ArticleInternational journal of oncology2017
Prediction of radiosensitive patients with gastric cancer by developing gene signature.
Article in International journal of oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Clinical Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy: A Systematic Review.Cancers · 2024Review
- More evidence for prediction model of radiosensitivity.Bioscience reports · 2021Article
- A signature of 14 immune-related gene pairs predicts overall survival in gastric cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2021Article
- Long noncoding RNA NEAT1 regulates radio-sensitivity via microRNA-27b-3p in gastric cancer.Cancer cell international · 2020Article
- An integrated classifier improves prognostic accuracy in non-metastatic gastric cancer.Oncoimmunology · 2020Article
- How Can Gene-Expression Information Improve Prognostic Prediction in TCGA Cancers: An Empirical Comparison Study on Regularization and Mixed Cox Models.Frontiers in genetics · 2020Article
- Integrating radiosensitive genes improves prediction of radiosensitivity or radioresistance in patients with oesophageal cancer.Oncology letters · 2019Article
- Low Expression of GLIS2 Gene Might Associate with Radiosensitivity of Gastric Cancer.Journal of oncology · 2019Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adjuvant radiotherapy is an important clinical treatment for the majority of gastric cancer, a common cancer. However, radiotherapy is a double-edged sword. It is necessary to develop a method to predict radiosensitive patients who are most likely to benefit from radiotherapy. Using the publicly available data of gastric cancer from The Cancer Genome Atlas (TCGA), we developed a gene signature that predicts radiosensitive patients through estimating a new index, nominal HR (nHR) (HR product of sensitive genes), for each patient. In this study, we provided several results to validate our prediction. Cross-validation results showed that the predicted radiosensitive patients who received radiotherapy had significantly better survival than predicted radiosensitive patients who did not receive radiotherapy. After adjusting for other clinical factors, including age, sex, target therapy, histologic diagnosis, tumor stage, the benefit of radiotherapy on predicted radiosensitive patient remained significant. In addition, predicted radiosensitive patients who received radiotherapy had a significantly reduced rate of disease progression. Taken together, we have obtained a set of genes, to identify radiosensitive patients with gastric cancer. These genes may be potential biomarkers for diagnosis and treatment of gastric cancer, which could give new insight for revealing the underlying mechanism of radiosensitivity of gastric cancer.
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