腺癌
免疫组织化学
ErbB公司
癌基因
医学
肿瘤科
肺癌
肺
单变量分析
比例危险模型
肺腺癌
人口
生存分析
内科学
病理
癌症
癌症研究
生物
多元分析
细胞周期
环境卫生
作者
David H. Harpole,Jeffrey R. Marks,William G. Richards,James E. Herndon,David J. Sugarbaker
出处
期刊:Lung Cancer
[Elsevier]
日期:1995-12-01
卷期号:13 (3): 331-332
被引量:69
标识
DOI:10.1016/0169-5002(96)84256-5
摘要
Historical information and pathological material from 150 consecutive patients with localized adenocarcinoma of the lung was collected to evaluate oncogene expression of erbB-2 and p53, and erbB-2 gene amplification. Pathological material after resection was reviewed to verify histological staging, and patient follow-up was complete in all cases for at least 68 months. Immunohistochemistry of erbB-2 (HER-2/neu) and p53 oncogene expression was performed on two separate paraffin tumor blocks for each patient with normal lung as control. Gene amplification of erbB-2 was measured after DNA extraction from 20-micrometer sections of erbB-2-positive and -negative tumors. All analyses were blinded and included Kaplan-Meier survival estimates with Cox proportional hazards regression modeling. Two adequate blocks of tumor and normal lung were available for 138 (92%) patients. Immunohistochemical identification of expression of p53 was observed in 49 (37%) patients and erbB-2 in 17 (13%) patients. DNA dot blot analyses were performed on 17 erbB-2-positive and 13 randomly selected erbB-2-negative tumors. There was 1 (6%) of 17 erbB-2-positve tumors with 4-fold erbB-2 gene amplification. Actual 5-year survival was 63% and actuarial 10-year survival was 59% for the entire population of 150 patients. Significant univariate predictors (P < 0.05) of cancer death were the presence of symptoms, tumor size >3 cm, poor differentiation, visceral pleural invasion, and p53 expression. Multivariate analysis associated symptoms and p53 expression as independent factors with decreased survival. Thus, this project examined p53 and erbB-2 expression in patients with localized adenocarcinoma and associated p53 status with survival. Multicenter collection of data should allow the development of a model of cancer recurrence in this most common lung cancer.
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