Oncotarget

Research Papers:

Development of a radiosensitivity gene signature for patients with soft tissue sarcoma

Zaixiang Tang, Qinghua Zeng, Yan Li, Xinyan Zhang, Jinlu Ma, Mark J. Suto, Bo Xu and Nengjun Yi _

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Oncotarget. 2017; 8:27428-27439. https://doi.org/10.18632/oncotarget.16194

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Abstract

Zaixiang Tang1,2,3,4, Qinghua Zeng5, Yan Li4, Xinyan Zhang4, Jinlu Ma5,6, Mark J. Suto5, Bo Xu5, Nengjun Yi4

1Department of Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou 215123, China

2Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, 215123, China

3Center for Genetic Epidemiology and Genomics, Medical College of Soochow University, Suzhou, 215123, China

4Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA

5Drug Discovery Division, Southern Research Institute, Birmingham, AL 35294, USA

6Department of Radiation Oncology, The First Hospital, Xi’an Jiaotong University, Xi’an, Shanxi, 710061, China

Correspondence to:

Nengjun Yi, email: nyi@uab.edu

Bo Xu, email: bxu@southernresearch.org, bxu@uab.edu

Keywords: gene signature, radio-sensitivity, radiotherapy, survival prediction, sarcoma

Received: September 27, 2016    Accepted: January 24, 2017    Published: March 15, 2017

ABSTRACT

Adjuvant radiotherapy is an important clinical treatment option for the majority of sarcomas. The motivation of current study is to identify a gene signature and to predict radiosensitive patients who are most likely to benefit from radiotherapy. Using the public available data of soft tissue sarcoma from The Cancer Genome Atlas, we developed a cross-validation procedure for identifying a gene signature and predicting radiosensitive patients through. The result showed that the predicted radiosensitive patients who received radiotherapy had a significantly better survival with a reduced rate of new tumor event and disease progression. Strata analysis showed that the predicted radiosensitive patients had significantly better survival under radiotherapy independent of histologic types. A hierarchical cluster analysis was used to validate the gene signature, and the results showed the predicted sensitivity for each patient well matched the results from cluster analysis. Together, we demonstrate a radiosensitive molecular signature that can be potentially used for identifying radiosensitive patients with sarcoma.


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