Dimitrios Spentzos

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OBJECTIVE We examined whether proteomic technologies identify novel urine proteins associated with subsequent development of diabetic nephropathy in subjects with type 2 diabetes before evidence of microalbuminuria. RESEARCH DESIGN AND METHODS In a nested case-control study of Pima Indians with type 2 diabetes, baseline (serum creatinine <1.2 mg/dl and(More)
The relatively new field of onco-metabolomics attempts to identify relationships between various cancer phenotypes and global metabolite content. Previous metabolomics studies utilized either nuclear magnetic resonance spectroscopy or gas chromatography/mass spectrometry, and analyzed metabolites present in urine and serum. However, direct metabolomic(More)
  • Panagiotis A Konstantinopoulos, Elena Fountzilas, Kamana Pillay, Luiz F Zerbini, Towia A Libermann, Stephen A Cannistra +1 other
  • 2008
BACKGROUND We performed a time-course microarray experiment to define the transcriptional response to carboplatin in vitro, and to correlate this with clinical outcome in epithelial ovarian cancer (EOC). RNA was isolated from carboplatin and control-treated 36M2 ovarian cancer cells at several time points, followed by oligonucleotide microarray(More)
  • Panagiotis A. Konstantinopoulos, Stephen A. Cannistra, Helen Fountzilas, Aedin Culhane, Kamana Pillay, Bo Rueda +7 others
  • 2011
BACKGROUND Public data integration may help overcome challenges in clinical implementation of microarray profiles. We integrated several ovarian cancer datasets to identify a reproducible predictor of survival. METHODOLOGY/PRINCIPAL FINDINGS Four microarray datasets from different institutions comprising 265 advanced stage tumors were uniformly(More)
We recently identified two robust ovarian cancer subtypes, defined by the expression of genes involved in angiogenesis, with significant differences in clinical outcome. To identify potential regulatory mechanisms that distinguish the subtypes we applied PANDA, a method that uses an integrative approach to model information flow in gene regulatory networks.(More)
Although ovarian cancer is often initially chemotherapy-sensitive, the vast majority of tumors eventually relapse and patients die of increasingly aggressive disease. Cancer stem cells are believed to have properties that allow them to survive therapy and may drive recurrent tumor growth. Cancer stem cells or cancer-initiating cells are a rare cell(More)
  • Panagiotis A. Konstantinopoulos, Elena Fountzilas, Jeffrey D. Goldsmith, Manoj Bhasin, Kamana Pillay, Nancy Francoeur +3 others
  • 2010
BACKGROUND Diagnosis of soft tissue sarcomas (STS) is challenging. Many remain unclassified (not-otherwise-specified, NOS) or grouped in controversial categories such as malignant fibrous histiocytoma (MFH), with unclear therapeutic value. We analyzed several independent microarray datasets, to identify a predictor, use it to classify unclassifiable(More)
Although microRNAs (miRNAs) are implicated in osteosarcoma biology and chemoresponse, miRNA prognostic models are still needed, particularly because prognosis is imperfectly correlated with chemoresponse. Formalin-fixed, paraffin-embedded tissue is a necessary resource for biomarker studies in this malignancy with limited frozen tissue availability. We(More)
Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI or SELDI-TOF MS) with protein arrays has facilitated the discovery of disease-specific protein profiles in serum. As array technologies in bioinformatics and proteomics multiply the quantity of data being generated, more automated hardware and computational methods will(More)
MicroRNAs (miRNAs) are nucleic acid regulators of many human mRNAs, and are associated with many tumorigenic processes. miRNA expression levels have been used in profiling studies, but some evidence suggests that expression levels do not fully capture miRNA regulatory activity. In this study we integrate multiple gene expression datasets to determine miRNA(More)