Yi Jun, Wei Xiang, Li Xinqiang, Wan Lei, Dong Jiashou, Wang Rui
Department of Cardiothoracic Surgery.
Department of Cardiothoracic Surgery, The Affiliated Tongji Hospital of Tongji Medical College, Huazhong University of Science, Wuhan.
Anticancer Drugs. 2018 Jan;29(1):10-18. doi: 10.1097/CAD.0000000000000571.
Lung cancer is one of the most common malignancies and the leading cause of cancer-related deaths worldwide. Although many oncogenes and tumor suppressors have been uncovered in the past decades, the pathogenesis and mechanisms of lung tumorigenesis and progression are unclear. The advancement of high-throughput sequencing technique and bioinformatics methods has led to the discovery of some unknown important protein-coding genes or noncoding RNAs in human cancers. In this study, we tried to identify and validate lung cancer driver genes to facilitate the diagnosis and individualized treatment of patients with this disease. To analyze distinct gene profile in lung cancer, the RNA sequencing data from TCGA and microarray data from Gene Expression Omnibus were used. Then, shRNA-pooled screen data and CRISPR-Cas9-based screen data in lung cancer cells were used to validate the functional roles of identified genes. We found that thousands of gene expression patterns are altered in lung cancer, and genomic alterations contribute to the dysregulation of these genes. Furthermore, we identified some potential lung cancer driver genes, such as TBX2, MCM4, SLC2A1, BIRC5, and CDC20, whose expression is significantly upregulated in lung cancer, and the copy number of these genes is amplified in the genome of patients with lung cancer. More importantly, overexpression of these genes is associated with poorer survival of patients with lung cancer, and knockdown or knockout of these genes results in decreased cell proliferation in lung cancer cells. Taken together, the genomewide comprehensive analysis combined with screen data analyses may provide a valuable help for identifying cancer driver genes for diagnosis and prevention of patients with lung cancer.
肺癌是全球最常见的恶性肿瘤之一，也是癌症相关死亡的主要原因。尽管在过去几十年中发现了许多癌基因和肿瘤抑制基因，但肺癌发生发展的发病机制仍不清楚。高通量测序技术和生物信息学方法的进步，促使人们在人类癌症中发现了一些未知的重要蛋白质编码基因或非编码RNA。在本研究中，我们试图鉴定和验证肺癌驱动基因，以促进该疾病患者的诊断和个体化治疗。为了分析肺癌中不同的基因谱，我们使用了来自TCGA的RNA测序数据和来自基因表达综合数据库的微阵列数据。然后，利用肺癌细胞中的shRNA混合筛选数据和基于CRISPR-Cas9的筛选数据，来验证所鉴定基因的功能作用。我们发现肺癌中有数千种基因表达模式发生改变，基因组改变导致这些基因的失调。此外，我们鉴定了一些潜在的肺癌驱动基因，如TBX2、MCM4、SLC2A1、BIRC5和CDC20，它们在肺癌中的表达显著上调，并且在肺癌患者的基因组中这些基因的拷贝数增加。更重要的是，这些基因的过表达与肺癌患者较差的生存率相关，敲低或敲除这些基因会导致肺癌细胞的增殖减少。综上所述，全基因组综合分析与筛选数据分析相结合，可能为肺癌患者的诊断和预防鉴定癌症驱动基因提供有价值的帮助。
