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此外:多组学 MR 引导的局部晚期直肠癌放疗优化。

MOREOVER: multiomics MR-guided radiotherapy optimization in locally advanced rectal cancer.

机构信息

Gemelli Advanced Radiotherapy center, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

Radiomics GSTeP core research facility, Fondazione Policlinico Universitario "A. Gemelli" IRCCS, Rome, Italy.

出版信息

Radiat Oncol. 2024 Jul 25;19(1):94. doi: 10.1186/s13014-024-02492-9.

Abstract

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.

摘要

背景

局部晚期直肠癌(LARC)患者的完全缓解预测通常集中在分期 MRI 的放射组学分析上。到目前为止,从肠道微生物组和循环肿瘤 DNA(ctDNA)中提取的组学信息尚未整合到基于复合生物标志物的模型中,从而遗漏了决策过程中的有价值信息。在这项研究中,我们旨在整合新辅助放化疗(nCRT)期间的放射组学与肠道微生物组和基于 ctDNA 的基因组学跟踪。

方法

MOREOVER 研究的主要假设是,将纳入 THUNDER-2 试验中基于放射组学模型的复合生物标志物与放射组学模型相结合,将提高此类模型对病理完全缓解(pCR)的预测能力,为更准确和全面的个性化治疗方法铺平道路。这是由于纳入了可能揭示与放射组学之前未知相关性的可操作组学变量。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,并根据治疗类型和时间提出未来的治疗策略,例如在无反应患者中进行粪便微生物群移植。- 描述 nCRT 治疗过程中整个基因组学模式和 ctDNA 数据的演变,以支持预测结果并确定新的风险分类分层剂。- 通过整合多组学方法(放射组学、宏基因组学、代谢组学、宏转录组学、人类基因组学、ctDNA)挖掘和组合收集的数据,以提高基于 LARC 患者接受 MR-Linac 治疗的 nCRT 的放射组学反应预测模型的性能。

实验设计

MOREOVER 项目的目的是通过探索增强所开发模型预测性能的可能性,用肠道微生物组和 ctDNA 组学信息丰富正在进行的 II 期 THUNDER-2 试验(NCT04815694)。将在 7 个时间点分析纵向 ctDNA 基因组学、微生物组和基因组数据:在 nCRT 之前、nCRT 期间每周一次以及在手术前。将根据 TRIPOD 声明对收获的数据进行特定建模。

讨论

我们预计在两组患者(pCR 和非 pCR)之间粪便微生物组、ctDNA 和放射组学特征会有所不同。此外,我们预计考虑的组学特征在时间上的稳定性会有所不同。所确定的特征将被插入到专用的建模解决方案中,以建立一个能够实现个性化治疗的多组学决策支持系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2280/11271028/6064d9aa33b6/13014_2024_2492_Fig1_HTML.jpg

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