PO.CL01.21 · 临床研究

接受放疗的宫颈癌患者阴道微生物组动态与临床结局

Vaginal microbiome dynamics and clinical outcomes in cervical cancer patients undergoing radiotherapy

海报缩略图:接受放疗的宫颈癌患者阴道微生物组动态与临床结局
编号 6529 展板 18 时间 4/21 02:00–05:00 区域 Section 43 主讲 Yogita Mehra, PhD
分会场 Diagnostic Biomarkers 2
查看 PDF 下载 PDF 🔒 查看 / 下载完整 PDF 需登录并开通下载套餐 · 查看套餐 / 开通 AACR 官方页面

作者与单位 Authors & Affiliations

Yogita Mehra1, Julia Chalif2, Elizabeth LaPlante3, Laura Flora3, Caroline Dravillas1, January Kim3, Jessica Aduwo3, Naa Korley3, Nyelia Williams3, Rebecca Hoyd1, David O’Malley2, Elizabeth K. Arthur3, Allison M. Quick2, Daniel Spakowicz1, Laura Chambers2

1The Ohio State University Comprehensive Cancer Center, Columbus, OH,2The Ohio State University Wexner Medical Center, Columbus, OH,3The Ohio State University, Columbus, OH

摘要 Abstract

中文摘要
晚期和复发性宫颈癌(CC)是全球主要死亡原因之一。尽管新型疗法的出现和免疫检查点抑制剂的应用日益增多,晚期或复发性CC患者仍预后不良、治疗选择有限,且伴有显著的治疗相关毒性。有限的证据表明阴道微生物组(VM)可能预测治疗结局和毒性。使用16S扩增子测序研究放疗(RT)后VM的研究观察到Lactobacillus减少和Prevotella增加。然而,我们对这些菌群的功能活动及其与宿主相互作用的理解仍存在显著空白。为填补这一空白,我们启动了"接受盆腔放疗女性的阴道健康"(GEORGIA)试验,以评估接受RT的CC患者的VM动态,并研究基线微生物组组成是否预测治疗后结局。GEORGIA试验(NCT04713618)纳入了31例接受盆腔RT的CC患者。在基线和治疗后长达24个月采集阴道拭子。我们使用2×150 bp测序文库(每个样本>5000万读数)评估宏转录组(metaT),以评价微生物丰度、活性和人类基因转录。使用纵向混合效应模型(R中的lme4)和差异丰度分析(ANCOM-BC2)将微生物数据与临床变量(包括复发状态)进行关联。共有27例患者具有完整的人口统计学信息和纵向测序数据。超过三分之一为当前吸烟者(35.5%),38.7%从不吸烟,45.2%在治疗时已绝经。阴道拭子RNAseq读数以大致相等的数量比对到人类和微生物参考基因组。盆腔RT显著改变了VM,随时间推移驱动向更高alpha多样性的转变,表现为Shannon指数(p = 0.001)和Simpson指数(p = 0.002)的增加。按复发状态分层时,未观察到alpha多样性轨迹的显著差异。差异丰度分析揭示了在既往VM研究中与HPV持续感染和CC复发相关的分类群的显著富集,包括Fusobacterium hominis(p = 0.02)和Fusobacterium gonidiaformans(p = 0.03),提示其在疾病进展中的潜在作用。这些发现强调了VM对临床结局的可能影响,并凸显其作为CC复发预测因素的新兴作用。正在进行的分析将探索功能谱分析和高级纵向建模,以识别复发前的早期微生物变化。我们将使用预测建模,整合微生物和临床特征,构建恢复模型并生成可通过实验检验的潜在生物学机制假设。
查看英文原文 English abstract
Advanced and recurrent cervical cancer (CC) is one of the major causes of death worldwide. Despite the advent of novel therapies and increasing utilization of immune checkpoint inhibitors, patients with advanced or recurrent CC have a poor prognosis, limited treatment options, and significant treatment-related toxicities. Limited evidence suggests that the vaginal microbiome (VM) may predict treatment outcomes and toxicity. Studies of the VM following radiotherapy (RT) using 16S amplicon sequencing observed a reduction in Lactobacillus and an increase in Prevotella . However, significant gaps remain in our understanding of the functional activities of these communities and their interactions with the host. To fill this gap, we initiated the “vaGinal hEalth in women ReceivinG pelvic radiation” (GEORGIA) trial to assess VM dynamics in CC patients undergoing RT and to investigate whether baseline microbiome composition predicts post-treatment outcomes. The GEORGIA trial (NCT04713618) enrolled 31 patients with CC who received pelvic RT. Vaginal swabs were collected at baseline and up to 24 months post-treatment. We assessed the metatranscriptome (metaT) using 2×150 bp sequencing libraries (>50 million reads per sample) to evaluate microbial abundance, activity, and human gene transcription. Longitudinal mixed-effects models (lme4 in R) and differential abundance analysis (ANCOM-BC2) were used to correlate microbial data with clinical variables, including recurrence status. A total of 27 patients had complete demographic information and longitudinal sequencing data. Over one-third were current smokers (35.5%), while 38.7% had never smoked, and 45.2% were post-menopausal at the time of treatment. Vaginal swab RNAseq reads aligned to human and microbe reference genomes in approximately equal numbers. Pelvic RT significantly altered the VM, driving a shift toward higher alpha diversity, as evidenced by increases in the Shannon (p = 0.001) and Simpson (p = 0.002) indices over time. When stratified by recurrence status, no significant differences in alpha diversity trajectories were observed. Differential abundance analysis revealed significant enrichment of taxa previously associated with HPV persistence and CC recurrence in VM studies, including Fusobacterium hominis (p = 0.02) and Fusobacterium gonidiaformans (p = 0.03), suggesting a potential role in disease progression. These findings underscore the possible influence of the VM on clinical outcomes and highlight its emerging role as a predictive factor in CC recurrence. Ongoing analysis will explore functional profiling and advanced longitudinal modeling to identify early microbial shifts preceding recurrence. We will use predictive modeling, integrating microbial and clinical features, to construct a recovery model and generate hypotheses for underlying biological mechanisms that can be tested experimentally.
利益披露 Disclosure
Y. Mehra, None.. J. Chalif, None.. E. LaPlante, None.. L. Flora, None.. C. Dravillas, None.. J. Kim, None.. J. Aduwo, None.. N. Korley, None.. N. Williams, None.. R. Hoyd, None.. D. O’Malley, None.. E. K. Arthur, None.. A. M. Quick, None.. D. Spakowicz, None.. L. Chambers, None.

← 返回 AACR 2026 检索