SPA: A Quantitation Strategy for MS Data in Patient-derived Xenograft Models
文献类型：期刊论文
| 作者 | Cheng, Xi4; Qian, Lili1,2,3; Wang, Bo4; Tan, Minjia1,2,3 ; Li, Jing4
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| 刊名 | GENOMICS PROTEOMICS & BIOINFORMATICS
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| 出版日期 | 2021-08-01 |
| 卷号 | 19期号:4页码:522-533 |
| 关键词 | Patient-derived xenograft model Label-free Shared peptide FGFR2 amplification Biomarker |
| ISSN号 | 1672-0229 |
| DOI | 10.1016/j.gpb.2019.11.016 |
| 通讯作者 | Tan, Minjia(mjtan@simm.ac.cn) ; Li, Jing(jing.li@sjtu.edu.cn) |
| 英文摘要 | With the development of mass spectrometry (MS)-based proteomics technologies, patient-derived xenograft (PDX), which is generated from the primary tumor of a patient, is widely used for the proteome-wide analysis of cancer mechanism and biomarker identification of a drug. However, the proteomics data interpretation is still challenging due to complex data deconvolution from the PDX sample that is a cross-species mixture of human cancerous tissues and immunodeficient mouse tissues. In this study, by using the lab-assembled mixture of human and mouse cells with different mixing ratios as a benchmark, we developed and evaluated a new method, SPA (shared peptide allocation), for protein quantitation by considering the unique and shared peptides of both species. The results showed that SPA could provide more convenient and accurate protein quantitation in human-mouse mixed samples. Further validation on a pair of gastric PDX samples (one bearing FGFR2 amplification while the other one not) showed that our new method not only significantly improved the overall protein identification, but also detected the differential phosphorylation of FGFR2 and its downstream mediators (such as RAS and ERK) exclusively. The tool pdxSPA is freely available at https://github.com/LiLab-Proteomics/pdxSPA. |
| WOS关键词 | FGFR2 GENE AMPLIFICATION ; PROTEOGENOMIC CHARACTERIZATION ; PROGNOSTIC-SIGNIFICANCE ; TUMOR XENOGRAFTS ; CANCER ; PLATFORM |
| 资助项目 | Special Project on Precision Medicine under the National Key R&D Program of China[2017YFC09066600] ; National Natural Science Foundation of China[31871329] ; National Natural Science Foundation of China[31670066] ; National Natural Science Foundation of China[31271416] ; National Science & Technology Major Project Key New Drug Creation and Manufacturing Program, China[2018ZX09711002007] ; Natural Science Foundation of Shanghai, China[17ZR1413900] |
| WOS研究方向 | Genetics & Heredity |
| 语种 | 英语 |
| WOS记录号 | WOS:000788533800002 |
| 出版者 | ELSEVIER |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/301007]  |
| 专题 | 新药研究国家重点实验室 |
| 通讯作者 | Tan, Minjia; Li, Jing |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Shanghai 201203, Peoples R China 3.Chinese Acad Sci, Chem Prote Ctr, Shanghai Inst Mat Med, Shanghai 201203, Peoples R China 4.Shanghai Jiao Tong Univ, Sch Life Sci & Biotechnol, Dept Bioinformat & Biostat, Shanghai 200240, Peoples R China |
| 推荐引用方式 GB/T 7714 | Cheng, Xi,Qian, Lili,Wang, Bo,et al. SPA: A Quantitation Strategy for MS Data in Patient-derived Xenograft Models[J]. GENOMICS PROTEOMICS & BIOINFORMATICS,2021,19(4):522-533. |
| APA | Cheng, Xi,Qian, Lili,Wang, Bo,Tan, Minjia,&Li, Jing.(2021).SPA: A Quantitation Strategy for MS Data in Patient-derived Xenograft Models.GENOMICS PROTEOMICS & BIOINFORMATICS,19(4),522-533. |
| MLA | Cheng, Xi,et al."SPA: A Quantitation Strategy for MS Data in Patient-derived Xenograft Models".GENOMICS PROTEOMICS & BIOINFORMATICS 19.4(2021):522-533. |
入库方式： OAI收割
来源：上海药物研究所
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