Wong Y F, Cheung T H, Lo K W K, Wang V W, Chan C S, Ng T B, Chung T K H, Mok S C
Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, N.T., Hong Kong, China.
Cancer Lett. 2004 Aug 10;211(2):227-34. doi: 10.1016/j.canlet.2004.02.014.
Analysis of multiple proteins is thought to be essential for establishment of signature proteomic patterns that may distinguish cancer from non-cancer. Surface-enhanced laser desorption/ionization (SELDI) is an affinity-based mass spectrometric method in which proteins of interest are selectively absorbed to a chemically modified surface on a biochip. This technology may provide protein profiling of a variety of biological specimens. In this study, we explored whether the protein biochip SELDI approach could differentiate cervical cancer from non-cancer cohorts. We screened protein profiles generated by SELDI in 62 cervical epithelial cell samples microdissected from 35 invasive cervical cancer and 27 age-matched normal cervix tissue specimens, respectively. The cell lysates of pure populations of cervical cells were applied onto Ciphergen ProteinChip WCX2 Arrays. Proteins bound to the chips were analyzed on a ProteinChip Reader Model PBS II. Derived proteomic patterns were converted to a simple proteomic scoring for distinguishing cancer from non-cancer cohorts. SELDI protein profiles of cell lysates from 20 cervical cancer and 15 normal cervix tissue specimens were used to train and develop a classification scoring system that used a seven-protein mass pattern. The training samples could be correctly discriminated. When a test set of 27 samples was used for evaluation of this scoring system to distinguish cervical cancer from non-cancer, a sensitivity of 87%, a specificity of 100%, a positive predictive value of 100%, and a negative predictive value of 86% for the test population were obtained. All seven proteins appeared to be down regulated in cervical cancer. The results from this study indicate that the proteomics approach of SELDI mass spectrometry, in combination with a simple scoring system, may distinguish cervical cancer from its normal counterpart. If this approach is also workable in the analysis of cervical exfoliated cell lysate, it might potentially be used in the early diagnosis of invasive cervical cancer. In addition, the identification of these specific proteins in cervical cancer may also facilitate the discovery of new cervical tumor marker(s).
对多种蛋白质进行分析被认为对于建立能够区分癌症与非癌症的标志性蛋白质组学模式至关重要。表面增强激光解吸/电离（SELDI）是一种基于亲和的质谱方法，其中感兴趣的蛋白质被选择性地吸附到生物芯片上经过化学修饰的表面。这项技术可以提供各种生物样本的蛋白质谱分析。在本研究中，我们探讨了蛋白质生物芯片SELDI方法能否区分宫颈癌与非癌症队列。我们筛选了通过SELDI分别从35例浸润性宫颈癌和27例年龄匹配的正常宫颈组织标本中显微切割得到的62个宫颈上皮细胞样本所产生的蛋白质谱。将宫颈细胞纯群体的细胞裂解物应用于Ciphergen ProteinChip WCX2阵列。在ProteinChip Reader Model PBS II上分析与芯片结合的蛋白质。将得到的蛋白质组学模式转换为一个简单的蛋白质组学评分，用于区分癌症与非癌症队列。来自20例宫颈癌和15例正常宫颈组织标本的细胞裂解物的SELDI蛋白质谱用于训练和开发一种使用七种蛋白质质量模式的分类评分系统。训练样本能够被正确区分。当使用27个样本的测试集来评估该评分系统以区分宫颈癌与非癌症时，测试人群的灵敏度为87%，特异性为100%，阳性预测值为100%，阴性预测值为86%。所有七种蛋白质在宫颈癌中似乎都下调。本研究结果表明，SELDI质谱的蛋白质组学方法与一个简单的评分系统相结合，可能区分宫颈癌与其正常对应物。如果这种方法在宫颈脱落细胞裂解物分析中也可行，它可能潜在地用于浸润性宫颈癌的早期诊断。此外，在宫颈癌中鉴定这些特定蛋白质也可能有助于发现新的宫颈肿瘤标志物。
