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在一项采用或不采用新辅助化疗的放射化学疗法的II期晚期宫颈癌试验中,对血管生成生物标志物进行探索性无监督机器学习。

Exploratory unsupervised machine learning of angiogenesis biomarkers in a phase II advanced cervical cancer trial of radiochemotherapy with or without neoadjuvant chemotherapy.

作者信息

Arai Roberto J, da Costa Thiago R, Bonadio Renata Colombo, Ferreira Silvaneide, Sichero Laura, Monteiro Hugo P, Stern Arnold, Estevez-Diz Maria Del Pilar

机构信息

Instituto do Câncer do Estado de São Paulo (ICESP), Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil; AW Scientific Engineering, Londrina, PR, Brazil.

Instituto do Câncer do Estado de São Paulo (ICESP), Faculdade de Medicina da Universidade de São Paulo, São Paulo, SP, Brazil.

出版信息

Clinics (Sao Paulo). 2025 Jul 30;80:100723. doi: 10.1016/j.clinsp.2025.100723.

Abstract

OBJECTIVE

In a prospective, randomized phase II study, exploratory data analysis was conducted to evaluate angiogenesis-associated plasma protein levels in patients with locally advanced cervical cancer METHODS: Participants were divided into two groups: Group A received neoadjuvant cisplatin and gemcitabine treatment (NAC) followed by chemoradiation with cisplatin and brachytherapy (CRT), while Group B received only CRT. Plasma samples were collected from patients in Group A at three time points: baseline, after NAC, and after CRT. Group B patients had samples taken at two time points: baseline and after CRT. The study analyzed an angiogenesis-associated panel of plasma proteins, including angiopoietin-2, G-CSF, endothelin-1, FGF-1, FGF-2, follistatin, IL-8, HGF, EGF, HB-EGF, PLGF, VEGF-A, VEGF-C, and VEGF- D. Receiver Operating Characteristic (ROC) analyses assessed the predictive value of baseline biomarkers for 12, 24, and 36-month survival outcomes. Additionally, Principal Component Analysis (PCA) was applied to post-CRT biomarker changes to identify coordinated modulation patterns. PCA was based on normalized delta values and eigenvector loadings, enabling identification of biomarkers aligned with Progression-Free Survival (PFS) and Overall Survival (OS).

RESULTS

Significant differences were observed in the levels of HB-EGF, IL-8, PLGF, and VEGF-C between Groups A and B following CRT. Additionally, angiopoietin-2 levels showed a significant increase in Group B only. NAC treatment in Group A appeared to downregulate IL-8. CRT induced significant changes in HB-EGF, IL-8, PLGF, and VEGF-C levels in both groups. Patients in Group B demonstrated improved PFS and OS compared to those in Group A. Despite these differences in survival outcomes, the authors observed no significant intergroup differences in the tested biomarkers after completion of CRT. ROC analysis of baseline angiogenesis biomarkers demonstrated limited predictive sensitivity for survival outcomes. However, PCA of biomarker changes following CRT highlighted VEGF-A, HB-EGF, and angiopoietin-2 as variables associated with PFS and OS.

CONCLUSION

Baseline biomarker levels were not predictive of long-term outcomes. In contrast, CRT alone modulated key angiogenic biomarkers, and post-CRT biomarker changes were associated with improved survival. Such biomarker alterations were not observed following NAC, which was not associated with clinical benefit in this study. These findings underscore the value of dynamic biomarker evaluation and highlight how treatment strategies differentially impact biomarker profiles in advanced cervical cancer.

摘要

目的

在一项前瞻性随机II期研究中,进行探索性数据分析以评估局部晚期宫颈癌患者中与血管生成相关的血浆蛋白水平。方法:参与者分为两组:A组接受新辅助顺铂和吉西他滨治疗(NAC),随后进行顺铂同步放化疗和近距离放疗(CRT),而B组仅接受CRT。在三个时间点从A组患者采集血浆样本:基线、NAC后和CRT后。B组患者在两个时间点采集样本:基线和CRT后。该研究分析了一组与血管生成相关的血浆蛋白,包括血管生成素-2、粒细胞集落刺激因子(G-CSF)、内皮素-1、成纤维细胞生长因子-1(FGF-1)、成纤维细胞生长因子-2(FGF-2)、卵泡抑素、白细胞介素-8(IL-8)、肝细胞生长因子(HGF)、表皮生长因子(EGF)、肝素结合表皮生长因子(HB-EGF)、胎盘生长因子(PLGF)、血管内皮生长因子-A(VEGF-A)、血管内皮生长因子-C(VEGF-C)和血管内皮生长因子-D(VEGF-D)。受试者工作特征(ROC)分析评估了基线生物标志物对12个月、24个月和36个月生存结局的预测价值。此外,主成分分析(PCA)应用于CRT后生物标志物的变化,以识别协同调节模式。PCA基于标准化的差值和特征向量载荷,能够识别与无进展生存期(PFS)和总生存期(OS)相关的生物标志物。

结果

CRT后,A组和B组之间的HB-EGF、IL-8、PLGF和VEGF-C水平存在显著差异。此外,血管生成素-2水平仅在B组显著升高。A组的NAC治疗似乎下调了IL-8。CRT使两组的HB-EGF、IL-8、PLGF和VEGF-C水平发生显著变化。与A组患者相比,B组患者的PFS和OS有所改善。尽管生存结局存在这些差异,但作者观察到CRT完成后,测试的生物标志物在组间无显著差异。基线血管生成生物标志物的ROC分析显示对生存结局的预测敏感性有限。然而,CRT后生物标志物变化的PCA突出了VEGF-A、HB-EGF和血管生成素-2作为与PFS和OS相关的变量。

结论

基线生物标志物水平不能预测长期结局。相比之下,单独的CRT调节关键的血管生成生物标志物,CRT后生物标志物的变化与生存率提高相关。NAC后未观察到此类生物标志物改变,本研究中NAC未带来临床获益。这些发现强调了动态生物标志物评估的价值,并突出了治疗策略如何对晚期宫颈癌的生物标志物谱产生不同影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3170/12332904/bc7de8fcb588/gr1.jpg

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