gas compound, HXeOXeH. HXeOXeH was prepared in solid xenon by photolysis of a suitable precursor, for example water, and subsequent mobilization of the photoproducts. The experimental identification was carried out by FTIR spectroscopy, isotopic substitution and by use of various precursors. The photolytical and thermal stability of the new rare-gas hydride was also studied. The experimental work was supported by extensive quantum chemical calculations provided by our co-workers. HXeOXeH forms in a cryogenic xenon matrix from neutral O and H atoms in a two-step diffusion-controlled process involving HXeO as an intermediate [reactions (1) and (2)]. This formation mechanism is unique in that a rare-gas hydride is formed from another rare-gas hydride. H + Xe + O → HXeO (1) HXeO + Xe + H → HXeOXeH (2) Similarly to other rare-gas hydrides, HXeOXeH has a strongly IR-active H-Xe stretching vibration, allowing its spectral detection at 1379.3 cm-1. HXeOXeH is a very high-energy metastable species, yet thermally more stable than many other rare-gas hydrides. The calculated bending barrier of 0.57 eV, is not enough to explain the observed stability, and HXeOXeH might be affected by additional stabilization from the solid xenon environment. Chemical bonding between xenon and environmentally abundant species like water is of particular importance due to the “missing-xenon” problem. The relatively high thermal stability of HXeOXeH compared to other oxygen containing rare-gas compounds is relevant in this respect. Our work also raises the possibility of polymeric (–Xe–O)n networks, similarly to the computationally studied (XeCC)n polymers.

Bayesian Inference for Retrospective Population Genetics Models Using Markov Chain Monte Carlo Methods

Genetics, the science of heredity and variation in living organisms, has a central role in medicine, in breeding crops and livestock, and in studying fundamental topics of biological sciences such as evolution and cell functioning. Currently the field of genetics is under a rapid development because of the recent advances in technologies by which molecular data can be obtained from living organisms. In order that most information from such data can be extracted, the analyses need to be carried out using statistical models that are tailored to take account of the particular genetic processes. In this thesis we formulate and analyze Bayesian models for genetic marker data of contemporary individuals. The major focus is on the modeling of the unobserved recent ancestry of the sampled individuals (say, for tens of generations or so), which is carried out by using explicit probabilistic reconstructions of the pedigree structures accompanied by the gene flows at the marker loci. For such a recent history, the recombination process is the major genetic force that shapes the genomes of the individuals, and it is included in the model by assuming that the recombination fractions between the adjacent markers are known. The posterior distribution of the unobserved history of the individuals is studied conditionally on the observed marker data by using a Markov chain Monte Carlo algorithm (MCMC). The example analyses consider estimation of the population structure, relatedness structure (both at the level of whole genomes as well as at each marker separately), and haplotype configurations. For situations where the pedigree structure is partially known, an algorithm to create an initial state for the MCMC algorithm is given. Furthermore, the thesis includes an extension of the model for the recent genetic history to situations where also a quantitative phenotype has been measured from the contemporary individuals. In that case the goal is to identify positions on the genome that affect the observed phenotypic values. This task is carried out within the Bayesian framework, where the number and the relative effects of the quantitative trait loci are treated as random variables whose posterior distribution is studied conditionally on the observed genetic and phenotypic data. In addition, the thesis contains an extension of a widely-used haplotyping method, the PHASE algorithm, to settings where genetic material from several individuals has been pooled together, and the allele frequencies of each pool are determined in a single genotyping.

Storage and retrieval of individual genomes

A repetitive sequence collection is one where portions of a base sequence of length n are repeated many times with small variations, forming a collection of total length N. Examples of such collections are version control data and genome sequences of individuals, where the differences can be expressed by lists of basic edit operations. Flexible and efficient data analysis on a such typically huge collection is plausible using suffix trees. However, suffix tree occupies O(N log N) bits, which very soon inhibits in-memory analyses. Recent advances in full-text self-indexing reduce the space of suffix tree to O(N log σ) bits, where σ is the alphabet size. In practice, the space reduction is more than 10-fold, for example on suffix tree of Human Genome. However, this reduction factor remains constant when more sequences are added to the collection. We develop a new family of self-indexes suited for the repetitive sequence collection setting. Their expected space requirement depends only on the length n of the base sequence and the number s of variations in its repeated copies. That is, the space reduction factor is no longer constant, but depends on N / n. We believe the structures developed in this work will provide a fundamental basis for storage and retrieval of individual genomes as they become available due to rapid progress in the sequencing technologies.