Iwao-Koizumi Kyoko, Matoba Ryo, Ueno Noriko, Kim Seung Jin, Ando Akiko, Miyoshi Yasuo, Maeda Eisaku, Noguchi Shinzaburo, Kato Kikuya
Osaka Medical Center for Cancer and Cardiovascular Diseases, 1-3-2 Nakamichi, Higashinari-ku, Osaka 537-8511, Japan.
J Clin Oncol. 2005 Jan 20;23(3):422-31. doi: 10.1200/JCO.2005.09.078.
Docetaxel is one of the most effective anticancer drugs available in the treatment of breast cancer. Nearly half of the treated patients, however, do not respond to chemotherapy and suffer from side effects. The ability to reliably predict a patient's response based on tumor gene expression will improve therapeutic decision making and save patients from unnecessary side effects.
A total of 44 breast tumor tissues were sampled by biopsy before treatment with docetaxel, and the response to therapy was clinically evaluated by the degree of reduction in tumor size. Gene expression profiling of the biopsy samples was performed with 2,453 genes using a high-throughput reverse transcriptase polymerase chain reaction technique. Using genes differentially expressed between responders and nonresponders, a diagnostic system based on the weighted-voting algorithm was constructed.
This system predicted the clinical response of 26 previously unanalyzed samples with over 80% accuracy, a level promising for clinical applications. Diagnostic profiles in nonresponders were characterized by elevated expression of genes controlling the cellular redox environment (ie, redox genes, such as thioredoxin, glutathione-S-transferase, and peroxiredoxin). Overexpression of these genes protected cultured mammary tumor cells from docetaxel-induced cell death, suggesting that enhancement of the redox system plays a major role in docetaxel resistance.
These results suggest that the clinical response to docetaxel can be predicted by gene expression patterns in biopsy samples. The results also suggest that one of the molecular mechanisms of the resistance is activation of a group of redox genes.
多西他赛是治疗乳腺癌最有效的抗癌药物之一。然而,近一半接受治疗的患者对化疗无反应且遭受副作用。基于肿瘤基因表达可靠预测患者反应的能力将改善治疗决策,并使患者免受不必要的副作用。
在用多西他赛治疗前,通过活检对44个乳腺肿瘤组织进行采样,并根据肿瘤大小的缩小程度对治疗反应进行临床评估。使用高通量逆转录聚合酶链反应技术对活检样本进行2453个基因的基因表达谱分析。利用反应者和无反应者之间差异表达的基因,构建了基于加权投票算法的诊断系统。
该系统对26个先前未分析的样本的临床反应预测准确率超过80%,这一水平有望用于临床应用。无反应者的诊断特征是控制细胞氧化还原环境的基因(即氧化还原基因,如硫氧还蛋白、谷胱甘肽-S-转移酶和过氧化物酶)表达升高。这些基因的过表达保护培养的乳腺肿瘤细胞免受多西他赛诱导的细胞死亡,表明氧化还原系统的增强在多西他赛耐药中起主要作用。
这些结果表明,活检样本中的基因表达模式可预测对多西他赛的临床反应。结果还表明,耐药的分子机制之一是一组氧化还原基因的激活。