A network approach to quantifying radiotherapy effect on cancer: Radiosensitive gene group centrality
文献类型：期刊论文
| 作者 | Yao, YX; Bing, ZT ; Huang, L8; Huang, ZG; Lai, YC
|
| 刊名 | JOURNAL OF THEORETICAL BIOLOGY
 |
| 出版日期 | 2019 |
| 卷号 | 462页码:528-536 |
| DOI | 10.1016/j.jtbi.2018.12.001 |
| 英文摘要 | Radiotherapy plays a vital role in cancer treatment, for which accurate prognosis is important for guiding sequential treatment and improving the curative effect for patients. An issue of great significance in radiotherapy is to assess tumor radiosensitivity for devising the optimal treatment strategy. Previous studies focused on gene expression in cells closely associated with radiosensitivity, but factors such as the response of a cancer patient to irradiation and the patient survival time are largely ignored. For clinical cancer treatment, a specific pre-treatment indicator taking into account cancer cell type and patient radiosensitivity is of great value but it has been missing. Here, we propose an effective indicator for radiosensitivity: radiosensitive gene group centrality (RSGGC), which characterizes the importance of the group of genes that are radiosensitive in the whole gene correlation network. We demonstrate, using both clinical patient data and experimental cancer cell lines, which RSGGC can provide a quantitative estimate of the effect of radiotherapy, with factors such as the patient survival time and the survived fraction of cancer cell lines under radiotherapy fully taken into account. Our main finding is that, for patients with a higher RSGGC score before radiotherapy, cancer treatment tends to be more effective. The RSGGC can have significant applications in clinical prognosis, serving as a key measure to classifying radiosensitive and radioresistant patients. (C) 2018 Elsevier Ltd. All rights reserved. |
| WOS记录号 | WOS:000455972600046 |
| 源URL | [http://119.78.100.186/handle/113462/136011]  |
| 专题 | 中国科学院近代物理研究所 |
| 作者单位 | 1.Arizona State Univ, Dept Phys, Tempe, AZ 85287 USA 2.Lanzhou Univ, Evidence Based Med Ctr, Sch Basic Med Sci, Lanzhou 730000, Gansu, Peoples R China 3.Key Lab Evidence Based Med & Knowledge Translat G, Lanzhou 730000, Gansu, Peoples R China 4.Chinese Acad Sci, Inst Modern Phys, Dept Computat Phys, Lanzhou 730000, Gansu, Peoples R China 5.Xi An Jiao Tong Univ, Key Lab Neuroinformat & Rehabil Engn, Natl Engn Res Ctr Hlth Care & Med Devices, Key Lab Biomed Informat Engn,Minist Educ,Minist C, Xian 710049, Shaanxi, Peoples R China 6.Xi An Jiao Tong Univ, Sch Life Sci & Technol, Inst Hlth & Rehabil Sci, Xian 710049, Shaanxi, Peoples R China 7.Arizona State Univ, Sch Elect Comp & Energy Engn, Tempe, AZ 85287 USA 8.[Yao, Yu-Xiang 9.Lanzhou Univ, Sch Phys Sci & Technol, Lanzhou 730000, Gansu, Peoples R China |
| 推荐引用方式 GB/T 7714 | Yao, YX,Bing, ZT,Huang, L,et al. A network approach to quantifying radiotherapy effect on cancer: Radiosensitive gene group centrality[J]. JOURNAL OF THEORETICAL BIOLOGY,2019,462:528-536. |
| APA | Yao, YX,Bing, ZT,Huang, L,Huang, ZG,&Lai, YC.(2019).A network approach to quantifying radiotherapy effect on cancer: Radiosensitive gene group centrality.JOURNAL OF THEORETICAL BIOLOGY,462,528-536. |
| MLA | Yao, YX,et al."A network approach to quantifying radiotherapy effect on cancer: Radiosensitive gene group centrality".JOURNAL OF THEORETICAL BIOLOGY 462(2019):528-536. |
入库方式： OAI收割
来源：近代物理研究所
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