Cutaneous squamous cell carcinoma (cSCC) encompasses a broad spectrum of disease severity, from superficial and easily treatable skin lesions to potentially life-threatening metastatic cancer. Adjuvant radiation therapy (ART) is recommended to reduce the likelihood of relapse following surgical resection in patients who are considered to be at high risk of recurrence. However, a significant challenge in SCC care is that the clinicopathological factors that are used in current risk stratification guidelines do not perfectly predict the risk of cSCC recurrence. As a result, not everyone who receives ART is likely to benefit from it. Recent research presented at the American Society for Dermatologic Surgery Annual Meeting in Chicago, examined the use of a gene expression profile (GEP) test based on patients’ individual tumor biology to predict response to ART.
Study author Sarah Arron, MD, PhD, of Peninsula Dermatology in Burlingame, California, discussed the findings and how they may impact practice with Practical Dermatology® magazine.
What was the objective of this study?
The objective of this study was to identify not only which cSCC tumors were most likely to metastasize, but also to see if we could identify patients who were most likely to benefit from radiation.
The Castle DecisionDx-SCC is a gene expression profile assay, or a biologic test that’s done using tumor tissue from an SCC biopsy or surgery. The test predicts the potential for the tumor to metastasize to the lymph nodes or to distant sites within the body, adding biologic information to the high-risk clinicopathologic features we already use. SCC tumors are classified into 3 separate and distinct groups, ranked by their risk of metastasis. Class 1 is low biological risk of metastasis, Class 2A is higher biological risk, and Class of 2B is highest risk. This translates into about a 7% to 10% risk for Class 1, 20% for class 2A, and between a 40% and 50% risk for the highest-risk, 2B group. A test like this is not typically used to predict treatment response, unless it’s developed as a companion biomarker. And this one was not; it was developed as a prediction tool. This is what we could call a secondary study. But we had a large population of patients with excellent data, and many of them were treated with radiation. This gave us the opportunity to examine the data we had collected to see if it could help us to determine which of our patients were most likely to benefit from radiation.
What did the data show regarding the use of DecisionDx-SCC for identifying patients who were most likely to benefit from ART?
We were able to look at metastasis rates and DecisionDx-SCC scores for nearly 900 patients. We compared patients who received radiation after clearance of their tumor versus those who did not. What we saw was that patients who received ART in that highest-risk group (group 2B) had a 50% reduction in metastasis compared with those who did not receive radiation, which was really a large benefit of ART in this highest-risk group.
In this study, we used a comprehensive and sophisticated statistical method called propensity score analysis to account for all of the other clinicopathological risk factors that we know are predisposing to metastasis. We wanted to account for as many risk factors as possible so that we could feel confident that the result we see in these Class 2B patients is due to fact that they are biologically at high risk, without confounding from any of the other risk features.
How does this affect patient management?
This gives us the opportunity to tell a patient that their risk is so high, it may be worth considering additional treatment to bring that risk of metastatic disease down. It’s helped me to make some treatment decisions for some high-risk patients that I might otherwise have sent to a tumor board. I’m now able to add this additional information in that referral process. —By Mark Bowes
