Study of differential proteins in lung adenocarcinoma using laser capture microdissection combined with liquid chip-mass spectrometry technology

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BU LinaYANG ShuanyingLI FengtaoSHANG WenliZHANG WeiHUO ShufenNAN Yandong TIAN YingxuanDU JieLIN XiuliLIU YanfengLIN Yurong and RONG Biaoxue Department of Respiratory Medicine Department of General Thoracic Surgery Second Affiliated Hospital of Medical SchoolXian Jiaotong UniversityXianShaanxi China Department of Respiratory MedicineXian Second Hospital XianShaanxi China [710004 ,710004 ]
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<正> Background In recent years the proportion of lung adenocarcinoma (adCA) which occurs in lung cancer patients hasincreased.Using laser capture microdissection (LCM) combined with liquid chip-mass spectrometry technology,weaimed 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 thehomogeneous adCA cells and normal cells from six cases of fresh adCA and matched normal lung tissues.The proteinswere 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 2.895×10~6 and 1.584×10~6 cells were satisfactorily obtained by LCM from six cases of fresh lung adCAand matched normal lung tissues,respectively.The homogeneities of cell population were estimated to be over 95% asdetermined by microscopic visualization.Comparing the differentially expressed proteins between the lung adCA and thematched 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 t test,the expression of two protein peaks at 7521.5 M/Z and 5079.3 M/Zhad the largest difference between tissues.They were more weakly expressed in the lung adCA compared to thematched normal group.The two protein peaks could accurately separate the lung adCA from the matched normal lunggroup by the sample distribution chart.A discriminatory pattern which can separate the lung adCA from the matchednormal lung tissue consisting of three proteins at 3358.1 M/Z,5079.3 M/Z and 7521.5 M/Z was established by a radialbasic 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-massspectrometry technology,and a biomarker model was established.It is possible that this technology is going to become apowerful tool in screening and early diagnosis of lung adCA.
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