First published online: November 1, 2010 / 名古屋大学博士学位論文 学位の種類 : 博士(医学)(課程) 学位授与年月日:平成23年3月25日 久島周氏の博士論文として提出された

As Mucopolissacaridoses (MPS) são um grupo de doenças de armazenamento lisossômico causadas por deficiência de enzimas que catalisam a degradação gradual das glicosaminoglicanas (GAGs). GAGs (anteriormente chamadas de mucopolissacarídeos) são produtos de degradação das proteoglicanas que existem na matriz extracelular e tem efeito proteolítico. A classificação das MPS é baseada na deficiência enzimática específica. A MPS IVA é causada por mutações no gene que codifica a enzima GALNS (Nacetilgalactosamina-6-sulfatase), a qual desempenha um papel crucial na degradação do sulfato de queratano e condroitina-6-sulfatase. As mutações na enzima se resumem em três categorias: interrupção do sítio ativo, alterações no núcleo hidrofóbico e exposição da superfície, onde mutações missense na estrutura podem afetar gravemente a atividade da proteína GALNS, alterando seu núcleo hidrofóbico ou modificando seu enovelamento (folding). Com a falta de tratamentos efetivos, sendo em sua maioria paliativos, e tendo como base a estrutura já resolvida da GLANS selvagem, este trabalho teve como objetivo modelar 3 variantes da enzima GALNs, sendo uma mutação no sítio ativo, uma no núcleo hidrofóbico e uma na superfície. Foi usado o software MODELLER 9.12 para a modelagem comparativa, os softwares Prochek, PROSA II, ERRATv2, Verify3d, ProQ para a avaliação dos modelos, o software NAND 2.10, para simulação de dinâmica molecular e o software Chimera 1.10.1 para cálculo de superfícies eletrostáticas e hidrofobicidade da superfície. Os modelos apresentaram bons resultados segundo os softwares de avaliação e análise visual. Apresentaram poucas diferenças estruturais em relação à estrutura da GALNS selvagem, demonstraram estabilidade em simulação de dinâmica molecular. Entretanto, algumas diferenças foram observadas com relação à distribuição de cargas e hidrofobicidade no sítio ativo do modelo da variante com mutação no sítio ativo. Pôde ser concluído que as 3 mutações analisadas não causaram alterações estruturais significativas, não interferiram na estabilidade estrutural em simulação de dinâmica molecular, entretanto, foi demonstrado que mutações na região do sítio ativo podem interferir na função da enzima. / The Mucopolysaccharidoses (MPS) are a group of lysosomal storage diseases caused by deficiencies in enzymes that catalyze the gradual glycosaminoglycans (GAGs) degradation. GAGs (formerly called mucopolysaccharides) are products of proteoglycan degradation that exist in the extracellular matrix and have proteolytic effect. The classification of MPS is based on the specific enzyme deficiency. MPS IVA is caused by mutations in the gene that encodes the GALNS enzyme (Nacetilgalactosamina-6-sulfatase), which plays a crucial role in the degradation of keratan sulfate and chondroitin-6-sulfatase. Mutations in the enzyme can be summarized in three categories: interruption of the active site, changes in the hydrophobic core and display surface, where missense mutations in the structure can seriously affect the activity of GALNS protein, changing its hydrophobic core or modifying its folding. With the lack of effective treatments, in its most palliative, and based on the wild GALNS structure already determined, this study aimed to model 3 variants of GALNS enzyme, a mutation in the active site, one in the hydrophobic core and a on the surface. 9.12 MODELLER was used for comparative modeling software, the software Prochek, Prose II, ERRATv2, Verify3d, ProQ models for the evaluation of the NAND 2.10 software, for molecular dynamics simulation and software Chimera 1.10.1 calculates electrostatic and hydrophobic surface. The models showed good results according to the evaluation software and visual analysis. Presented few structural differences from the wild GALNS structure and showed stability in molecular dynamics simulation. However, some differences were observed with respect to the charge distribution and hydrophobicity in the active site of the variants of the model with a mutation in the active site. It might be concluded that the three mutations analyzed did not cause significant structural changes and did not affect the structural stability in molecular dynamics simulation, however, it has been shown that mutations in the active site region may interfere with the function of this enzyme.

As Mucopolissacaridoses (MPS) são um grupo de doenças de armazenamento lisossômico causadas por deficiência de enzimas que catalisam a degradação gradual das glicosaminoglicanas (GAGs). GAGs (anteriormente chamadas de mucopolissacarídeos) são produtos de degradação das proteoglicanas que existem na matriz extracelular e tem efeito proteolítico. A classificação das MPS é baseada na deficiência enzimática específica. A MPS IVA é causada por mutações no gene que codifica a enzima GALNS (Nacetilgalactosamina-6-sulfatase), a qual desempenha um papel crucial na degradação do sulfato de queratano e condroitina-6-sulfatase. As mutações na enzima se resumem em três categorias: interrupção do sítio ativo, alterações no núcleo hidrofóbico e exposição da superfície, onde mutações missense na estrutura podem afetar gravemente a atividade da proteína GALNS, alterando seu núcleo hidrofóbico ou modificando seu enovelamento (folding). Com a falta de tratamentos efetivos, sendo em sua maioria paliativos, e tendo como base a estrutura já resolvida da GLANS selvagem, este trabalho teve como objetivo modelar 3 variantes da enzima GALNs, sendo uma mutação no sítio ativo, uma no núcleo hidrofóbico e uma na superfície. Foi usado o software MODELLER 9.12 para a modelagem comparativa, os softwares Prochek, PROSA II, ERRATv2, Verify3d, ProQ para a avaliação dos modelos, o software NAND 2.10, para simulação de dinâmica molecular e o software Chimera 1.10.1 para cálculo de superfícies eletrostáticas e hidrofobicidade da superfície. Os modelos apresentaram bons resultados segundo os softwares de avaliação e análise visual. Apresentaram poucas diferenças estruturais em relação à estrutura da GALNS selvagem, demonstraram estabilidade em simulação de dinâmica molecular. Entretanto, algumas diferenças foram observadas com relação à distribuição de cargas e hidrofobicidade no sítio ativo do modelo da variante com mutação no sítio ativo. Pôde ser concluído que as 3 mutações analisadas não causaram alterações estruturais significativas, não interferiram na estabilidade estrutural em simulação de dinâmica molecular, entretanto, foi demonstrado que mutações na região do sítio ativo podem interferir na função da enzima. / The Mucopolysaccharidoses (MPS) are a group of lysosomal storage diseases caused by deficiencies in enzymes that catalyze the gradual glycosaminoglycans (GAGs) degradation. GAGs (formerly called mucopolysaccharides) are products of proteoglycan degradation that exist in the extracellular matrix and have proteolytic effect. The classification of MPS is based on the specific enzyme deficiency. MPS IVA is caused by mutations in the gene that encodes the GALNS enzyme (Nacetilgalactosamina-6-sulfatase), which plays a crucial role in the degradation of keratan sulfate and chondroitin-6-sulfatase. Mutations in the enzyme can be summarized in three categories: interruption of the active site, changes in the hydrophobic core and display surface, where missense mutations in the structure can seriously affect the activity of GALNS protein, changing its hydrophobic core or modifying its folding. With the lack of effective treatments, in its most palliative, and based on the wild GALNS structure already determined, this study aimed to model 3 variants of GALNS enzyme, a mutation in the active site, one in the hydrophobic core and a on the surface. 9.12 MODELLER was used for comparative modeling software, the software Prochek, Prose II, ERRATv2, Verify3d, ProQ models for the evaluation of the NAND 2.10 software, for molecular dynamics simulation and software Chimera 1.10.1 calculates electrostatic and hydrophobic surface. The models showed good results according to the evaluation software and visual analysis. Presented few structural differences from the wild GALNS structure and showed stability in molecular dynamics simulation. However, some differences were observed with respect to the charge distribution and hydrophobicity in the active site of the variants of the model with a mutation in the active site. It might be concluded that the three mutations analyzed did not cause significant structural changes and did not affect the structural stability in molecular dynamics simulation, however, it has been shown that mutations in the active site region may interfere with the function of this enzyme.

Missense mutations account for more than 50% of the mutations known to be involved in human inherited diseases. Missense classification is a challenging task that involves sequencing of the genome, identifying the variations, and assessing their deleteriousness. This is a very laborious, time and cost intensive task to be carried out in the laboratory. Advancements in bioinformatics have led to several large-scale next-generation genome sequencing projects, and subsequently the identification of genome variations. Several studies have combined this data with information on established deleterious and neutral variants to develop machine learning based classifiers. There are significant issues with the missense classifiers due to which missense classification is still an open area of research. These issues can be classified under two broad categories: (a) Dataset overlap issue - where the performance estimates reported by the state-of-the-art classifiers are overly optimistic as they have often been evaluated on datasets that have significant overlaps with their training datasets. Also, there is no comparative analysis of these tools using a common benchmark dataset that contains no overlap with the training datasets, therefore making it impossible to identify the best classifier among them. Also, such a common benchmark dataset is not available. (b) Inadequate capture of vital biological information of the protein and mutations - such as conservation of long-range amino acid dependencies, changes in certain physico-chemical properties of the wild-type and mutant amino acids, due to the mutation. It is also not clear how to extract and use this information. Also, some classifiers use structural information that is not available for all proteins. In this study, we compiled a new dataset, containing around 2 - 15% overlap with the popularly used training datasets, with 18,036 mutations in 5,642 proteins. We reviewed and evaluated 15 state-of-the-art missense classifiers - SIFT, PANTHER, PROVEAN, PhD-SNP, Mutation Assessor, FATHMM, SNPs&GO, SNPs&GO3D, nsSNPAnalyzer, PolyPhen-2, SNAP, MutPred, PON-P2, CONDEL and MetaSNP, using the six metrics - accuracy, sensitivity, specificity, precision, NPV and MCC. When evaluated on our dataset, we observe huge performance drops from what has been claimed. Average drop in the performance for these 13 classifiers are around 15% in accuracy, 17% in sensitivity, 14% in specificity, 7% in NPV, 24% in precision and 30% in MCC. With this we show that the performance of these tools is not consistent on different datasets, and thus not reliable for practical use in a clinical setting. As we observed that the performance of the existing classifiers is poor in general, we tried to develop a new classifier that is robust and performs consistently across datasets, and better than the state-of-the-art classifiers. We developed a novel method of capturing long-range amino acid dependency conservation by boosting the conservation frequencies of substrings of amino acids of various lengths around the mutation position using AdaBoost learning algorithm. This score alone performed equivalently to the sequence conservation based tools in classifying missense mutations. Popularly used sequence conservation properties was combined with this boosted long-range dependency conservation scores using AdaBoost algorithm. This reduced the class bias, and improved the overall accuracy of the classifier. We trained a third classifier by incorporating changes in 21 important physico-chemical properties, due to the mutation. In this case, we observed that the overall performance further improved and the class bias further reduced. The performance of our final classifier is comparable with the state-of-the-art classifiers. We did not find any significant improvement, but the class-specific accuracies and precisions are marginally better by around 1-2% than those of the existing classifiers. In order to understand our classifier better, we dissected our benchmark dataset into: (a) seen and unseen proteins, and (b) pure and mixed proteins, and analysed the performance in detail. Finally we concluded that our classifier performs consistently across each of these categories of seen, unseen, pure and mixed protein.

Indiana University-Purdue University Indianapolis (IUPUI) / Thousands of missense mutations have been found to be associated with human diseases, ~60% of which have been predicted to affect protein stability and/or protein-protein interactions (PPIs). Current proteomic methods for studying the effects of mutations on the cell focus on measures of protein abundance or post-translational modifications (PTMs), which cannot directly be used for PPI analysis. High-throughput methodology to evaluate how mutations in a single protein affect PPI networks would help streamline the characterization of global effects caused by mutant proteins and aid in the prediction of phenotypic outcomes resulting from genomic mutations. Temperature sensitive Mutant Proteome Profiling (TeMPP) is a novel application of a mass spectrometry (MS) based thermal proteome profiling (TPP) approach that measures changes in missense mutant containing proteomes without the requirement for large amounts of starting material, specific antibodies against proteins of interest, and/or genetic manipulation of the biological system. This study measures the impact of temperature sensitivity-inducing missense mutations of proteins in the ubiquitin proteasome system and the transcription termination machinery on the thermal stability of the proteome at large. Results reveal distinct mechanistic details that were not obtained using only steady-state transcriptome and proteome analyses. Furthermore, my data suggests that TeMPP is highly specific to proteins functionally related to the mutated protein of interest and capable of differentiating effects between two proteins in the same complex. Overall, TeMPP provides unique mechanistic insights into missense mutation dysfunction and connection of genotype to phenotype in a rapid, non-biased fashion. Use of this method along with other complementary -omics approaches will help to characterize how missense mutations affect cellular protein homeostasis and thus enable deeper insight into disease phenotypes. / 2022-08-10

No description available.

Androgens are critical for the development and maintenance of adult male characteristics such as muscle mass and sexual function. Consequently, the established decline with age of serum testosterone (T) in males has major health implications. While the androgen receptor (AR) is the major mediator of genomic androgen action and is required for the development of the male phenotype, reproductive organs and the maintenance of male secondary sexual characteristics, it is the entrance of androgens into the cell that mediates the activation of the AR and the subsequent modulation of expression of androgen regulated genes. Testosterone, biologically the most important androgen in male serum, circulates either free, loosely bound to albumin or tightly bound to sex hormone binding globulin (SHBG). Each of these forms of serum T have different abilities to enter cells, and which proportion of serum T is capable of entering cells and initiating the androgen signalling cascade, thereby leading to the activation of the AR has not been precisely defined. The AR amino terminal domain (NTD) is responsible for the majority of the ability of the AR to activate genes but the relative roles of the two activation functions in the AR NTD (activation functions 1 and 5; AF1 and 5) have not been precisely defined while the role of the AF2 surface which forms in the ligand binding domain upon agonist binding is responsible for interactions with key coregulators and also with the NTD in the amino-carboxyl (N/C) interaction. Our laboratory has recently identified a region within AF5 between amino acids 500-535 to which somatic mutations in castrate resistant prostate tumour samples collocate. Due to the lack of functional information on the AF5 region and the NTD in general, the function of this region and the functional consequences of the mutations remain to be defined. The objectives of this thesis were to develop a specific mammalian cell based bioassay capable of reliable measuring T in serum and to determine the ability of this bioassay to measure a physiologically relevant fraction of T in serum. Additionally, this thesis aimed to determine the relative contributions and roles of the activation functions of the AR to overall AR transcriptional activity along with the functional consequences for AR signalling of prostate cancer mutations which have previously been identified in the AF5 region of the AR NTD. The mammalian-cell based bioassay developed in this thesis is capable of sensitively and reliably measuring serum T. However, evaluation of this bioassay utilising approximately 1000 serum samples from the Florey Adelaide Male Aging Study reveals that this bioassay measures a fraction of T in serum that most closely relates to serum T. Furthermore, this measure does not correlate more strongly with grip strength, sexual function or waist circumference than the existing immunoassay-based measures of serum T, highlighting the limitations of utilising a static mammalian cell-based androgen bioassay to measure physiological levels of serum T in males. The investigation of the roles of the activation functions in the AR in this thesis have revealed that while the AF1 domain is responsible for the majority of the transactivation activity of the AR, AF5 and AF2 govern the sensitivity and cellular response of the AR to androgens by providing protein and interdomain interaction interfaces. Furthermore, the evidence in this thesis demonstrates that the AR requires interdomain communication for sensitive AR signalling. Finally, the findings in this thesis demonstrate that the AF5 surface is required for the N/C interaction and coregulator interactions while advanced prostate cancer mutations identified within this region confer increased transactivation activity of the AR in the presence of high cellular levels of coregulators. Collectively, the findings in this thesis provide several novel insights into the mechanism of action of serum androgens and challenges several long held assumptions of androgenic action in males. These findings also delineate a mechanism of treatment failure in advanced prostate cancer, provide a novel model for the events leading to sensitive AR transactivation and contribute to the understanding of physiologically relevant levels of serum T. / Thesis (Ph.D.) -- University of Adelaide, School of Medicine, 2008

The peroxisome is a subcellular organelle that carries out a diverse range of metabolic functions, including the b-oxidation of very long chain fatty acids, the breakdown of peroxide and the a-oxidation of fatty acids. Disruption of peroxisome metabolic functions leads to severe disease in humans. These diseases can be broadly grouped into two categories: those in which a single enzyme is defective, and those known as the peroxisome biogenesis disorders (PBDs), which result from a generalised failure to import peroxisomal matrix proteins (and consequently result in disruption of multiple metabolic pathways). The PBDs result from mutations in PEX genes, which encode protein products called peroxins, required for the normal biogenesis of the peroxisome. PEX1 encodes an AAA ATPase that is essential for peroxisome biogenesis, and mutations in PEX1 are the most common cause of PBDs worldwide. This study focused on the identification of mutations in PEX1 in an Australasian cohort of PBD patients, and the impact of these mutations on PEX1 function. As a result of the studies presented in this thesis, twelve mutations in PEX1 were identified in the Australasian cohort of patients. The identified mutations can be broadly grouped into three categories: missense mutations, mutations directly introducing a premature termination codon (PTC) and mutations that interrupt the reading frame of PEX1. The missense mutations that were identified were R798G, G843D, I989T and R998Q; all of these mutations affect amino acid residues located in the AAA domains of the PEX1 protein. Two mutations that directly introduce PTCs into the PEX1 transcript (R790X and R998X), and four frameshift mutations (A302fs, I370fs, I700fs and S797fs) were identified. There was also one mutation found in an intronic region (IVS22-19A>G) that is presumed to affect splicing of the PEX1 mRNA. Three of these mutations, G843D, I700fs and G973fs, were found at high frequency in this patient cohort. At the commencement of these studies, it was hypothesised that missense mutations would result in attenuation of PEX1 function, but mutations that introduced PTCs, either directly or indirectly, would have a deleterious effect on PEX1 function. Mutations introducing PTCs are thought to cause mRNA to be degraded by the nonsense-mediated decay of mRNA (NMD) pathway, and thus result in a decrease in PEX1 protein levels. The studies on the cellular impact of the identified PEX1 mutations were consistent with these hypotheses. Missense mutations were found to reduce peroxisomal protein import and PEX1 protein levels, but a residual level of function remained. PTC-generating mutations were found to have a major impact on PEX1 function, with PEX1 mRNA and protein levels being drastically reduced, and peroxisomal protein import capability abolished. Patients with two missense mutations showed the least impact on PEX1 function, patients with two PTC-generating mutations had a severe defect in PEX1 function, and patients carrying a combination of a missense mutation and a PTC-generating mutation showed levels of PEX1 function that were intermediate between these extremes. Thus, a correlation between PEX1 genotype and phenotype was defined for the Australasian cohort of patients investigated in these studies. For a number of patients, mutations in the coding sequence of one PEX1 allele could not be identified. Analysis of the 5' UTR of this gene was therefore pursued for potential novel mutations. The initial analyses demonstrated that the 5' end of PEX1 extended further than previously reported. Two co-segregating polymorphisms were also identified, termed –137 T>C and –53C>G. The -137T>C polymorphism resided in an upstream, in-frame ATG (termed ATG1), and the possibility that the additional sequence represented PEX1 coding sequence was examined. While both ATGs were found to be functional by virtue of in vitro and in vivo expression investigations, Western blot analysis of the PEX1 protein in patient and control cell extracts indicated that physiological translation of PEX1 was from the second ATG only. Using a luciferase reporter approach, the additional sequence was found to exhibit promoter activity. When examined alone the -137T>C polymorphism exerted a detrimental effect on PEX1 promoter activity, reducing activity to half that of wild-type levels, and the -53C>G polymorphism increased PEX1 promoter activity by 25%. When co-expressed (mimicking the physiological condition) these polymorphisms compensated for each other to bring PEX1 promoter activity to near wild-type levels. The PEX1 mutations identified in this study have been utilised by collaborators at the National Referral Laboratory for Lysosomal, Peroxisomal and Related Genetic Disorders (based at the Women's and Children's Hospital, Adelaide), in prenatal diagnosis of the PBDs. In addition, the identification of three common mutations in Australasian PBD patients has led to the implementation of screening for these mutations in newly referred patients, often enabling a precise diagnosis of a PBD to be made. Finally, the strong correlation between genotype and phenotype for the patient cohort investigated as part of these studies has generated a basis for the assessment of newly identified mutations in PEX1.

The Human Genome Project, initiated in 1990, creates an enormous amount of excitement in human genetics—a field of study that seeks answers to the understanding of human evolution, diseases and development, gene therapy, and preventive medicine. The first completion of a human genome in 2003 and the breakthroughs of sequencing technologies in the past few years deliver the promised benefits of genome studies, especially in the roles of genomic variability and human health. However, intensive resource requirements and the associated costs make it infeasible to experimentally verify the effect of every genetic variation. At this stage of genome studies, in silico predictions play an important role in identifying putative functional variants. The most common practice for genome variant evaluation is based on the evolutionary conservation at the mutation site. Nonetheless, sequence conservation is not the absolute predictor for deleteriousness since phylogenetic diversity of aligned sequences used to construct the prediction algorithm has substantial effects on the analysis. This dissertation aims at overcoming the weaknesses of the conservation-based assumption for predicting the variant effects. The dissertation describes three different integrative computational approaches to identify a subset of high-priority amino acid mutations, derived from human genome data. The methods investigate variant-function relationships in three aspects of genome studies—personal genomics, genomics of epilepsy disorders, and genomics of variable drug responses. For genetic variants found in genomes of healthy individuals, an eight-level variant classification scheme is implemented to rank variants that are important towards individualized health profiles. For candidate genetic variants of epilepsy disorders, a novel 3-dimensional structure-based assessment protocol for amino acid mutations is established to improve discrimination between neutral and causal variants at less conserved sites, and to facilitate variant prioritization for experimental validations. For genomic variants that may affect inter-individual variability in drug responses, an explicit structure-based predictor for structural disturbances is developed to efficiently evaluate unknown variants in pharmacogenes. Overall, the three integrative approaches provide an opportunity for examining the effects of genomic variants from multiple perspectives of genome studies. They also introduce an efficient way to catalog amino acid variants on a large scale genome data.

Abstract Breast cancer is the most common cancer among women, and inherited predisposition is one of the major recognized causes of increased breast cancer risk. Only about half of the hereditary cases are explained by mutations in the known susceptibility genes, including the DNA damage response genes BRCA1, BRCA2 and PALB2, leaving the majority still uncovered. Identification of the missing genetic predisposing factors is important for more effective diagnostics and counseling of the risk families, and also for better understanding of the etiology and cellular characteristics of breast cancer. The first aim of this study was to investigate the cancer associations of six rare germline copy number variant (CNV) deletions, which were previously identified in breast cancer patients by a genome-wide microarray approach. The second aim was to identify novel susceptibility alleles, both protein-truncating variants and missense mutations, by next-generation sequencing (NGS) of nearly 800 DNA damage response genes in 189 hereditary breast cancer patients. The cancer-associations of all selected candidate alleles (6 CNVs, 39 protein-truncating variants and 35 missense mutations) were studied by case-control approach using DNA samples from several hundred breast cancer patients and healthy controls. The prevalence of the studied CNVs did not significantly differ between the cases and controls, but when studying the associations with specific clinical parameters, deletion in the CYP2C19 gene showed enrichment in the breast cancer patients with hormonally triple-negative tumors (p=0.021). As CYP2C19 functions in estrogen metabolism, the results indicate that disturbance of hormonal balance due to enzyme defects may predispose specifically to the estrogen receptor-negative subtype of breast cancer. Two protein truncating-variants, TEX15 c.7253dupT and FANCD2 c.2715+1G>A showed significant breast cancer association in the Northern Finnish cohort (p=0.018 and p=0.036, respectively). Similarly, two of the studied missense variants, RECQL p.Ile156Met (p=0.043) and POLG p.Leu392Val (p=0.010), were enriched in the breast cancer cases. Thus, this study provided novel connections between increased breast cancer risk and inherited mutations in TEX15, FANCD2 and POLG genes, and further supported the recently established role of RECQL as a breast cancer susceptibility gene. / Tiivistelmä Rintasyöpä on naisten yleisin syöpä, ja perinnöllinen alttius on yksi merkittävimmistä sairastumisriskiin vaikuttavista tekijöistä. Tunnetuimpia alttiustekijöitä ovat mutaatiot BRCA1-, BRCA2- ja PALB2-DNA-vauriovastegeeneissä, mutta ne yhdessä muiden altistavien geenimutaatioiden kanssa selittävät kuitenkin vain noin puolet perinnöllisistä rintasyöpätapauksista. Uusien alttiusgeenien löytäminen mahdollistaa tehokkaamman diagnostiikan ja korkeassa syöpäriskissä olevien sukujen perinnöllisyysneuvonnan, sekä auttaa ymmärtämään syvemmin rintasyövän etiologiaa ja syntymekanismeja solutasolla. Tämän väitöskirjan ensimmäisenä päämääränä oli tutkia tarkemmin aiemmin genominlaajuisella mikrosirumenetelmällä rintasyöpäpotilailta tunnistettujen harvinaisten perinnöllisten DNA-kopiolukuvariaatioiden (CNV) yhteyttä rintasyöpäriskiin. Toisena tavoitteena oli tunnistaa uusia rintasyöpäalttiusalleeleja, sekä proteiinitrunkaatioita että missense-mutaatioita, hyödyntämällä uuden sukupolven sekvensointitekniikkaa, jonka avulla tutkittiin mutaatioita lähes 800 DNA-vauriovastegeenistä 189 pohjoissuomalaiselta rintasyöpäpotilaalta. Valittujen kandidaattialleelien (6 deleetion aiheuttavaa CNV:tä, 39 proteiinitrunkaatiota ja 35 missense-mutaatiota) yhteyttä rintasyöpään tutkittiin tapaus-verrokkimenetelmällä käyttäen DNA-näytteitä usealta sadalta rintasyöpäpotilaalta ja terveeltä kontrollihenkilöltä. Tutkittujen CNV:iden esiintyvyydessä ei ollut merkitseviä eroja potilaiden ja kontrollien välillä, mutta tarkasteltaessa yhteyttä potilaiden kasvaimista saatuihin kliinisiin parametreihin, deleetio CYP2C19-geenissä oli yleisempi hormonaalisesti kolmoisnegatiivisissa rintatuumoreissa kuin muissa tuumorityypeissä (p=0.021). Koska CYP2C19 on estrogeenimetaboliaan osallistuva entsyymi, sen viallinen toiminta voi mahdollisesti altistaa erityisesti estrogeenireseptorinegatiiviselle rintasyövälle. Kaksi tutkituista proteiinitrunkaatioista, TEX15 c.7253dupT ja FANCD2 c.2715+1G>A, olivat rikastuneet perinnöllisessä rintasyöpäpotilasaineistossa verrattuna kontrolleihin (p=0.018 ja p=0.036). Myös kaksi missense-alleelia, RECQL p.Ile156Met (p=0.043) ja POLG p.Leu392Val (p=0.010), olivat yleisempiä rintasyöpäpotilailla. Tulokset osoittivat uuden yhteyden kohonneen rintasyöpäriskin ja perinnöllisten muutosten TEX15-, FANCD2- ja POLG-geenien välillä, sekä tukivat aiempia tutkimustuloksia, joiden mukaan RECQL on kohtalaisen riskin rintasyöpäalttiusgeeni.