Spatiotemporal Genomic Analysis to Identify and Extract Rare Cancer Cells


Isolation and analysis of phenotype and genome of rare cell types within a tumor for research and potential diagnostics.

Key Benefits

  • Allows the identification of a single cell or group of cells within a tumor sample using phenotypic criteria.
  • Enables both phenotypic and genetic analysis of the same rare cells within a tumor.

Market Summary

For many years, tumors were thought to be homogeneous, made up of a single proliferative cancer cell type. Today, tumors are thought to be comprised of a variety of cell types. Cells within a tumor can vary across cellular morphology, gene expression, metabolism, motility, proliferation, and metastatic potential. This heterogeneity is believed to contribute to challenges faced by oncologists in designing effective treatment strategies because not all cells will respond the same to a single therapy. Tools are needed to study rare cell types within a tumor and connect genomic information to a particular subset of rare tumor cells.

Technical Summary

Emory University researchers have developed a method for precisely selecting a single cell or group of cells from a tumor sample. This method allows the collection of both morphological and phenotypic information about those tumor cells as well as gather specific genetic information of those same cells. The cells are selected using cellular imaging and the target cells are exposed to UV light to precisely photoconvert the photoconvertible fluorophore in the cells. This is followed by cell sorting to isolate those marked cells. Genomic analysis of choice may then be run on the sorted cells of interest, and cells are viable post-sorting for molecular analysis. This technique may contribute to better understanding of rare subpopulations in tumors as well as development of cancer therapeutics.

Developmental Stage

Currently being used to identify new diagnostic panels and screen for oncology drugs.

Publication: Konen, J. et al. (2017) Nature Communications, 8.

Patent Information

Tech ID: 14176
Published: 7/13/2017