SCI
25 August 2024
Lung-MAP Next Generation Sequencing Analysis of Advanced Squamous Cell Lung Cancers (SWOG S1400)
(Journal of Thoracic Oncology, IF: 21.0)
David Kozono, Xing Hua, Michael C. Wu, Khaled A. Tolba, Saiama N. Waqar, Konstantin H. Dragnev, Haiying Cheng, Fred R. Hirsch, Philip C. Mack, Jhanelle E. Gray, Karen Kelly, Hossein Borghaei, Roy S. Herbst, David R. Gandara, Mary W. Redman
CORRESPONDENCE TO: dkozono@bwh.harvard.edu
Squamous cell cancer (SqCC) is a lung cancer subtype with few targeted therapy options. Molecular characterization, i.e., by next generation sequencing (NGS), is needed to identify potential targets. Lung-MAP SWOG S1400 enrolled patients with previously treated stage IV or recurrent SqCC to assess NGS biomarkers for therapeutic substudies.
肺鳞状细胞癌（SqCC）是肺癌的一种亚型，且几乎没有靶向治疗选择。目前需要二代测序（NGS）来了解其分子表征，来鉴定潜在靶点。Lung MAP SWOG S1400研究招募了之前接受过治疗的肺鳞癌IV期患者或SqCC复发的患者，以评估NGS生物标志物用于治疗的亚研究。
Tumors underwent NGS using Foundation Medicine’s Foundation One research platform, which sequenced the exons and/or introns of 313 cancer-related genes. Mutually Exclusive Gene Set Analysis (MEGSA) and Selected Events Linked by Evolutionary Conditions across human Tumors (SELECT) were performed to identify mutually exclusive and co-occurring gene alterations. Comparisons were performed with data on 495 lung SqCC downloaded from The Cancer Genome Atlas. Cox proportional hazards models were used to examine associations between genetic variants and survival.
使用Foundation Medicine的Foundation One研究平台对肿瘤进行NGS测序，对313个癌症相关基因的外显子和/或内含子进行测序。同时进行了互斥基因集分析（MEGSA）和人类肿瘤进化条件关联选定事件分析（SELECT），以确定互斥和共同发生的基因改变。将所得数据与从癌症基因组图谱（Cancer Genome Atlas）下载的495例肺SqCC的数据进行比较。Cox比例风险模型用于检验遗传变异与生存之间的关联。
NGS data are reported for 1672 patients enrolled on S1400 between 2014 and 2019. MEGSA identified two non-overlapping sets of mutually exclusive alterations with a false discovery rate < 15%: NFE2L2, KEAP1 and PARP4; and CDKN2A and RB1. PARP4, a relatively uncharacterized gene, showed three frequent mutations suggesting functional significance: 3116T>C (I1039T), 3176A>G (Q1059R) and 3509C>T (T1170I). NFE2L2 and KEAP1 alterations when taken together were associated with poorer survival.
本研究报告了2014年至2019年间S1400研究纳入的1672名患者的NGS数据。MEGSA确定了两组不重叠的互斥改变（错误发现率<15%）：NFE2L2、KEAP1和PARP4；CDKN2A和RB1。PARP4是一个相对非典型的基因，显示出三种常见的突变，说明其具有特定的功能意义，该三种常见突变为：3116T>C（I1039T）、3176A>G（Q1059R）和3509C>T（T1170I）。NFE2L2和KEAP1的改变与较差的生存率有关。
As the largest dataset to-date of lung SqCC profiled on a clinical trial, the S1400 NGS dataset establishes a rich resource for biomarker discovery. Mutual exclusivity of PARP4 and NFE2L2 or KEAP1 alterations suggests that PARP4 may have an uncharacterized role in a key pathway known to impact oxidative stress response and treatment resistance.
作为迄今为止临床试验中最大的肺部SqCC数据集，S1400 NGS数据集为生物标志物发现提供了丰富的资源。PARP4和NFE2L2或KEAP1改变的互斥性表明，PARP4可能在已知影响氧化应激反应和治疗耐药性的关键途径中具有未被描述的作用。
