Prediction of clinical outcomes of advanced cutaneous squamous cell carcinoma to PD-1 inhibition directly from histopathology slides using inferred transcriptomics

IntroductionMetastatic or locally advanced cutaneous squamous cell carcinoma (cSCC) that is not amenable to local therapy is treated with programmed death-1 (PD-1) inhibitors. Although response rates are relatively high, there are no validated predictive biomarkers to guide treatment.

As a result, a subset of patients — particularly frail and elderly patients which can be treated with local palliative therapy — are exposed to immune-related adverse events without clinical benefit. Here, we present a retrospective evaluation of ENLIGHT-DP, a novel digital pathology biomarker which predicts response to PD-1 inhibition in advanced cSCC directly from histopathology slides using inferred transcriptomics.MethodsWe scanned high-resolution hematoxylin and eosin (H&E) slides from pretreatment tumor samples of 38 patients with advanced cSCC treated with cemiplimab and retrospectively generated an individualized prediction score using the ENLIGHT-DP pipeline in a two-step process: (i) inference of mRNA expression profiles directly from H&E slides using the DeepPT deep-learning algorithm, and (ii) integration of these inferred transcriptomes into ENLIGHT, a transcriptomics-based precision oncology platform that predicts therapeutic response.