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前瞻性分析 VEGF-A 基因多态性对转移性乳腺癌患者贝伐珠单抗治疗药效学的影响。

Prospective analysis of the impact of VEGF-A gene polymorphisms on the pharmacodynamics of bevacizumab-based therapy in metastatic breast cancer patients.

机构信息

Centre Antoine Lacassagne, Nice, France.

出版信息

Br J Clin Pharmacol. 2011 Jun;71(6):921-8. doi: 10.1111/j.1365-2125.2010.03896.x.

Abstract

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

• Functional polymorphisms on the VEGF-A gene, known to be linked to cancer risk or to VEGF-A plasma concentrations, have been identified. So far, limited knowledge has been published on the relationships between toxicity/efficacy of bevacizumab-based therapy and VEGF-A polymorphisms (tumoral DNA). We therefore prospectively tested the impact of these five gene polymorphisms (blood DNA) on the pharmacodynamics of bevacizumab-based treatment administered in metastatic breast cancer patients.

WHAT THIS STUDY ADDS

• Present data obtained from a prospective study suggest a role for VEGF-A 936C > T polymorphism as a potential predictor of time to progression in breast cancer patients receiving bevacizumab-containing therapy. Also, the VEGF-A-634G > C polymorphism was linked to bevacizumab-related toxicity. AIMS To test prospectively the impact of VEGF-A gene polymorphisms on the pharmacodynamics of bevacizumab-chemotherapy in breast cancer patients.

METHODS

As part of the single-arm MO19391 trial, 137 women with locally recurrent or metastatic breast cancer receiving first-line bevacizumab-containing therapy were analysed. Patients received bevacizumab associated (76%) or not (24%) with taxane-based chemotherapy. Clinical evaluation included clinical response, time to progression (TTP) and a toxicity score corresponding to the sum of each maximum observed toxicity grade (hypertension, haemorrhage, arterial and venous thrombo-embolism). Functional VEGF-A polymorphisms at position -2578 C > A, -1498 T > C, -1154 G > A, -634 G > C and 936 C > T were analysed by PCR-RFLP (blood DNA).

RESULTS

Overall response rate (complete response (CR) + partial response (PR)) was 61%. Median TTP was 11 months. None of the VEGF-A polymorphisms was significantly linked to clinical response. Analysis of the 936C > T polymorphism revealed that the 96 patients homozygous for the 936C allele exhibited a marked tendency for a shorter TTP (median 9.7 months) than the 32 patients bearing the 936T allele (median 11.5 months, P= 0.022) of which 30 were CT and two were homozygous TT. Other polymorphisms did not influence TTP. VEGF-A-634 G > C was significantly related to the toxicity score with 39%, 49% and 81% of patients with score >1 in GG, GC and CC patients, respectively (P= 0.01).

CONCLUSIONS

The role for VEGF-A 936C > T polymorphism as a potential marker of TTP in breast cancer patients receiving bevacizumab-containing therapy concords with the known impact of VEGF-A 936C > T polymorphism on VEGF-A expression.

摘要

已知该主题的相关信息

  • 已鉴定出血管内皮生长因子 A (VEGF-A)基因上的功能多态性,已知这些多态性与癌症风险或 VEGF-A 血浆浓度有关。迄今为止,关于贝伐珠单抗治疗的毒性/疗效与 VEGF-A 多态性(肿瘤 DNA)之间的关系,发表的知识有限。因此,我们前瞻性地检测了这 5 个基因多态性(血液 DNA)对转移性乳腺癌患者接受贝伐珠单抗治疗的药效学的影响。

本研究的新发现

  • 目前从一项前瞻性研究中获得的数据表明,VEGF-A936C>T 多态性可作为乳腺癌患者接受贝伐珠单抗治疗时进展时间的潜在预测因子。此外,VEGF-A-634G>C 多态性与贝伐珠单抗相关毒性有关。

目的

前瞻性检测 VEGF-A 基因多态性对乳腺癌患者接受贝伐珠单抗联合化疗的药效学的影响。

方法

作为 MO19391 单臂试验的一部分,对 137 例局部复发或转移性乳腺癌患者进行了分析,这些患者接受了一线贝伐珠单抗联合治疗。患者接受了贝伐珠单抗联合(76%)或不联合(24%)紫杉醇类药物化疗。临床评估包括临床反应、无进展生存期(TTP)和毒性评分,毒性评分对应于每个最大观察到的毒性等级的总和(高血压、出血、动脉和静脉血栓栓塞)。通过 PCR-RFLP(血液 DNA)分析了 VEGF-A 基因在位置-2578C > A、-1498T > C、-1154G > A、-634G > C 和 936C > T 的功能多态性。

结果

总缓解率(完全缓解(CR)+部分缓解(PR))为 61%。中位 TTP 为 11 个月。VEGF-A 多态性均与临床反应无显著相关性。对 936C>T 多态性的分析表明,96 例纯合子 936C 等位基因的患者 TTP 明显缩短(中位 9.7 个月),而 32 例携带 936T 等位基因的患者 TTP 较长(中位 11.5 个月,P=0.022),其中 30 例为 CT,2 例为 TT。其他多态性对 TTP 没有影响。VEGF-A-634G>C 与毒性评分显著相关,GG、GC 和 CC 患者的评分>1 的患者分别为 39%、49%和 81%(P=0.01)。

结论

VEGF-A936C>T 多态性作为接受贝伐珠单抗治疗的乳腺癌患者 TTP 的潜在标志物的作用与 VEGF-A936C>T 多态性对 VEGF-A 表达的已知影响一致。

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本文引用的文献

2
Biomarkers of angiogenesis and their role in the development of VEGF inhibitors.
Br J Cancer. 2010 Jan 5;102(1):8-18. doi: 10.1038/sj.bjc.6605483. Epub 2009 Dec 15.
3
Bevacizumab in the treatment of breast cancer.
Cancer Treat Rev. 2010 Feb;36(1):75-82. doi: 10.1016/j.ctrv.2009.10.007. Epub 2009 Nov 22.
4
The role of vascular endothelial growth factor SNPs as predictive and prognostic markers for major solid tumors.
Mol Cancer Ther. 2009 Sep;8(9):2496-508. doi: 10.1158/1535-7163.MCT-09-0302. Epub 2009 Sep 15.
7
VEGF-A splicing: the key to anti-angiogenic therapeutics?
Nat Rev Cancer. 2008 Nov;8(11):880-7. doi: 10.1038/nrc2505. Epub 2008 Oct 16.
10
Paclitaxel plus bevacizumab versus paclitaxel alone for metastatic breast cancer.
N Engl J Med. 2007 Dec 27;357(26):2666-76. doi: 10.1056/NEJMoa072113.

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