Prediction of lymph node metastasis by gene expression profiling in patients with primary resected lung cancer
Prediction of lymph node metastasis by gene expression profiling in patients with primary resected lung cancer
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DOI：
10.1016/j.lungcan.2008.06.022
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发表时间：
2009-04-01
期刊：
影响因子：
5.3
通讯作者：
Yoshino, Ichiro
中科院分区：
文献类型：
--
作者：
Moriya, Yasumitsu;Iyoda, Akira;Yoshino, Ichiro
虽然淋巴结转移是与癌症预后不良相关的主要因素，但对其分子机制知之甚少。本研究的目的是寻找肺癌与非癌肺组织中差异表达的基因，并研究41例原发性肺腺癌的基因表达谱，以筛选肺癌淋巴结转移的预测基因。使用寡核苷酸微阵列获得基因表达谱，并通过评估所选基因表达水平的统计学显著性构建预测集。基因分析发现15个肺腺癌淋巴结转移的预测基因。使用最合适的基因组，有可能预测肺癌患者的淋巴结转移。预测评分系统在14个独立测试病例中预测淋巴结转移的准确率为71.4%。与23例病理性LN阳性或根据分子分类预测为LN阳性的病例相比，18例病理性LN阴性且根据分子分类预测为LN阴性的病例的生存率也明显更好。基因表达分析结合统计学分析成功地区分了淋巴结转移。本研究结果表明，病理诊断结合分子分型可清楚地区分良恶性肿瘤患者。(C)2008年由Elsevier爱尔兰有限公司出版。
While lymph node metastasis is a major factor associated with poor prognosis in cancer, little is known of its molecular mechanisms. The aim of this Study was to identify genes differentially expressed between non-cancerous and cancerous lung tissues, and to investigate the gene expression profiles of 41 primary lung adenocarcinomas to select sets of gene predictors for lymph node metastasis Of lung cancer. Gene expression Profiles were obtained using oligonucleotide microarrays, and predictor sets constructed by evaluating the statistical significance of expression levels of selected genes. Gene analysis revealed 15 predictor genes for lymph node metastasis of lung adenocarcinoma. Using the most suitable set of genes, it was possible to predict the lymph node metastasis of patients with lung cancer. The prediction scoring system yielded 71.4% accuracy for forecasting lymph node metastasis in 14 independent test cases. Survival was also significantly better in 18 cases that were pathologically LN negative and predicted to be LN negative according to molecular classification, compared with 23 cases that were pathologically LN positive or predicted to be LN positive according to molecular classification. Gene expression analysis combined with statistical analysis successfully distinguished lymph node metastasis. The findings of this study showed that pathological diagnosis combined with molecular classification clearly distinguished patients with good prognoses from patients with poor prognoses. (C) 2008 Published by Elsevier Ireland Ltd.