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Gut. 2004 Apr;53(4):581-6.

Histological categorisation of fibrotic cancer stroma in advanced rectal cancer.

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Department of Surgery I, National Defence Medical College, Japan.



Based on conflicting reports regarding the role of the fibrotic stromal response in cancer development--namely, that a desmoplastic reaction can favour either the host or the tumour--it is clear that the role of the stromal response is varied. We have classified the fibrotic stroma of rectal adenocarcinoma penetrating the muscularis propria, based on histologically identified stromal components.


Three categories of stroma were used: mature-when the stroma was composed of mature collagen fibres (fine and elongated fibres into multiple layers); intermediate-when keloid-like collagen was intermingled with mature fibres; and immature-consisting of a myxoid stroma in which no mature fibres were included.


In a data set of 862 patients, 53% of patients had mature fibrotic cancer stroma, 33% had intermediate stroma, and 15% had immature stroma. Five year survival rates decreased as follows: mature stroma (80%), intermediate stroma (55%), and immature stroma (27%). The adverse tumour phenotype, tumour cell budding (conspicuous isolated cells or small clusters of cancer cells), was observed in the cancer fronts in tumours with unfavourable fibrotic stroma (p<0.0001). Based on multivariate analysis, categorised fibrotic stroma was selected as an independent prognostic parameter (hazard ratio 1.39; 95% confidence interval 1.17-1.64) together with tumour differentiation. By immunohistochemical examination, as maturation of the fibrotic stroma decreased, stromal T cells became significantly sparser. Furthermore, myofibroblasts were distributed extensively in immature fibrotic stroma compared with mature and intermediate fibrotic stroma.


The morphological categorisation of fibrotic cancer stroma highlights the role of the stromal response in relation to the behaviour and host immune reactions of rectal adenocarcinoma and would be a useful tool for predicting patient prognostic outcome.

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