Darrell L. Ellsworth

Heritability of coronary artery calcium quantity measured by electron beam computed tomography in asymptomatic adults

Background—Electron beam computed tomography is an accurate, noninvasive method to detect and quantify coronary artery calcification (CAC), a marker of subclinical and clinical coronary artery atherosclerosis. CAC quantity predicts future coronary artery disease end points in asymptomatic adults, but measured risk factors explain less than half the variability in CAC quantity. Although several candidate genes for CAC have been identified, the relative importance of genetic influences on CAC quantity has not been assessed in asymptomatic adults in a community. Methods and Results—We quantified the relative contributions of measured risk factors and genetic influences on CAC quantity measured by electron beam computed tomography in 698 asymptomatic white adults from 302 families. Before adjusting for any risk factors, 43.5% of the variation in CAC quantity was attributable to genetic factors (P =0.0007). Independent predictors of CAC quantity were identified with stepwise linear regression. After adjusting for these risk factors, including age, sex, fasting glucose level, systolic blood pressure, pack-years of smoking, and LDL cholesterol, 41.8% of the residual variation in CAC quantity was attributable to genetic factors (P =0.0003). Conclusions—These results demonstrate the importance of genetic factors in subclinical coronary atherosclerosis variation as measured by CAC quantity. The presence of genetic effects suggests that unknown genes that influence CAC quantity are yet to be identified.

Genomic instability in histologically normal breast tissues: implications for carcinogenesis.

Breast cancer is an important contributor to morbidity and mortality in society, but factors that affect the cause of the disease are poorly defined. Genomic instability drives tumorigenic processes in invasive carcinomas and premalignant breast lesions, and might promote the accumulation of genetic alterations in apparently normal tissues before histological abnormalities are detectable. Evidence suggests that genomic changes in breast parenchyma affect the behaviour of epithelial cells, and ultimately might affect tumour growth and progression. Inherent instability in genes that maintain genomic integrity, as well as exogenous chemicals and environmental pollutants, have been implicated in breast-cancer development. Although molecular mechanisms of tumorigenesis are unclear at present, carcinogenic agents could contribute to fields of genomic instability localised to specific areas of the breast. Understanding the functional importance of genomic instability in early carcinogenesis has important implications for improvement of diagnostic and treatment strategies.

Breast Cancer in the Personal Genomics Era

Breast cancer is a heterogeneous disease with a complex etiology that develops from different cellular lineages, progresses along multiple molecular pathways, and demonstrates wide variability in response to treatment. The “standard of care” approach to breast cancer treatment in which all patients receive similar interventions is rapidly being replaced by personalized medicine, based on molecular characteristics of individual patients. Both inherited and somatic genomic variation is providing useful information for customizing treatment regimens for breast cancer to maximize efficacy and minimize adverse side effects. In this article, we review (1) hereditary breast cancer and current use of inherited susceptibility genes in patient management; (2) the potential of newly-identified breast cancer-susceptibility variants for improving risk assessment; (3) advantages and disadvantages of direct-to-consumer testing; (4) molecular characterization of sporadic breast cancer through immunohistochemistry and gene expression profiling and opportunities for personalized prognostics; and (5) pharmacogenomic influences on the effectiveness of current breast cancer treatments. Molecular genomics has the potential to revolutionize clinical practice and improve the lives of women with breast cancer.

Outer breast quadrants demonstrate increased levels of genomic instability.

AbstractBackground: Theory holds that the upper outer quadrant of the breast develops more malignancies because of increased tissue volume. This study evaluated genomic patterns of loss of heterozygosity (LOH) and allelic imbalance (AI) in non-neoplastic tissues from quadrants of diseased breasts following mastectomy to characterize relationships between genomic instability and the propensity for tumor development. Methods: Tissues from breast quadrants were collected from 21 patients with various stages of breast carcinoma. DNA was isolated from non-neoplastic tissues using standard methods and 26 chromosomal regions commonly deleted in breast cancer were examined to assess genomic instability. Results: Genomic instability was observed in breast quadrants from patients with ductal carcinomas in situ and advanced carcinomas. Levels of instability by quadrant were not predictive of primary tumor location (P = .363), but outer quadrants demonstrated significantly higher levels of genomic instability than did inner quadrants (P = .017). Marker D8S511 on chromosome 8p22– 21.3, one of the most frequently altered chromosomal regions in breast cancer, showed a significantly higher level of instability (P = .039) in outer compared with inner quadrants. Conclusions: Non-neoplastic breast tissues often harbor genetic changes that can be important to understanding the local breast environment within which cancer develops. Greater genomic instability in outer quadrants can partially explain the propensity for breast cancers to develop there, rather than simple volume-related concepts. Patterns of field cancerization in the breast appear to be complex and are not a simple function of distance from a developing tumor.

Genomic patterns of allelic imbalance in disease free tissue adjacent to primary breast carcinomas.

Mammary stroma plays an important role in facilitating the neoplastic transformation of epithelial cells, modulating integrity of the extracellular matrix, and maintaining genomic stability, but molecular mechanisms by which stroma affects epithelial structure and function are not well-defined. We used laser-assisted microdissection of paraffin-embedded breast tissues from 30 patients with breast disease and a panel of 52 microsatellite markers defining 26 chromosomal regions to characterize genomic patterns of allelic imbalance (AI) in disease-free tissue adjacent to sites of breast disease and to define genomic regions that may contain genes associated with early carcinogenic processes. The mean frequency of AI in histologically normal tissue adjacent to the primary carcinomas (15.4) was significantly higher than that in distant tissue from the same breast (3.7). The pattern of AI across all chromosomal regions differed between the adjacent tissue and primary tumor in every case. Unique AI events, observed only in tumor (15 of informative markers) or only in adjacent cells (10 of informative markers), were far more common than AI events shared between tumor and adjacent cells (~ 4). Levels of AI characteristic of advanced invasive carcinomas were already present in non-invasive ductal carcinomas in situ, and appreciable levels of AI were observed in adjacent non-neoplastic tissue at all pathological stages. Chromosome 11p15.1 showed significantly higher levels of AI in adjacent cells (p < 0.01), suggesting that this region may harbor genes involved in breast cancer development and progression. Our data indicate that genomic instability may be inherently greater in disease-free tissue close to developing tumors, which may have important implications for defining surgical margins and predicting recurrence.

Molecular heterogeneity in breast cancer: State of the science and implications for patient care.

The identification of extensive genetic heterogeneity in human breast carcinomas poses a significant challenge for designing effective treatment regimens. Significant genomic evolution often occurs during breast cancer progression, creating variability within primary tumors as well as between the primary carcinoma and metastases. Current risk allocations and treatment recommendations for breast cancer patients are based largely on characteristics of the primary tumor; however, genetic differences between disseminated tumor cells and the primary carcinoma may negatively impact treatment efficacy and survival. In this review we (1) present current information about genomic variability within primary breast carcinomas, between primary tumors and regional/distant metastases, among circulating tumor cells (CTCs) and disseminated tumor cells (DTCs), and in cell-free nucleic acids in circulation, and (2) describe how this heterogeneity affects clinical care and outcomes such as recurrence and therapeutic resistance. Understanding the evolution and functional significance of the composite breast cancer genome within each patient is critical for developing effective therapies that can overcome obstacles presented by molecular heterogeneity.

Amplification of HER2 is a marker for global genomic instability

BackgroundGenomic alterations of the proto-oncogene c-erbB-2 (HER-2/neu) are associated with aggressive behavior and poor prognosis in patients with breast cancer. The variable clinical outcomes seen in patients with similar HER2 status, given similar treatments, suggests that the effects of amplification of HER2 can be influenced by other genetic changes. To assess the broader genomic implications of structural changes at the HER2 locus, we investigated relationships between genomic instability and HER2 status in patients with invasive breast cancer.MethodsHER2 status was determined using the PathVysion® assay. DNA was extracted after laser microdissection from the 181 paraffin-embedded HER2 amplified (n = 39) or HER2 negative (n = 142) tumor specimens with sufficient tumor available to perform molecular analysis. Allelic imbalance (AI) was assessed using a panel of microsatellite markers representing 26 chromosomal regions commonly altered in breast cancer. Student t-tests and partial correlations were used to investigate relationships between genomic instability and HER2 status.ResultsThe frequency of AI was significantly higher (P < 0.005) in HER2 amplified (27%) compared to HER2 negative tumors (19%). Samples with HER2 amplification showed significantly higher levels of AI (P < 0.05) at chromosomes 11q23, 16q22-q24 and 18q21. Partial correlations including ER status and tumor grade supported associations between HER2 status and alterations at 11q13.1, 16q22-q24 and 18q21.ConclusionThe poor prognosis associated with HER2 amplification may be attributed to global genomic instability as cells with high frequencies of chromosomal alterations have been associated with increased cellular proliferation and aggressive behavior. In addition, high levels of DNA damage may render tumor cells refractory to treatment. In addition, specific alterations at chromosomes 11q13, 16q22-q24, and 18q21, all of which have been associated with aggressive tumor behavior, may serve as genetic modifiers to HER2 amplification. These data not only improve our understanding of HER in breast pathogenesis but may allow more accurate risk profiles and better treatment options to be developed.

Functional relationship and gene ontology classification of breast cancer biomarkers

Breast cancer is a complex disease that still imposes a significant healthcare burden on women worldwide. The etiology of breast cancer is not known but significant advances have been made in the area of early detection and treatment. The advent of advanced molecular biology techniques, mapping of the human genome and availability of high throughput genomic and proteomic strategies opens up new opportunities and will potentially lead to the discovery of novel biomarkers for early detection and prognostication of breast cancer. Currently, many biomarkers, particularly the hormonal and epidermal growth factor receptors, are being utilized for breast cancer prognosis. Unfortunately, none of the biomarkers in use have sufficient diagnostic, prognostic and/or predictive power across all categories and stages of breast cancer. It is recognized that more useful information can be generated if tumors are interrogated with multiple markers. But choosing the right combination of biomarkers is challenging, because 1) multiple pathways are involved, 2) up to 62 genes and their protein products are potentially involved in breast cancer-related mechanisms and 3) the more markers evaluated, the more the time and cost involved. This review summarizes the current literature on selected biomarkers for breast cancer, discusses the functional relationships, and groups the selected genes based on a Gene Ontology classification.

Management of Incidental Findings in the Era of Next-generation Sequencing

Next-generation sequencing (NGS) technologies allow for the generation of whole exome or whole genome sequencing data, which can be used to identify novel genetic alterations associated with defined phenotypes or to expedite discovery of functional variants for improved patient care. Because this robust technology has the ability to identify all mutations within a genome, incidental findings (IF)- genetic alterations associated with conditions or diseases unrelated to the patient’s present condition for which current tests are being performed- may have important clinical ramifications. The current debate among genetic scientists and clinicians focuses on the following questions: 1) should any IF be disclosed to patients, and 2) which IF should be disclosed – actionable mutations, variants of unknown significance, or all IF? Policies for disclosure of IF are being developed for when and how to convey these findings and whether adults, minors, or individuals unable to provide consent have the right to refuse receipt of IF. In this review, we detail current NGS technology platforms, discuss pressing issues regarding disclosure of IF, and how IF are currently being handled in prenatal, pediatric, and adult patients.

Intensive Cardiovascular Risk Reduction Induces Sustainable Changes in Expression of Genes and Pathways Important to Vascular Function

Background—Healthy lifestyle changes are thought to mediate cardiovascular disease risk through pathways affecting endothelial function and progression of atherosclerosis; however, the extent, persistence, and clinical significance of molecular change during lifestyle modification are not well known. We examined the effect of a rigorous cardiovascular disease risk reduction program on peripheral blood gene expression profiles in 63 participants and 63 matched controls to characterize molecular responses and identify regulatory pathways important to cardiovascular health. Methods and Results—Dramatic changes in dietary fat intake (−61%; P<0.001 versus controls) and physical fitness (+34%; P<0.001) led to significant improvements in cardiovascular disease risk factors. Analysis of variance with false discovery rate correction for multiple testing (P<0.05) identified 26 genes after 12 weeks and 143 genes after 52 weeks that were differentially expressed from baseline in participants. Controls showed little change in cardiovascular disease risk factors or gene expression. Quantitative reverse transcription polymerase chain reaction validated differential expression for selected transcripts. Lifestyle modification effectively reduced expression of proinflammatory genes associated with neutrophil activation and molecular pathways important to vascular function, including cytokine production, carbohydrate metabolism, and steroid hormones. Prescription medications did not significantly affect changes in gene expression. Conclusions—Successful and sustained modulation of gene expression through lifestyle changes may have beneficial effects on the vascular system not apparent from traditional risk factors. Healthy lifestyles may restore homeostasis to the leukocyte transcriptome by downregulating lactoferrin and other genes important in the pathogenesis of atherosclerosis. Clinical Trial Registration—URL: www.clinicaltrials.gov. Unique identifier: NCT01805492