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    Virginia Litwin

    Flow cytometry is a powerful and flexible analytical tool used during all stages of drug development. While substantial effort is invested in development and validation of analytical methods, instrument validation is often neglected. Flow... more
    Flow cytometry is a powerful and flexible analytical tool used during all stages of drug development. While substantial effort is invested in development and validation of analytical methods, instrument validation is often neglected. Flow cytometers are evolving at a pace that surpasses the protracted timeline of drug discovery and development. Therefore, it becomes fundamentally important to the success of the study to document the validated state of the flow cytometer and verify data integrity at the time of study conduct. It is important to bear in mind that validation strategies are critical components of the entire process involved in bringing new therapeutic options to the medical community; drugs which eventually manifest as successful new treatments for those individuals afflicted with disease. Formal industry guidance is provided through Good Laboratory Practices [GLP], which require validation of all computerized systems and equipment used to support pre-clinical studies for regulatory submissions. Key elements of instrument validation processes have been delineated through guidance documents published by regulatory agencies and industry working groups to support the rigorous compliance needs of GLP. However, most testing to support drug development is conducted in less strict regulatory environments. Such comprehensive validation efforts may not be appropriate for laboratories supporting early discovery or basic research, however, laboratories involved in regulated stages of development, such as pre-clinical and clinical phases, should consider these recommendations. This paper presents a consensus methodological approach that the authors have used successfully to ensure data integrity in flow cytometric studies conducted during drug development.
    The beta-chemokines MIP-1alpha, MIP-1beta and RANTES inhibit infection of CD4+ T cells by primary, non-syncytium-inducing (NSI) HIV-1 strains at the virus entry stage, and also block env-mediated cell-cell membrane fusion. CD4+ T cells... more
    The beta-chemokines MIP-1alpha, MIP-1beta and RANTES inhibit infection of CD4+ T cells by primary, non-syncytium-inducing (NSI) HIV-1 strains at the virus entry stage, and also block env-mediated cell-cell membrane fusion. CD4+ T cells from some HIV-1-exposed uninfected individuals cannot fuse with NSI HIV-1 strains and secrete high levels of beta-chemokines. Expression of the beta-chemokine receptor CC-CKR-5 in CD4+, non-permissive human and non-human cells renders them susceptible to infection by NSI strains, and allows env-mediated membrane fusion. CC-CKR-5 is a second receptor for NSI primary viruses.
    Cytolysis by NK cells that possess the NKB1 killer cell inhibitory receptor is inhibited by target cell expression of Bw4+ HLA-B molecules. The inhibitory effect can be prevented by addition of mAbs which block recognition of class I... more
    Cytolysis by NK cells that possess the NKB1 killer cell inhibitory receptor is inhibited by target cell expression of Bw4+ HLA-B molecules. The inhibitory effect can be prevented by addition of mAbs which block recognition of class I molecules by NKB1. The epitopes recognized by two anti-class I mAbs, DX15 and DX16, which inhibit the interaction of NKB1 with class I have been characterized. Binding of DX15 and DX16 to class I allotypes was investigated by flow cytometric analysis of transfected cell lines which express just one HLA-A, B, or C allele, and by immunoprecipitation of class I molecules from HLA typed B-lymphoblastoid cell lines, followed by isoelectric focusing. The DX16 mAb recognizes class I allotypes which possess alanine at position 71 of the alpha 1 helix, and therefore has a specificity resembling that of the ME1 mAb but with broader specificity. Class I recognition by DX15 is affected by polymorphisms of the C-terminal part of the alpha 1 helix, and the N-terminal part of the alpha 2 helix. DX15 thus appears to recognize a complex epitope near the end of the peptide binding groove which may be conformationally determined. Both antibodies are as effective as the anti-NKB1 mAb (DX9) in preventing class I recognition by the NKB1 receptor. DX16 also blocked recognition by a B*0702 allospecific CTL clone, whereas DX15 did not.
    Natural killer (NK) cells kill normal and transformed hematopoietic cells that lack expression of major histocompatibility complex (MHC) class I antigens. Lysis of HLA-negative Epstein Barr virus-transformed B lymphoblastoid cell lines... more
    Natural killer (NK) cells kill normal and transformed hematopoietic cells that lack expression of major histocompatibility complex (MHC) class I antigens. Lysis of HLA-negative Epstein Barr virus-transformed B lymphoblastoid cell lines (B-LCL) by human NK cell clones can be inhibited by transfection of the target cells with certain HLA-A, -B, or -C alleles. NK cell clones established from an individual demonstrate clonal heterogeneity in HLA recognition and a single NK clone can recognize multiple alleles. We describe a potential human NK cell receptor (NKB1) for certain HLA-B alleles (e.g., HLA-B*5101 and-B*5801) identified by the mAb DX9. NKB1 is a 70-kD glycoprotein that is expressed on a subset of NK cells and NK cell clones. DX9 monoclonal antibody (mAb) specifically inhibits the interaction between NK cell clones and B-LCL targets transfected with certain HLA-B alleles, but does not affect recognition of HLA-A or HLA-C antigens. An individual NK cell clone can independently recognize B-LCL targets transfected with HLA-B or HLA-C antigens; however, DX9 mAb only affects interaction with transfectants expressing certain HLA-B alleles. These findings demonstrate the existence of NK cell receptors involved in the recognition of HLA-B and imply the presence of multiple receptors for MHC on an individual NK clone.