Recent evidence has shown that the capacity of a tumor to grow and propagate is dependent on a small subset of cells within a tumor. According to this idea malignant tumors are comprised of a small subset of distinct cancer stem cells (typically <5% of total tumor cells based on cell surface marker expression) which have great proliferative potential, as well as more differentiated cancer cells, which have very limited proliferative potential. These cells are termed cancer stem cells since, like normal stem cells, they can self-renew and produce differentiated progeny. These cancer stem cells can be differentiated from tumor cells based on their surface cell markers and it has been shown that there are several different populations of cancer stem cells defined by unique surface markers which may result in different proliferative potentials. A major issue in cancer stem cell research has been the identification of surface markers to identify the presence of cancer stem cells and their subpopulations which may represent different levels of aggressiveness. We have used cell flow sorting, glycoproteomics and mass spectrometry to identify the presence of potential cancer stem cells and their subpopulations in neurosphere cultures of glioblastoma multiforme (GBMs), a very aggressive form of brain cancer. The surface markers associated with these cancer stem cell populations can then be used to identify the presence of these cancer stem cells and the different subpopulations in tissue sections using fluorescent antibody staining against the surface glycoproteins of various grades of glioma tissue including early benign disease to the very aggressive GBM grade 4. This work will identify the presence of surface markers for aggressive cancer stem cells that are unique to late stage disease versus benign tissue. The cancer stem cells identified from the tissue sections using immunohostochemistry will then be captured using laser immuno-fluorescence microdissection and analyzed by nanoLC-MS/MS to provide a signature of the major proteins and pathways in each of the cancer stem cell subpopulations. Also, the surface glycoproteins of the cancer stem cell populations in these tissue sections will be analyzed using micro-monolithic lectin columns that can extract glycoproteins from very small samples. These tissue experiments will identify the variations in cancer stem cell populations, their surface markers and the major pathways involved over a sample population in human GBM samples. Ultimately, this information will be used to study human biopsy samples of GBMs from the area of the tumor and from normal tissue near the tumors where the cancer stem cells may have infiltrated. The use of lectin micro-monoliths together with Multiple Reaction Monitoring mass spectrometry will allow us the ability to detect relatively small numbers of cancer stem cells that may have infiltrated into normal tissue based on unique protein signatures. This information will be essential for cancer therapy, treatment and prognosis.

Public Health Relevance

The proposed research project will provide a means of studying the unique surface markers that identify the presence of a limited population of cancer stem cells and their subpopulations in glioblastoma multiforme, a very aggressive form of brain cancer. Analysis of tissue sections using laser immuno-fluorescence microdissection, micro-monolithic columns and mass spectrometry will be used to study the variation in cancer stem cell populations in human tissues and to detect them in tissue biopsies. The ability to study the subpopulations of cancer stem cells will be essential for therapy, treatment and prognosis of this deadly disease.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
4R01GM049500-18
Application #
9059745
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Edmonds, Charles G
Project Start
1994-09-12
Project End
2017-04-30
Budget Start
2016-05-01
Budget End
2017-04-30
Support Year
18
Fiscal Year
2016
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Surgery
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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