ArticleOncology letters2019
Integrating radiosensitive genes improves prediction of radiosensitivity or radioresistance in patients with oesophageal cancer.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- A Review of Radiation-Induced Alterations of Multi-Omic Profiles, Radiation Injury Biomarkers, and Countermeasures.Radiation research · 2023Review
- Cooperative effects of RIG-I-like receptor signaling and IRF1 on DNA damage-induced cell death.Cell death & disease · 2022Article
- Proteomic analysis to identify markers for response to neoadjuvant treatment in esophageal and gastroesophageal cancer.Cancer reports (Hoboken, N.J.) · 2022Article
- Adaptive Mechanisms of Tumor Therapy Resistance Driven by Tumor Microenvironment.Frontiers in cell and developmental biology · 2021Review
- Molecular profiling of neuroendocrine tumours to predict response and toxicity to peptide receptor radionuclide therapy.The Lancet. Oncology · 2020Review
- Machine Learning Based on a Multiparametric and Multiregional Radiomics Signature Predicts Radiotherapeutic Response in Patients with Glioblastoma.Behavioural neurology · 2020Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Oesophageal cancer is a serious disease worldwide. In China, the incidence of esophageal cancer was reported to be ~478,000 in 2015. In the same year, the incidence of esophageal cancer in the United States was ~16,910. Radiotherapy serves as an important tool in the treatment of oesophageal cancer, and although radiation therapy has progressed over time, the prognosis of the majority of patients with oesophageal cancer remains poor. Additionally, the sensitivity of patients with oesophageal cancer to radiotherapy and chemotherapy is not yet clear. Although there are a number of studies on the radiosensitivity of oesophageal cancer cell lines, the vastly different results from different cell lines make them unreliable to use as a guide in clinical practice. Therefore, a common radiosensitive gene signature may provide more reliable results, and using different combinations of common gene signatures to predict the outcome of patients with oesophageal cancer may generate a unique gene signature in oesophageal cancer. In the present study, the radiosensitive index and prognostic index were calculated to predict clinical outcomes. The prognostic index of a 41-gene signature combination is the largest combination of gene signatures used for classifying oesophageal cancer patients into radiosensitive (RS) and radioresistance (RR) groups, to the best of our knowledge, and this gene signature was more effective in patients classified as having Stage III oesophageal cancer. Furthermore, four genes (
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