| Literature DB >> 12402153 |
R Kikuchi1, T Noguchi, S Takeno, Y Funada, H Moriyama, Y Uchida.
Abstract
BAG-1 is a recently identified Bcl-2-interacting anti-apoptotic protein. The aim of our study was to investigate the immunohistochemical staining pattern of BAG-1 protein in patients with colorectal cancer and examine associations of BAG-1 expression with various clinicopathological factors and patient survival. Tumour samples were collected from 86 patients diagnosed with colorectal cancer. There was significant variation in the immunohistochemical staining patterns for BAG-1, including absent staining and staining of either the cytoplasm, nucleus or both. Twenty-one colorectal carcinomas (24.4%) exhibited a nuclear staining pattern whilst 56 (65.1%) exhibited cytoplasmic staining. The percentage of cases exhibiting nuclear BAG-1 positivity was significantly higher in distant metastasis-positive cases (55.6%) than in distant metastasis-negative cases (20.8%; P=0.036). Overall survival was significantly shorter for patients with tumours exhibiting BAG-1 positive nuclei than those with absent nuclear BAG-1-staining (P=0.011). In addition, the multivariate cox proportional hazard models indicated that nuclear BAG-1 expression was the only independent prognostic variable for mortality (P=0.013). These studies demonstrate that nuclear BAG-1 expression is a useful predictive factor for distant metastasis and a poor prognosis in patients with colorectal cancer. Copyright 2002 Cancer Research UKEntities:
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Year: 2002 PMID: 12402153 PMCID: PMC2376197 DOI: 10.1038/sj.bjc.6600579
Source DB: PubMed Journal: Br J Cancer ISSN: 0007-0920 Impact factor: 7.640
Figure 1Immunolocalisation of BAG-1 in samples of human colorectal carcinomas. Immunostaining revealed BAG-1 is immunostained in the tumour cell nucleus (A) and the cytoplasm (B: Original magnification ×400).
Correlation between the expression of BAG-1 and clinicopathologic factors
Figure 2Overall survival probability in relation to nuclear (A) and cytoplasm (B) BAG-1 expression status.
Multivariate analysis of prognostic factors