WARF: P180292US02

Method and Device to Screen and Sort Cancer Immunotherapy Cells


Melissa Skala, Alexandra Walsh

The Wisconsin Alumni Research Foundation (WARF) is seeking commercial partners interested in developing optical technology for sorting T cells by activation state. This non-invasive method uses the autofluorescence signals of NAD(P)H and FAD to determine T cell activation state without the use of contrast agents or requiring tissue/cell fixation.
OVERVIEWA new cancer treatment being studied at a few major centers including UW Health is CAR T (Chimeric Antigen Receptor T cell) therapy. CAR T therapy uses a patient's own cells and 'reengineers' them to fight cancer. The procedure starts with removing the patient's T cells from the blood and sending them to a lab where they are altered to produce cancer-fighting proteins called chimeric antigen receptors (CARs) on their surface. These 'supercharged' or activated T cells are multiplied at the lab, and then shipped back to the hospital where they are reinjected into the patient's blood.

Determining T cell activation is imperative for studying these cells in vivo and for quality control of cell therapies like CAR T. Current methods to determine T cell activation (e.g., flow cytometry, cytokine release assay) are either invasive, requiring the use of contrast agents and possibly tissue/cell fixation, or cannot capture population heterogeneity.
THE INVENTIONUW–Madison researchers have developed a highly accurate label-free method to non-invasively detect T cell activation by detection of free-NAD(P)H fraction, NAD(P)H α1. NAD(P)H α1 can be measured by fluorescence lifetime imaging or spectroscopy systems. The device could also sort T cells based on NAD(P)H α1. If increased accuracy of T cell activation is needed for a specific application, additional measurements of the other NAD(P)H and FAD autofluorescence endpoints can be obtained and used for classification.
  • Screening and sorting T cells
  • Non-invasive and contrast agent-free
  • Classification accuracy exceeds 95 percent
STAGE OF DEVELOPMENTMost of the difference between the activated and not activated T cells comes from one feature, NAD(P)H α1. Using only this top feature, the classification accuracy is 97 percent. Accuracy increases to around 99 percent for the CD8 specific subset of T cells.
Contact Information
For current licensing status, please contact Jeanine Burmania at or 608-960-9846.
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