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• W2760542596 abstract "Soft tissue sarcomas are rare and aggressive tumors arising from connective tissues. Adjuvant radiotherapy is a commonly used treatment approach for the majority of sarcomas. We attempted to identify a gene signature that can predict radiosensitive patients who are most likely to have a better treatment response from radiotherapy, compared with disease progression. Using the publicly available data of soft tissue sarcoma from The Cancer Genome Atlas, we developed a cross-validation procedure to identify a predictive gene signature for radiosensitivity. The results showed that the predicted radiosensitive patients who received radiotherapy had significantly improved treatment response. We further provide supportive evidence to validate our sensitivity prediction. Results showed that the predicted radiosensitive patients who received radiotherapy had significantly improved survival than patients who did not. ROC analysis showed that the developed gene signature had a powerful prediction on treatment response. We further found that predicted radiosensitive patients who received radiotherapy had a significantly reduced rate of new tumor events. Finally, we validated our gene signature using a hierarchical cluster analysis, and found that the predicted sensitivities were well-matched with results from the cluster analysis. These results are consistent with our expectation, suggesting that the identified gene signature and radiosensitivity prediction are effective. The genes involved in the signature may provide a molecular basis for prognostic studies and radiotherapy target discovery." @default.
• W2760542596 created "2017-10-06" @default.
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• W2760542596 date "2017-09-25" @default.
• W2760542596 modified "2023-09-25" @default.
• W2760542596 title "Predicting radiotherapy response for patients with soft tissue sarcoma by developing a molecular signature" @default.
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• W2760542596 doi "https://doi.org/10.3892/or.2017.5999" @default.
• W2760542596 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/5780036" @default.
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• W2760542596 hasPublicationYear "2017" @default.
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