Proteomic Analysis of Small Extracellular Vesicles From Lymphatic Affluents in Developing Premetastatic Niche in Melanoma

Melanoma is an aggressive form of skin cancer that often metastasizes through lymph nodes (LNs). Lymphatic small extracellular vesicles (sEVs) derived from melanoma play a crucial role in establishing a premetastatic niche (PMN) within the sentinel lymph node (SLN). Therefore, analyzing the proteomic content of tumor-draining lymphatic sEVs that deliver oncogenic signals to the SLN is vital in understanding the PMN. To investigate this, we performed multiplexing (18 samples) using tandem mass tag labeling to profile the lymphatic sEV proteomes obtained from afferent lymphatic channels leading to the SLN of melanoma patients (n = 6), non-cancer-associated afferent lymphatic channels (n = 3), and postoperative lymphatic fluid after LN dissection (n = 9). We identified 595 new proteomic cargoes compared with those reported in ExoCarta and 1003 new cargo proteins relative to three previously reported lymphatic EV datasets. The analysis revealed 145 differentially expressed proteins of melanoma sEVs that link to increased cellular stress and injury pathways and a decrease in extracellular matrix organization (-log[p value] >7.0). Analysis of the top 50 differentially expressed proteins included expressions of normal, primary, and metastatic samples across multiple omics datasets. Hierarchical clustering with postoperative samples demonstrated nine upregulated and two downregulated proteins specific to melanoma sEVs, which are associated with melanoma progression (p < 0.05). Notably, several common proteins associated with melanoma and postoperative samples were related to the wound healing mechanism. The multiplex immunofluorescence analysis of selected proteins reveals significantly increased expression levels of CD38, galectin-9 (LGALS9), and tenascin-C (TNC) in the lymphatic sinuses of SLN (-) compared with the control LN sinuses. Moreover, higher levels of LGALS9 protein in LN tissue are associated with poor overall survival of melanoma patients (p = 0.0018). In summary, this study reveals an altered landscape of sEV proteome in the afferent lymphatic fluid of melanoma, highlighting distinct sEV proteins that are uniquely present in the SLN during PMN development.

Authors

Institutions

Publication Details

Journal
Molecular & Cellular Proteomics
Published
2025-11-20
DOI
https://doi.org/10.1016/j.mcpro.2025.101472
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Proteomic Analysis of Small Extracellular Vesicles From Lymphatic Affluents in Developing Premetastatic Niche in Melanoma

Xiaowei Zhao, Raymond M. Moore, Jaeyun Sung, Ray Guo et al.
Molecular & Cellular Proteomics
Extracellular vesicles in disease
article

Proteomic Analysis of Small Extracellular Vesicles From Lymphatic Affluents in Developing Premetastatic Niche in Melanoma

Xiaowei Zhao, Raymond M. Moore, Jaeyun Sung, Ray Guo, Akhilesh Pandey, Sarah A. McLaughlin, Wendy K. Nevala, James W. Jakub, Svetomir N. Markovic, Richard K. Kandasamy, Liyi Geng, Shankar Suman, Chathu Atherton
article en

Abstract

Melanoma is an aggressive form of skin cancer that often metastasizes through lymph nodes (LNs). Lymphatic small extracellular vesicles (sEVs) derived from melanoma play a crucial role in establishing a premetastatic niche (PMN) within the sentinel lymph node (SLN). Therefore, analyzing the proteomic content of tumor-draining lymphatic sEVs that deliver oncogenic signals to the SLN is vital in understanding the PMN. To investigate this, we performed multiplexing (18 samples) using tandem mass tag labeling to profile the lymphatic sEV proteomes obtained from afferent lymphatic channels leading to the SLN of melanoma patients (n = 6), non-cancer-associated afferent lymphatic channels (n = 3), and postoperative lymphatic fluid after LN dissection (n = 9). We identified 595 new proteomic cargoes compared with those reported in ExoCarta and 1003 new cargo proteins relative to three previously reported lymphatic EV datasets. The analysis revealed 145 differentially expressed proteins of melanoma sEVs that link to increased cellular stress and injury pathways and a decrease in extracellular matrix organization (-log[p value] >7.0). Analysis of the top 50 differentially expressed proteins included expressions of normal, primary, and metastatic samples across multiple omics datasets. Hierarchical clustering with postoperative samples demonstrated nine upregulated and two downregulated proteins specific to melanoma sEVs, which are associated with melanoma progression (p < 0.05). Notably, several common proteins associated with melanoma and postoperative samples were related to the wound healing mechanism. The multiplex immunofluorescence analysis of selected proteins reveals significantly increased expression levels of CD38, galectin-9 (LGALS9), and tenascin-C (TNC) in the lymphatic sinuses of SLN (-) compared with the control LN sinuses. Moreover, higher levels of LGALS9 protein in LN tissue are associated with poor overall survival of melanoma patients (p = 0.0018). In summary, this study reveals an altered landscape of sEV proteome in the afferent lymphatic fluid of melanoma, highlighting distinct sEV proteins that are uniquely present in the SLN during PMN development.

Molecular & Cellular ProteomicsVol. 25(1)
Mayo Clinic (US), Manipal Academy of Higher Education (IN), Jacksonville College (US), WinnMed (US), University of Minnesota Rochester (US), Mayo Clinic in Arizona (US), Mayo Clinic in Florida (US)
Openalex Percentile: Top 68%
Extracellular vesicles in disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.