Gene Expression Signature in Peripheral Blood Detects Thoracic Aortic Aneurysm

BACKGROUND: Thoracic aortic aneurysm (TAA) is usually asymptomatic and associated with high mortality. Adverse clinical outcome of TAA is preventable by elective surgical repair; however, identifying at-risk individuals is difficult. We hypothesized that gene expression patterns in peripheral blood cells may correlate with TAA disease status. Our goal was to identify a distinct gene expression signature in peripheral blood that may identify individuals at risk for TAA. METHODS AND FINDINGS: Whole genome gene expression profiles from 94 peripheral blood samples (collected from 58 individuals with TAA and 36 controls) were analyzed. Significance Analysis of Microarray (SAM) identified potential signature genes characterizing TAA vs. normal, ascending vs. descending TAA, and sporadic vs. familial TAA. Using a training set containing 36 TAA patients and 25 controls, a 41-gene classification model was constructed for detecting TAA status and an overall accuracy of 78+/-6% was achieved. Testing this classifier on an independent validation set containing 22 TAA samples and 11 controls yielded an overall classification accuracy of 78%. These 41 classifier genes were further validated by TaqMan real-time PCR assays. Classification based on the TaqMan data replicated the microarray results and achieved 80% classification accuracy on the testing set. CONCLUSIONS: This study identified informative gene expression signatures in peripheral blood cells that can characterize TAA status and subtypes of TAA. Moreover, a 41-gene classifier based on expression signature can identify TAA patients with high accuracy. The transcriptional programs in peripheral blood leading to the identification of these markers also provide insights into the mechanism of development of aortic aneurysms and highlight potential targets for therapeutic intervention. The classifier genes identified in this study, and validated by TaqMan real-time PCR, define a set of promising potential diagnostic markers, setting the stage for a blood-based gene expression test to facilitate early detection of TAA

Post-stenotic aortic dilatation

Aortic stenosis is the most common valvular heart disease affecting up to 4% of the elderly population. It can be associated with dilatation of the ascending aorta and subsequent dissection. Post-stenotic dilatation is seen in patients with AS and/or aortic regurgitation, patients with a haemodynamically normal bicuspid aortic valve and following aortic valve replacement. Controversy exists as to whether to replace the aortic root and ascending aorta at the time of aortic valve replacement, an operation that potentially carries a higher morbidity and mortality. The aetiology of post-stenotic aortic dilatation remains controversial. It may be due to haemodynamic factors caused by a stenotic valve, involving high velocity and turbulent flow downstream of the stenosis, or due to intrinsic pathology of the aortic wall. This may involve an abnormality in the process of extracellular matrix remodelling in the aortic wall including inadequate synthesis, degradation and transport of extracellular matrix proteins. This article reviews the aetiology, pathology and management of patients with post-stenotic aortic dilatation

Increased estrogen receptor and epidermal growth factor receptor gene product co-expression in surgically resected gastric adenocarcinomas

Background: Evidence exists that estrogens influence the action of epidermal growth factor (EGF) and its receptor (EGF-R) at multiple levels. Estrogen and antiestrogen action on gastric and other gastrointestinal malignancies has been evaluated by several groups with conflicting results, and EGF-R has been implicated in the current growth factor-mediated models for gastric cancer progression. Methods: ERs and EGF-Rs were detected immunohistochemically in a total of 53 advanced gastric carcinomas using monoclonal antibodies (mAbs) to human ERs and EGF-Rs. Results: ERs were expressed in 30 (56%) and EGF-Rs in 20 (38%) of the gastric tumors. ER(+) gastric tumors were closely associated with the intestinal type (P < 0.01), whereas EGF-R(+) tumors were significantly correlated with poor differentiation status and ER(+) expression (P < 0.01). Of EGF-R(+) tumors, 85% were also ER(+). EGF-R and ER co-expression was demonstrated in 17 tumors (32% of the group). These cases were significantly corelated with poor differentiation and large tumor size upon resection (P < 0.05). Conclusions: ER and EGF-R co-expression indicates that a functional interaction between estrogens and EGF may exist in gastric cancer and that when such an interaction becomes operative, it may lead to dedifferentiation and increased tumor growth. (C) 1996 Wiley-Liss, Inc