Biomedical Engineering Reference
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prognostic in a disease. In a preclinical research setting, a set of inhibitors chosen to
target a profile of signaling events specifically observed in a patient's cancer cells
could be studied in primary cancer specimens. A tailored therapy may be no better
than a single-agent inhibitor. However, the potential exists that a tailored therapy will
be far more effective at killing cancer cells—and only cancer cells—if based on
multiple unique signaling features of each disease. Single-cell assays for cell death
can help determine the cell-type specificity of therapies in primary patient samples.
Flow cytometry reveals whether all the disease cells are being killed or only a
subpopulation. Finally, a validated clinical signaling profile can be used when
designing a clinical trial to initially stratify patient risk, guide patients toward the
trial, balance treatment arms of the trial, and measure, as a corollary end point,
changes in the signaling profile over time.
15.6.3 Measuring and Targeting Cell Subsets
As discussed in Section 15.5, a key advantage of flow cytometry is the ability to track
multiple populations of cells and to know which cell types are inhibited, when
conducting assays. In primary tumor samples from cancer patients, tumors have
variable, but significant, nonmalignant immune cell infiltrate [23]. Flow cytometry
analysis of live cells from cryopreserved lymphoma tumor samples allows simulta-
neous study of both cancer cells and the patient's immune system cells. We used
single-cell signaling profiles to identify cell-intrinsic changes to BCR signaling
kinetics that distinguished lymphoma B cells from nonmalignant B cells within a
patient's tumor [26]. The same approach can also be applied to dissect signaling in
developmental subsets of healthy cells, providing a valuable reference point for
characterizing abnormal signaling in tumor cells.
In studies of clinical therapeutics, the ability to measure the effects of a therapy in
all patient sample cells is significant advantage of single-cell assays. Signaling
inhibitors may have greater potency in killing primary human cancer cells while
remaining below the threshold of toxicity to adjacent nonmalignant cells that are less
dependent on abnormal signaling events. For example, for a B cell cancer, the effects
of a drug on lymphoma B cells, tumor-infiltrating T cells, and nonmalignant B cells
might be compared. An ideal drug might induce apoptosis specifically in the cancer
B cells, while having minimal toxicity against the healthy cells. With flow cytometry,
researchers can identify control cell populations within a single well of a plate,
providing confidence that all cells were treated with equivalent conditions during an
experiment.
In addition to comparing tumor and nonmalignant subsets, flow cytometry can
identify subpopulations within the tumor that have distinct signaling profiles and
these subsets can be related to the patients' clinical outcomes [19]. Defining tumor
heterogeneity in terms of signaling cell subsets gives us insight into the complexity of
individual patient's disease. Populations such as cancer stem cells, evolving tumor
subclones, or therapy-resistant cell subsets could be identified by flow cytometry and
tracked over time.
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