Suppr超能文献

基于基因组的局部晚期直肠癌患者放疗剂量调整模型(GARD)的验证

Validation of a genome-based model for adjusting radiotherapy dose (GARD) in patients with locally advanced rectal cancer.

作者信息

Xia Huang, Li Zeyuan, Lin Yineng, Lin Yu, Zeng Lijing, Xu Benhua, Yao Qiwei, Zheng Rong

机构信息

Department of Radiation Oncology, Fujian Medical University Union Hospital, Fuzhou, Fujian Province, People's Republic of China.

Fujian Key Laboratory of Intelligent Imaging and Precision Radiotherapy for Tumors, Fujian Medical University, Fuzhou, Fujian Province, People's Republic of China.

出版信息

Sci Rep. 2024 Sep 16;14(1):21572. doi: 10.1038/s41598-024-72818-w.

Abstract

Neoadjuvant radiotherapy is the standard care of locally advanced rectal cancer. Although a majority of patients received the same dose, the curative efficacy varies among individuals. In recent years, cancer treatment has entered the era of precise medical care, and how to identify patients for proper treatment by molecular signature is an important path of individualized therapy. This study aimed to establish and validate a genome-based model for adjusting radiation dose (GARD) for Chinese locally advanced rectal cancer through gene expression microarrays, and to evaluate the response of the GARD model in predicting the efficacy of neoadjuvant radiotherapy. Fresh-frozen primary tumor from 64 patients with locally advanced rectal cancer undergoing neoadjuvant radiotherapy from 2015 to 2018 were included. The gene expression profile was analyzed using Affymetrix 3000Dx gene-chip scanner. The radiosensitivity index (RSI) and GARD were calculated using the pGRT™ algorithm. Neoadjuvant rectal cancer score (NAR) was selected as efficacy evaluation indicators. Patients were divided into high and low NAR scoring groups, and two-sample t-test was used to analyze the differences in GARD values between different NAR subgroups. ROC curves were used to calculate the cut-off values and the area under the curve (AUC) for assessing the validity of the GARD models. The personalized radiation dose ( pGRT dose )can be computed using the formula nd = GARD / (α + βd). Among patients, 1.5% T2, 46.3% T3, and 52.2% T4. Wherein pCR (n = 10; 15.6%) and no pCR (n = 54; 84.4%). The median NAR is 8.43 (rang from 0 to 50.34, IQR 3.75-14.98). NAR > 8.43 (n = 27; 42.2%) and NAR ≤ 8.43 (n = 37; 57.8%), suggesting that there are significant individual differences in clinical efficacy of patients with similar tumor stages and under the same treatment conditions. The median RSI is 0.48 (rang from 0.22 to 0.92, IQR 0.41-0.55). Median GARD was 18.40 rang from (rang from 2.26 to 37.52, IQR 14.94-22.28) within tumor tissue, suggesting individual differences in the efficacy of radiation therapy. The RSI value was significantly lower in the NAR low group (NAR ≤ 8.43) than in NAR high group (NAR > 8.43) (0.44 vs. 0.54, p = 0.0003). The GARD value was significantly higher in the NAR low group (NAR ≤ 8.43) than in NAR high group (NAR > 8.43) (21.01 vs. 15.88, p = 0.0004). Using the Receiver Operating Characteristic (ROC) curve analysis, a GARD threshold of 17 was identified as optimal, covering 37.5% of the 64-patient sample, with an area under the curve (AUC) of 0.75. In the external validation cohort, the high GARD score group demonstrated superior DFS compared to the low GARD score group(p < 0.001). Only 17% of patients had pGRT dose within the guideline recommended dose (45-50 Gy). The differences in NAR values among LARC patients receiving standard neoadjuvant radiotherapy suggest significant individual differences in clinical outcomes among patients with similar tumor stage and the same treatment conditions. Patients with a GARD value exceeding 17 exhibit a more favorable prognosis. Our results suggest that the gene expression-based pGRT™ algorithm has good efficacy prediction performance in preoperative concurrent radiotherapy for locally advanced rectal cancer, suggesting the potential clinical application of this method to guide the designation of individualized radiotherapy doses.

摘要

新辅助放疗是局部晚期直肠癌的标准治疗方法。尽管大多数患者接受相同剂量的放疗,但其疗效在个体间存在差异。近年来,癌症治疗已进入精准医疗时代,如何通过分子特征识别适合治疗的患者是个体化治疗的重要途径。本研究旨在通过基因表达微阵列建立并验证一种基于基因组的中国局部晚期直肠癌放疗剂量调整模型(GARD),并评估GARD模型在预测新辅助放疗疗效方面的作用。纳入了2015年至2018年期间64例接受新辅助放疗的局部晚期直肠癌患者的新鲜冷冻原发性肿瘤。使用Affymetrix 3000Dx基因芯片扫描仪分析基因表达谱。使用pGRT™算法计算放射敏感性指数(RSI)和GARD。选择新辅助直肠癌评分(NAR)作为疗效评估指标。将患者分为NAR评分高、低两组,采用两样本t检验分析不同NAR亚组间GARD值的差异。采用ROC曲线计算临界值和曲线下面积(AUC),以评估GARD模型的有效性。个性化放疗剂量(pGRT剂量)可使用公式nd = GARD / (α + βd) 计算。患者中,1.5%为T2期,46.3%为T3期,52.2%为T4期。其中病理完全缓解(pCR)者10例(15.6%),未达到pCR者54例(84.4%)。NAR的中位数为8.43(范围为0至50.34,四分位间距为3.75 - 14.98)。NAR > 8.43者27例(42.2%),NAR ≤ 8.43者37例(57.8%),提示在肿瘤分期相似且治疗条件相同的患者中,临床疗效存在显著个体差异。RSI的中位数为0.48(范围为0.22至0.92,四分位间距为0.41 - 0.55)。肿瘤组织内GARD的中位数为18.40(范围为2.26至37.52,四分位间距为14.94 - 22.28),提示放疗疗效存在个体差异。NAR低分组(NAR ≤ 8.43)的RSI值显著低于NAR高分组(NAR > 8.43)(0.44对0.54,p = 0.0003)。NAR低分组(NAR ≤ 8.43)的GARD值显著高于NAR高分组(NAR > 8.43)(21.01对15.88,p = 0.0004)。通过受试者工作特征(ROC)曲线分析,确定GARD阈值为17时最佳,涵盖64例患者样本的37.5%,曲线下面积(AUC)为0.75。在外部验证队列中,GARD评分高的组与GARD评分低的组相比,无病生存期(DFS)更优(p < 0.001)。仅17%的患者pGRT剂量在指南推荐剂量(45 - 50 Gy)范围内。接受标准新辅助放疗的局部晚期直肠癌患者NAR值的差异表明,在肿瘤分期相似且治疗条件相同的患者中,临床结局存在显著个体差异。GARD值超过17的患者预后更佳。我们的结果表明,基于基因表达的pGRT™算法在局部晚期直肠癌术前同步放疗中具有良好的疗效预测性能,提示该方法在指导个体化放疗剂量制定方面具有潜在的临床应用价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/229f/11405410/3cd482682b9e/41598_2024_72818_Fig1_HTML.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验