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faculty
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David
M. Lubman
Maude T. Lane Professor
of Surgery,
Professor of Pathology, Professor of Chemistry
Ph.D., Stanford University
Biological Mass Spectrometry, Proteomics, Cancer Research, Biological
Separations, Glycoproteomics, Biomarkers, Stem Cell Research
Phone: (734) 647-6945
(734) 647-8834
E-mail: dmlubman@umich.edu
Lubman
Research Laboratory
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Our
group is involved in developing novel biotechnologies
to solve difficult biological problems. The focus
of the work has been in the field of Proteomics
and Cancer Research. Proteomics involves the
study of the protein expression of a cell, where
proteins are the entities that perform the functions
of the cell. Our work has involved developing
methods to profile large numbers of proteins
expressed by cancer cells and to understand how
these proteins are different than those observed
from normal cells. Proteins that are modified
or overexpressed in cancer cells often result
in new protein pathways that lead to tumorogenesis
and metastasis of the cancer.
We
have developed a total liquid 2-dimensional separations
method based upon isoelectric focusing in the
first phase followed by nonporous RP HPLC to
generate an image of the protein content of a
cell lysate. The proteins in the liquid phase
can then be analyzed by electrospray-TOF mass
spectrometry to produce a molecular weight map
of the proteins in the cell up to 100 kDa. In
addition, tryptic mapping and MALDI-TOF MS can
be used to identify proteins against various
computer DNA databases. The result is that comparisons
can be made between different cancer cell lines
to identify proteins that might be important
biomarkers of cancer. These proteins are often
important in cancer development and the identification
of such proteins is being used by collaborators
to develop drugs to specifically act against
these proteins to impede cancer growth. Further
details on the structure of proteins identified
as important to cancer are being determined using
sequencing by capillary electrophoresis/TOF-mass
spectrometry, where changes in sequence and posttranslational
modifications can be determined. Tissue microarrays
are being used to learn about the response
of antibodies to these proteins in different
tissue samples.
Ultimately, proteins identified
as being important to a specific type of cancer
are being developed into a protein chip format
as a means for early diagnosis of cancer. Biostatistics
are being used to determine which proteins
are important in cancer transformation and
how different cancers can be classified according
to the protein expression of the cell.
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AWARDS
- Eli
Lilly Postdoctoral Teaching Fellow William
F. Meggers Award of the Society for Applied
Spectroscopy Research
Fellow, Alfred P. Sloan Foundation American
Association for the Advancement of Science
Fellow
- R & D
100 Innovation Award
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REPRESENTATIVE PUBLICATIONS
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Kan Zhu, Jia Zhao, David M. Lubman, Fred R. Miller, and Timothy J. Barder, "Protein PI Shifts Due To Post-Translational Modifications In The Separation And Characterization Of Proteins", Anal Chem, 2005, 77, 2745-2755.
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Y. Wang, R. Wu, K.R. Cho, K.A. Shedden, T.J. Barder, D.M. Lubman, "Classification of Cancer Cell Lines using an Automated 2-D Liquid Mapping Method With Hierarchical Clustering Techniques", Molecular and Cellular Proteomics, Molecular and Cellular Proteomics,2006, 5(1), 43-52.
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Manoj Pal, Allison Moffa, Arun Sreekumar, Stephen P. Ethier, Arul Chinnaiyan and David M. Lubman, "Differential Phosphoprotein Mapping in Cancer Cells Using Protein Microarrays Produced From 2-D Liquid Fractionation", Anal Chem, 2006, 78, 702-710
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Jia Zhao, Kan Zhu, David M. Lubman, Fred R. Miller, and Timothy J. Barder, "Proteomic Analysis of Estrogen Response of Premalignant Human Breast Cells Using a 2-D Liquid Separations/Mapping Technique", Proteomics, 2006, 6, 3847-3861.
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Jia Zhao, M.A. Anderson, D.M. Simeone, D.M. Lubman, "Protein Markers of Pancreatic Cancer in Human Serum Using Lectin Selected Sialic Acid Glycoproteins With Mass Spectrometric Analysis", Journal of Proteome Research, 2006, 5(7), 1792-1802.
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