Prediction of survival in resected non-small cell lung cancer using a protein expression-based risk model: implications for personalized chemoprevention and therapy.
Prediction of survival in resected non-small cell lung cancer using a protein expression-based risk model: implications for personalized chemoprevention and therapy.
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DOI：
10.1158/1078-0432.ccr-13-1959
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发表时间：
2014-04-01
期刊：
影响因子：
--
通讯作者：
Hong WK
中科院分区：
文献类型：
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作者：
Gold KA;Kim ES;Liu DD;Yuan P;Behrens C;Solis LM;Kadara H;Rice DC;Wistuba II;Swisher SG;Hofstetter WL;Lee JJ;Hong WK
切除的非小细胞肺癌(NSCLC)患者有复发的风险，但我们没有工具来预测哪些患者风险最高。我们着手创建一个同时包含临床数据和生物标记物的风险模型。我们收集了2002-2005年间切除的非小细胞肺癌患者的档案组织和临床随访的综合数据库。从我们的临床前研究中发现了21种与肺癌发生相关的蛋白质，包括与代谢、DNA修复、炎症和生长因子相关的途径。用免疫组织化学方法对蛋白表达进行定量。选择免疫组织化学是因为它广泛可用，可以在福尔马林固定的石蜡包埋标本上进行。用Cox模型估计临床因素和生物标志物对无复发生存期(RFS)和总生存期(OS)的影响。我们的分析包括370名患者。中位随访期为5.3年，中位总生存期为6.4年。观察209例复发或死亡病例。建立了包括相关生物标记物、年龄和分期在内的RFS和OS的多变量风险模型。PAMPK、pmTOR、EpCAM和CAASK的表达增加是有利的RFS的显著预测因素(p<；0.05)；胰岛素受体、CXCR2和IGF1R的表达增加是RFS不利的预测因素。重要的(p<；0.05)预测因素包括pAMPK、pmTOR和EpCAM；CXCR2和FEN1预测不良的OS。我们已经在我们的大型回顾数据库中开发了一个预测复发的全面风险模型，这是已报道的最大的切除非小细胞肺癌系列之一。
Patients with resected non-small cell lung cancer (NSCLC) are at risk for recurrence of disease but we do not have tools to predict which patients are at highest risk. We set out to create a risk model incorporating both clinical data and biomarkers. We assembled a comprehensive database with archival tissues and clinical follow-up from patients with NSCLC resected between 2002-2005. Twenty-one proteins identified from our preclinical studies as related to lung carcinogenesis were investigated, including pathways related to metabolism, DNA repair, inflammation and growth factors. Expression of proteins was quantified using immunohistochemistry. Immunohistochemistry was chosen because it is widely available and can be performed on formalin-fixed paraffin-embedded specimens. Cox models were fitted to estimate effects of clinical factors and biomarkers on recurrence free survival (RFS) and overall survival (OS). 370 patients are included in our analysis. With median follow-up of 5.3 years, median overall survival is 6.4 years. 209 cases with recurrence or death were observed. Multicovariate risk models for RFS and OS were developed including relevant biomarkers, age and stage. Increased expression of pAMPK, pmTOR, EpCAM, and CASK were significant (p<0.05) predictors for favorable RFS; insulin receptor, CXCR2, and IGF1R predicted for unfavorable RFS. Significant (p<0.05) predictors for favorable OS include pAMPK, pmTOR, and EpCAM; CXCR2 and FEN1 predicted unfavorable OS. We have developed a comprehensive risk model predictive for recurrence in our large retrospective database, which is one of the largest reported series of resected NSCLC.