Seth Pollack, MD
Several challenges remain in the treatment landscape of soft tissue sarcoma, a disease whose diagnosis can range from one that is quite indolent for patients, to a more life-threatening, metastatic, aggressive cancer.
One such challenge is accurately predicting individual patient outcomes. Radiomics, an emerging research field, may serve to alleviate that struggle. Radiomics quantifies complex aspects of tumor images related to tumor biology. Research has validated the use of this technique to predict patient outcomes in lung and head and neck cancers, and it is now quickly making headway in the treatment of patients with sarcoma.
In an interview with OncLive
at the Connective Tissue Oncology Society (CTOS) conference, Seth Pollack, MD, assistant member, Fred Hutchinson Cancer Research Center, assistant professor, University of Washington Medical Center, medical oncologist, Seattle Cancer Care Alliance, discusses the evolving role that radiomics will play in the prediction of patient outcomes in sarcoma. He also sheds some light on the exciting future of immunotherapy in the treatment of this disease.
OncLive: What is the role of radiomics in sarcoma?
: Radiomics is really a brand new field. It’s something that we’re only just starting to scratch the surface of. And it’s not something that has a currently established role in the management of patients. But it’s something that’s really exciting. Radiomics is essentially a way to look at images that actually takes the viewer out of it, and lets the computer look for elements to the radiologic files that a person wouldn’t be able to see.
So what exactly was the research on radiomics that was presented here at CTOS?
Sarcoma may be an ideal place to study radiomics because so many of our patients have MRIs, which are one of the best ways to do radiomics research. So in this study, patients with primary soft tissue sarcomas—who were treated at the University of Washington and Seattle Cancer Care Alliance—had their images analyzed through this list of radiomic features, and a model was made to predict patients’ outcomes.
What we found was that that model was really, really accurate. It actually did better than all of the normal ways that you predict outcomes of patients, based on tumor grade, tumor size, and other clinical features. That’s why we’re really excited about it. But I do think that the data need to be validated on other data sets and other patient cohorts.
We’re already doing another internal validation with another cohort at our institution, but I think we’ll also ultimately need to validate this at an external institution in order to really demonstrate that this is a good way to predict patient outcomes.
What impact do you expect that this will have on clinical practice?
I think having a better way to predict patient outcomes is really promising. Once we have that tool validated in a way that is really reliable, then I think we’ll be able to do the really exciting work, of seeing whether these features predict outcomes to treatments. And once we start doing that, then maybe we can use these things to choose which treatment a patient is best suited for.
What would you like the community oncologist to ultimately take away from these findings?
I think for the community oncologist, radiomics is a new field, and it’s not something that’s going to be affecting their practice today, but maybe it will tomorrow. So I think for the community oncologist, this is something to put on their radar, and kind of start watching because it’s going to be really exciting.
What do you hope to see in the treatment landscape of this disease in the next 5 to 10 years?
From my perspective, in terms of the radiomics work, I should mention that Matt Spraker is a radiation oncology resident who really did all of the work, and we have a great biophysics team led by Matt Nyflot at the University of Washington, and it’s been really exciting for me as a medical oncologist specializing in sarcoma to be involved in this project.
But my main focus has been immunotherapy, and that’s where I’m really excited for the field to move toward in the next 5 to 10 years. I thought the exciting data from SARC028 that we saw at this meeting was really great, where we saw these patients with pleomorphic undifferentiated sarcoma that achieved responses with pembrolizumab (Keytruda). I think that’s really exciting. At our center, we have a trial looking at doxorubicin plus pembrolizumab; I think that’s going to be exciting.