Helen B Forrester1, Jason Li2, Trevor Leong3, Michael J McKay4, Carl N Sprung5. 1. Centre for Innate Immunity and Infectious Disease, Monash Institute of Medical Research, Monash University, Clayton, Australia; MIMR-PHI Institute of Medical Research, Clayton, Australia. 2. Division of Research, Peter MacCallum Cancer Centre, East Melbourne, Australia. 3. Division of Radiation Oncology and Cancer Imaging, Peter MacCallum Cancer Centre, East Melbourne, Australia. 4. University of Sydney and North Coast Cancer Institute, Lismore, Australia. 5. Centre for Innate Immunity and Infectious Disease, Monash Institute of Medical Research, Monash University, Clayton, Australia; MIMR-PHI Institute of Medical Research, Clayton, Australia. Electronic address: carl.sprung@monash.edu.
Abstract
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 TGFβ 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.
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 cancerpatients 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 TGFβ or retinoic acid both having known links to fibrosis. CONCLUSION: A combinatorial gene expression approach provides a promising strategy to predict fibrosis in cancerpatients prior to radiotherapy.
Authors: Bradley S Gordon; Jennifer L Steiner; David L Williamson; Charles H Lang; Scot R Kimball Journal: Am J Physiol Endocrinol Metab Date: 2016-05-17 Impact factor: 4.310
Authors: Pavel Lobachevsky; Trevor Leong; Patricia Daly; Jai Smith; Nickala Best; Jonathan Tomaszewski; Ella R Thompson; Na Li; Ian G Campbell; Roger F Martin; Olga A Martin Journal: Cancer Lett Date: 2016-09-28 Impact factor: 8.679