Analysis of the p53/BAX pathway: Low BAX expression is a negative prognostic factor in patients with resected liver metastases of colorectal adenocarcinoma

Citation
Pt. Daniel et al., Analysis of the p53/BAX pathway: Low BAX expression is a negative prognostic factor in patients with resected liver metastases of colorectal adenocarcinoma, LANG ARCH S, 1999, pp. 163-169
Citations number
5
Categorie Soggetti
Surgery
Journal title
LANGENBECKS ARCHIVES OF SURGERY
ISSN journal
14352443 → ACNP
Year of publication
1999
Supplement
1
Pages
163 - 169
Database
ISI
SICI code
1435-2443(1999):<163:AOTPPL>2.0.ZU;2-6
Abstract
Background: We determined the prognostic value of the central downstream ap optosis effetor BAX in relation to its upstream regulator p53. Methods: This analysis was pefformee in RO-resected hepatic metastases of c olorectal cancer in a retrospective analysis of 41 patients who underwent p otentially curative resection of liver metastases from colorectal cancer. T umor DNA was screened for p53 mutations by SSCP-PCR (exon 5 to 8) and for B AX frameshift mutations by PCR fragment length analysis. Results: Spiking experiments of LoVo cell (biallelic BAX mutation) into SW6 20 cells (BAX wild type) showed a cutoff for BAX mutation detection of 10% mutated cells. Tumors with BAX frameshift mutations were negative for BAX p rotein expression. Patients with high BAX protein expression had a median s urvival of 53.6 months versus 35.4 months with low BAX expression (p < 0.05 ). The negative prognostic value of low BAX expression was even more eviden t in those patients with wild type p53 tumors (median survival 54.0 months versus 23.3 months for Bar-negative tumors, p < 0.01). Low BAX expression w as an independent negative prognostic marker in p53 wild type tumor patient s in multivariate regression analysis (Cox Proportional Hazard model, relat ive risk = 7.0, p = 0.015). Conclusion: Thus, pathway analysis of p53 in concert with its downstream de ath effector BAX is recommended for individual risk assessment rather than analysis of single genes, such as p53 alone.