English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

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.

Prediction of radiosensitive patients with gastric cancer by developing gene signature