Cancer is characterized by genetic heterogeneity that is caused by tumorigenesis. Several research groups have begun to measure the degree of genetic heterogeneity in tumors to establish the impact of heterogeneity on cancer diagnostics, prognosis, and selection and monitoring of treatment. This tutorial shows how researchers at the Children’s Hospital in Boston, the Klinikum Rechts der Isar in Munich, and The University of Texas M.D. Anderson Cancer Center use Advalytix’ AmpliGrid single-cell molecular analysis platform in their quest to improve cancer diagnostics, prognostics, and treatment.
Laurie Jackson-Grusby, Ph.D., of the Children’s Hospital Boston, is working to improve diagnostic methods and treatment of brain cancer. Her research aims to uncover the mechanisms of epigenetic control that permit self-renewal of cancer stem cells, and to describe phenotypes that characterize cancer stem cells. Ultimately, her research could lead to the development of drugs that specifically target stem cells to stop a tumor’s ability to spread.
Using flow cytometry, Dr. Jackson-Grusby tests potential stem cell markers by sorting stem cells into groups that are enriched for markers of interest vs. groups that do not express those markers. She then tests the ability of either group to form a tumor by injecting those cells into mouse brains, and also tests the stem cell self-renewal properties in cell culture. The idea that tumors originate from rare, individual cells is tested in these experiments by using the AmpliGrid platform (Figure) for mutation and epi-mutation analysis of individual cells.
Assuming stem cells differ in gene expression from nonstem cells, and that only a sub-population of enriched cells has the ability to self-renew, Dr. Jackson-Grusby’s team uses single-cell genetic analysis on marker-enriched cell fractions along with population-based qPCR to identify candidate genetic and epigenetic changes that might identify tumor-initiating or cancer stem cells.
Since gene-expression analysis destroys the cells, geno-phenotype cannot directly be associated with cell function. Therefore, the group translates expression hypothesis using immuno-enrichment to refine cell populations in each successive experiment. Using this iterative approach, the group expects to define more and more accurate phenotypes of stem cells.