Amanda G. Paulovich
Fellowship, Dana Farber Cancer Institute, Medical Oncology, 2004.
Postdoctoral Fellowship, MIT-Whitehead Center for Genomic Research, Computational Biology (Dr. Eric Lander), 2003.
Residency, Massachusetts General Hospital, Internal Medicine, 2000.
M.D., University of Washington, 1998.
Ph.D., University of Washington, Genetics (Dr. Leland Hartwell), 1996.
B.S., Carnegie Mellon University, Biological Sciences, 1988.
The focus of my laboratory is the study of human phenotypic variation. Sample projects include:
1. Development of high throughput, multiplexed technologies for targeted protein quantification in blood plasma and solid tissues. We use targeted multiple reaction monitoring mass spectrometry coupled to stable isotope dilution and anti-peptide antibody-based enrichment to measure the abundance of proteotypic peptides as surrogates for quantification of proteins of diagnostic interest. Initially, this work is being done in a highly controlled experimental system: inbred mouse strains genetically engineered to develop cancers. The use of mouse models allows us to minimize biological variation ("noise") and to generate as much sample as needed for technology development. Ultimately, we apply working technologies developed using the mouse model to measurement of candidate diagnostic markers in human patients.
2. Development of high throughput functional assays to determine human phenotypic variation in the cellular DNA damage response. The cellular response to DNA damage is clinically relevant in human cancer. For example, familial cancer syndromes mostly result from germline mutations that compromise the cellular DNA damage response. Second, somatic inactivation of the DNA damage response is ubiquitous in solid tumors and is associated with chromosomal instability. Third radiation and many chemotherapeutics used to treat cancers are DNA damaging agents. Little is known about naturally existing phenotypic variation in the DNA damage response amongst humans, aside from rare familial syndromes. To characterize phenotypic variation in the human population, we are developing high throughput, quantitative assays (e.g. ELISAs) to measure the kinetics of activation of the DNA damage response pathway following gamma-irradiation. Understanding human variation in this response may be clinically important for predicting risk for developing cancer as well as for predicting toxicity to cancer therapies. Also, because the cellular response to radiation is rapid, dose- dependent, time-dependent, and occurs at clinically relevant doses, these assays may also have utility for biodosimetry in the event of a nuclear disaster.
3. Elucidate the network of genes and pathways that buffer defects in the DNA damage response. The cellular DNA damage response shows robustness in that networks of multiple genes (from multiple cellular pathways) buffer the effects of defects in any one gene in the pathway. We use genetic studies in the model yeast Saccharomyces cerevisiae to discover interacting genes and pathways determining sensitivity to DNA damage, and we subsequently test for conservation of these interactions in human cells using RNA interference. The ultimate goals of these studies are to identify novel therapeutic targets, to discover novel tumor suppressor genes, and to understand the underlying molecular mechanisms of the cellular DNA damage response.
American Association for Cancer Research
American Association for Clinical Chemistry
American Chemical Society
American Society for Mass Spectrometry
FHCRC/UW Cancer Consortium
Molecular Signatures Database (MSigDB) Scientific Advisory Board
Radiation Research Society
Scientific Advisory Board, Bio-Rad Life Sciences
Steering Committee, International Biomarker Research Consortium
Steering Committee, NCI Affinity Reagents Project
Technology Advisory Board, Canary Foundation
Honors and Awards
2005, Roger Moe Award for Translational Research, Fred Hutchinson Cancer Research Center
2002-2003, Damon Runyon Research Fellowship, Abbott Fellow, Whitehead Institute Center for Genomics Research, DNA damage response, microarrays, computational biology
1992, Merck Distinguished Fellow Award, University of Washington, S phase regulation in yeast responding to DNA damage
1989, HHMI Research Fellowship, University of Washington, Characterization of transgenic mouse model of pancreatic cancer
1988, Carnegie Mellon Award for Outstanding Research, Carnegie Mellon University, Coordinate Regulation of a ribosomal protein gene family in yeast
1987, Genetics Society of America Undergraduate Research Fellowship, Carnegie Mellon University, Coordinate Regulation of a ribosomal protein gene family in yeast
1986, Beta Beta Beta National Biological Honor Society, Beta Beta Beta National Biological Honor Society
2005-2010, Assistant Professor, University of Washington, School of Medicine, Medicine, Oncology
2003-2009, Assistant Member, Fred Hutchinson Cancer Research Center, Clinical Research Division, Early Detection Initiative
CPTAC Assay Portal: a repository of targeted proteomic assays.. Nature methods. 11(7):703-4.. 2014.
Targeted Peptide Measurements in Biology and Medicine: Best Practices for Mass Spectrometry-based Assay Development Using a Fit-for-Purpose Approach.. Molecular & cellular proteomics : MCP.. 2014.
Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins.. Nature methods. 11(2):149-55.. 2014.
Panorama: A Targeted Proteomics Knowledge Base.. Journal of proteome research.. 2014.
Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels.. Molecular & cellular proteomics : MCP.. 2014.
The Human Salivary Proteome is Radiation Responsive.. Radiation research.. 2014.
High-Affinity Recombinant Antibody Fragments (Fabs) Can Be Applied in Peptide Enrichment Immuno-MRM Assays.. Journal of proteome research. 13(4):2187-2196.. 2014.
Connecting genomic alterations to cancer biology with proteomics: the NCI Clinical Proteomic Tumor Analysis Consortium.. Cancer discovery. 3(10):1108-12.. 2013.
Interlaboratory evaluation of automated, multiplexed peptide immunoaffinity enrichment coupled to multiple reaction monitoring mass spectrometry for quantifying proteins in plasma.. Molecular & cellular proteomics : MCP. 11(6):M111.013854.. 2012.
Peptide immunoaffinity enrichment coupled with mass spectrometry for peptide and protein quantification.. Clinics in laboratory medicine. 31(3):385-96.. 2011.
Blood-based detection of radiation exposure in humans based on novel phospho-Smc1 ELISA.. Radiation research. 175(3):266-81.. 2011.
A targeted proteomics-based pipeline for verification of biomarkers in plasma.. Nature biotechnology. 29(7):625-34.. 2011.
Evaluation of large scale quantitative proteomic assay development using peptide affinity-based mass spectrometry.. Molecular & cellular proteomics : MCP. 10(4):M110.005645.. 2011.
Proteome and transcriptome profiles of a Her2/Neu-driven mouse model of breast cancer.. Proteomics. Clinical applications. 5(3-4):179-88.. 2011.
Quantification of proteins using Peptide immunoaffinity enrichment coupled with mass spectrometry.. Journal of visualized experiments : JoVE. (53). 2011.
Lymphatic endothelial murine chloride channel calcium-activated 1 is a ligand for leukocyte LFA-1 and Mac-1.. Journal of immunology (Baltimore, Md. : 1950). 185(10):5769-77.. 2010.
An automated and multiplexed method for high throughput peptide immunoaffinity enrichment and multiple reaction monitoring mass spectrometry-based quantification of protein biomarkers.. Molecular & cellular proteomics : MCP. 9(1):184-96.. 2010.
Repeatability and reproducibility in proteomic identifications by liquid chromatography-tandem mass spectrometry.. Journal of proteome research. 9(2):761-76.. 2010.
Automated screening of monoclonal antibodies for SISCAPA assays using a magnetic bead processor and liquid chromatography-selected reaction monitoring-mass spectrometry.. Journal of immunological methods. 353(1-2):49-61.. 2010.
Interlaboratory study characterizing a yeast performance standard for benchmarking LC-MS platform performance.. Molecular & cellular proteomics : MCP. 9(2):242-54.. 2010.
Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses.. Molecular & cellular proteomics : MCP. 9(2):225-41.. 2010.
Effect of collision energy optimization on the measurement of peptides by selected reaction monitoring (SRM) mass spectrometry.. Analytical chemistry. 82(24):10116-24.. 2010.
Antibody-based screen for ionizing radiation-dependent changes in the Mammalian proteome for use in biodosimetry.. Radiation research. 171(5):549-61.. 2009.