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- SUMMARY AND PERSPECTIVES
- LITERATURE CITED
Cytomics is a novel perspective from which to look at life. As with genomics and proteomics before, this discipline requires novel and innovative techniques and technologies to focus on its substrate of research—the cytome. With cytomics being the discipline that analyzes cellular systems and their interdependencies, advanced microscopy represents a key technology in cytomics research. Yet, conventional microscopy-based investigations, i.e., “look and conclude” analyses, do not meet the major cytomics criteria of 1) relating multiple parameters to each other, 2) within large populations of cells, 3) on a single-cell basis, and 4) in a quantitative and observer-independent manner. However, emerging improvements in the fields of fluorophore technology, sensitive fluorescence detection devices, and sophisticated image analysis procedures, are important and necessary steps into the cytomics era. Tissue represents an important class of cytomes, hence tissue cytometry—on the single cell level—can be expected to become an important cytomics technology. In this report, the techniques and technologies of microscopy-based multicolor tissue cytometry (MMTC) are outlined and applications are discussed, including the phenotypic characterization of tissue infiltrating leukocytes, in situ quantification of proliferation markers and tumor suppressors, and in situ quantification of apoptosis. © 2004 Wiley-Liss, Inc.
With the advent of cytomics, an increasing amount of cellular parameters and molecular markers, as well as their interrelations (1, 2), have to be determined on a single-cell level and in a quantitative manner. This means a substantial challenge to microscopy. However, the vast majority of microscopy-based investigations are currently evaluated visually, in a ‘look and conclude’ manner. Although important gross effects can be observed by a human observer, complex interdependencies among and between different cellular events are often beyond our observation capabilities and remain undiscovered. In cytomics approaches, however, techniques are required that permit quantitative analysis of multiple markers and of an unlimited number of single cells simultaneously, instead of just visual evaluation.
To date, several techniques of slide-based cytometry have been introduced and have been applied to biomedical research (3–11). Moreover, first clinical applications have been addressed and have yielded promising results (12–17). Advanced instruments for slide-based cytometry typically offer: 1) recognition of single objects by utilizing fluorescence of antigenic markers or DNA dyes; 2) fluorimetric determination of the mean relative intensities of all recognized objects in all channels (colors), whereby the localization of analyzed cells is known; 3) computation of the number of positive objects depending on their fluorescence staining pattern, size, and shape; and 4) definition of cellular subpopulations and statistical evaluation. Available instruments comprise laser scanners as well as charge-coupled device (CCD)-based imaging.
Although current techniques can be applied to tissue sections and cell monolayers, automated and quantitative analysis of tissue sections (i.e., tissue cytometry) is an extremely difficult task. The reason for this difficulty relates to a major problem in medical image analysis that is both old and current: pattern recognition (8, 18–20). This is particularly true in cytomics, in which tissue cytometry on a single-cell level is required. Identification of individual cells in tissue context is a challenging task, because tissues are complex structures composed of a variety of changing attributes. On the one hand, there is a high redundancy with many (optically distinguishable) features being common to most or even all types of cells, and, on the other hand, there is a high variability in particular structures characteristic of certain cell types, and there are many exceptions to the rule. Additionally, individual tissue cells stay in close contact, making it difficult, not only some of the time, but most of the time, to separate them optically and to distinguish between neighboring cells. Hence, a first and major challenge in tissue cytometry in terms of a cytomics technique is reliable recognition of individual cells in tissue context.
In order to address this challenge, our group previously introduced a method for slide-based cytometry utilizing a commercial confocal laser scanning microscope LSM 510/META (Zeiss, Jena, Germany) and advanced image analysis (21). The motorized microscope Axiovert 200M (Zeiss) has been fully automated. Only the scanning area and the instrument settings (laser, filters, channel assignment) have to be defined by the user. Once the data acquisition procedure has been started, the entire area of interest is scanned without the need for a user being present. The control software performs an autofocus and systematic data storage for each field of view (i.e., image) scanned. After data acquisition has been completed, the analysis procedure starts, using predefined search strategies (e.g., for leukocytes) and protocols (i.e., parameters for the selected search strategy). Identification strategies continue to be developed for automated recognition of individual cells using multiple antigenic markers and/or DNA dyes and advanced pattern-recognition algorithms. These algorithms can be used in microscopy-based multicolor tissue cytometry (MMTC) for various purposes, e.g., subclassification of tissue infiltrating leukocytes, measurement of tumor marker (co-)expression, and quantification of apoptosis in defined cell types in situ—all at the single-cell level.
In this report, we will present an overview of the current state-of-the-art, outline recent applications, and discuss some future perspectives.
SUMMARY AND PERSPECTIVES
- Top of page
- SUMMARY AND PERSPECTIVES
- LITERATURE CITED
MMTC is capable of objectively evaluating the intrinsic advantages of immunohistology, i.e., phenotypic characteristics in correlation with morphologic features, and to provide a standardized method for improved differential analysis. Variable methods for recognition of individual cells in tissue context have been successfully applied. In general, the use of tissue cytometry in biomedical research and clinical diagnosis, as well as approaches towards predictive medicine (30, 31), could contribute to improved patient care. Using MMTC, the investigator may get 1) very detailed analyses of single immunofluorescent images or 2) evaluation of large image series analyzed for thoroughly defined areas of interest, which will presumably be required more frequently. While immunohistology so far has been primarily based on just visual “look and conclude” evaluations, observer-independent numerical data are now available based on an arbitrary number of single measurement values.
MMTC is prepared to be used to analyze as many channels as necessary. The number of channels that can be analyzed simultaneously is limited only by the detection device used. When equipment for spectral imaging (e.g., Zeiss LSM META) is used, analysis of eight (23) or more channels appears to be feasible. When conventional microscopes with band-pass filters and a CCD-camera are used, the number of channels that can be synchronously analyzed will usually be limited to three or four. However, CCD-based imaging is faster than laser scanning and the respective equipment for CCD-based imaging is significantly cheaper than for laser scanning. Hence, it depends on the application (clinical routine: primarily fast, versus research applications: primarily sophisticated) as to which equipment is most appropriate. Regardless of these requirements, MMTC can be done with both laser scanners and CCD imagers, as well as band-pass and spectral imaging devices. In the context of cytomics, MMTC is especially useful in combination with advanced detection techniques in fluorescence microscopy. A combination of spectral imaging (23, 32, 33) and advanced image analysis currently permits multicolor tissue cytometry on the single-cell level with eight parameters (antigens); in the future this combination may allow the use of even more parameters.
It could be further envisaged that MMTC will be appropriate to routinely analyze tissue specimens for which it has so far been difficult or impossible to determine the phenotypic characteristics in situ. We expect that with the advent of cytomics, tissue cytometry in general, and tissue cytometry on the single-cell level in particular, will become a standard requirement for the determination of tissue status for various types of disease—from malignant and benign neoplasia to autoimmune disorders. The quantitative determination of immunophenotypically-identified cell populations in tissue sections will significantly increase both our knowledge and understanding of cytologic relations and the diagnostic capacity (34). Cells with similar or identical morphology but different phenotype (function) can be discriminated from each other and the cytologic in situ tissue measurements are orders of magnitude more accurate than what has been available before.
Using MMTC, excellent results of tissue cytometry were obtained despite the short time required for evaluation. Due to the automated processing of measurements, the problem of observer-dependant discrepancies, as reported by several authors (35–38), is avoided, and results are highly reproducible (21). These results refer to the protein-level, the single cell and its localization, and the distribution of the protein under investigation within the tissue section. In contrast to PCR-based methods and biochips (for review see39,40), MMTC never leaves unanswered the question of whether a protein is present or not. Of special interest in routine cancer diagnosis are the predictive value of cell-cycle related proteins and tumor suppressor proteins. The samples may be huge specimens of solid tissues, as with tumor nephrectomy, but may also be biopsy material. Therefore, the potential applications of MMTC go beyond the field of oncology; it is, for example, also qualified for monitoring the allograft status after transplantation by determining the extent to which a host versus graft immune response occurs. The differential diagnosis can be very detailed, e.g., the amount of leukocytes of a particular phenotype can be evaluated for intraglomerular, perivascular, and peritubular localization.
The variable identification strategies make MMTC a highly versatile analysis system that can help to investigate various types of cells in various kinds of tissues. MMTC is also applicable to in situ analysis of cultured cells, and phenotypic characterization of smears (data not shown).
MMTC allows the quantification of tissue-, cell-, and function-specific molecular patterns within cytomes on the single-cell level, and may thereby constitute an important technique in cytomics approaches.