{'fraction_non_alphanumeric': 0.04207650273224044, 'fraction_numerical': 0.0273224043715847, 'mean_word_length': 5.610108303249097, 'pattern_counts': {'":': 0, '<': 1, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Significance of genetic abnormalities of p53 protein in Slovenian patients with gastric carcinoma.

AIM
To analyze genetic alterations of p53 gene in Slovenian gastric cancer patients and to compare these alterations with clinicopathological parameters in order to assess the value of p53 as a prognostic factor.


METHODS
We analyzed the samples from 230 Slovenian patients with gastric cancer, collected between 1983 and 2001. p53 expression was evaluated immunohistochemically with DO-7 monoclonal antibody. In addition, loss of heterozigosity (LOH) and microsatellite instability (MSI) of p53 gene were evaluated, as well as its mutational status in the selected population of patients.


RESULTS
p53 expression was associated with poorer survival and it was an independent predictor in multivariate analysis, along with TNM (T--size of tumor, N--nodal involvement, M--distant metastasis) stage status. Loss of heterozigosity and microsatellite instability status did not influence survival, however we found association of loss of heterozigosity with Lauren's (Mantel-Haenszel test, P=0.004) and Ming's (Mantel-Haenszel test, P<0.001) classification, whereas microsatellite instability was associated with gender (Mantel-Haenszel test, P=0.017), TNM stage (chi(2) test, P=0.006) of gastric cancer, and lymph node involvement (pN) (chi(2) test, P=0.004). Conclusions. The data on p53 abnormalities, when considered separately, could be of relative value for predicting the behavior of gastric tumors. However, our analyses showed that studying p53 overexpression, loss of heterozigosity, microsatellite instability, and mutational analysis could provide data that, particularly in combination with some clinicopathological features, might be of clinical value for predicting the tumor behavior and patient response to therapy.