基于二级质谱数据的非标记定量人肾透明细胞癌组织蛋白质组学研究

引用本文: 郭佳, 刘金华, 杨照微, 李毅, 何成彦. 基于二级质谱数据的非标记定量人肾透明细胞癌组织蛋白质组学研究[J]. 分析化学, 2020, 48(10): 1351-1358. doi: 10.19756/j.issn.0253-3820.201373 shu

Citation: GUO Jia, LIU Jin-Hua, YANG Zhao-Wei, LI Yi, HE Cheng-Yan. Proteomics Analysis of Human Renal Clear Cell Carcinoma by Two MS2-based Label-free Approaches[J]. Chinese Journal of Analytical Chemistry, 2020, 48(10): 1351-1358. doi: 10.19756/j.issn.0253-3820.201373 shu

基于二级质谱数据的非标记定量人肾透明细胞癌组织蛋白质组学研究

郭佳 ^1, ,
刘金华 ^1, ,
杨照微 ^1, ,
李毅 ^2, ,
何成彦 ^1,

1.
吉林大学中日联谊医院, 长春 130033;
2.
吉林大学口腔医院, 长春 130022
基金项目:
本文系国家自然科学基金项目（No.81572082）和吉林省科学技术厅基金项目（No.20190201215JC）资助

摘要: 晚期肾癌的化学疗法或放射疗法效果均不佳，缺少有效的诊疗分子靶标和治疗手段。本研究基于二级质谱（MS2）数据的非标记定量蛋白质组学方法，对晚期肾透明细胞癌和对应的肾脏正常组织样本进行了蛋白质组学分析，共鉴定出2406个蛋白质。采用谱图计数和MS2总离子流（Total ion current，TIC）两种数据处理方法，对蛋白质组学鉴定结果数据进行定量分析。结果表明，MS2总离子流方法可筛选出144个差异蛋白，谱图计数方法筛选出120个差异蛋白，MS2总离子流方法优于谱图计数方法。两种方法共筛选出147个差异蛋白。其中，肿瘤组织上调蛋白有46个，包括膜联蛋白A4、层粘连蛋白α-4亚基、丙酮酸激酶、ATP-柠檬酸合成酶、组蛋白H1.5和碳酸酐酶9等；下调蛋白有101个，包括电子转移黄素蛋白β亚基、3-酮脂酰基CoA硫解酶、绒毛蛋白-1、V型质子ATP合成酶F亚基、线粒体磷酸盐载体蛋白、细胞色素b-c1复合物8亚基、多重耐药抗性蛋白1、视黄醛脱氢酶2和尿调蛋白等。使用MS1数据对部分差异蛋白分析结果进行了相互验证。本研究基于MS2数据的非标记定量分析研究方法，对肾透明细胞癌组织进行蛋白质组学分析，筛选出的差异蛋白可作为肾透明细胞癌诊治、预后判断的候选标志物，为寻找晚期肾透明细胞癌有效的治疗靶点提供了基础数据。

关键词:

English

Proteomics Analysis of Human Renal Clear Cell Carcinoma by Two MS2-based Label-free Approaches

1.
China-Japan Union Hospital of Jilin University, Changchun 130033, China;
2.
Hospital of Stomatology, Jilin University, Changchun 130022, China
Received Date: 27 June 2020
Revised Date: 25 August 2020
Fund Project:
This work was supported by the National Nature Science Foundation of China (No. 81572082) and the Project of Jilin Province Science and Technology Department (No. 20190201215JC).

Abstract: Advanced renal cancer is not sensitive to chemotherapy or radiotherapy, and its effective treatment is very limited. At present, the recognition of specific and effective molecular targets for advanced renal cancer is far from enough. In this work, 2046 proteins were identified from the renal clear cell carcinoma and its adjacent normal tissues by using label-free quantitative proteomics approaches based on MS2 data. Two kinds of data processing methods, i.e. spectral counting and MS2 total ion current (MS2 TIC), were used to analyze the data derived from proteomics identification. The results showed that 144 differential proteins and 120 differential proteins were screened by MS2 TIC method and spectral counting method, respectively. A total of 147 differential proteins were screened by the two methods. Among them, there were 46 up-regulated proteins in tumor tissue, including annexin A4, laminin α-4 subunit, pyruvate kinase, ATP citrate synthetase and histone H1.5, carbonic anhydrase 9, etc.; there were 101 down-regulated proteins in tumor tissue, including beta subunit of electron transfer flavin, 3-ketoalkyl COA thiolase, villin-1, f subunit of V-type proton ATP synthetase, mitochondrial phosphate carrier protein, 8 subunit of cytochrome b-c1 complex, multidrug resistance protein 1, retinol dehydrogenase 2, uromodulin, etc. The results of some differential protein analyses were validated by using MS1-based quantitative method. The label-free quantification using MS2 data was used to analyze the proteome in renal clear cell carcinoma and its adjacent normal tissues. The differential proteins could be used as candidate biomarkers for diagnosis, treatment and prognosis of renal clear cell carcinoma, which could used to find the potential targets for effective treatment of advanced renal clear cell carcinoma.

Key words:

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沈阳化工大学材料科学与工程学院沈阳 110142

基于二级质谱数据的非标记定量人肾透明细胞癌组织蛋白质组学研究

English

Proteomics Analysis of Human Renal Clear Cell Carcinoma by Two MS2-based Label-free Approaches

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通讯作者: 陈斌, bchen63@163.com

中国化学会秘书处

基于二级质谱数据的非标记定量人肾透明细胞癌组织蛋白质组学研究

English

Proteomics Analysis of Human Renal Clear Cell Carcinoma by Two MS2-based Label-free Approaches

CCS Chemistry：嵌段共聚物自组装成 “三明治”二维有机材料，实现纳米级压力传感功能

CCS Chemistry：颜徐州、鲍哲南： 你的皮肤可能是一片SPMs

CCS Chemistry：工作高效不疲劳，只须让催化剂动起来

CCS Chemistry：静电组装导向聚合- 聚电解质纳米凝胶量化制备新策略

CCS Chemistry：金黄色葡萄球菌醛基脱氢酶是如何识别特异性底物的？

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