Tool Would Use Tumor Gene Expression to Inform Radiation Dose

Interesting approach! Cancer is history!

"... GARD is based on an earlier model ... In 2009, his team published a molecular assay they developed, dubbed the radiosensitivity index (RSI), to determine how susceptible tumors are to radiation. The RSI was based on their finding that in multiple human cancer cell lines, the expression of ten genes could predict tumor response to a given radiation dose. In 2016, the researchers integrated the RSI and the radiation dose received by a patient into a model—GARD—that aims to predict the biological effect of a given dose. ..."

From the abstract:

"Despite advances in cancer genomics, radiotherapy is still prescribed on the basis of an empirical one-size-fits-all paradigm. Previously, we proposed a novel algorithm using the genomic-adjusted radiation dose (GARD) model to personalise prescription of radiation dose on the basis of the biological effect of a given physical dose of radiation, calculated using individual tumour genomics. ...
The biological effect of radiotherapy, as quantified by GARD, is significantly associated with time to first recurrence and overall survival for patients with cancer treated with radiation. It is predictive of radiotherapy benefit, and physical dose of radiation is not. We propose integration of genomics into radiation dosing decisions, using a GARD-based framework, as the new paradigm for personalising radiotherapy prescription dose."

Tool Would Use Tumor Gene Expression to Inform Radiation Dose | The Scientist Magazine® In a retrospective analysis, a team found that an algorithm integrating the gene expression of a tumor with the radiation dose a patient received predicted how well the patient responded to the treatment.

Pan-cancer prediction of radiotherapy benefit using genomic-adjusted radiation dose (GARD): a cohort-based pooled analysis (no public access)