Precision Oncology Arrives for Skin Cancer: How Genomic Testing is Rewriting SCC Treatment
For decades, predicting which cutaneous squamous cell carcinomas (SCCs) would metastasize – and therefore require aggressive treatment – has been a clinical guessing game. Now, a 40-gene expression profile test, DecisionDx-SCC, is changing that, offering a level of precision previously unseen in managing this common, yet potentially deadly, skin cancer. Recent studies confirm its ability to accurately stratify risk, potentially sparing many patients from unnecessary radiation and ensuring those at genuine risk receive the intensive care they need.
Understanding the Challenge with High-Risk SCC
SCC is the second most common skin cancer, and while highly curable when caught early, its aggressive potential is significant. Even after complete surgical removal, the risk of local recurrence and distant metastasis looms for some patients. Traditionally, clinicians relied on factors like tumor size, depth, location, and the presence of features like immunosuppression or perineural invasion to assess risk. However, these clinicopathologic factors often fall short of providing a definitive answer, leading to overtreatment in some and undertreatment in others.
DecisionDx-SCC: A Deep Dive into Tumor Biology
Launched in 2020 by Castle Biosciences, Inc., DecisionDx-SCC analyzes the gene expression within an SCC tumor. This isn’t simply looking for mutations; it’s assessing the overall biological activity of the cancer cells. The test categorizes tumors into three risk classes: Class 1 (low risk), Class 2A (intermediate risk), and Class 2B (highest risk). “DecisionDx-SCC looks at a specific set of genes that can give clinicians higher predictive value in terms of stratifying where a patient’s potential risk is for certain factors,” explains Milan Shah, MD, a dermatology resident at the Medical University of South Carolina. This stratification allows for a more tailored approach to post-surgical management.
How Risk Classification Impacts Treatment
The implications of these risk classifications are substantial. Désirée Ratner, MD, PC, a clinical professor of dermatology at NYU Grossman School of Medicine, highlights the practical benefits: “If a patient has class 1 disease, even with high-risk features, we can often monitor them less frequently – perhaps every six months. Conversely, a Class 2B designation signals a significantly higher risk, prompting more frequent monitoring, potentially every three months, or consideration of adjuvant radiation therapy.” This nuanced approach minimizes unnecessary interventions while maximizing the chances of early detection and treatment of recurrence.
Study Results: Validating Predictive Accuracy
Recent research reinforces the clinical utility of DecisionDx-SCC. A study analyzing 414 patients with high-risk SCC found a clear correlation between risk class and outcomes. Patients in Class 1 exhibited significantly higher local recurrence-free survival (95.3%) and metastasis-free survival (97.1%) compared to those in Classes 2A and 2B (85.5%/89.3% and 71.4%/57.1%, respectively; P < .001). Importantly, incorporating DecisionDx-SCC classifications improved the accuracy of predicting local recurrence risk beyond traditional clinicopathologic factors alone.
Further bolstering confidence in the test, a survey of 244 clinicians revealed that a majority view genetic testing via DecisionDx-SCC as a crucial factor in assessing disease progression and guiding treatment decisions, particularly regarding adjuvant radiation therapy. The test accurately predicted risk levels aligning with clinical thresholds for surveillance imaging and radiation consideration.
The Future of SCC Management: Beyond Genomic Testing
DecisionDx-SCC represents a significant step towards personalized medicine in dermatology. However, the story doesn’t end here. The increasing sophistication of genomic testing is likely to lead to even more refined risk stratification. We can anticipate the development of tests that identify specific therapeutic targets within SCC tumors, paving the way for targeted therapies tailored to individual patients. The Skin Cancer Foundation provides valuable resources on SCC prevention and treatment, highlighting the importance of early detection and ongoing research.
Furthermore, the integration of artificial intelligence (AI) and machine learning (ML) with genomic data promises to unlock even deeper insights into SCC biology. AI algorithms could potentially identify subtle patterns in gene expression that are currently undetectable, leading to even more accurate risk predictions and personalized treatment strategies. The convergence of genomics, AI, and clinical expertise will undoubtedly reshape the landscape of SCC management in the years to come.
What are your predictions for the role of genomic testing in skin cancer treatment? Share your thoughts in the comments below!
