MOREOVER:局部晚期直肠癌的多组学磁共振引导放疗优化。

IF 3.3 2区 医学 Q2 ONCOLOGY
Luca Boldrini, Giuditta Chiloiro, Silvia Di Franco, Angela Romano, Lana Smiljanic, Elena Huong Tran, Francesco Bono, Diepriye Charles Davies, Loris Lopetuso, Maria De Bonis, Angelo Minucci, Luciano Giacò, Davide Cusumano, Lorenzo Placidi, Diana Giannarelli, Evis Sala, Maria Antonietta Gambacorta
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引用次数: 0

摘要

背景:局部晚期直肠癌(LARC)患者的完全缓解预测通常侧重于分期磁共振成像的放射组学分析。迄今为止,从肠道微生物群和循环肿瘤 DNA(ctDNA)中提取的全局组学信息尚未整合到基于生物标记物的复合模型中,因此在决策过程中遗漏了有价值的信息。在本研究中,我们旨在将放射组学与新辅助化放疗(nCRT)期间基于肠道微生物群和ctDNA的基因组学追踪结合起来:MOREOVER研究的主要假设是,将复合生物标志物与霹雳-2试验中使用的基于放射组学的模型相结合,将提高此类模型的病理完全反应(pCR)预测能力,为更准确、更全面的个性化治疗方法铺平道路。这是因为纳入了可操作的omics变量,这些变量可能会揭示以前未知的与放射组学的相关性。本研究的目的是- 生成与 nCRT 耐药性相关的纵向微生物组数据,并从治疗类型和时机两方面推测未来的治疗策略,例如对无应答患者进行粪便微生物群移植。- 描述 nCRT 治疗过程中的基因组学模式和 ctDNA 数据演变,以支持预测结果并确定新的风险类别分层药物。- 通过综合多组学方法(放射组学、元基因组学、代谢组学、元转录组学、人类基因组学、ctDNA)挖掘和整合所收集的数据,以提高基于放射组学的反应预测模型的性能,该模型适用于在MR-Linac上接受nCRT治疗的LARC患者:MOREOVER项目的目标是利用肠道微生物群和ctDNA omics信息丰富THUNDER-2二期试验(NCT04815694),探索提高所开发模型预测性能的可能性。将对 7 个时间点的纵向 ctDNA 基因组学、微生物组和基因组学数据进行分析:nCRT 前、nCRT 期间的每周和手术前。根据TRIPOD声明,将对收集的数据进行特定建模:我们预计两组患者(pCR 和非 pCR)的粪便微生物组、ctDNA 和放射组学特征会有所不同。此外,我们还希望发现所考虑的 omics 特征随时间变化的稳定性。确定的特征将被插入专用的建模解决方案中,以建立一个多组学决策支持系统,实现个性化治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
MOREOVER: multiomics MR-guided radiotherapy optimization in locally advanced rectal cancer.

Background: Complete response prediction in locally advanced rectal cancer (LARC) patients is generally focused on the radiomics analysis of staging MRI. Until now, omics information extracted from gut microbiota and circulating tumor DNA (ctDNA) have not been integrated in composite biomarkers-based models, thereby omitting valuable information from the decision-making process. In this study, we aim to integrate radiomics with gut microbiota and ctDNA-based genomics tracking during neoadjuvant chemoradiotherapy (nCRT).

Methods: The main hypothesis of the MOREOVER study is that the incorporation of composite biomarkers with radiomics-based models used in the THUNDER-2 trial will improve the pathological complete response (pCR) predictive power of such models, paving the way for more accurate and comprehensive personalized treatment approaches. This is due to the inclusion of actionable omics variables that may disclose previously unknown correlations with radiomics. Aims of this study are: - to generate longitudinal microbiome data linked to disease resistance to nCRT and postulate future therapeutic strategies in terms of both type of treatment and timing, such as fecal microbiota transplant in non-responding patients. - to describe the genomics pattern and ctDNA data evolution throughout the nCRT treatment in order to support the prediction outcome and identify new risk-category stratification agents. - to mine and combine collected data through integrated multi-omics approaches (radiomics, metagenomics, metabolomics, metatranscriptomics, human genomics, ctDNA) in order to increase the performance of the radiomics-based response predictive model for LARC patients undergoing nCRT on MR-Linac.

Experimental design: The objective of the MOREOVER project is to enrich the phase II THUNDER-2 trial (NCT04815694) with gut microbiota and ctDNA omics information, by exploring the possibility to enhance predictive performance of the developed model. Longitudinal ctDNA genomics, microbiome and genomics data will be analyzed on 7 timepoints: prior to nCRT, during nCRT on a weekly basis and prior to surgery. Specific modelling will be performed for data harvested, according to the TRIPOD statements.

Discussion: We expect to find differences in fecal microbiome, ctDNA and radiomics profiles between the two groups of patients (pCR and not pCR). In addition, we expect to find a variability in the stability of the considered omics features over time. The identified profiles will be inserted into dedicated modelling solutions to set up a multiomics decision support system able to achieve personalized treatments.

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来源期刊
Radiation Oncology
Radiation Oncology ONCOLOGY-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
6.50
自引率
2.80%
发文量
181
审稿时长
3-6 weeks
期刊介绍: Radiation Oncology encompasses all aspects of research that impacts on the treatment of cancer using radiation. It publishes findings in molecular and cellular radiation biology, radiation physics, radiation technology, and clinical oncology.
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