Background Recently, due to the rapid development of proteomic techniques, great advance has been made in many scientific fields. We aimed to use magnetic beads （liquid chip） based matrix-assisted laser desorption/ionization time-of-flight mass spectrometry （MALDI-TOF-MS） technology to screen distinctive biomarkers for lung adenocarcinoma （adCA）, and to establish the diagnostic protein profiles. Methods Using weak cation exchange magnetic beads （MB-WCX） to isolate and purify low molecular weight proteins from sera of 35 lung adCA, 46 benign lung diseases （BLDs） and 44 healthy individuals. The resulting spectra gained by anchor chip-MALDI-TOF-MS were analyzed by ClinProTools and a pattern recognition genetic algorithm （GA）. Results In the working mass range of 800-10 000 Da, 99 distinctive peaks were resolved in lung adCA versus BLDs, while 101 peaks were resolved in lung adCA versus healthy persons. The profile gained by GA that could distinguish adCA from BLDs was comprised of 4053.88, 4209.57 and 3883.33 Da with sensitivity of 80%, specificity of 93%, while that could separate adCA from healthy control was comprised of 2951.83 Da and 4209.73 Da with sensitivity of 94%, specificity of 95%. The sensitivity provided by carcinoembryonic antigen （CEA） in this experiment was significantly lower than our discriminatory profiles （P 〈0.005）. We further identified a eukaryotic peptide chain release factor GTP-binding subunit （eRF3b） （4209 Da） and a complement C3f （1865 Da） that may serve as candidate biomarkers for lung adCA. Conclusion Magnetic beads based MALDI-TOF-MS technology can rapidly and effectively screen distinctive proteins/polypeptides from sera of lung adCA patients and controls, which has potential value for establishing a new diagnostic method for lung adCA.
LIN Xiu-liYANG Shuan-yingDU JieTIAN Ying-xuanBU Li-naHUO Shu-fenWANG Feng-pengNAN Yan-dong
Background In recent years the proportion of lung adenocarcinoma （adCA） which occurs in lung cancer patients has increased. Using laser capture microdissection （LCM） combined with liquid chip-mass spectrometry technology, we aimed to screen lung cancer biomarkers by studying the proteins in the tissues of adCA. Methods We used LCM and magnetic bead based weak cation exchange （MB-WCX） to separate and purify the homogeneous adCA cells and normal cells from six cases of fresh adCA and matched normal lung tissues. The proteins were analyzed and identified by matrix assisted laser desorption/ionization time-of-fight mass spectrometry （MALDI-OF-MS）. We screened for the best pattern using a radial basic function neural network algorithm. Results About 2.895x10s and 1.584x10s cells were satisfactorily obtained by LCM from six cases of fresh lung adCA and matched normal lung tissues, respectively. The homogeneities of cell population were estimated to be over 95% as determined by microscopic visualization. Comparing the differentially expressed proteins between the lung adCA and the matched normal lung group, 221 and 239 protein peaks, respectively, were found in the mass-to-charge ration （M/Z） between 800 Da and 10 000 Da. According to ttest, the expression of two protein peaks at 7521.5 M/Zand 5079.3 M/Z had the largest difference between tissues. They were more weakly expressed in the lung adCA compared to the matched normal group. The two protein peaks could accurately separate the lung adCA from the matched normal lung group by the sample distribution chart. A discriminatory pattern which can separate the lung adCA from the matched normal lung tissue consisting of three proteins at 3358.1 M/Z, 5079.3 M/Z and 7521.5 M/Z was established by a radial basic function neural network algorithm with a sensitivity of 100% and a specificity of 100%. Conclusions Differential proteins in lung adCA were screened using LCM combined with liquid chip-mass spectrometry technology, and a biomarker model was establis
目的评价酶联免疫吸附(ELISA)法检测血清胃泌素释放前体肽(Pro-GRP)诊断小细胞肺癌(SCLC)的价值。方法检索PubMed、Cochrane、ISI Web of Knowledge等数据库,检索时间为1990～2009年发表的文献,收集关于ELISA法检测血清Pro-GRP诊断SCLC的相关文献并进行信息统计、科学性评估及质量分级;采用Meta-Disc1.4软件进行数据分析;通过汇总敏感度、特异度、汇总似然比及汇总受试者工作特征曲线(SROC曲线)等统计指标综合评价ELISA法检测血清Pro-GRP对SCLC的早期诊断价值。结果共纳入11篇文献,其中英文文献6篇,中文文献5篇,样本量为3 554例,其中经病理学确诊的SCLC为1 122例,NSCLC为2 432例。异质性检验显示纳入研究齐性好,通过确定模型的汇总计算得出汇总敏感度为0.75(0.73,0.78),汇总特异度为0.93(0.92,0.94),汇总阳性似然比11.44,汇总阴性似然比0.27,SROC曲线下面积为0.93。结论 Pro-GRP在早期诊断SCLC中具有一定的参考价值,可作为较重要的参考指标之一。
目的应用Meta分析法综合评价痰细胞学液基薄层检测技术对支气管肺癌的诊断价值。方法检索PubMed、Cochrane、ISI Web of Knowledge等数据库,检索时间为1990年1月至2011年2月发表的相关文献,收集关于痰细胞学液基薄层检测技术诊断支气管肺癌的相关研究文献并进行信息统计、科学性评估及质量分级;采用Meta-Disc1.4软件固定效应模型进行数据分析;通过汇总敏感度、特异度、汇总似然比及汇总受试者工作特征曲线(SROC曲线)等统计指标综合评价痰细胞学液基薄层检测技术对支气管肺癌的诊断价值。结果共纳入8篇文献,其中英文2篇,中文6篇,样本量为2584例,其中经组织病理学确诊或明确临床诊断的支气管肺癌共1719例,865例非肺部恶性肿瘤患者为对照。异质性检验显示纳入研究齐性好,通过固定模型的汇总计算得出汇总灵敏度为0.44(95%CI0.42,0.46),汇总特异度为1.00(95%CI0.99,1.00),汇总阳性似然比为72.54(95%CI31.66,166.17),汇总阴性似然比为0.50(95%CI0.47,0.53),SROC曲线下面积为0.9736。结论汇总相关研究结果表明:痰细胞学液基薄层检测技术在支气管肺癌的诊断中特异度达到0.99～1.00,但灵敏度仅为0.44,尚不适用于支气管肺癌的筛查。但是本研究纳入文献有限,需要更多高质量、大样本、多中心的研究加以验证。
