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Updated: Mar 22, 2026

A Robust Discovery Platform for the Identification of Novel Mediators of Melanoma Metastasis
Published on: March 8, 2022
Associations Between Pigmentation and the Clinicopathologic and Immune Landscape of Melanoma
Helana Ghali1, Ayah N Al-Bzour2, Aleena Boby1
1University of South Florida Morsani College of Medicine, Tampa, FL.
Abstract:
Pigmentation varies widely in cutaneous melanoma, but its clinicopathologic and immunologic implications are incompletely defined. We retrospectively reviewed 627 patients with stage II-III melanoma treated at H. Lee Moffitt Cancer Center (2010-2019) and correlated pathologist-graded tumor pigmentation (0-3) with tumor features and sentinel lymph node biopsy results. We then evaluated transcript levels of pigmentation markers (TYR, DCT, MITF) for associations with overall survival (OS), tumor microenvironment (TME) composition, and immune checkpoint inhibitor (ICI) response using TCGA-SKCM bulk RNA-seq (n = 443) and public cohorts (GSE91061, GSE115978, GSE120575). Pigmented tumors (74.2%) showed lower Breslow depth ( P = 0.001), more tumor-infiltrating lymphocytes ( P < 0.001), greater angiolymphatic invasion ( P = 0.03), enrichment for superficial spreading subtype ( P < 0.001), and higher sentinel lymph node biopsy positivity ( P < 0.05) versus nonpigmented tumors. In TCGA, high TYR, DCT, and MITF expression independently correlated with worse OS. xCell analysis showed that low expression groups were enriched for multiple effector T- and B-cell populations, whereas high expression associated with immunosuppressive cell types (e.g., M2 macrophages, Tregs). In an ICI-treated cohort (GSE91061), baseline MITF was higher in nonresponders ( P = 0.023). Single-cell analyses confirmed pigmentation gene expression in malignant cells and demonstrated elevated MITF within myeloid subsets of nonresponders. Overall, both histologic pigmentation and pigmentation-gene signatures associate with tumor characteristics, immune contexture, and clinical outcomes, suggesting potential utility for risk stratification and treatment response prediction.
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