Kohri Takayuki, Sugano Masayuki, Kawashima Osamu, Saito Ryusei, Sakurai Shinji, Sano Takaaki, Nakajima Takashi
Department of Tumor Pathology, Gunma University Graduate School of Medicine, Maebashi, Japan.
Surg Today. 2006;36(12):1039-46. doi: 10.1007/s00595-006-3319-1. Epub 2006 Dec 25.
We aimed to identify the key proteins that influence the prognosis of non-small cell lung cancer (NSCLC) using protein expression profiles of previously known prognostic markers.
Thirty-one cases of Stage II NSCLC with 5-year follow-up data were selected. Tissue microarrays (TMA) and immunohistochemistry were used to make protein expression profiles of 18 previously reported immunohistochemical prognostic markers and their value in NSCLC was statistically re-evaluated by a discriminant analysis.
For the discriminant analysis using marker protein expression profiles, we selected three significant markers, TTF-1, RCAS1 and c-MET, to evaluate each patient's 5-year survival. The requested discriminant function was V = -1.08754 x (RCAS1 score) - 0.83174 x (TTF1 score) + 0.55204 x (cMET score) + 5.46972, and V = 0 served as a cut-off point. The correctness for evaluating a patient's 5-year survival by a discriminant analysis was 87.1%.
A discriminant analysis is thus considered to be a useful statistical method for analyzing the protein expression profiles obtained by combined TMA and immunohistochemical techniques using archival NSCLC tissues. However, the sample size and selection of the marker protein depending on the histology greatly influence the results of a NSCLC study.
我们旨在利用先前已知预后标志物的蛋白质表达谱,鉴定影响非小细胞肺癌(NSCLC)预后的关键蛋白质。
选取31例具有5年随访数据的II期NSCLC病例。采用组织微阵列(TMA)和免疫组织化学方法制作18种先前报道的免疫组织化学预后标志物的蛋白质表达谱,并通过判别分析对其在NSCLC中的价值进行统计学重新评估。
对于使用标志物蛋白质表达谱的判别分析,我们选择了三个显著标志物,即TTF-1、RCAS1和c-MET,以评估每位患者的5年生存率。所需的判别函数为V = -1.08754×(RCAS1评分) - 0.83174×(TTF1评分) + 0.55204×(cMET评分) + 5.46972,且以V = 0作为分界点。通过判别分析评估患者5年生存率的正确率为87.1%。
因此,判别分析被认为是一种用于分析使用存档NSCLC组织通过联合TMA和免疫组织化学技术获得的蛋白质表达谱的有用统计方法。然而,样本量以及取决于组织学的标志物蛋白质的选择极大地影响NSCLC研究的结果。