4.7 Article

Identification of a radiation sensitivity gene expression profile in primary fibroblasts derived from patients who developed radiotherapy-induced fibrosis

期刊

RADIOTHERAPY AND ONCOLOGY
卷 111, 期 2, 页码 186-193

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.radonc.2014.03.007

关键词

Radiosensitivity prediction; Gene expression; Exon array; Fibrosis

资金

  1. Collaborative Cancer Research Scheme [1002743]
  2. Australian Government Department of Health and Ageing
  3. Australian National Health and Medical Research Council [145780, 288713]
  4. Australian National Breast Cancer Foundation [PG-08-06]
  5. National Institute of Health [5U19AI067773-07]
  6. Victorian Government's Operational Infrastructure Support Program

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Background and purpose: During radiotherapy, normal tissue is unavoidably exposed to radiation which results in severe normal tissue reactions in a small fraction of patients. Because those who are sensitive cannot be determined prior to radiotherapy, the doses are limited to all patients to avoid an unacceptable number of severe adverse normal tissue responses. This limitation restricts the optimal treatment for individuals who are more tolerant to radiation. Genetic variation is a likely source for the normal tissue radiosensitivity variation observed between individuals. Therefore, understanding the radiation response at the genomic level may provide knowledge to develop individualized treatment and improve radiotherapy outcomes. Material and methods: Exon arrays were utilized to compare the basal expression profile between cell lines derived from six cancer patients with and without severe fibrosis. These data were supported by qRT-PCR and RNA-Seq techniques. Results: A set of genes (FBN2, FST, GPRC5B, NOTCH3, PLCB1, DPT, DDIT4L and SGCG) were identified as potential predictors for radiation-induced fibrosis. Many of these genes are associated with TGF beta or retinoic acid both having known links to fibrosis. Conclusion: A combinatorial gene expression approach provides a promising strategy to predict fibrosis in cancer patients prior to radiotherapy. (C) 2014 Elsevier Ireland Ltd. All rights reserved.

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