PO.CL01.18 · 临床研究
揭示肺癌早期转录改变：来自波士顿肺癌跨组学（BOLT）计划的初步见解
Uncovering early transcriptional alterations in lung cancer: Preliminary insights from the Boston Lung Trans-omics (BOLT) Initiative
作者与单位 Authors & Affiliations
摘要 Abstract
中文摘要
肺癌的高死亡率源于晚期诊断和高复发率。现有的基因组标志物在早期检测和预测复发方面缺乏敏感性，构成了持续存在的临床挑战。我们介绍波士顿肺癌跨组学（BOLT）计划，这是波士顿肺癌研究的一个早期亚队列，包含来自723例NSCLC患者的1446份配对肿瘤/邻近正常组织的bulk RNA测序组织样本。我们使用limma-voom对肿瘤组织与邻近正常组织进行配对差异基因表达分析，并对批次效应和患者ID进行校正以消除个体间的混杂因素。具有统计学显著性的差异表达基因定义为FDR校正p<0.05且log2变化|LFC|>2的基因。为强调生物学相关性并尽量减少假阳性，我们使用Gene-set Enrichment Analysis软件，结合从Broad研究所分子特征数据库（Molecular Signature Database）检索的经过整理的通路数据，进行通路富集分析。随后，我们对所有样本中变异性最高的前5000个基因应用加权基因共表达网络分析（WGCNA），以识别基因模块并评估模块与性状的关联。在配对肿瘤/正常组织比较中，我们识别出738个显著的DEG。其中,387个（52%）在肿瘤中相较正常肺组织上调。晚期糖基化终产物受体（RAGE）通路的AGER是肿瘤相较邻近正常组织中下调最显著的基因（FDR=3.3*10-156；LFC=-4.4），而PI3K/mTORC1信号通路和糖酵解通路的SPP1是肿瘤相较正常肺组织中上调最显著的基因（FDR=3.6*10-134；LFC=4.8）。通路富集分析显示，肿瘤相较正常组织中上调的基因与MYC靶点激活、MTORC1信号通路、糖酵解和炎症反应的关联最为强烈。WGCNA定义的模块重现了肿瘤/正常的区分，提示存在支撑早期肿瘤发生的系统层面基因程序。这些来自BOLT的初步见解揭示了NSCLC肿瘤与邻近正常组织之间一致的早期转录差异，其特征是新发和已知致癌通路以及免疫/炎症反应的上调。共表达网络支持肿瘤/正常状态是NSCLC早期基因模块的主要驱动因素。建模复发时间仍是肺癌研究中一个关键但研究不足的领域。我们将在BOLT中开发并验证预测性基因表达特征和共表达网络，以根据复发风险和原发治疗或新辅助治疗后的预期复发时间对早期NSCLC患者进行分层。
查看英文原文 English abstract
Lung cancer's high mortality is driven by advanced-stage diagnoses and high recurrence rates. Existing genomic markers lack sensitivity for early detection and predicting recurrence, presenting ongoing clinical challenges. We introduce the Boston Lung Trans-omics (BOLT) Initiative, an early-stage sub-cohort of the Boston Lung Cancer Study with 1446 paired tumor/adjacent-normal bulk RNA-sequenced tissues from 723 NSCLC patients. We performed paired differential gene expression analysis between tumor and adjacent normal tissues using limma-voom, adjusting for batch effects and patient ID to account for inter-individual confounding. Statistically significant differentially expressed genes were defined as genes with FDR-adjusted p <0.05 and log2 change |LFC|>2. To emphasize biological relevance and minimize false positives, we performed pathway enrichment analysis with the Gene-set Enrichment Analysis software using curated pathway data retrieved from the Molecular Signature Database, Broad Institute. We then applied weighted gene co-expression network analysis (WGCNA) to the top 5000 most variable genes across all samples to identify gene modules and assessed module-trait associations. We identified 738 significant DEGs in the paired tumor/normal comparison. Among these, 387 (52%) were upregulated in tumor compared to normal lung tissues. AGER of the receptor for advanced glycation end-products (RAGE) pathway was the top downregulated gene in tumor compared to adjacent normal tissues (FDR=3.3*10 -156 ; LFC=-4.4) while SPP1 of the PI3K/mTORC1 signaling and glycolysis pathways was the top upregulated gene in tumor compare to normal lung tissues (FDR=3.6*10 -134 ; LFC=4.8). Pathway enrichment analysis revealed that genes upregulated in tumors compared to normal tissues were most strongly associated with MYC target activation, MTORC1 signaling, glycolysis, and inflammatory responses. Modules defined by WGCNA recapitulated tumor/normal distinctions, suggesting system-level gene programs underlying early tumorigenesis.These preliminary insights from BOLT reveal consistent early transcriptional differences between NSCLC tumors and adjacent normal tissues characterized by upregulation of both novel and known oncogenic pathways and immune/inflammatory responses. Co-expression networks support the tumor/normal status as the principal driver of gene modules at early stages of NSCLC. Modeling time to recurrence remains a critical yet understudied area in lung cancer research. We will develop and validate predictive gene expression signatures and co-expression networks in BOLT to stratify early-stage NSCLC patients by recurrence risk and anticipated time to recurrence following primary treatment or neoadjuvant therapies.
利益披露 Disclosure
Y. Zhao, None..
L. Su, None..
L. A. Mucci, None..
T. R. Rebbeck, None..
Y. Li, None..
D. C. Christiani, None.