Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models
文献类型：期刊论文
| 作者 | Chen, Lei5,6,7; Zhang, Yu-Hang7; Huang, Tao7; Pan, Xiaoyong4; Hu, Xiaohua3; Feng, KaiYan1; Cai, Yu-Dong2; , |
| 刊名 | FRONTIERS IN GENETICS
 |
| 出版日期 | 2019 |
| 卷号 | 10期号:-页码:738 |
| 关键词 | Patient-derived tumor xenograft gene expression profile Monte Carlo feature selection support vector machine rule learning algorithm |
| ISSN号 | 1083-7159 |
| DOI | 10.3389/fgene.2019.00738 |
| 文献子类 | Article |
| 英文摘要 | Patient-derived tumor xenograft (PDX) mouse models are widely used for drug screening. The underlying assumption is that PDX tissue is very similar with the original patient tissue, and it has the same response to the drug treatment. To investigate whether the primary tumor site information is well preserved in PDX, we analyzed the gene expression profiles of PDX mouse models originated from different tissues, including breast, kidney, large intestine, lung, ovary, pancreas, skin, and soft tissues. The popular Monte Carlo feature selection method was employed to analyze the expression profile, yielding a feature list. From this list, incremental feature selection and support vector machine (SVM) were adopted to extract distinctively expressed genes in PDXs from different primary tumor sites and build an optimal SVM classifier. In addition, we also set up a group of quantitative rules to identify primary tumor sites. A total of 755 genes were extracted by the feature selection procedures, on which the SVM classifier can provide a high performance with MCC 0.986 on classifying primary tumor sites originated from different tissues. Furthermore, we obtained 16 classification rules, which gave a lower accuracy but clear classification procedures. Such results validated that the primary tumor site specificity was well preserved in PDX as the PDXs from different primary tumor sites were still very different and these PDX differences were similar with the differences observed in patients with tumor. For example, VIM and ABHD17C were highly expressed in the PDX from breast tissue and also highly expressed in breast cancer patients. |
| 学科主题 | Genetics & Heredity |
| WOS关键词 | CARLO FEATURE-SELECTION ; GENE-EXPRESSION ; BREAST-CANCER ; IDENTIFICATION ; IDENTIFY ; CELLS ; METASTASIS ; POPULATION |
| 语种 | 英语 |
| WOS记录号 | WOS:000480567300001 |
| 出版者 | FRONTIERS MEDIA SA |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/536]  |
| 专题 | 中国科学院上海生命科学研究院营养科学研究所 |
| 作者单位 | 1.Guangdong AIB Polytech, Dept Comp Sci, Guangzhou, Guangdong, Peoples R China; 2.Shanghai Univ, Sch Life Sci, Shanghai, Peoples R China, 3.Fudan Univ, Sch Life Sci, Dept Biostat & Computat Biol, Shanghai, Peoples R China; 4.Erasmus MC, Dept Med Informat, Rotterdam, Netherlands; 5.East China Normal Univ, Shanghai Key Lab PMMP, Shanghai, Peoples R China; 6.Shanghai Maritime Univ, Coll Informat Engn, Shanghai, Peoples R China; 7.Chinese Acad Sci, Shanghai Inst Nutr & Hlth, Shanghai Inst Biol Sci, Shanghai, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Chen, Lei,Zhang, Yu-Hang,Huang, Tao,et al. Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models[J]. FRONTIERS IN GENETICS,2019,10(-):738. |
| APA | Chen, Lei.,Zhang, Yu-Hang.,Huang, Tao.,Pan, Xiaoyong.,Hu, Xiaohua.,...&,.(2019).Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models.FRONTIERS IN GENETICS,10(-),738. |
| MLA | Chen, Lei,et al."Primary Tumor Site Specificity is Preserved in Patient-Derived Tumor Xenograft Models".FRONTIERS IN GENETICS 10.-(2019):738. |
入库方式： OAI收割
来源：上海营养与健康研究所
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