Ho AY, Atencio DP, Peters S, Stock RG, Formenti SC, Cesaretti JA, Green S, Haffty B, Drumea K, Leitzin L, Kuten A, Azria D, Ozsahin M, Overgaard J, Andreassen CN, Trop CS, Park J, Rosenstein BS. Genetic predictors of adverse radiotherapy effects: the Gene-PARE project.
Int J Radiat Oncol Biol Phys 2006;
65:646-55. [PMID:
16751059 DOI:
10.1016/j.ijrobp.2006.03.006]
[Citation(s) in RCA: 71] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2005] [Revised: 02/27/2006] [Accepted: 03/01/2006] [Indexed: 01/12/2023]
Abstract
PURPOSE
The development of adverse effects resulting from the radiotherapy of cancer limits the use of this treatment modality. The validation of a test capable of predicting which patients would be most likely to develop adverse responses to radiation treatment, based on the possession of specific genetic variants, would therefore be of value. The purpose of the Genetic Predictors of Adverse Radiotherapy Effects (Gene-PARE) project is to help achieve this goal.
METHODS AND MATERIALS
A continuously expanding biorepository has been created consisting of frozen lymphocytes and DNA isolated from patients treated with radiotherapy. In conjunction with this biorepository, a database is maintained with detailed clinical information pertaining to diagnosis, treatment, and outcome. The DNA samples are screened using denaturing high performance liquid chromatography (DHPLC) and the Surveyor nuclease assay for variants in ATM, TGFB1, XRCC1, XRCC3, SOD2, and hHR21. It is anticipated that additional genes that control the biologic response to radiation will be screened in future work.
RESULTS
Evidence has been obtained that possession of variants in genes, the products of which play a role in radiation response, is predictive for the development of adverse effects after radiotherapy.
CONCLUSIONS
It is anticipated that the Gene-PARE project will yield information that will allow radiation oncologists to use genetic data to optimize treatment on an individual basis.
Collapse