Shao Bin, Tian Zhihua, Ding Huirong, Wang Qingsong, Song Guohong, Di Lijun, Zhang Hong, Li Huiping, Shen Jing
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Department of Medical Oncology, Peking University Cancer Hospital & Institute Beijing, P. R. China.
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Central Laboratory, Peking University Cancer Hospital & Institute Beijing, P. R. China.
Int J Clin Exp Pathol. 2018 Feb 1;11(2):650-663. eCollection 2018.
Chemotherapy resistance is a great obstacle in effective treatment for metastatic triple negative breast cancer (TNBC). The ability to predict chemotherapy response would allow chemotherapy administration to be directed toward only those patients who would benefit, thus maximizing treatment efficiency. Differentially expressed plasma proteins may serve as putative biomarkers for predicting chemotherapy outcomes.
In this study, 26 plasma samples (10 samples with partial response (S) and 16 samples with progression disease (R)) from patients with metastatic TNBC were measured by Tandem Mass Tag (TMT)-based proteomics analysis to identify differentially expressed proteins between the S and R group. Potential proteinswere validated with enzyme-linked immunosorbent assay (ELISA) in another 67 plasma samples.
A total of 320 plasma proteins were identified, and statistical analysis showed that 108 proteins were significantly dysregulated between R and S groups in the screening stage. Bioinformatics revealed relevant pathways and regulatory networks of the differentially expressed proteins. Three differentially expressed proteins were validated by ELISA with 67 samples from TNBC patients. The R group had significantly higher plasma CAMK2A level than the S group (=0.0074). The ROC curve analysis showed an AUC of 0.708, with sensitivity 48.4% and specificity 86.1%. In multivariate logistic regression analysis, the level of plasma CAMK2A was also significant for chemotherapeutic response (=0.009, OR=0.152). Furthermore, the patients with higher CAMK2A level had shorter OS than those with lower CAMK2A level, which amounted to 13.9 and 28.9 months, respectively (=0.034). In the multivariate Cox regression analysis, CAMK2A level still had significant effect on OS (=0.031, HR=1.865).
TMT-based proteomic analysis was able to identify potential biomarkers in plasma that predicted chemotherapy resistance in the metastatic TNBC. The plasma of CAMK2A level may serve as apotential predictive and prognostic biomarker for chemotherapy in metastatic TNBC.
化疗耐药是转移性三阴性乳腺癌（TNBC）有效治疗的一大障碍。预测化疗反应的能力可使化疗仅针对那些将从中受益的患者进行，从而最大限度地提高治疗效率。差异表达的血浆蛋白可能作为预测化疗结果的潜在生物标志物。
在本研究中，通过基于串联质谱标签（TMT）的蛋白质组学分析对26例转移性TNBC患者的血浆样本（10例部分缓解（S）样本和16例疾病进展（R）样本）进行检测，以鉴定S组和R组之间差异表达的蛋白质。在另外67份血浆样本中用酶联免疫吸附测定（ELISA）对潜在蛋白质进行验证。
共鉴定出320种血浆蛋白，统计分析显示在筛选阶段R组和S组之间有108种蛋白显著失调。生物信息学揭示了差异表达蛋白的相关通路和调控网络。用ELISA对来自TNBC患者的67份样本验证了3种差异表达蛋白。R组血浆CAMK2A水平显著高于S组（P = 0.0074）。ROC曲线分析显示曲线下面积（AUC）为0.708，敏感性为48.4%，特异性为86.1%。在多因素逻辑回归分析中，血浆CAMK2A水平对化疗反应也具有显著性（P = 0.009，比值比（OR）= 0.152）。此外，CAMK2A水平较高的患者总生存期（OS）短于CAMK2A水平较低的患者，分别为13.9个月和28.9个月（P = 0.034）。在多因素Cox回归分析中，CAMK2A水平对OS仍有显著影响（P = 0.031，风险比（HR）= 1.865）。
基于TMT的蛋白质组学分析能够鉴定出血浆中预测转移性TNBC化疗耐药的潜在生物标志物。血浆CAMK2A水平可能作为转移性TNBC化疗的潜在预测和预后生物标志物。
