A network approach to quantifying radiotherapy effect on cancer : Radiosensitive gene group centrality
Copyright © 2018 Elsevier Ltd. All rights reserved..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:462 |
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| Enthalten in: |
Journal of theoretical biology - 462(2019) vom: 07. Feb., Seite 528-536 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Yao, Yu-Xiang [VerfasserIn] |
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| Links: |
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| Themen: |
Cancer |
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| Anmerkungen: |
Date Completed 23.03.2020 Date Revised 23.03.2020 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jtbi.2018.12.001 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM291522246 |
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| 100 | 1 | |a Yao, Yu-Xiang |e verfasserin |4 aut | |
| 245 | 1 | 2 | |a A network approach to quantifying radiotherapy effect on cancer |b Radiosensitive gene group centrality |
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| 500 | |a Date Revised 23.03.2020 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2018 Elsevier Ltd. All rights reserved. | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Research Support, U.S. Gov't, Non-P.H.S. | |
| 650 | 4 | |a Cancer | |
| 650 | 4 | |a Network centrality | |
| 650 | 4 | |a Network science | |
| 650 | 4 | |a Radiosensitive | |
| 650 | 4 | |a Radiotherapy | |
| 700 | 1 | |a Bing, Zhi-Tong |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Liang |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Zi-Gang |e verfasserin |4 aut | |
| 700 | 1 | |a Lai, Ying-Cheng |e verfasserin |4 aut | |
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