Schweiger Thomas, Liebmann-Reindl Sandra, Glueck Olaf, Starlinger Patrick, Laengle Johannes, Birner Peter, Klepetko Walter, Pils Dietmar, Streubel Berthold, Hoetzenecker Konrad
Division of Thoracic Surgery, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
Core Facility Genomics, Comprehensive Cancer Center, Informatics and Intelligent Systems, Medical University of Vienna, Vienna, Austria.
J Thorac Dis. 2018 Nov;10(11):6147-6157. doi: 10.21037/jtd.2018.10.72.
Pulmonary metastasectomy is one of the cornerstones in the treatment of oligometastatic colorectal cancer (CRC). However, the selection of patients who benefit from a surgical resection is difficult. Mutational profiling has become an essential part of diagnosis and treatment of malignant disease. Despite this, comprehensive data on the mutational profile of CRC and its clinical impact in the context of pulmonary metastasectomy is sparse. We therefore aimed to provide a complete mutational status of CRC pulmonary metastases (PM) and corresponding primary tumors by targeted next-generation sequencing (tNGS), and correlate sequencing data with clinical outcome variables.
Case-matched, formalin-fixed paraffin embedded surgical specimens of lung metastases (n=47) and matched primary CRC (n=24) were sequenced using the TruSeq Amplicon Cancer Panel (Illumina platform). Penalized Cox regression models were applied to identify mutations with prognostic impact.
Mutations were found most frequently in , and , in both PM and matched primary tumors. Concordance between primary tumors and PM was 83.5%. Adaptive elastic-net regularized Cox regression models identified mutations being prognostic for time to pulmonary recurrence (, , , , and ) and for overall survival (OS) (, , and ).
Our findings suggest that CRC PM harbor a variety of conserved and mutations. We could identify a mutational profile predicting clinical outcome after pulmonary metastasectomy. Moreover, our data provide a rationale for future targeted therapies of patients with CRC lung metastases.
肺转移瘤切除术是寡转移性结直肠癌(CRC)治疗的基石之一。然而,选择能从手术切除中获益的患者却很困难。突变谱分析已成为恶性疾病诊断和治疗的重要组成部分。尽管如此,关于CRC的突变谱及其在肺转移瘤切除背景下的临床影响的全面数据却很匮乏。因此,我们旨在通过靶向二代测序(tNGS)提供CRC肺转移灶(PM)及相应原发肿瘤的完整突变状态,并将测序数据与临床结局变量相关联。
使用TruSeq Amplicon Cancer Panel(Illumina平台)对病例匹配的、福尔马林固定石蜡包埋的肺转移灶手术标本(n = 47)和匹配的原发CRC标本(n = 24)进行测序。应用惩罚性Cox回归模型来识别具有预后影响的突变。
在PM和匹配的原发肿瘤中,最常发现的突变位于 、 和 。原发肿瘤与PM之间的一致性为83.5%。自适应弹性网络正则化Cox回归模型确定了对肺复发时间( 、 、 、 和 )以及总生存期(OS)( 、 和 )具有预后意义的突变。
我们的研究结果表明,CRC的PM含有多种保守和 突变。我们能够识别出预测肺转移瘤切除术后临床结局的突变谱。此外,我们的数据为未来CRC肺转移患者的靶向治疗提供了理论依据。