Noninvasive technique predicts how cancerous tumors will respond to radiation

A new study from Johns Hopkins University in Baltimore may help physicians identify which patients will benefit the most from radiation treatment before that treatment even begins.  

The research, published in Cancer Research, details the use of Raman spectroscopy—a method utilizing light from a low-power laser to examine how molecules vibrate—to determine how cancerous tumors will respond to radiation. This could help reduce overtreatment, according to the study's authors. 

“Our eventual hope is to be able to predict a patient’s response before radiation therapy even begins, thus sparing patients whose tumors can’t be treated with radiation from going through the arduous multi-week process, saving them both time and money,” corresponding author Ishan Barman, PhD, an assistant professor of mechanical engineering at Johns Hopkins, said in a prepared statement.  

For the study, the researchers examined responses from multiple types of cancers and used smaller doses of radiation to more accurately reflect current radiation therapy practices.  

Using Raman spectroscopy, the researchers characterized changes in the biochemical composition of various tumors and their surroundings and examined the biological processes of radiation treatment.  

To test reactions from radiation-resistant versus radiation sensitive tumors, the researchers used cell lines of both types of tumors from the human lung, as well as head and neck cancers to grow tumors in mice. Once the tumors grew to a desired size, the research team removed them and scanned them with Raman spectroscopy.  

Over the course of two weeks, all tumor types showed changes in response to the small doses of radiation. The team also observed consistent changes in lipid and collagen content in both lung, and head and neck tumors. 

In a second part of the study, the researchers used Raman spectroscopy to examined untreated lung tumors. The method allowed the team to distinguish between radiation-resistant and radiation-sensitive tumors and identify subtle differences in each tumor type’s spectrographic signature, according to the researchers.  

From these patterns, the researchers created an algorithm that could identify radiation resistance and sensitivity with a 97 percent success rate. 

“In addition to accurately evaluating tumor response to therapy, the combination of Raman spectral markers potentially offers a route to predicting response in untreated tumors prior to commencing treatment,” Barman et al. wrote. “Combined with its non-invasive nature, our findings provide a rationale for in vivo studies using Raman spectroscopy, with the ultimate goal of clinical translation for patient stratification and guiding adaptation of radiotherapy during the course of treatment.”