ArticleOncology reports2017
Predicting radiotherapy response for patients with soft tissue sarcoma by developing a molecular signature.
Article in Oncology reports, 2017. 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Epigenome-wide analysis reveals potential biomarkers for radiation-induced toxicity risk in prostate cancer.Clinical epigenetics · 2025Article
- Clinical Biomarkers of Tumour Radiosensitivity and Predicting Benefit from Radiotherapy: A Systematic Review.Cancers · 2024Review
- Predictive Biomarkers of Pathological Response to Neoadjuvant Chemoradiotherapy for Locally Advanced Soft Tissue Sarcomas.Cancers · 2023Article
- SETD2 regulates gene transcription patterns and is associated with radiosensitivity in lung adenocarcinoma.Frontiers in genetics · 2022Article
- Developing ZNF Gene Signatures Predicting Radiosensitivity of Patients with Breast Cancer.Journal of oncology · 2021Article
- Modeling the effect of intratumoral heterogeneity of radiosensitivity on tumor response over the course of fractionated radiation therapy.Radiation oncology (London, England) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.