CD103 and periplakin are potential biomarkers for response of metastatic melanoma to pembrolizumab.

Melanoma research(2022)

Cited 2|Views15
No score
Abstract
This study was designed to screen for preliminary evidence of predictive markers of melanoma response to PD-1 blockade. We hypothesized that the following immune markers would be positive predictors of response: increased densities of CD103 + CD8 + T cells or Th1 lineage T-bet + T cells, high expression of CXCL9-11 and presence of tertiary lymphoid structures. Conversely, we hypothesized that the high expression of barrier molecules would be a negative predictor of response. Patients with advanced melanoma treated with pembrolizumab were identified, and clinical response as well as overall survival data were collected. Tumor samples were evaluated by multiplex immunofluorescence histology. All statistical analyses were performed in R Studio and Microsoft Excel using the Mann-Whitney U test, chi-square test, Spearman's rank correlation and Kaplan-Meier survival curves. Sixty-five advanced melanoma patients were identified, of whom 46 met inclusion criteria and were included in this study. Increased densities ( P  = 0.04) and proportions ( P  = 0.02) of CD8 + T cells expressing CD103 + were associated with complete response (CR) to pembrolizumab. Improved survival was associated with increased proportions of CD8 + cells expressing CD103 ( P  = 0.0085) as well as decreased density of periplakin + cells ( P  = 0.012) and periplakin + SOX10 + cells ( P  = 0.0012). The density and proportion of CD8 + T cells expressing CD103 + positively correlated with PD-L1 expression, though PD-L1 expression was not significantly correlated with outcomes. This screening study found that increased density and proportion of CD8 + T cells expressing CD103 and decreased density of periplakin were associated with positive outcomes in patients with melanoma metastases treated with pembrolizumab and may warrant further study.
More
Translated text
Key words
metastatic melanoma,periplakin,potential biomarkers
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined