血浆血管生成因子是转移性结直肠癌二线化疗联合血管生成抑制剂疗效的预测因子：GI-SCREEN CRC-Ukit研究结果

IF 4.3 3区材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-06-01 DOI:10.1016/j.clcc.2024.01.003

Satoshi Yuki , Kentaro Yamazaki , Yu Sunakawa , Hiroya Taniguchi , Hideaki Bando , Manabu Shiozawa , Tomohiro Nishina , Hisateru Yasui , Akiyoshi Kanazawa , Koji Ando , Yosuke Horita , Masahiro Goto , Naohiro Okano , Toshikazu Moriwaki , Taroh Satoh , Akihito Tsuji , Kaname Yamashita , Chiharu Asano , Yukiko Abe , Shogo Nomura , Takayuki Yoshino

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引用次数: 0

摘要

背景血管生成因子与血管生成抑制剂联合治疗转移性结直肠癌（mCRC）时作为二线化疗（2L）疗效预测因子的意义仍未确定。患者与方法在这项多中心前瞻性观察研究中，使用 Luminex® 多重检测法对治疗前和进展期采集的血浆样本中的 17 种血管生成因子进行了分析。研究对象包括接受化疗加贝伐单抗（BEV 组）、FOLFIRI 加 Ramucirumab（RAM 组）或 FOLFIRI 加 aflibercept（AFL 组）作为 2L 治疗的患者。使用倾向分数加权 Cox 比例危险模型评估了预处理与治疗组之间在无进展生存期（PFS）、总生存期（OS）和应答率（RR）方面的相互作用。结果从 2018 年 2 月到 2020 年 9 月，在 2L 队列中分析了 283 例患者。观察到BEV和RAM与HGF、sNeuropilin-1、sVEGFR-1和sVEGFR-3的PFS之间存在强烈的相互作用。sNeuropilin-1和sVEGFR-1与BEV组和RAM组的RR之间存在相互作用。相反，OS、PlGF、sVEGFR-1 和 sVEGFR-3 可区分 BEV 和 AFL 的治疗效果。对 203 例患者的血浆样本进行了动态分析评估。结论在2L mCRC联合化疗时，治疗前血浆sVEGFR-1和sVEGFR-3水平可作为区分BEV和RAM的预测性生物标志物。临床试验编号UMIN000028616MicroAbstract：我们研究了血浆血管生成因子能否预测抗血管生成抑制剂联合化疗在转移性结直肠癌（mCRC）二线（2L）治疗中的疗效。研究还评估了二线治疗期间进展期血浆血管生成因子的动态变化。治疗前血浆sVEGFR-1和sVEGFR-3水平可能是区分贝伐珠单抗和雷莫芦单抗与化疗联合治疗mCRC二线疗程的预测性生物标志物。

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Plasma Angiogenic Factors as Predictors of the Efficacy of Second-line Chemotherapy Combined with Angiogenesis Inhibitors in Metastatic Colorectal Cancer: Results From the GI-SCREEN CRC-Ukit Study

Background

The significance of angiogenic factors as predictors of second-line (2L) chemotherapy efficacy when combined with angiogenesis inhibitors for metastatic colorectal cancer (mCRC) remains unestablished.

Patients and Methods

In this multicenter prospective observational study, 17 angiogenic factors were analyzed in plasma samples collected at pretreatment and progression stages using a Luminex multiplex assay. Patients who received chemotherapy plus bevacizumab (BEV group), FOLFIRI plus ramucirumab (RAM group), or FOLFIRI plus aflibercept (AFL group) as the 2L treatment were included. Interactions between pretreatment and treatment groups for progression-free survival (PFS), overall survival (OS), and response rate (RR) were assessed using the propensity-score weighted Cox proportional hazards model.

Results

From February 2018 to September 2020, 283 patients were analyzed in the 2L cohort. A strong interaction was observed for PFS between BEV and RAM with HGF, sNeuropilin-1, sVEGFR-1, and sVEGFR-3. Interactions for RR between the BEV and RAM groups were observed for sNeuropilin-1 and sVEGFR-1. Contrarily, OS, PlGF, sVEGFR-1, and sVEGFR-3 differentiated the treatment effect between BEV and AFL. Plasma samples were evaluable for dynamic analysis in 203 patients. At progression, VEGF-A levels significantly decreased in the BEV group and increased in the RAM and AFL groups.

Conclusion

The pretreatment plasma sVEGFR-1 and sVEGFR-3 levels could be predictive biomarkers for distinguishing BEV and RAM when combined with chemotherapy in 2L mCRC treatment. Based on the VEGF-A dynamics at progression, selecting RAM or AFL for patients with significantly elevated VEGF-A levels may be a 2L treatment strategy, with BEV considered for the third-line treatment.