31 research outputs found
Total loss of MHC class I is an independent indicator of good prognosis in breast cancer
Tumours can be recognised by CTL and NK cells. CTL recognition depends on expression of MHC Class I loaded with peptides from tumour antigens. In contrast, loss of MHC Class I results in NK activation. In our study a large set of samples from patients with primary operable invasive breast cancer was evaluated for the expression of MHC Class I heavy and light by immunohistochemical staining of 439 breast carcinomas in a tissue microarray. Forty-seven percent (206 of 439) of breast carcinomas were considered negative for HLA Class I heavy chain (HC10), whereas lack of anti-β2m-antibody staining was observed in 39% (167 of 424) of tumours, with only 3% of the β2m-negative tumours expressing detectable HLA Class I heavy chain. Correlation with patient outcome showed direct relationship between patient survival and HLA-negative phenotype (log rank = 0.004). A positive relationship was found between the intensity of expression of MHC Class I light and heavy chains expression and histological grade of invasive tumour (p < 0.001) and Nottingham Prognostic Index (p < 0.001). To investigate whether HLA Class I heavy and light chains expression had independent prognostic significance, Cox multivariate regression analysis, including the parameters of tumour size, lymph node stage, grade and intensity of HC10 and anti-β2m staining, was carried out. In our analysis, lymph node stage (p < 0.001), tumour grade (p = 0.005) and intensity of MHC Class I light and heavy chains expression were shown to be independent prognostic factors predictive of overall survival (p-values HC10 = 0.047 and β2m = 0.018)
Molecular and structural basis for Lewis glycan recognition by a cancer-targeting antibody
Immunotherapy has been successful in treating many tumour types. The development of additional tumour-antigen binding monoclonal antibodies (mAbs) will help expand the range of immunotherapeutic targets. Lewis histo-blood group and related glycans are overexpressed on many carcinomas, including those of the colon, lung, breast, prostate and ovary, and can therefore be selectively targeted by mAbs. Here we examine the molecular and structural basis for recognition of extended Lea and Lex containing glycans by a chimeric mAb. Both the murine (FG88.2) IgG3 and a chimeric (ch88.2) IgG1 mAb variants showed reactivity to colorectal cancer cells leading to significantly reduced cell viability. We determined the X-ray structure of the unliganded ch88.2 fragment antigen-binding (Fab) containing two Fabs in the unit cell. A combination of molecular docking, glycan grafting and molecular dynamics simulations predicts two distinct subsites for recognition of Lea and Lex trisaccharides. While light chain residues were exclusively used for Lea binding, recognition of Lex involved both light and heavy chain residues. An extended groove is predicted to accommodate the Lea–Lex hexasaccharide with adjoining subsites for each trisaccharide. The molecular and structural details of the ch88.2 mAb presented here provide insight into its cross-reactivity for various Lea and Lex containing glycans. Furthermore, the predicted interactions with extended epitopes likely explains the selectivity of this antibody for targeting Lewis-positive tumours
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Genetic Influences on Disease Risk and Severity
Investigating the genetic causes of disease allows for better understanding of disease pathology, and can lead to improved prevention, detection, and treatment of these diseases. In this dissertation I focus on investigations into the genetic architecture of two rare diseases, congenital heart disease (CHD) and coccidioidomycosis (also known as Valley Fever). First, I investigate CHD genetics. One percent of babies are born with congenital heart birth defects, defined by a failure of normal heart development leading to significant physiological defects. Only 30% of cases have a known, single-gene, pathogenic mutation associated with the CHD phenotype. All phenotypes have genetic and environmental contributions to them though. Thus, for a large proportion of individuals, we do not know what the genetic contribution is to the birth defect. We used a trio-based cohort of individuals that contains probands with CHD that remain genetically undiagnosed. We asked whether common variants can have an effect on disease phenotype presence and severity. We use genome-wide association (GWAS) data on CHD endo-phenotypes from publicly available datasets to develop polygenic risk scores (PRS) correlating with disease risk and disease severity. We find that PRS estimated using a GWAS for heart valve problems and heart murmur explain 2.5% of the variance in case-control status of CHD (all SNVs p=7.90e-3, fetal cardiac SNVs p=8.00e-3), and 1.8% of the variance in severity of CHD (fetal cardiac SNVs p=6.20e-3, all SNVs p=0.015). These results show that common variants captured in CHD phenotype-matched GWAS have a modest, but significant contribution to phenotypic expression of CHD.
As a second project, I investigate the genetics of susceptibility to severe manifestations of coccidioidomycosis. Currently, it remains unknown why some individuals get more severe Valley Fever infections than others. Coccidioidomycosis, or Valley Fever, is a caused by a fungal infection with Coccidiodes Immities or Posadasii, which are endemic to the Southwest United States and parts of Central and South America. While 60% of people who inhale the fungal spores are asymptomatic (and thus often are not even reported), 40% of people develop a pneumonia-like infection. Most people recover, but a subset of the population develops chronic pulmonary disease and an even smaller number of people, 1% of all infected people, develop disseminated infections which spread to other areas of the body and can lead to meningitis and death. Treatment involves prolonged antifungal use, which contains the infection but has numerous side effects after long-term use. So, it is imperative we develop better ways to detect patients at risk for severe disease and then treat those patients. We use a cohort of Valley Fever patients to look at the genetic causes of having more severe phenotypes. Our dataset is split into patients with uncomplicated Valley Fever (UVF), chronic pulmonary coccidioidomycosis (CPC), and disseminated coccidioidomycosis (DCM). For the purposes of this study we considered UVF patients to be controls, as these patients recover without prolonged antifungal treatment. There is no large cohort of patients who have established coccidioidomycosis infection but without any symptoms. We show that having African genetic similarity is associated with increased risk of severe disease. We also explain how African genetic similarity does not necessarily correlate with self-identified race and ethnicity (SIRE) or skin-color. We also identify identity-by-descent segments shared by individuals with severe disease that may contain risk variants for developing severe disease.
In conclusion, I present here a dissertation focused on the genetics of two rare conditions: congenital heart disease and of susceptibility to severe coccidioidomycosis. Researching rare diseases is important because although they affect a smaller proportion of the population, they can have a severe effect on the lives of the individuals with these diseases. In addition, collectively all rare-disease patients around the world represent over 350 million people and represent a significant disease burden. Finally, understanding the genetics of rare disease can help us understand and interpret genetic variation contributing to rare diseases
Local Genetic Correlation Gives Insights into the Shared Genetic Architecture of Complex Traits
Although genetic correlations between complex traits provide valuable insights into epidemiological and etiological studies, a precise quantification of which genomic regions disproportionately contribute to the genome-wide correlation is currently lacking. Here, we introduce ρ-HESS, a technique to quantify the correlation between pairs of traits due to genetic variation at a small region in the genome. Our approach requires GWAS summary data only and makes no distributional assumption on the causal variant effect sizes while accounting for linkage disequilibrium (LD) and overlapping GWAS samples. We analyzed large-scale GWAS summary data across 36 quantitative traits, and identified 25 genomic regions that contribute significantly to the genetic correlation among these traits. Notably, we find 6 genomic regions that contribute to the genetic correlation of 10 pairs of traits that show negligible genome-wide correlation, further showcasing the power of local genetic correlation analyses. Finally, we report the distribution of local genetic correlations across the genome for 55 pairs of traits that show putative causal relationships
Polygenic risk scores of endo-phenotypes identify the effect of genetic background in congenital heart disease
Congenital heart disease (CHD) is a rare structural defect that occurs in ∼1% of live births. Studies on CHD genetic architecture have identified pathogenic single-gene mutations in less than 30% of cases. Single-gene mutations often show incomplete penetrance and variable expressivity. Therefore, we hypothesize that genetic background may play a role in modulating disease expression. Polygenic risk scores (PRSs) aggregate effects of common genetic variants to investigate whether, cumulatively, these variants are associated with disease penetrance or severity. However, the major limitations in this field have been in generating sufficient sample sizes for these studies. Here we used CHD-phenotype matched genome-wide association study (GWAS) summary statistics from the UK Biobank (UKBB) as our base study and whole-genome sequencing data from the CHD cohort (n1 = 711 trios, n2 = 362 European trios) of the Gabriella Miller Kids First dataset as our target study to develop PRSs for CHD. PRSs estimated using a GWAS for heart valve problems and heart murmur explain 2.5% of the variance in case-control status of CHD (all SNVs, p = 7.90 × 10-3; fetal cardiac SNVs, p = 8.00 × 10-3) and 1.8% of the variance in severity of CHD (fetal cardiac SNVs, p = 6.20 × 10-3; all SNVs, p = 0.015). These results show that common variants captured in CHD phenotype-matched GWASs have a modest but significant contribution to phenotypic expression of CHD. Further exploration of the cumulative effect of common variants is necessary for understanding the complex genetic etiology of CHD and other rare diseases
What\u27s Up With Fat?
Background: Didactic dietetic students felt that dietary fat phobia is an apparent issue at Utah State University that needed to be addressed. Additionally, using a variety of teaching methods such as interactive games, food tasting, and informational pamphlets to reach a variety of individual learning preferences.
Purpose: The purpose of this study was to determine the impact of booths on educating about fat and fat containing foods in Food Day attendees.
Setting: Food Day 2016 at Utah State University in the Taggart Student Center Hub
Methods: Food Day participants (84) completed a pre-survey (including a 27 item food frequency questionnaire (FFQ) and 16 questions on knowledge, self-efficacy and intent to change) before entering and a post-survey before leaving. Participants (47) completed a follow-up survey 4 weeks later. Repeated measures ANOVA was used to evaluate knowledge, self-efficacy, and intent to change questions. Paired t-test found mean differences in pre and follow-up FFQ.
Results: Participants spent an average of 21 minutes at Food Day. Knowledge and self- efficacy showed more of a short-term effect as opposed to a longer-term. At follow-up, participants reported consuming less whole milk, full fat dairy products, nuts, medium and high fat meats (p
Conclusion: Food Day 2016 had a positive effect on students\u27 perception of fat in foods and the effect on health but less impact on food habits related to fat intake
Upregulation of MICA on high-grade invasive operable breast carcinoma
The MHC class I chain-related gene A (MICA) is frequently expressed
on the surface of intestinal epithelium and by many epithelial tumours.
MICA is a stress-induced antigen which was identified as an activator
of natural killer cells via interaction with the NKG2D receptor.
We have raised a rabbit polyclonal antibody against a synthetic
peptide that recognises denatured MICA on both Western blots and
in formalin-fixed paraffin-embedded sections. In the present study
this antibody was used to undertake a definitive study of 530 breast
cancer cases with mean follow up of 7 years to determine the prognostic
significance of MICA expression. To detect any association between
MICA expression and NK infiltration, whole sections of 50 tumours
were also analysed for CD56 staining. Univariate analysis showed
significant relationships between MICA expression and histological
grade (P = 0.006), lymph
node stage (P = 0.013),
Nottingham Prognostic Index (NPI, P = 0.002),
the presence of vascular invasion (P = 0.045)
and tumour type (P = 0.023).
Upregulation of MICA was more often found in histological grade
3, poor prognosis (NPI >5.4) tumours. Association of high
MICA expression with NK cell infiltration was not demonstrated,
as very few NK cells were present in whole breast sections. Our
results suggest that induced expression of MICA may be an indicator
of poor prognosis in breast carcinoma and is indicative of a tumour
environment that has undergone stresses such as apoptosis, necrosis,
or hypoxia