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First genomics-driven model for personalized radiation therapy developed

Date:
December 19, 2016
Source:
Moffitt Cancer Center
Summary:
A novel genomics model has been created that allows a personalized approach to radiation therapy.
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Cancer therapeutics is currently in the era of precision medicine -- personalized medicine for individual patients based on their tumor biology. Precision medicine is generally drug-based and little emphasis is placed on radiation therapy that is often assumed to be a "one-size-fits-all" treatment. Moffitt Cancer Center researchers have been instrumental is changing this assumption. Their study published in The Lancet Oncology describes a novel genomics model that allows a personalized approach to radiation therapy.

Cancer is a highly heterogeneous disease, and it is now understood that patients can achieve better outcomes if their treatments are tailored to the specific biology of their tumors. However, despite the growth of precision medicine, little progress has been made in personalizing radiation therapy. It is generally assumed that all patients have the same potential to benefit from it. Moffitt researchers believe that precision medicine also has a role in radiation therapy and that it could be used to improve patient outcomes and reduce toxicities.

Previously, a team of Moffitt researchers, led by Javier F. Torres-Roca, M.D., developed a gene-expresssion based radiosensitivity index (RSI) that predicts tumor sensitivity to radiation therapy based on the expression of 10 specific genes. The RSI accurately predicts clinical outcomes in many different cancer patients treated with radiation, including breast, head and neck, glioblastoma, pancreas, and metastatic colorectal cancer patients.

The researchers used the RSI to develop a genomics model called the genomic-adjusted radiation dose (GARD) that predicts thetherapeutic effect for radiotherapy and could guide radiation dosing to match an individual's tumor radiosensitivity. They demonstrate that GARD values were consistent with the clinical heterogeneity of radiotherapy therapeutic benefit. For example, gliomas and sarcomas are known to be resistant to radiation and had the lowest GARD values, while cervical and head and neck cancers which are known to be sensitive and radiocurable had the highest GARD values.

"There is a high degree of variability among the GARD values for different patients within a single tumor type," said Torres-Roca. "This suggests that different patients with the same type of tumor have different sensitivities to radiation therapy, further suggesting that the 'one-size-fits-all' approach to radiation therapy dose can be further optimized and personalized using tumor genomics The study confirmed that the GARD model could predict the clinical outcomes of 263 breast cancer patients who were treated with radiation therapy and surgery. It could also predict the outcomes of additional sets of patients, including glioblastoma, lung, and pancreatic cancer patients.

This study demonstrates that it is possible to differentiate those patients who may benefit from radiation therapy through genomics approaches. GARD could be used to customize a patient's radiation dose so that they are receiving the optimum dose to achieve the greatest benefit with the least amount of toxicity. Additionally, GARD could be used in clinical trials to stratify patients based on their radiation sensitivity.

"With multi-disciplinary care becoming standard for the majority of cancer patients, it is critical that precision medicine is expanded beyond drug therapy," said Louis B. Harrison, M.D, FASTRO, chair of Moffitt's Radiation Oncology Department. "The GARD model provides the first opportunity to genomically-inform radiation dose and is a safe and feasible approach to precision radiation oncology."


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Materials provided by Moffitt Cancer Center. Note: Content may be edited for style and length.


Journal Reference:

  1. Jacob G Scott, Anders Berglund, Michael J Schell, Ivaylo Mihaylov, William J Fulp, Binglin Yue, Eric Welsh, Jimmy J Caudell, Kamran Ahmed, Tobin S Strom, Eric Mellon, Puja Venkat, Peter Johnstone, John Foekens, Jae Lee, Eduardo Moros, William S Dalton, Steven A Eschrich, Howard McLeod, Louis B Harrison, Javier F Torres-Roca. A genome-based model for adjusting radiotherapy dose (GARD): a retrospective, cohort-based study. The Lancet Oncology, 2016; DOI: 10.1016/S1470-2045(16)30648-9

Cite This Page:

Moffitt Cancer Center. "First genomics-driven model for personalized radiation therapy developed." ScienceDaily. ScienceDaily, 19 December 2016. <www.sciencedaily.com/releases/2016/12/161219161856.htm>.
Moffitt Cancer Center. (2016, December 19). First genomics-driven model for personalized radiation therapy developed. ScienceDaily. Retrieved May 28, 2017 from www.sciencedaily.com/releases/2016/12/161219161856.htm
Moffitt Cancer Center. "First genomics-driven model for personalized radiation therapy developed." ScienceDaily. www.sciencedaily.com/releases/2016/12/161219161856.htm (accessed May 28, 2017).

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