基于4D-蛋白组学的乳腺癌肿瘤演进研究

4D-proteomics-based breast cancer progression

乳腺癌肿瘤的发生发展经历多个过程,其演进中的蛋白分子信息错综复杂。采用4D-蛋白组学技术对MMTV-PyMT乳腺癌转基因小鼠肿瘤演进开展研究,经蛋白鉴定和表达差异分析,共鉴定蛋白5819个,其中可用于定量的蛋白数5667个。与3周龄的乳腺癌肿瘤相比,5周龄肿瘤具有显著性差异的蛋白数为270个,7周龄肿瘤是255个。随着肿瘤经历3周、5周和7周的演进,有23个蛋白表达倍数逐渐增加(Srpk1和Tinagl1等),有35个蛋白表达倍数逐渐降低(Pdgfrb,Col1a2和Col1a1等)。差异蛋白的亚细胞定位、GO功能分析、通路富集分析发现,随着肿瘤生长时间增加,并没有改变差异蛋白参与的生物过程(免疫调控和脂质代谢)和富集通路(代谢相关通路),但改变了细胞组分(5周龄集中分布于细胞外区域和生物膜,7周龄集中分布于细胞质)和分子功能(5周龄重点参与蛋白结合功能,7周龄重点参与核苷酸结合)。本研究获得的肿瘤演进相关的蛋白生物标志物和通路结果,对于揭示乳腺癌形成的分子机制、筛查乳腺癌分子靶点、评估发展阶段并制定个性化治疗方案具有重要意义。

The occurrence and development of breast cancer go through multiple processes,and the protein molecular information in its evolution is intricate and complex.The 4D-proteomics technique was used to investigate the tumor progression of MMTV-PyMT transgenic mice.The results of protein identification and differential expression analysis showed that a total of 5819 proteins were identified in 4D-proteomics analysis and 5667 proteins were quantifiable.Compared with 3-week-old tumors,a total of 270 differentially expressed proteins were found in the 5-week-old tumors,while 255 proteins in the 7-week-old tumors.We also detected 23 of proteins(such as,Srpk11 and Tinagl1)with gradual up-regulation and 35 of proteins(such as,Pdgfrb,Col1a2 and Col1a1)with gradual down-regulation during the tumor progression,including 3-,5-and 7-weeks.We also performed bioinformatics analysis,including subcellular localization,GO function analysis and pathway enrichment analysis.The results showed that the biological processes(immune regulation and lipid metabolism)and enrichment pathways(metabolic pathway)involved in differentially expressed proteins remained the same during the tumor progression,but some cellular components and molecular functions changed,such as,protein locations were extracellular region and membrane in 5-weeks-old tumors as well as cytoplasm in 7-weeks-old tumors.And important protein functions were protein binding functions in 5-weeks-old tumors as well as nucleotide binding in 7-weeks-old tumors.The acquired protein biomarkers and pathways could help with the accurate exploration of molecular mechanisms of tumor progression,screening of molecular targets of breast cancer,and evaluation of personalized treatment programs.