The Cutaneous Microbiome: Implications for Dermatology Practice.

The human integument is inhabited by a vast array of microorganisms known collectively as the cutaneous microbiome. As a result of advances in laboratory science, our understanding of the diversity and complexity of the human microbiome is rapidly evolving. In particular, advances in the field of genomics have enabled the study of the cutaneous microbiome with a hitherto unimaginable level of detail, resulting in a maturation of our understanding of cutaneous health and disease. Herein, we review current microbiology concepts and highlight the key features of recent laboratory advances, particularly with respect to genomics. We provide a summary of new findings related to normal skin flora, interactions between host immunity and microbial communities, and microbial relationships with common skin disorders. Finally, we review the implications for dermatologists.

Evaluation of the modified immune prognostic index to prognosticate outcomes in metastatic uveal melanoma patients treated with immune checkpoint inhibitors.

BACKGROUND: Metastatic uveal melanoma (MUM) is associated with poor survival and inferior response to immune checkpoint inhibitor (ICI) therapy when compared with metastatic cutaneous melanoma. Currently, prognostic biomarkers are lacking to guide treatment decisions. PATIENTS AND METHODS: We conducted a multicenter, retrospective cohort study using a centralized, province-wide cancer database in Alberta, Canada. We identified 37 patients with histologically confirmed MUM who received at least one dose of single-agent pembrolizumab or nivolumab, or combination therapy nivolumab and ipilimumab. A modified immune prognostic index (IPI), based on the previously reported lung immune prognostic index, was used to stratify patients into favorable and poor IPI groups. Survival analyses were conducted using the Kaplan-Meier method and Cox proportional hazards models, adjusting for baseline age (≥60) and ECOG performance status, to assess the associations between IPI and overall survival (OS). Time to treatment failure (TTF) was also assessed using the Kaplan-Meier method. The association between IPI and objective response rate was examined using chi-squared tests. Logistic regression was used to determine the association between IPI and immune-related adverse events (irAEs). RESULTS: Median OS was 15.6 (range 0.6-57.6) months with 45.9% 1-year survival rate at a median follow-up of 11.8 months. We found that a favorable IPI was significantly associated with OS [median 30.5 (12.0-not reached) months in the favorable IPI group compared with 4.6 (2.1-16.0) months in the poor IPI group (p = 0.001)] (HR=4.81, 95% CI; 1.64-14.10, p = 0.004), TTF [median 5.1 (95% CI; 2.1-10.4) months in the favorable IPI group compared with 3.7 (95% CI; 1.4-6.4) months in the poor IPI group (p = 0.0191)], and irAE (HR=6.67, 95% CI; 1.32-33.69, p = 0.0220). CONCLUSIONS: The modified IPI may be a useful tool in clinical practice for identifying MUM patients who are more likely to experience irAEs and realize a survival benefit from ICI treatment.