Identifying and analyzing different cancer subtypes using RNA-seq data of blood platelets
文献类型：期刊论文
| 作者 | Zhang, Yu-Hang2,3; Huang, Tao3; Hu, Yu3; Hu, Lan-Dian3; Kong, Xiangyin3; Cai, Yudong4; Chen, Lei5; Xu, YaoChen1; , |
| 刊名 | ONCOTARGET
 |
| 出版日期 | 2017 |
| 卷号 | 8期号:50页码:87494-87511 |
| 关键词 | cancer detection liquid biopsy RNA-seq data support vector machine maximum relevance minimum redundancy |
| ISSN号 | 1949-2553 |
| DOI | 10.18632/oncotarget.20903 |
| 文献子类 | Article |
| 英文摘要 | Detection and diagnosis of cancer are especially important for early prevention and effective treatments. Traditional methods of cancer detection are usually time-consuming and expensive. Liquid biopsy, a newly proposed noninvasive detection approach, can promote the accuracy and decrease the cost of detection according to a personalized expression profile. However, few studies have been performed to analyze this type of data, which can promote more effective methods for detection of different cancer subtypes. In this study, we applied some reliable machine learning algorithms to analyze data retrieved from patients who had one of six cancer subtypes (breast cancer, colorectal cancer, glioblastoma, hepatobiliary cancer, lung cancer and pancreatic cancer) as well as healthy persons. Quantitative gene expression profiles were used to encode each sample. Then, they were analyzed by the maximum relevance minimum redundancy method. Two feature lists were obtained in which genes were ranked rigorously. The incremental feature selection method was applied to the mRMR feature list to extract the optimal feature subset, which can be used in the support vector machine algorithm to determine the best performance for the detection of cancer subtypes and healthy controls. The ten-fold cross-validation for the constructed optimal classification model yielded an overall accuracy of 0.751. On the other hand, we extracted the top eighteen features (genes), including TTN, RHOH, RPS20, TRBC2, in another feature list, the MaxRel feature list, and performed a detailed analysis of them. The results indicated that these genes could be important biomarkers for discriminating different cancer subtypes and healthy controls. |
| 学科主题 | Oncology ; Cell Biology |
| WOS关键词 | DIAMOND-BLACKFAN ANEMIA ; SQUAMOUS-CELL CARCINOMA ; CIRCULATING TUMOR-CELLS ; BREAST-CANCER ; COLORECTAL-CANCER ; LUNG-CANCER ; HEPATOCELLULAR-CARCINOMA ; PROSTATE-CANCER ; GASTRIC-CANCER ; LIQUID BIOPSY |
| 语种 | 英语 |
| WOS记录号 | WOS:000413341400041 |
| 出版者 | IMPACT JOURNALS LLC |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/669]  |
| 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.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Biochem & Cell Biol, Shanghai 200031, Peoples R China, 2.Shanghai Jiao Tong Univ, Dept Gen Surg, Peoples Hosp 6, Shanghai 200233, Peoples R China; 3.Univ Chinese Acad Sci, Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Hlth Sci, Shanghai 200031, Peoples R China; 4.Shanghai Univ, Sch Life Sci, Shanghai 200444, Peoples R China; 5.Shanghai Maritime Univ, Coll Informat Engn, Shanghai 201306, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Zhang, Yu-Hang,Huang, Tao,Hu, Yu,et al. Identifying and analyzing different cancer subtypes using RNA-seq data of blood platelets[J]. ONCOTARGET,2017,8(50):87494-87511. |
| APA | Zhang, Yu-Hang.,Huang, Tao.,Hu, Yu.,Hu, Lan-Dian.,Kong, Xiangyin.,...&,.(2017).Identifying and analyzing different cancer subtypes using RNA-seq data of blood platelets.ONCOTARGET,8(50),87494-87511. |
| MLA | Zhang, Yu-Hang,et al."Identifying and analyzing different cancer subtypes using RNA-seq data of blood platelets".ONCOTARGET 8.50(2017):87494-87511. |
入库方式： OAI收割
来源：上海营养与健康研究所
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