There is an urgent need for predictive platforms for response to immunotherapy in patients. In vivo phenotyping of tumor-immune microenvironment (TiME) for predicting response to immunotherapy was evaluated using non-invasive reflectance confocal microscopy (RCM) in skin cancer patients. Phenotypes were correlated with underlying biology and response to topical immunotherapy. Using both inflammation and vasculature features, four major phenotypes were observed. The VaschiInfhi phenotype correlated with high immune activation, exhaustion, and vascular signatures while VaschiInflo with endothelial anergy and immune exclusion. Highest response to immunotherapy was seen in VascloInfhi phenotype. This study establishes proof-of-concept for in vivo TiME phenotyping in patients.
The limited sampling of biopsy and histopathology can lead to incomplete and/or inaccurate assessment of basal cell carcinomas (BCCs), subtypes and depth, which can affect diagnosis and treatment outcome. Reflectance confocal microscopy (RCM) combined with optical coherence tomography (OCT) can help achieve comprehensive 3-dimensional sampling in vivo, which may improve the diagnostic accuracy and margin assessment of BCCs. In a clinical study, we tested a combined RCM-OCT probe on 85 patients, with either clinically-suspicious (n=60, in intact skin) or biopsy-proven BCCs (n=25, in scarred skin). We correlated BCC features in RCM and OCT images with histopathology, calculated diagnostic accuracy and correlated depth predicted by OCT with histopathologically measured depth. The main features were small tumors extending from the basal cell layer at the dermal-epidermal junction; small and large tumor nests; in dermis; dark silhouettes; dilated blood vessels; horn cyst and bright peritumoral stroma. Deeper features such as necrosis and intratumoral mucin pools were correlated on OCT and histology. Higher sensitivity and negative predictive value (100%) and comparable specificity (48% vs 56% on RCM) and positive predictive value (82.19 vs 84.59 % on RCM) were observed for the combined RCM-OCT device for diagnosis of all lesions (n=85). Relatively higher specificity (94.1%) and positive predictive value (75%) were observed in the clinically suspicious lesions (n=60, in intact skin). High correlation was observed (R=0.86) between the OCT predicted depth and histopathologically measured depth. Therefore, RCM-OCT imaging may be prospectively used to comprehensively diagnose suspicious BCC lesions, determine subtype and triage for treatment.
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