Leavitt & Black et al. SITC Spring Scientific (2025)
Poster Highlights
In this poster, presented at the SITC Spring Scientific 2025, we used unsupervised clustering to analyze a 29M cell cytometry dataset to identify immune cell populations and subsets that correlate with response outcomes in melanoma patients treated with anti-PD1 therapy.
The clustering revealed a CD161+ positive subset of CD4+ T Cells that were associated with response.
A statistically significant increase in TBET and decrease in CCR7 expression were associated with response.
This confirms literature findings that these trends in marker expression were associated with higher survival.
Unsupervised clustering, paired with advanced quality control methods, can overcome the inherent challenges of high-dimensional data analysis, paving the way for deeper insights into immunological complexity.
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