Clinical and biological specimens are often available in limited amounts, which greatly hampers the progress in diagnostics, therapy development and biomedical research. Microbiopsy and liquid biopsies containing rare cell populations such as circulating tumor cells, hematopoietic stem cells (HSCs) and immune cells may contain only low thousands of cells, and be heterogeneous. Proteins and their post-translational modifications (PTMs) are an essential component of all biological processes and therefore, there is a critical need for deep proteomic profiling of clinical and biological samples of limited amounts (e.g. only a few 10s or 100s cells). Yet, such comprehensive analysis cannot be readily conducted and many clinically relevant proteomics-based studies are not undertaken because the lack of technology for such low level samples. The overall goal of the proposed research is to develop new on-line integrated technologies for deep proteomic profiling of rare hematopoietic and immune cells using limited volumes of blood. The proposed on-line integrated platform that will combine novel highly efficient techniques for sample processing, ultralow flow separation and MS-based proteomic analysis to minimize sample losses, enhance the depth of molecular characterization of rare cells in limited amounts of biological fluids and improve our understanding of HSC signaling and differentiation mechanisms. Further development of the proposed high sensitivity platform will ultimately allow molecular profiling of isolated single cells and their microenvironments (e.g., stem cell niche). This project will be carried out by a strong interdisciplinary team with world-class expertise in bioanalytical chemistry and MS- based proteomics (Ivanov), microfluidics (Murthy), hematopoiesis and cancer biology (Frank). Building on our strong preliminary data in ultralow flow rate separation, analysis of complex proteomes, proteins, nESI-MS interfacing, microfluidics and bioinformatics, the following goals will be pursued: (i) develop on-line sample preparation technique to process samples of the order of few hundred cells or less and ultimately enable deep profiling of individual cells; (ii) couple the ultra-low flow-based analytical techniques with a microfluidic cell isolation device and sample preparation techniques for integrated procurement, processing, molecular characterization and phenotyping of rare cells without losses; and (iii) apply the developed analytical platform to enable processing, deep profiling and molecular phenotyping of rare hematopoietic stem cells. The development of the proposed analytical platform is critical for determining the outcome in patients undergoing hematopoietic stem cell transplantation for the treatment of leukemia. Such platform with the ability of comprehensive proteome profiling from such small sample size will provide a quantum leap in the information that can be obtained from routine clinical specimens, and provide the underpinnings for a new level of personalized medical care.

Public Health Relevance

The proposed research will be focused on technology development for deep proteomic analysis of rare cells in limited amounts of biological fluids. Comprehensive proteome characterization of such samples is presently a formidable challenge, and the proposed technology offers an unprecedented opportunity for biological insight into molecular mechanisms of disease processes and discovery of biomarkers for diagnostic, prognostic and theranostic purposes. OMB No. 0925-0001/0002 (Rev. 08/12 Approved Through 8/31/2015) Page Continuation Format Page

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM120272-01
Application #
9158675
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Edmonds, Charles G
Project Start
2016-09-01
Project End
2020-08-31
Budget Start
2016-09-01
Budget End
2017-08-31
Support Year
1
Fiscal Year
2016
Total Cost
$371,593
Indirect Cost
$110,343
Name
Northeastern University
Department
Type
Organized Research Units
DUNS #
001423631
City
Boston
State
MA
Country
United States
Zip Code
02115
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Kreimer, Simion; Belov, Mikhail E; Danielson, William F et al. (2016) Advanced Precursor Ion Selection Algorithms for Increased Depth of Bottom-Up Proteomic Profiling. J Proteome Res 15:3563-3573