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通过基因表达谱预测早期非小细胞肺癌患者的脑转移

Predicting brain metastasis in early stage non-small cell lung cancer patients by gene expression profiling.

作者信息

Kamer Iris, Steuerman Yael, Daniel-Meshulam Inbal, Perry Gili, Izraeli Shai, Perelman Marina, Golan Nir, Simansky David, Barshack Iris, Ben Nun Alon, Gottfried Teodor, Onn Amir, Gat-Viks Irit, Bar Jair

机构信息

Institute of Oncology, Sheba Medical Center, Tel Hashomer, Israel.

Department of Cell Research and Immunology, School of Molecular Cell Biology and Biotechnology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv, Israel.

出版信息

Transl Lung Cancer Res. 2020 Jun;9(3):682-692. doi: 10.21037/tlcr-19-477.

Abstract

BACKGROUND

Non-small cell lung cancer (NSCLC) is the most common cause of cancer-death due to early metastatic spread, in many cases primarily to the brain. Organ-specific pattern of spread of disease might be driven by the activity of a specific signaling pathway within the primary tumors. We aimed to identify an expression signature of genes and the relevant signaling associated with the development of brain metastasis (BM) after surgical resection of NSCLC.

METHODS

Rapidly frozen NSCLC surgical specimens were procured from tumor banks. RNA was extracted and analyzed by RNA-sequencing (Illumina HiSeq 2500). Clinical parameters and gene expression were examined for differentiating between patients with BM, patients with metastases to sites other than brain, and patients who did not develop metastatic disease at a clinically significant follow up. Principal component analysis and pathway enrichments studies were done.

RESULTS

A total of 91 patients were included in this study, 32 of which developed BM. Stage of disease at diagnosis (P=0.004) and level of differentiation (P=0.007) were significantly different between BM and control group. We identified a set of 22 genes which correlated specifically with BM, and not with metastasis to other sites. This set achieved 93.4% accuracy (95% CI: 86.2-97.5%), 96.6% specificity and 87.5% sensitivity of correctly identifying BM patients in a leave-one-out internal validation analysis. The oxidative phosphorylation pathway was strongly correlated with BM risk.

CONCLUSIONS

Expression level of a small set of genes from primary tumors was found to predict BM development, distinctly from metastasis to other organs. These genes and the correlated oxidative phosphorylation pathway require further validation as potentially clinically useful predictors of BM and possibly as novel therapeutic targets for BM prevention.

摘要

背景

非小细胞肺癌(NSCLC)是癌症死亡的最常见原因,因为其早期会发生转移扩散,在许多情况下主要转移至脑部。疾病的器官特异性扩散模式可能由原发性肿瘤内特定信号通路的活性驱动。我们旨在确定NSCLC手术切除后与脑转移(BM)发生相关的基因表达特征及相关信号通路。

方法

从肿瘤库获取快速冷冻的NSCLC手术标本。提取RNA并通过RNA测序(Illumina HiSeq 2500)进行分析。检查临床参数和基因表达,以区分发生BM的患者、发生脑外转移的患者以及在具有临床意义的随访中未发生转移性疾病的患者。进行主成分分析和通路富集研究。

结果

本研究共纳入91例患者,其中32例发生了BM。BM组和对照组在诊断时的疾病分期(P = 0.004)和分化程度(P = 0.007)存在显著差异。我们鉴定出一组22个基因,这些基因与BM特异性相关,而与转移至其他部位无关。在留一法内部验证分析中,该基因集正确识别BM患者的准确率达到93.4%(95% CI:86.2 - 97.5%),特异性为96.6%,敏感性为87.5%。氧化磷酸化通路与BM风险密切相关。

结论

发现原发性肿瘤中一小部分基因的表达水平可预测BM的发生,与转移至其他器官明显不同。这些基因以及相关的氧化磷酸化通路需要进一步验证,作为BM潜在的临床有用预测指标,也可能作为预防BM的新治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36ed/7354143/21b72b464a04/tlcr-09-03-682-f1.jpg

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