Cell therapy is a major hope for future tailored therapy in many human diseases and cytometry is a central player in its development. The technologies and assays developed for quantitative analysis of individual cells and cell systems is of major importance in the development of cell therapy, clear-cut identification of cell based diseases like cancer, as well as monitoring success of the therapy.
It is crucial for personalized medicine to unequivocally identify disease types for individualized therapy. Until today, state of the art for judging histological specimens in the pathology laboratory is done by the experienced pathologists. Unfortunately, standardization of this expertise is hardly possible, sometimes rendering contradictory results. In addition, institutions that lack such experts need to send their material to other laboratories which becomes difficult for remote places, if possible at all.
Manifold approaches have been made to automate and standardize histopathology and make it quantitative (1). Now, Orlov and colleagues from Baltimore and Bethesda, Maryland, Philadelphia, Pennsylvania and Southfield, Michigan, USA (this issue, page 364) developed an image based method for tissue microarrays in order to automate detection of the progression of melanomas. The authors analyzed automatically acquired microscopic images of hematoxylin/eosin stained tissue microarrays containing melanoma sections at different stages of the disease progression. Using their algorithm they could “teach” the software to learn differences between various tumor stages and healthy tissue. This algorithm was then able to identify unknown specimens in a test set with high sensitivity and specificity. It turned out that color is an important discriminator.
Whereas the above approach was based on morphological criteria, single cell analysis in tissues may have additional benefits for classification. However, single cell identification by segmentation algorithms is still challenging and prone to failure (2). Mashburn and colleagues from Nashville, Tennessee, USA (this issue, page 409) developed a new interactive algorithm, termed SeedWater Segmenter to identify and track individual cells in cell cultures. Their test system was a primary strain of Drosophila melanogaster expressing cadherin-GFP fusion protein so that cell boundaries were visible in confocal fluorescence images. The authors report that their approach is based on a simple and useful paradigm, the interactive manual segmentation correction using direct seed manipulation. It fills a niche as a convenient tool for extremely accurate tracking of cells in living tissues.
Cell based therapy of tumors and metastasis by preconditioned lymphocytes that become primed for the specific tumor cells of the excised tumor of a patient is an emerging technology for personalized therapy of minimal residual disease (3). This so-called adoptive cell therapy requires thorough quality control which is the detailed characterization of the cell products that are to be administered to the patient. Among others, purity of the lymphocytes and freedom from live tumor cells needs to be proven. By a sophisticated panel of live/dead discrimination as well as an antibody cocktail staining for extra- and intracellular tumor antigens, Richards and colleagues from Milwaukee, Wisconsin, USA (this issue, page 374) present an important flow-cytometry assay to characterize and quantitate contaminating tumor cells from primary cultures of excised tumors. The authors conclude that flow cytometry could be an alternative method to immunohistochemistry due to its higher sensitivity and statistical accuracy.
Important additional information that would be useful in targeted therapy is to characterize the lymphocytes intended for adoptive transfer with respect to their more detailed phenotyping and biological function. This functional characterization would include also their ability to specifically respond to tumor derived antigens with cytokine secretion. In this regard, the polychromatic panel developed by Lamoreaux and colleagues from Bethesda, Maryland, USA (OMIP-009, this issue, page 362) for the characterization on antigen-specific human T-cells could be of substantial relevance. The related and similar polychromatic panel shown in OMIP-005 and developed by Foulds and colleagues, also from Bethesda (this issue, page 360) is designed to study T-cell response in Rhesus Macaques.
The OMIP-009 panel allows characterizing antigen specific human T-cells based on phenotypic markers and chemokine receptor and cytokine expression. It could therefore presumably provide a useful tool for characterizing antigen specific response of tumor specific T-cells prior to their therapeutic application. OMIP-009 would be of substantial relevance for translational therapy studies in test animals.
The formation of microparticles could be an interesting candidate parameter for testing of the effect and efficacy of adoptive transfer in vitro and in the patient. Microparticles (also termed microvesicles or exosomes) can be characterized and counted by flow cytometry (4). They are abundant in human plasma and are found in elevated numbers in inflammatory, cardiovascular and certain tumor diseases. These particles can then stem from stressed or apoptotic tissue. The particles can also be assigned to the specific cells from which they came from because they are carrying cell specific antigens on their membrane that can be labeled by monoclonal antibodies and identified by flow cytometry.
Holtom and colleagues from London and Hatfield, United Kingdom (this issue, page 390) developed a straight forward in vitro assay to study microparticle formation of endothelial cells of the umbilical artery when in contact with blood leukocytes under flow conditions. This study continues the earlier work of the group wherein they used cultured endothelial cells from human umbilical cord as target cells in a flow system and microparticle characterization and quantitation by flow cytometry (5). Using their novel flow system that has more similarity to biological reality, the authors could characterize microparticles derived from endothelium, leukocytes and, surprisingly, massively from erythrocytes under flow conditions.
In conclusion, there are manifold methods under development or that have reached maturity to be adapted into the clinical work-flow for cell therapy using cytometry technologies. Importantly, most of the above reported studies wherein flow cytometry was used were prepared according to the MIFlowCyt standards (6) providing high quality studies applicable for a broad audience.