Correlation between major histocompatibility complex class I molecules and CD8+ T lymphocytes in prostate, and quantification of CD8 and interferon‐γ mRNA in prostate tissue specimens

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Abstract
To investigate the immunology of host-tumour interaction, critical for the development of immunotherapy against cancers, by assessing the major histocompatibility complex (MHC) class I expression in both benign and malignant prostate disease, and the relationship between their expression and degree of tumour-infiltrating lymphocytes. Direct serial analysis of gene expression in tumours is an extremely sensitive and powerful tool for monitoring immunological changes in the immunotherapy of solid tumours. Most previous monitoring protocols rely mainly on the analysis of patient's peripheral blood but in the present study the direct molecular analysis of small tissue samples was used, and its accuracy compared with that of conventional immunohistochemical analysis. Twenty-four formalin-fixed, paraffin-embedded prostate samples (11 benign and 13 carcinoma) were used for the immunohistochemical analysis of CD8+ T lymphocytes and MHC class I expression. CD8+ T lymphocytes were counted using an ocular grid and MHC class I measured using digital image-analysis software. Twenty-seven frozen prostate tissue samples (12 benign and 15 carcinoma) were used for direct gene measurements of CD8 and interferon-gamma using a quantitative real-time polymerase chain reaction. There were significantly fewer CD8+ T lymphocytes in prostate carcinoma nests than in benign prostate. There was a significant correlation between the number of CD8+ T lymphocytes and MHC class I expression in the prostate. There was a strong correlation between the immunohistochemical estimates of CD8+ T lymphocytes and CD8 gene by polymerase chain reaction, but no significant difference between benign prostate and prostate carcinoma tissue in gene measurements. Down-regulation of MHC class I expression by prostate cancer cells is associated with fewer CD8+ T lymphocytes and hence might be important in cancer growth. In addition, the measurement of gene expression in small tissue samples might be useful for monitoring the efficacy of treatment throughout cancer therapy.