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arXiv · 1812.02384

A network approach to quantifying radiotherapy effect on cancer: Radiosensitive gene group centrality

Yu-Xiang Yao·Zhi-Tong Bing·Liang Huang·Zi-Gang Huang·Ying-Cheng Lai
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Abstract

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.

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Yu-Xiang Yao, Zhi-Tong Bing, Liang Huang, Zi-Gang Huang, Ying-Cheng Lai. 2018-12-06. A network approach to quantifying radiotherapy effect on cancer: Radiosensitive gene group centrality. https://arxiv.org/abs/1812.02384

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