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

Paula M Loughlin1, Timothy G Cooke, W David George

  • 1Section of Surgical Sciences and Translational Research, University of Glasgow, UK.

Journal of Immunological Methods
|February 28, 2007
PubMed
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This study presents an efficient method for quantifying tumour-infiltrating lymphocyte (TIL) subsets in breast cancer tissue. The developed technique uses common software for accurate and precise histological analysis of TIL density.

Area of Science:

  • Immunohistochemistry
  • Digital Pathology
  • Quantitative Biology

Background:

  • Accurate quantification of tumour-infiltrating lymphocytes (TILs) is crucial for understanding their role in human cancer.
  • Existing methods for TIL subset analysis in archival tissues can be inefficient.
  • Developing a streamlined histological quantification method is needed.

Purpose of the Study:

  • To develop an efficient and accurate method for quantifying T and B lymphocyte (TIL) subsets in archival breast cancer tissues.
  • To establish a reliable histological quantification technique for TIL density.

Main Methods:

  • Acquired ten x40 digital images from 16 ductal invasive breast carcinoma microsections stained for CD3, CD4, CD8, and CD20.
  • Utilized Adobe Photoshop 7 'Color range' and 'Histogram' tools to count pixels corresponding to immunostained cells.

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  • Converted pixel counts to cell counts per mm(2) using a calibration factor derived from image analysis.
  • Main Results:

    • Individual calibration per case/antibody combination was necessary due to variations in labelled pixels per cell.
    • Calibration using two fields yielded cell counts minimally higher (+5.3%) than ten-field calibration, with acceptable confidence limits (-14.7 to +25.3%).
    • The achieved accuracy and precision are suitable given the potential 100-fold variation in TIL density between cases.

    Conclusions:

    • The described methodology provides sufficient accuracy, precision, and efficiency for quantifying TIL sub-populations in breast cancer.
    • This method employs commonly available software and can be adapted for batch processing of image files.
    • The technique facilitates investigations into the role of TILs in cancer biology using archival specimens.