Publications by Year: 2012

2012
Kassem HS, Girolami F, Sanoudou D. Molecular genetics made simple. Glob Cardiol Sci PractGlob Cardiol Sci PractGlob Cardiol Sci Pract. 2012;2012:6.Abstract
Genetics have undoubtedly become an integral part of biomedical science and clinical practice, with important implications in deciphering disease pathogenesis and progression, identifying diagnostic and prognostic markers, as well as designing better targeted treatments. The exponential growth of our understanding of different genetic concepts is paralleled by a growing list of genetic terminology that can easily intimidate the unfamiliar reader. Rendering genetics incomprehensible to the clinician however, defeats the very essence of genetic research: its utilization for combating disease and improving quality of life. Herein we attempt to correct this notion by presenting the basic genetic concepts along with their usefulness in the cardiology clinic. Bringing genetics closer to the clinician will enable its harmonious incorporation into clinical care, thus not only restoring our perception of its simple and elegant nature, but importantly ensuring the maximal benefit for our patients.
Kalozoumi G, Tzimas C, Sanoudou D. The expanding role of epigenetics. Glob Cardiol Sci PractGlob Cardiol Sci PractGlob Cardiol Sci Pract. 2012;2012:7.
Totary-Jain H, Sanoudou D, Dautriche CN, Schneller H, Zambrana L, Marks AR. Rapamycin resistance is linked to defective regulation of Skp2. Cancer ResCancer ResCancer Res. 2012;72:1836-43.Abstract
The mammalian target of rapamycin (mTOR) plays a role in controlling malignant cellular growth. mTOR inhibitors, including rapamycin (sirolimus), are currently being evaluated in cancer trials. However, a significant number of tumors are rapamycin resistant. In this study, we report that the ability of rapamycin to downregulate Skp2, a subunit of the ubiquitin protein ligase complex, identifies tumors that are sensitive to rapamycin. RNA interference (RNAi)-mediated silencing of Skp2 in human tumor cells increased their sensitivity to rapamycin in vitro and inhibited the growth of tumor xenografts in vivo. Our findings suggest that Skp2 levels are a key determinant of antitumor responses to mTOR inhibitors, highlighting a potentially important pharmacogenomic marker to predict sensitivity to rapamycin as well as Skp2 silencing strategies for therapeutic purposes.
Sanoudou D, Mountzios G, Arvanitis DA, Pectasides D. Array-based pharmacogenomics of molecular-targeted therapies in oncology. Pharmacogenomics JPharmacogenomics JPharmacogenomics J. 2012;12:185-96.Abstract
The advent of microarrays over the past decade has transformed the way genome-wide studies are designed and conducted, leading to an unprecedented speed of acquisition and amount of new knowledge. Microarray data have led to the identification of molecular subclasses of solid tumors characterized by distinct oncogenic pathways, as well as the development of multigene prognostic or predictive models equivalent or superior to those of established clinical parameters. In the field of molecular-targeted therapy for cancer, in particular, the application of array-based methodologies has enabled the identification of molecular targets with 'key' roles in neoplastic transformation or tumor progression and the subsequent development of targeted agents, which are most likely to be active in the specific molecular setting. Herein, we present a summary of the main applications of whole-genome expression microarrays in the field of molecular-targeted therapies for solid tumors and we discuss their potential in the clinical setting. An emphasis is given on deciphering the molecular mechanisms of drug action, identifying novel therapeutic targets and suitable agents to target them with, and discovering molecular markers/signatures that predict response to therapy or optimal drug dose for each patient.
Sakellariou A, Sanoudou D, Spyrou G. Combining multiple hypothesis testing and affinity propagation clustering leads to accurate, robust and sample size independent classification on gene expression data. BMC BioinformaticsBMC BioinformaticsBMC Bioinformatics. 2012;13:270.Abstract
BACKGROUND: A feature selection method in microarray gene expression data should be independent of platform, disease and dataset size. Our hypothesis is that among the statistically significant ranked genes in a gene list, there should be clusters of genes that share similar biological functions related to the investigated disease. Thus, instead of keeping N top ranked genes, it would be more appropriate to define and keep a number of gene cluster exemplars. RESULTS: We propose a hybrid FS method (mAP-KL), which combines multiple hypothesis testing and affinity propagation (AP)-clustering algorithm along with the Krzanowski & Lai cluster quality index, to select a small yet informative subset of genes. We applied mAP-KL on real microarray data, as well as on simulated data, and compared its performance against 13 other feature selection approaches. Across a variety of diseases and number of samples, mAP-KL presents competitive classification results, particularly in neuromuscular diseases, where its overall AUC score was 0.91. Furthermore, mAP-KL generates concise yet biologically relevant and informative N-gene expression signatures, which can serve as a valuable tool for diagnostic and prognostic purposes, as well as a source of potential disease biomarkers in a broad range of diseases. CONCLUSIONS: mAP-KL is a data-driven and classifier-independent hybrid feature selection method, which applies to any disease classification problem based on microarray data, regardless of the available samples. Combining multiple hypothesis testing and AP leads to subsets of genes, which classify unknown samples from both, small and large patient cohorts with high accuracy.
Psarras S, Mavroidis M, Sanoudou D, Davos CH, Xanthou G, Varela AE, Panoutsakopoulou V, Capetanaki Y. Regulation of adverse remodelling by osteopontin in a genetic heart failure model. Eur Heart JEur Heart JEur Heart J. 2012;33:1954-63.Abstract
AIMS: Desmin, the muscle-specific intermediate filament protein, is a major target in dilated cardiomyopathy and heart failure in humans and mice. The hallmarks of desmin-deficient (des(-/-)) mice pathology include pronounced myocardial degeneration, extended fibrosis, and osteopontin (OPN) overexpression. We sought to identify the molecular and cellular events regulating adverse cardiac remodelling in des(-/-) mice and their potential link to OPN. METHODS AND RESULTS: In situ hybridization, histology, and immunostaining demonstrated that inflammatory cells and not cardiomyocytes were the source of OPN. RNA profile comparison revealed that activation of inflammatory pathways, sustained by innate immunity mechanisms, predominated among all changes occurring in degenerating des(-/-) myocardium. The expression of the most highly up-regulated genes (OPN: 226x, galectin-3: 26x, osteoactivin/Gpnmb/DC-HIL: 160x and metalloprotease-12: 98x) was associated with heart infiltrating macrophages. To evaluate the role of OPN, we generated des(-/-)OPN(-/-) mice and compared their cardiac function and remodelling indices with those of des(-/-). Osteopontin promoted cardiac dysfunction in this model since des(-/-)OPN(-/-) mice showed 53% improvement of left ventricular function, paralleled to an up to 44% reduction in fibrosis. The diminished fibrotic response in the absence of OPN could be partly mediated by a dramatic reduction in myocardial galectin-3 levels, associated with an impaired galectin-3 secretion by OPN-deficient infiltrating macrophages. CONCLUSION: Cardiomyocyte death due to desmin deficiency leads to inflammation and subsequent overexpression of a series of remodelling modulators. Among them, OPN seems to be a major regulator of des(-/-) adverse myocardial remodelling and it functions at least by potentiating galectin-3 up-regulation and secretion.