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Quantifying tumour-infiltrating lymphocyte subsets : a practical immuno-histochemical method

Loughlin, P.M. and Cooke, Timothy G. and George, W. David and Gray, Alison and Stott, David J. and Going, James J. (2007) Quantifying tumour-infiltrating lymphocyte subsets : a practical immuno-histochemical method. Journal of Immunological Methods, 32-40. pp. 32-40.

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    Abstract

    Background: Efficient histological quantification of tumour-infiltrating T and B lymphocyte (TIL) subsets in archival tissues would greatly facilitate investigations of the role of TIL in human cancer biology. We sought to develop such a method. Methods: Ten ×40 digital images of 4 μ sections of 16 ductal invasive breast carcinomas immunostained for CD3, CD4, CD8, and CD20 were acquired (a total of 640 images). The number of pixels in each image matching a partition of Lab colour space corresponding to immunostained cells were counted using the ‘Color range’ and ‘Histogram’ tools in Adobe Photoshop 7. These pixel counts were converted to cell counts per mm2 using a calibration factor derived from one, two, three or all 10 images of each case/antibody combination. Results: Variations in the number of labelled pixels per immunostained cell made individual calibration for each case/antibody combination necessary. Calibration based on two fields containing the most labelled pixels gave a cell count minimally higher (+ 5.3%) than the count based on 10-field calibration, with 95% confidence limits − 14.7 to + 25.3%. As TIL density could vary up to 100-fold between cases, this accuracy and precision are acceptable. Conclusion: The methodology described offers sufficient accuracy, precision and efficiency to quantify the density of TIL sub-populations in breast cancer using commonly available software, and could be adapted to batch processing of image files.

    Item type: Article
    ID code: 30367
    Keywords: breast cancer, semi-automatd cell counting, photoshop, lab colour space, Immunology, Immunology, Immunology and Allergy
    Subjects: Science > Microbiology > Immunology
    Department: Faculty of Science > Mathematics and Statistics
    Related URLs:
    Depositing user: Pure Administrator
    Date Deposited: 08 Apr 2011 13:35
    Last modified: 05 Sep 2014 23:50
    URI: http://strathprints.strath.ac.uk/id/eprint/30367

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