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Cellular interactions in the sentinel lymph node predict melanoma recurrence.

Sabrina M Solis1, Yang Yang2, Yee Hoon Foong1

  • 1Department of Medicine, NYU Grossman School of Medicine, New York, New York, USA.

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|December 25, 2025
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Summary
This summary is machine-generated.

Spatial mapping of melanoma sentinel lymph nodes reveals that interactions between regulatory T cells (Tregs) and exhausted CD8 T cells predict disease recurrence. This immune cell interaction signature offers new insights into melanoma outcomes.

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Area of Science:

  • Immunology
  • Oncology
  • Spatial Biology

Background:

  • Melanoma outcomes have improved, yet recurrence persists, especially in later stages.
  • The sentinel lymph node (SLN) immune microenvironment, including CD8 T cells and regulatory T cells (Tregs), is altered, but its spatial organization is poorly understood.

Purpose of the Study:

  • To investigate the spatial organization of immune cells within melanoma SLNs.
  • To identify spatial immune cell interaction patterns associated with melanoma patient outcomes and disease progression.

Main Methods:

  • Spatial proteomic profiling of Stage I and II melanoma SLNs using multiplexed immunofluorescence imaging.
  • Deep learning for cell segmentation and clustering, identifying 33 immune and tumor cell subsets.
  • Effect Size Interaction mapping (ESI-map) to analyze nearest-neighbor cell interactions.

Main Results:

  • A foundational spatial map of the melanoma SLN was created, showing distinct immune cell positioning.
  • Rewiring of cell-cell interaction pairs was observed across disease progression, particularly involving exhausted TOX+ CD8 T cells.
  • Stage II patients with recurrence showed enriched interactions between Tregs and TOX+ CD8 T cells, correlating with reduced cytotoxic markers.

Conclusions:

  • Specific spatial interactions between Tregs and exhausted CD8 T cells in the SLN serve as a novel immune signature for predicting melanoma outcomes.
  • Understanding the spatial immune microenvironment is crucial for deciphering melanoma progression and recurrence patterns.