Zhang Xing, Wang Bo, Zhang Xiao-shi, Li Zhi-ming, Guan Zhong-zhen, Jiang Wen-qi
Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, 510060, China.
BMC Cancer. 2007 Dec 29;7:235. doi: 10.1186/1471-2407-7-235.
Currently, there are no satisfactory biomarkers available to screen for diffuse large B cell lymphoma (DLBCL) or to identify patients who do not benefit from standard anti-cancer therapies. In this study, we used serum proteomic mass spectra to identify potential serum biomarkers and biomarker patterns for detecting DLBCL and patient responses to therapy.
The proteomic spectra of crude sera from 132 patients with DLBCL and 75 controls were performed by SELDI-TOF-MS and analyzed by Biomarker Patterns Software.
Nine peaks were considered as potential DLBCL discriminatory biomarkers. Four peaks were considered as biomarkers for predicting the patient response to standard therapy. The proteomic patterns achieved a sensitivity of 94% and a specificity of 94% for detecting DLBCL samples in the test set of 85 samples, and achieved a sensitivity of 94% and a specificity of 92% for detecting poor prognosis patients in the test set of 66 samples.
These proteomic patterns and potential biomarkers are hoped to be useful in clinical applications for detecting DLBCL patients and predicting the response to therapy.
目前,尚无令人满意的生物标志物可用于筛查弥漫性大B细胞淋巴瘤(DLBCL)或识别无法从标准抗癌治疗中获益的患者。在本研究中,我们使用血清蛋白质组质谱来识别潜在的血清生物标志物和生物标志物模式,以检测DLBCL及患者对治疗的反应。
采用表面增强激光解吸电离飞行时间质谱(SELDI-TOF-MS)对132例DLBCL患者和75例对照的粗血清进行蛋白质组质谱分析,并通过生物标志物模式软件进行分析。
九个峰被视为潜在的DLBCL鉴别生物标志物。四个峰被视为预测患者对标准治疗反应的生物标志物。在85个样本的测试集中,蛋白质组模式检测DLBCL样本的灵敏度为94%,特异性为94%;在66个样本的测试集中,检测预后不良患者的灵敏度为94%,特异性为92%。
这些蛋白质组模式和潜在的生物标志物有望在临床应用中用于检测DLBCL患者并预测治疗反应。