Cytomics

Abstract: Flow cytometry has evolved over the past 30 y from a niche laboratory technique to a routine tool used by clinical pathologists and immunologists for diagnosis and monitoring of patients with cancer and immune deficiencies. Identification of novel patterns of expressed Ags has led to the recognition of cancers with unique pathophysiologies and treatment strategies. FACS had permitted the isolation of tumor-free populations of hematopoietic stem cells for cancer patients undergoing stem cell transplantation. Adaptation of flow cytometry to the analysis of multiplex arrays of fluorescent beads that selectively capture proteins and specific DNA sequences has produced highly sensitive and rapid methods for high through-put analysis of cytokines, Abs, and HLA genotypes. Automated data analysis has contributed to the development of a "cytomics" field that integrates cellular physiology, genomics, and proteomics. In this article, we review the impact of the flow cytometer in these areas of medical practice.

Abstract: Background Molecular cell systems research (cytomics) aims at the understanding of the molecular architecture and functionality of cell systems (cytomes) by single-cell analysis in combination with exhaustive bioinformatic knowledge extraction. In this way, loss of information as a consequence of molecular averaging by cell or tissue homogenisation is avoided. Progress The cytomics concept has been significantly advanced by a multitude of current developments. Amongst them are confocal and laser scanning microscopy, multiphoton fluorescence excitation, spectral imaging, fluorescence resonance energy transfer (FRET), fast imaging in flow, optical stretching in flow, and miniaturised flow and image cytometry within laboratories on a chip or laser microdissection, as well as the use of bead arrays. In addition, biomolecular analysis techniques like tyramide signal amplification, single-cell polymerase chain reaction (PCR), and the labelling of biomolecules by quantum dots, magnetic nanobeads, or aptamers open new horizons of sensitivity and molecular specificity at the single-cell level. Data sieving or data mining of the vast amounts of collected multiparameter data for exhaustive multilevel bioinformatic knowledge extraction avoids the inadvertent loss of information from unknown molecular relations being inaccessible to an a priori hypothesis. Challenge It seems important to address the challenge of a human cytome project using hypothesis-driven molecular information collection from disease associated cell systems, supplemented by systematic and exhaustive knowledge extraction. This will allow the description of the molecular setup of normal and abnormal cell systems within a relational knowledge system, permitting the standardised discrimination of abnormal cell states in disease. As one of the consequences, individualised predictions of further disease course in patients (predictive medicine by cytomics) by characteristic discriminatory data patterns will permit individualised therapies, identification of new pharmaceutical targets, and establishment of a standardised framework of relevant molecular alterations in disease. This special issue of Cytometry, on new technologies in cytomics, focuses on prominent examples of this presently fast-moving scientific field, and represents one of the preconditions for the formulation of a human cytome project. © 2004 Wiley-Liss, Inc.

Abstract: Specific signal detection has been a fundamental issue in fluorescence microscopy. In the context of tissue samples, this problem has been even more pronounced, with respect to spectral overlap and autofluorescence.