Molecular Analysis of the Genetic Heterogeneity Between Primary and Recurrent Glioblastoma

Introduction: Glioblastoma multiforme (GBM) is one of the deadliest forms of brain cancer, and affects more than 18,000 new cases each year in the United States alone. The current standard of treatment for GBM includes surgical removal of the tumor, along with radiation and chemotherapy. Despite these treatments, recurrence of GBM is extremely common, and once it recurs, the life expectancy is measured in weeks or months. One of the reasons for the deadly nature of the recurrent GBM is thought to be selection for therapy-resistant tumor cells. In this project, we sought to characterize the molecular changes in recurrent GBM specimens compared to primary GBM specimens from the same subjects. Methods: Whole-genome DNA microarrays were used to identify genes changed in mRNA expression in seven recurrent GBM samples compared to seven primary GBM samples from the same subjects. Real-time quantitative RT-PCR was used in an attempt to validate changes seen by microarray for 18 genes of interest chosen from the microarray screen. Results: The microarray experiments identified several dozen mRNA transcripts with evidence of significant differences in expression. From these genes, we chose 18 for PCR validation. Overall, the PCR experiments validated the microarray findings quite well. There was a very high correlation for the magnitude of expression changes seen for the 18 genes (Pearson’s R = 0.852, P \u3c 0.001). Individually, 13 of the 18 genes showed statistically significant changes by PCR in the recurrent versus primary tumor pairs. Of the 5 genes that did not validate at the P\u3c0.05 level, 4 showed trends in the direction predicted by the microarray, while 1 gene did not. Conclusion: Real time PCR has proven useful for validating changes in recurrent GBMs that could have important clinical applications

Investigation of de novo mutations in human genomes using whole genome sequencing data

De novo mutations (DNMs) are novel mutations which occur for the first time in an offspring and are not inherited from the parents. High-Throughput Sequencing (HTS) technologies such as whole genome sequencing (WGS) and whole exome sequencing (WES) of trios have allowed the investigation of DNMs and their role in diseases. Increased contribution of DNMs in both rare monogenic and common complex disorders is now known. Identification of DNMs from WGS is challenging since the error rates in the HTS data are much higher than the expected DNM rate. To facilitate the evaluation of existing DNM callers and development of new callers, I developed TrioSim, the first automated tool to generate simulated WGS datasets for trios with a feature to spike-in DNMs in the offspring WGS data. Several computational methods have been developed to call DNMs from HTS data. I performed the first systematic evaluation of current DNM callers for WGS trio data using real dataset and simulated trio datasets and found that DNM callers have high sensitivity and can detect the majority of true DNMs. However, they suffer from very low specificity with thousands of false positive calls made by each caller. To address this, I developed MetaDeNovo, a consensus-based ensemble computational method to call DNMs using cloud-based technologies. MetaDeNovo is a fully automated methodology that utilises existing DNM callers and integrates their results. It demonstrates much higher specificity than all other callers while maintaining high sensitivity. Congenital Heart Disease (CHD) is the most common birth disorder worldwide. DNMs have been found to contribute to CHD causation. Most CHD cases are sporadic, suggesting role of DNMs in large proportion of them. I applied MetaDeNovo to detect DNMs in a WGS dataset of CHD trios to aid with genetic variant prioritisation. MetaDeNovo can dramatically reduce the number of false positive DNMs as compared to individual DNM callers. This has improved the current practices of identifying the genetic causes of disease in such cohorts. MetaDeNovo is applicable to other trio WGS datasets of other genetic diseases. This thesis has contributed new knowledge by in depth exploration of existing DNM callers, development of a novel tool (TrioSim) to simulate trio WGS data and an ensemble improved automated tool (MetaDeNovo) to identify DNMs with high specificity. MetaDeNovo demonstrates its use to identify disease-causing mutations in a trio analysis using WGS

NOTCH2 in breast cancer: association of SNP rs11249433 with gene expression in ER-positive breast tumors without TP53 mutations

<p>Abstract</p> <p>Background</p> <p>A recent genome-wide association study (GWAS) has identified a single nucleotide polymorphism (SNP) rs11249433 in the 1p11.2 region as a novel genetic risk factor for breast cancer, and this association was stronger in patients with estrogen receptor (ER)⁺versus ER^-cancer.</p> <p>Results</p> <p>We found association between SNP rs11249433 and expression of the <it>NOTCH2 </it>gene located in the 1p11.2 region. Examined in 180 breast tumors, the expression of <it>NOTCH2 </it>was found to be lowest in tumors with <it>TP53 </it>mutations and highest in <it>TP53 </it>wild-type/ER⁺tumors (p = 0.0059). In the latter group, the <it>NOTCH2 </it>expression was particularly increased in carriers of the risk genotypes (AG/GG) of rs11249433 when compared to the non-risk AA genotype (p = 0.0062). Similar association between <it>NOTCH2 </it>expression and rs11249433 was observed in 60 samples of purified monocytes from healthy controls (p = 0.015), but not in total blood samples from 302 breast cancer patients and 76 normal breast tissue samples. We also identified the first possible dominant-negative form of <it>NOTCH2</it>, a truncated version of <it>NOTCH2 </it>consisting of only the extracellular domain.</p> <p>Conclusion</p> <p>This is the first study to show that the expression of <it>NOTCH2 </it>differs in subgroups of breast tumors and by genotypes of the breast cancer-associated SNP rs11249433. The NOTCH pathway has key functions in stem cell differentiation of ER⁺luminal cells in the breast. Therefore, increased expression of <it>NOTCH2 </it>in carriers of rs11249433 may promote development of ER⁺luminal tumors. Further studies are needed to investigate possible mechanisms of regulation of <it>NOTCH2 </it>expression by rs11249433 and the role of <it>NOTCH2 </it>splicing forms in breast cancer development.</p

A polymorphism in HLA-G modifies statin benefit in asthma

Several reports have shown that statin treatment benefits patients with asthma, however inconsistent effects have been observed. The mir-152 family (148a, 148b and 152) has been implicated in asthma. These microRNAs suppress HLA-G expression, and rs1063320, a common SNP in the HLA-G 3’UTR which is associated with asthma risk, modulates miRNA binding. We report that statins up-regulate mir-148b and 152, and affect HLA-G expression in an rs1063320 dependent fashion. In addition, we found that individuals who carried the G minor allele of rs1063320 had reduced asthma related exacerbations (emergency department visits, hospitalizations or oral steroid use) compared to non-carriers (p=0.03) in statin users ascertained in the Personalized Medicine Research Project at the Marshfield Clinic (n=421). These findings support the hypothesis that rs1063320 modifies the effect of statin benefit in asthma, and thus may contribute to variation in statin efficacy for the management of this disease

Maximizing service uptime of smartphone-based distributed real-time and embedded systems

Abstract-Smartphones are starting to find use in missioncritical applications, such as search-and-rescue operations, wherein the mission capabilities are realized by deploying a collaborating set of services across a group of smartphones involved in the mission. Since these missions are deployed in environments where replenishing resources, such as smartphone batteries, is hard, it is necessary to maximize the lifespan of the mission while also maintaining its real-time quality of service (QoS) requirements. To address these requirements, this paper presents a deployment framework called SmartDeploy, which integrates bin packing heuristics with evolutionary algorithms to produce near-optimal deployment solutions that are computationally inexpensive to compute for maximizing the lifespan of smartphone-based mission critical applications. The paper evaluates the merits of deployments produced by SmartDeploy for a search-and-rescue mission comprising a heterogeneous mix of smartphones by integrating a worst-fit bin packing heuristic with particle swarm optimization and genetic algorithm. Results of our experiments indicate that the missions deployed using SmartDeploy have a lifespan that is 20% to 162% greater than those deployed using just the bin packing heuristic or evolutionary algorithms. Although SmartDeploy is slightly slower than the other algorithms, the slower speed is acceptable for offline computations of deployment

Evaluating the role of race and medication in protection of uterine fibroids by type 2 diabetes exposure

Abstract Background Uterine fibroids (UF) affect 77% of women by menopause, and account for $9.4 billion in annual healthcare costs. Type-2-diabetes (T2D) has inconsistently associated with protection from UFs in prior studies. To further evaluate the relationship between T2D and UFs we tested for association between T2D and UF risk in a large clinical population as well as the potential differences due to T2D medications and interaction with race. Methods This nested case–control study is derived from a clinical cohort. Our outcome was UF case-control status and our exposure was T2D. UF outcomes and T2D exposure were classified using validated electronic medical record (EMR) algorithms. Logistic regression, adjusted for covariates, was used to model the association between T2D diagnosis and UF risk. Secondary analyses were performed evaluating the interaction between T2D exposure and race and stratifying T2D exposed subjects by T2D medication being taken. Results We identified 3,789 subjects with UF outcomes (608 UF cases and 3,181 controls), 714 were diabetic and 3,075 were non-diabetic. We observed a nominally significant interaction between T2D exposure and race in adjusted models (interaction p = 0.083). Race stratified analyses demonstrated more protection by T2D exposure on UF risk among European Americans (adjusted odds ratio [aOR] = 0.50, 95% CI 0.35 to 0.72) than African Americans (aOR = 0.76, 95% CI 0.50 to 1.17). We also observed a protective effect by T2D regardless of type of T2D medication being taken, with slightly more protection among subjects on insulin treatments (European Americans aOR = 0.42, 95% CI 0.26 to 0.68; African Americans aOR = 0.60, 95% CI 0.36 to 1.01). Conclusions These data, conducted in a large population of UF cases and controls, support prior studies that have found a protective association between diabetes presence and UF risk and is further modified by race. Protection from UFs by T2D exposure was observed regardless of medication type with slightly more protection among insulin users. Further mechanistic research in larger cohorts is necessary to reconcile the potential role of T2D in UF risk

Systematic screening of promoter regions pinpoints functional cis-regulatory mutations in a cutaneous melanoma genome

© 2015 American Association for Cancer Research. With the recent discovery of recurrent mutations in the TERT promoter in melanoma, identification of other somatic causal promoter mutations is of considerable interest. Yet, the impact of sequence variation on the regulatory potential of gene promoters has not been systematically evaluated. This study assesses the impact of p romoter mutations on promoter activity in the wholegenome sequenced malignant melanoma cell line COLO-829. Combining somatic mutation calls from COLO-829 with genome-wide chromatin accessibility and histone modification data revealed mutations within promoter elements. Interestingly, a high number of potential promoter mutations (n = 23) were found, a result mirrored in subsequent analysis of TCGA wholemelanoma genomes. The impact of wild-type and mutant promoter sequences were evaluated by subcloning into luciferase reporter vectors and testing their transcriptional activity in COLO-829 cells. Of the 23 promoter regions tested, four mutations significantly altered reporter activity relative to wild-type sequences. These data were then subjected to multiple computational algorithms that score the cis-regulatory altering potential of mutations. These analyses identified one mutation, located within the promoter region of NDUFB9, which encodes the mitochondrial NADH dehydrogenase (ubiquinone) 1 beta subcomplex 9, to be recurrent in 4.4% (19 of 432) of TCGA wholemelanoma exomes. The mutation is predicted to disrupt a highly conserved SP1/KLF transcription factor binding motif and its frequent co-occurrence with mutations in the coding sequence of NF1 supports a pathologic role for this mutation in melanoma. Taken together, these data show the relatively high prevalence of promoter mutations in the COLO-829 melanoma genome, and indicate that a proportion of these significantly alter the regulatory potential of gene promoters. Implications: Genomic-based screening within gene promoter regions suggests that functional cis-regulatory mutations may be common inmelanoma genomes, highlighting the need to examine their role in tumorigenesisLink_to_subscribed_fulltex