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使用靶向大规模平行测序对具有神经内分泌特征的肺肿瘤进行突变分析:对一个被忽视的肿瘤组的比较

Mutational analysis of pulmonary tumours with neuroendocrine features using targeted massive parallel sequencing: a comparison of a neglected tumour group.

作者信息

Vollbrecht Claudia, Werner Robert, Walter Robert Fred Henry, Christoph Daniel Christian, Heukamp Lukas Carl, Peifer Martin, Hirsch Burkhard, Burbat Lina, Mairinger Thomas, Schmid Kurt Werner, Wohlschlaeger Jeremias, Mairinger Fabian Dominik

机构信息

Institute of Pathology, University Hospital Cologne, Cologne, Germany.

Institute of Pathology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany.

出版信息

Br J Cancer. 2015 Dec 22;113(12):1704-11. doi: 10.1038/bjc.2015.397. Epub 2015 Dec 8.

Abstract

BACKGROUND

Lung cancer is the leading cause of cancer-related deaths worldwide. The typical and atypical carcinoid (TC and AC), the large-cell neuroendocrine carcinoma (LCNEC) and the small-cell lung cancers (SCLC) are subgroups of pulmonary tumours that show neuroendocrine differentiations. With the rising impact of molecular pathology in routine diagnostics the interest for reliable biomarkers, which can help to differentiate these subgroups and may enable a more personalised treatment of patients, grows.

METHODS

A collective of 70 formalin-fixed, paraffin-embedded (FFPE) pulmonary neuroendocrine tumours (17 TCs, 17 ACs, 19 LCNECs and 17 SCLCs) was used to identify biomarkers by high-throughput sequencing. Using the Illumina TruSeq Amplicon-Cancer Panel on the MiSeq instrument, the samples were screened for alterations in 221 mutation hot spots of 48 tumour-relevant genes.

RESULTS

After filtering >26 000 detected variants by applying strict algorithms, a total of 130 mutations were found in 29 genes and 49 patients. Mutations in JAK3, NRAS, RB1 and VHL1 were exclusively found in SCLCs, whereas the FGFR2 mutation was detected in LCNEC only. KIT, PTEN, HNF1A and SMO were altered in ACs. The SMAD4 mutation corresponded to the TC subtype. We prove that the frequency of mutations increased with the malignancy of tumour type. Interestingly, four out of five ATM-mutated patients showed an additional alteration in TP53, which was by far the most frequently altered gene (28 out of 130; 22%). We found correlations between tumour type and IASLC grade for ATM- (P=0.022; P=0.008) and TP53-mutated patients (P<0.001). Both mutated genes were also associated with lymph node invasion and distant metastasis (P⩽0.005). Furthermore, PIK3CA-mutated patients with high-grade tumours showed a reduced overall survival (P=0.040) and the mutation frequency of APC and ATM in high-grade neuroendocrine lung cancer patients was associated with progression-free survival (PFS) (P=0.020).

CONCLUSIONS

The implementation of high-throughput sequencing for the analysis of the neuroendocrine lung tumours has revealed that, even if these tumours encompass several subtypes with varying clinical aggressiveness, they share a number of molecular features. An improved understanding of the biology of neuroendocrine tumours will offer the opportunity for novel approaches in clinical management, resulting in a better prognosis and prediction of therapeutic response.

摘要

背景

肺癌是全球癌症相关死亡的主要原因。典型与非典型类癌(TC和AC)、大细胞神经内分泌癌(LCNEC)和小细胞肺癌(SCLC)是表现出神经内分泌分化的肺肿瘤亚组。随着分子病理学在常规诊断中的影响不断增加,对可靠生物标志物的兴趣日益增长,这些生物标志物有助于区分这些亚组,并可能实现更个性化的患者治疗。

方法

使用一组70例福尔马林固定、石蜡包埋(FFPE)的肺神经内分泌肿瘤(17例TC、17例AC、19例LCNEC和17例SCLC)通过高通量测序鉴定生物标志物。使用Illumina TruSeq Amplicon-Cancer Panel在MiSeq仪器上,对样本进行48个肿瘤相关基因的221个突变热点的改变筛查。

结果

通过应用严格算法过滤>26000个检测到的变异后,在29个基因和49例患者中总共发现130个突变。JAK3、NRAS、RB1和VHL1的突变仅在SCLC中发现,而FGFR2突变仅在LCNEC中检测到。KIT、PTEN、HNF1A和SMO在AC中发生改变。SMAD4突变与TC亚型相对应。我们证明突变频率随肿瘤类型的恶性程度增加。有趣的是,五分之四的ATM突变患者在TP53中还存在额外改变,TP53是迄今为止改变最频繁的基因(130个中有28个;22%)。我们发现ATM突变患者(P=0.022;P=0.008)和TP53突变患者(P<0.001)的肿瘤类型与IASLC分级之间存在相关性。这两个突变基因也与淋巴结侵犯和远处转移相关(P⩽0.005)。此外,PIK3CA突变的高级别肿瘤患者总生存期缩短(P=0.040),高级别神经内分泌肺癌患者中APC和ATM的突变频率与无进展生存期(PFS)相关(P=0.020)。

结论

高通量测序用于分析肺神经内分泌肿瘤的结果表明,即使这些肿瘤包括几种具有不同临床侵袭性的亚型,它们仍具有一些分子特征。对神经内分泌肿瘤生物学的更好理解将为临床管理中的新方法提供机会,从而带来更好的预后和治疗反应预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6b7e/4701994/14f07f7ff3e4/bjc2015397f1.jpg

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