Detecting Small Cell Transformation in Patients with Advanced EGFR Mutant Lung Adenocarcinoma through Epigenomic cfDNA Profiling

表观遗传学 DNA甲基化 仿形(计算机编程) 腺癌 突变体 癌症研究 生物 肺癌 基因表达谱 病理 计算生物学 癌症 肿瘤科 内科学 医学 遗传学 基因 计算机科学 基因表达 操作系统
作者
Talal El Zarif,Catherine B. Meador,Xintao Qiu,Ji-Heui Seo,Matthew P. Davidsohn,Hunter Savignano,Gitanjali Lakshminarayanan,Heather M. McClure,John Canniff,Brad Fortunato,Rong Li,Mandeep K. Banwait,Karl Semaan,Marc Eid,Henry W. Long,Yin P. Hung,Navin R. Mahadevan,David A. Barbie,Matthew G. Oser,Zofia Piotrowska
出处
期刊:Clinical Cancer Research [American Association for Cancer Research]
卷期号:30 (17): 3798-3811 被引量:20
标识
DOI:10.1158/1078-0432.ccr-24-0466
摘要

Abstract Purpose: Histologic transformation to small cell lung cancer (SCLC) is a mechanism of treatment resistance in patients with advanced oncogene-driven lung adenocarcinoma (LUAD) that currently requires histologic review for diagnosis. Herein, we sought to develop an epigenomic cell-free DNA (cfDNA)-based approach to noninvasively detect small cell transformation in patients with EGFR mutant (EGFRm) LUAD. Experimental Design: To characterize the epigenomic landscape of transformed (t)SCLC relative to LUAD and de novo SCLC, we performed chromatin immunoprecipitation sequencing (ChIP-seq) to profile the histone modifications H3K27ac, H3K4me3, and H3K27me3; methylated DNA immunoprecipitation sequencing (MeDIP-seq); assay for transposase-accessible chromatin sequencing; and RNA sequencing on 26 lung cancer patient-derived xenograft (PDX) tumors. We then generated and analyzed H3K27ac ChIP-seq, MeDIP-seq, and whole genome sequencing cfDNA data from 1 mL aliquots of plasma from patients with EGFRm LUAD with or without tSCLC. Results: Analysis of 126 epigenomic libraries from the lung cancer PDXs revealed widespread epigenomic reprogramming between LUAD and tSCLC, with a large number of differential H3K27ac (n = 24,424), DNA methylation (n = 3,298), and chromatin accessibility (n = 16,352) sites between the two histologies. Tumor-informed analysis of each of these three epigenomic features in cfDNA resulted in accurate noninvasive discrimination between patients with EGFRm LUAD versus tSCLC [area under the receiver operating characteristic curve (AUROC) = 0.82–0.87]. A multianalyte cfDNA-based classifier integrating these three epigenomic features discriminated between EGFRm LUAD versus tSCLC with an AUROC of 0.94. Conclusions: These data demonstrate the feasibility of detecting small cell transformation in patients with EGFRm LUAD through epigenomic cfDNA profiling of 1 mL of patient plasma.
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