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Stephen R Master, MD, PhD

Stephen R Master, MD, PhD

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Assistant Professor of Pathology and Laboratory Medicine at the Hospital of the University of Pennsylvania
Department: Pathology and Laboratory Medicine
Graduate Group Affiliations

Contact information
613A Stellar-Chance Labs
422 Curie Blvd.
Philadelphia, PA 19104-6100
Office: 215-898-8198
Fax: 215-746-4650
A.B. (Molecular Biology)
Princeton University , 1990.
Ph.D. (Cell and Molecular Biology)
University of Pennsylvania School of Medicine, 2001.
M.D. (Medicine)
University of Pennsylvania School of Medicine, 2002.
M.S.T.R. (Translational Research)
University of Pennsylvania, 2011.
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Description of Research Expertise

The primary research focus of my laboratory is using systems biology to understand human tumor evolution. Specifically, I am interested in understanding how properties of cellular networks influence the specific sequence of mutations that can give rise to a tumor in a given cell type. Our primary approach utilizes bottom-up, high-resolution mass spectrometry in conjunction with protein microarrays to measure specific changes in the proteome and phospho-proteome characterizing cells at various points along the transformation pathway.

We are currently utilizing neuroblastoma as a model system. Neuroblastoma accounts for ~15% of childhood deaths due to cancer, and as such it is of substantial clinical significance. Additionally, neuroblastoma has several characteristic subtypes that appear to reflect alternative evolutionary pathways. For these reasons, it is an ideal model system in which to investigate the ways that cellular network properties influence and are influenced by specific genomic alterations. As an adjunct to these studies, we are analyzing changes in yeast protein-protein interactions resulting from telomere disruption in order to better understand the ways in which these types of data may contribute to our understanding of mammalian tumor behavior and aging.

A critical component of these investigations will be the ability to not only classify tumors on the basis of a proteomic and/or phospho-proteomic patterns but also to understand the combinations of changes in intracellular pathways that give rise to these patterns. We are currently designing studies that will allow us to create a library of proteomic patterns arising from defined cellular perturbations. We hypothesize that this library, in combination with an extension of bioinformatics techniques that we have previously used to interpret patterns in complex cellular mixtures, will allow us to detect disruption of a large set of known cellular pathways using MS-based proteomic profiling.

In addition to its use as a basic research tool for studying pathways of tumor evolution, such a library would also be of substantial clinical utility. Specifically, it would enable diagnostic interpretation of tumor specimens at the level of functional cellular subnetworks, thereby providing the necessary diagnostic platform on which a “personalized medicine” therapeutic approach can be based. Given the substantial potential of these approaches for clinical laboratory medicine, my laboratory is strongly interested in using this combination of proteomic profiling with novel bioinformatics analyses for both biomarker discovery and diagnostic translation in a number of disease states.

Description of Clinical Expertise

My clinical work is based within the Clinical Chemistry section of the Division of Laboratory Medicine. I have a particular clinical interest in quality control for highly multiplexed genomic (DNA microarray) and proteomic (tandem mass spectrometry or protein microarray) assays.

Selected Publications

Wertheim GBW, Smith C, Luskin M, Rager A, Figueroa ME, Carroll M, Master SR: Validation of DNA Methylation to Predict Outcome in Acute Myeloid Leukemia using xMELP. Clin Chem 61(1): 249-58, January 2015.

Liu KD, Yang W, Go AS, Anderson AH, Feldman HI, Fischer MJ, He J, Kallem RR, Kusek JW, Master SR, Miller ER, Rosas SE, Steigerwalt S, Tao K, Weir MR, Hsu CY: Urine Neutrophil Gelatinase-Associated Lipocalin and Risk of Cardiovascular Disease and Death in CKD: Results From the Chronic Renal Insufficiency Cohort (CRIC) Study. Am J Kidney Dis 2014, in press.

Arsenault PR, Heaton-Johnson KJ, Li LS, Song D, Ferreira VS, Patel N, Master SR (*), Lee FS (*): Identification of Prolyl Hydroxylation Modifications in Mammalian Cell Proteins. Proteomics Page: doi: 10.1002/pmic.201400398 (epub ahead of print), 2014, in press.

Babushok DV, Cardamone D, Rulander N, Master SR, Hexner EO: A Common, Under-Recognized Cause of Elevated Serum Erythropoietin. Am J Med Page: S0002-9343(14)00685-8, Aug 2014.

Song D, Li LS, Arsenault PR, Heaton-Johnson KJ, Master SR, Lee FS: Defective Tibetan PHD2 Binding to p23 Links High Altitude Adaptation to Altered Oxgen Sensing. J Biol Chem 289(21): 14656-65, May 2014.

Wertheim GBW, Smith C, Figueroa ME, Kalos M, Bagg A, Carroll M, Master SR: Microsphere-based Multiplex Analysis of DNA Methylation in Acute Myeloid Leukemia. J Mol Diagn 16(2): 207-15, Mar 2014.

Wing MR, Yang W, Teal V, Navaneethan S, Tao K, Ojo A, Guzman NN, Reilly M, Wolman M, Rosas SE, Cuevas M, Fischer M, Lustigova E, Master SR, Xie D, Appleby D, Joffe M, Kusek J, Feldman HI, Raj DS; for the Chronic Renal Insufficiency Cohort (CRIC) Study.: Race modifies the association between adiposity and inflammation in patients with chronic kidney disease: Findings from the CRIC study. Obesity (Silver Spring) Page: doi: 10.1002/oby.20692, Jan 2014.

Mehta NN, Matthews G, Krishnamoorthy P, Shah R, McLaughlin C, Patel P, Budoff M, Chen J, Wolman M, Go A, He J, Kanetsky PA, Master S, Rader DJ, Raj D, Gadegbeku CA, Shah R, Schreiber M, Fischer MJ, Townsend RR, Kusek J, Feldman HI, Foulkes A, Reilly MP, and the Chronic Renal Insufficiency Cohort (CRIC) Study Investigators: Higher plasma CXCL12 levels predict incident myocardial infarction and death in chronic kidney disease: Findings from the Chronic Renal Insufficiency Cohort Study. Eur Heart J Page: doi: 10.1016/j.jmoldx.2013.10.010, Dec 2013.

Raess P, ven de Geijn G-J, Njo T, Klop B, Sukhachev D, Wertheim G, McAleer T, Master SR (*), Bagg A (*): Automated screening for myelodysplastic syndromes through analysis of complete blood count and cell population data parameters. Am J Hematology Page: 10.1002/ajh.23643. [Epub ahead of print] Nov 2013 Notes: (*) co-corresponding authors, contributed equally.

Ferguson JF, Matthews GJ, Townsend RR, Raj DS, Kanetsky PA, Budoff M, Fischer MJ, Rosas SE, Kanthety R, Rahman M, Master SR, Qasim A, Li M, Mehta NN, Shen H, Mitchell BD, O'Connell JR, Shuldiner AR, Ho WK, Young R, Rasheed A, Danesh J, He J, Kusek JW, Ojo AO, Flack J, Go AS, Gadegbeku CA, Wright JT Jr, Saleheen D, Feldman HI, Rader DJ, Foulkes AS, Reilly MP; CRIC Study Principal Investigators.: Candidate gene association study of coronary artery calcification in chronic kidney disease: findings from the CRIC study (Chronic Renal Insufficiency Cohort). J Am Coll Cardiol 62(9): 789-98, Aug 2013.

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Last updated: 01/05/2015
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