Campbell Family Institute for Breast Cancer Research, University Health Network, Toronto, Ontario, Canada.
PLoS One. 2012;7(2):e30992. doi: 10.1371/journal.pone.0030992. Epub 2012 Feb 20.
Breast cancer is the most common malignancy among women worldwide in terms of incidence and mortality. About 10% of North American women will be diagnosed with breast cancer during their lifetime and 20% of those will die of the disease. Breast cancer is a heterogeneous disease and biomarkers able to correctly classify patients into prognostic groups are needed to better tailor treatment options and improve outcomes. One powerful method used for biomarker discovery is sample screening with mass spectrometry, as it allows direct comparison of protein expression between normal and pathological states. The purpose of this study was to use a systematic and objective method to identify biomarkers with possible prognostic value in breast cancer patients, particularly in identifying cases most likely to have lymph node metastasis and to validate their prognostic ability using breast cancer tissue microarrays.
Differential proteomic analyses were employed to identify candidate biomarkers in primary breast cancer patients. These analyses identified decorin (DCN) and endoplasmin (HSP90B1) which play important roles regulating the tumour microenvironment and in pathways related to tumorigenesis. This study indicates that high expression of Decorin is associated with lymph node metastasis (p<0.001), higher number of positive lymph nodes (p<0.0001) and worse overall survival (p = 0.01). High expression of HSP90B1 is associated with distant metastasis (p<0.0001) and decreased overall survival (p<0.0001) these patients also appear to benefit significantly from hormonal treatment.
Using quantitative proteomic profiling of primary breast cancers, two new promising prognostic and predictive markers were found to identify patients with worse survival. In addition HSP90B1 appears to identify a group of patients with distant metastasis with otherwise good prognostic features.
乳腺癌是全球女性中发病率和死亡率最高的最常见恶性肿瘤。约 10%的北美女性在其一生中会被诊断患有乳腺癌，其中 20%的患者将死于该疾病。乳腺癌是一种异质性疾病，需要能够将患者正确分类为预后组的生物标志物，以更好地定制治疗方案并改善预后。用于生物标志物发现的一种强大方法是使用质谱进行样本筛选，因为它允许在正常和病理状态之间直接比较蛋白质表达。本研究的目的是使用系统和客观的方法来鉴定乳腺癌患者中具有潜在预后价值的生物标志物，特别是在确定最有可能发生淋巴结转移的病例方面，并使用乳腺癌组织微阵列来验证其预后能力。
采用差异蛋白质组学分析鉴定原发性乳腺癌患者的候选生物标志物。这些分析鉴定了核心蛋白聚糖 (DCN) 和内质网蛋白 90kDaβ1 (HSP90B1)，它们在调节肿瘤微环境和与肿瘤发生相关的途径中发挥重要作用。本研究表明，高表达 Decorin 与淋巴结转移 (p<0.001)、阳性淋巴结数量较多 (p<0.0001) 和总体生存较差 (p=0.01) 相关。HSP90B1 高表达与远处转移 (p<0.0001) 和总体生存降低 (p<0.0001) 相关，这些患者似乎也从激素治疗中显著获益。
使用原发性乳腺癌的定量蛋白质组学分析，发现了两个新的有前途的预后和预测标志物，可用于识别生存较差的患者。此外，HSP90B1 似乎可以识别出一组具有远处转移但预后良好的患者。
