短期放疗后CAPOXIRI与CAPOX对局部晚期直肠癌的III期试验:ENSEMBLE试验

J. Watanabe , Y. Kagawa , K. Chida , K. Ando , D. Kotani , K. Oba , H. Bando , H. Hojo , S. Shimamoto , S. Sakashita , T. Kuwata , T. Tsuboyama , N. Hosomi , M. Uemura , K. Uehara , M. Ito , E. Oki , I. Takemasa , E. Misugi , G. Sledge , T. Yoshino
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引用次数: 1

摘要

治疗局部晚期癌症(LARC)的两个关键问题如下:(i)通过减少远处转移来延长生存期;(ii)通过安全避免直肠切除来维持存活患者的肛门直肠功能和生活质量。为了解决这些问题,近年来,全新辅助治疗(TNT),一种放化疗或短程放疗(SCRT)与全身化疗的术前组合,已被开发为LARC的一种多学科治疗方法。目前还没有关于SCRT后巩固三联方案与三联方案的前瞻性研究。这项随机III期试验(ENSEMBLE试验)旨在测试在SCRT作为TNT治疗LARC后,合并伊立替康、卡培他滨和奥沙利铂相对于卡培他宾和奥沙利拉丁的优越性。主要终点将是意向治疗人群中器官保存适应的无病生存率。此外,尚未建立LARC的预测性生物标志物。因此,为了探索评估TNT反应和非手术治疗的预测性生物标志物,我们计划使用多组学数据进行转化研究,包括组织和血液样本的全基因组/转录组测序的基因组图谱、液体活检、放射组学、数字病理学、人工智能深度学习的临床特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Phase III trial of short-course radiotherapy followed by CAPOXIRI versus CAPOX in locally advanced rectal cancer: the ENSEMBLE trial

The two key concerns in treating locally advanced rectal cancer (LARC) are as follows: (i) prolonging survival by reducing distant metastases and (ii) maintaining anorectal function and quality of life in surviving patients by safely avoiding rectal resection. To resolve these issues, in recent years, total neoadjuvant therapy (TNT), a preoperative combination of chemoradiotherapy or short-course radiotherapy (SCRT) and systemic chemotherapy, has been developed as a multidisciplinary treatment of LARC. There have been no prospective studies on consolidation triplet versus doublet regimens after SCRT. This randomized phase III trial (the ENSEMBLE trial) aims to test the superiority of consolidation irinotecan, capecitabine, and oxaliplatin over capecitabine and oxaliplatin after SCRT as TNT for LARC. The primary endpoint will be organ preservation-adapted disease-free survival in the intention-to-treat population. Moreover, no predictive biomarkers have been established for LARC. Therefore, to explore the predictive biomarkers for estimating the response to TNT and non-operative management, we planned translational research using multi-omics data, including genomic profiling with whole-genome/transcriptome sequencing of tissue and blood samples, liquid biopsy, radiomics, digital pathology, clinical features by deep learning with artificial intelligence.

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