Zhou E, Wu Feng, Guo Mengfei, Yin Zhengrong, Li Yumei, Li Minglei, Xia Hui, Deng Jingjing, Yang Guanghai, Jin Yang
Department of Respiratory and Critical Care Medicine, Hubei Province Clinical Research Center for Major Respiratory Diseases, Key Laboratory of Pulmonary Diseases of National Health Commission, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Hubei Province Engineering Research Center for Tumor-Targeted Biochemotherapy, Key Laboratory of Biological Targeted Therapy, the Ministry of Education, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Front Oncol. 2022 Dec 1;12:1008283. doi: 10.3389/fonc.2022.1008283. eCollection 2022.
Tyrosine kinase inhibitors (TKIs) that target epidermal growth factor receptor (EGFR) mutations are commonly administered to EGFR-positive lung cancer patients. However, resistance to EGFR-TKIs (mostly gefitinib and erlotinib) is presently a significant problem. Limited studies have focused on an EGFR-TKI resistance-related gene signature (ERS) in lung adenocarcinoma (LUAD).
Gefitinib and erlotinib resistance-related genes were obtained through the differential analyses of three Gene Expression Omnibus datasets. These genes were investigated further in LUAD patients from The Cancer Genome Atlas (TCGA). Patients in the TCGA-LUAD cohort were split into two groups: one for training and one for testing. The training cohort was used to build the ERS, and the testing cohort was used to test it. GO and KEGG analyses were explored for the enriched pathways between the high-risk and low-risk groups. Various software, mainly CIBERSORT and ssGSEA, were used for immune infiltration profiles. Somatic mutation and drug sensitivity analyses were also explored.
An ERS based on five genes (FGD3, PCDH7, DEPDC1B, SATB2, and S100P) was constructed and validated using the TCGA-LUAD cohort, resulting in the significant stratification of LUAD patients into high-risk and low-risk groups. Multivariable Cox analyses confirmed that ERS had an independent prognostic value in LUAD. The pathway enrichment analyses showed that most of the genes that were different between the two risk groups were related to the immune system. Further immune infiltration results revealed that a lower immune infiltration score was observed in high-risk patients, and that various leukocytes were significantly related to the ERS. Importantly, samples from the high-risk group showed lower levels of PD-1, PD-L1, and CTLA-4, which are important biomarkers for immunotherapy responses. Patients in the high-risk group also had more gene mutation changes and were more sensitive to chemotherapy drugs like docetaxel and sorafenib. The ERS was also validated in the GSE30219, GSE11969 and GSE72094, and showed a favorable prognostic value for LUAD patients.
The ERS established during this study was able to predict a poor prognosis for LUAD patients and had great potential for predicting drug responses.
针对表皮生长因子受体(EGFR)突变的酪氨酸激酶抑制剂(TKIs)常用于EGFR阳性肺癌患者。然而,目前对EGFR-TKIs(主要是吉非替尼和厄洛替尼)的耐药性是一个重大问题。有限的研究集中在肺腺癌(LUAD)中与EGFR-TKI耐药相关的基因特征(ERS)上。
通过对三个基因表达综合数据库进行差异分析,获得吉非替尼和厄洛替尼耐药相关基因。在来自癌症基因组图谱(TCGA)的LUAD患者中对这些基因进行进一步研究。TCGA-LUAD队列中的患者被分为两组:一组用于训练,一组用于测试。训练队列用于构建ERS,测试队列用于对其进行测试。对高风险组和低风险组之间的富集通路进行基因本体(GO)和京都基因与基因组百科全书(KEGG)分析。使用各种软件,主要是CIBERSORT和单样本基因集富集分析(ssGSEA),进行免疫浸润分析。还探讨了体细胞突变和药物敏感性分析。
构建了一个基于五个基因(FGD3、PCDH7、DEPDC1B、SATB2和S100P)的ERS,并使用TCGA-LUAD队列进行了验证,从而将LUAD患者显著分层为高风险组和低风险组。多变量Cox分析证实ERS在LUAD中具有独立的预后价值。通路富集分析表明,两个风险组之间差异的大多数基因与免疫系统有关。进一步的免疫浸润结果显示,高风险患者的免疫浸润评分较低,并且各种白细胞与ERS显著相关。重要的是,高风险组的样本显示出较低水平的程序性死亡受体-1(PD-1)、程序性死亡配体-1(PD-L1)和细胞毒性T淋巴细胞相关蛋白4(CTLA-4),这些是免疫治疗反应的重要生物标志物。高风险组的患者也有更多的基因突变变化,并且对多西他赛和索拉非尼等化疗药物更敏感。ERS在GSE30219、GSE11969和GSE72094中也得到了验证,并且对LUAD患者显示出良好的预后价值。
本研究中建立的ERS能够预测LUAD患者的不良预后,并且在预测药物反应方面具有巨大潜力。