Label-Free Flow Cytometry For Cancer Cell Discrimination - Project Summary
Flow cytometry is a workhorse technique in research and development as well as in clinical laboratories for
diagnosis and monitoring of disease. Standard flow cytometers use fluorescent tags, often conjugated to
monoclonal antibodies, to give qualitative and quantitative information about specific molecules in the cell on a
cell-by-cell basis at very high throughput.
Metabolic imaging of cancer cells relying on measurements of the inherent fluorescence of the ubiquitous
metabolic co-enzyme NADH (the reduced form of nicotinamide adenine dinucleotide), particularly the
fluorescence lifetime of NADH, yields a robust, generalized indicator of carcinogenesis. This is based on the
well-established ‘Warburg Effect’, a shift from oxidative phosphorylation to glycolysis as the preferred
metabolic pathway in many cancer cells, and the involvement of NADH as a key player in both of these
pathways. However, most of this work has been done in the field of fluorescence lifetime imaging microscopy
(FLIM), a low-throughput method not amenable to development of a clinical diagnostic assay. Translating this
method to high-throughput flow cytometry would pave the way for such a clinical diagnostic test.
Since the 1990’s, efforts to implement lifetime measurements in flow have been hampered by a variety of
technical barriers associated with hardware cost and speed, and computationally intense analysis. This work
overcomes these obstacles, leveraging an existing fluorescence lifetime flow cytometry platform and modifying
it to create a built-for-purpose tool for cancer cell analysis using NADH fluorescence lifetime that also employs
an innovative method for rapid data analysis which would enable on-line analysis and cell sorting. Feasibility
will be demonstrated by challenging the system with a comprehensive set of verification and validation tests.
The method requires no exogenous cell labeling, relying instead on the inherent fluorescence of NADH. This
instrument will provide a unique, high-throughput, label-free method for cancer cell discrimination at the single-
cell level compatible for use on both blood-borne cancer cells and dissociated cells from solid tumors. Such an
instrument would speed cancer drug development; have utility in cancer diagnostics and monitoring cancer
treatment; help identify and understand tumor heterogeneity and treatment-resistant subpopulations of cells;
and could enable development of personalized treatment regimens.
