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

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.

Keywords: differentially expressed proteins; lymph nodes; lymphatic fluid; melanoma; premetastatic niche; proteomics; small extracellular vesicles; tandem mass tags.

Graphical abstract

Fig. 1

Collection of lymphatic fluid for sEV isolation from control cases (preventive mastectomy) and cutaneous melanoma cases. The afferent lymphatic channel that drains lymph from peripheral tissue to the sentinel lymph node (LN) was identified by surgeons using blue dye injection as part of their routine procedure. The excised intraoperative afferent lymphatic channel was clipped, and lymphatic fluid was collected by washing the channel with syringes from the following subjects: 1. Individuals undergoing preventive mastectomy (control). 2. Melanoma patients undergoing lymphadenectomy for LN metastasis screening. In addition, lymphatic fluid that drains postlymphadenectomy is referred to as postoperative lymph fluid and categorized as 3. postoperative lymph. These three categories of samples used isolation of lymphatic sEVs, and the proteomic analysis was performed. sEV, small extracellular vesicle.

Fig. 2

Experimental workflow for characterization of lymphatic sEVs and proteomic analysis.A, lymphatic fluid was used to isolate sEV particles through size-exclusion chromatography (qEV1 70 nm column; IZON), followed by concentration using a cutoff column (30 kDa). The sEVs were characterized using nanoparticle tracking analysis (NTA) performed in triplicate. B, transmission electron microscopy (TEM) analysis was conducted to examine the size and morphology of lymphatic sEV. C, a dot plot indicates the average size of sEV from each sample in control, melanoma and postoperative lymphatic fluid. D, Western blot analysis was performed to assess the presence of classical sEV markers, including Alix, CD9, and syntenin-1, as well as negative makers, albumin and calnexin in plasma, lymph, and exosomal particles. E, the TMTpro workflow involved labeling lymphatic sEVs collected from afferent channel control, melanoma, and postoperative samples with 18 different TMTpro tags, which were further pooled, cleaned, and then analyzed using mass spectrometry. sEV, small extracellular vesicle; TMT, tandem mass tag.

Fig. 3

Lymphatic sEVs exhibit distinct proteomic cargo profiles that differ from those reported in datasets.A, Venn diagram displays the unique cargoes found in lymphatic sEVs in comparison to the total proteins of human ExoCarta as well as ExoCarta top 100. B, Gene Ontology (GO) analysis of the unique proteins identified in lymphatic sEVs. C, Venn diagram analysis of our dataset with three published lymphatic datasets. sEV, small extracellular vesicle.

Fig. 4

Melanoma lymphatic sEVs contain unique proteomic cargoes to establish oncogenic pathways in the SLN.A, the volcano plot illustrates the significant upregulation and downregulation of proteins in the sEVs derived from the afferent lymphatic channel of melanoma in comparison to the control group. B, top 25 upregulated and top 25 downregulated proteins in melanoma lymphatic sEVs compared with control. C, KEGG pathway enrichment analysis reveals that modulated proteomic cargoes are associated with immunoregulation and cellular structural remodeling. D, comparison of top 50 modulated proteins with SKCM datasets in primary (n = 103) and metastatic tumors (n = 367). Significance levels are indicated as follows: ∗p < 0.05; ∗∗p < 0.01; and ∗∗∗p < 0.001. KEGG, Kyoto Encyclopedia of Genes and Genomes; sEV, small extracellular vesicle; SKCM, skin cutaneous melanoma; SLN, sentinel lymph node.

Fig. 5

Comparative analysis of sEV deregulated proteins with melanoma Cero and Cuarto proteomic datasets.A, Venn diagram analysis of all differentially expressed proteins (DEPs) in melanoma sEVs with Cero and Cuarto datasets. The top 25 DEPs, included both upregulated and downregulated proteins were compared across both these datasets by Venn diagram, and their expression level are shown by box plots. B–C, among the top 25 downregulated DEPs, six common proteins are shown using box plots. D–E, among the top 25 DEPs, with eight upregulated proteins from either the Cero or Cuarto dataset displayed through box plots. sEV, small extracellular vesicle.

Fig. 6

Proteomic analysis of control, melanoma, and postoperative lymphatic fluid sEVs demonstrates distinct proteomic cargoes of melanoma.A, heatmap indicating sEV proteomic differences among control, melanoma, and postoperative lymphatic fluid. B, box plot with individual data points display proteins of melanoma and postoperative lymphatic fluid, compared with the control, along with expression plots from TNMplotter, indicating the direct involvement of the highlighted proteins in the melanoma metastasis. This analysis utilizes RNA-Seq data derived from 474 samples of normal tissues from noncancer patients, 103 tumor samples, and 368 metastatic cases. These findings underscore the significance of unique proteomic cargoes within the context of melanoma. sEV, small extracellular vesicle.

Fig. 7

Significance of identified proteins derived from melanoma afferent lymphatic sEVs in melanoma tumorigenesis.A, the proteomic network of all upregulated proteins found in melanoma lymphatic sEVs, when compared with controls, reveals four significant protein network clusters identified using the MCL clustering method. B, a Spearman's correlation matrix of the melanoma-associated upregulated proteins shows a higher correlation in melanoma tumor data compared with the normal dataset. C, gene signature analysis using RNA-Seq data in relation to the SKCM dataset of the highlighted upregulated and downregulated proteins in lymphatic sEVs of melanoma patients. MCL Markov Cluster algorithm; sEV, small extracellular vesicle; SKCM, skin cutaneous melanoma.

Fig. 8

Primary melanoma communicates sEV signals to facilitate a premetastatic niche within the sentinel lymph node (SLN). Key melanoma-associated proteins, including CD38, LGALS9, and TNC, were analyzed in the sinuses of lymph nodes, comparing control and tumor-uninvolved SLN (−). The dot plot indicates the mean fluorescence intensity of these proteins, with each dot representing an individual field of view (FOV). sEV, small extracellular vesicle.

Fig. 9

Expression analysis and clinical significance of lymphatic sEV signals in melanoma tissues.A, the cargo of lymphatic sEVs, including CD38 and LGALS9, along with the universal sEVs marker CD9, was analyzed in the blood plasma of six melanoma patients and six healthy subjects. B, bar plots showing the relative changes in expression levels of CD9, LGALS9, and CD38 with total protein normalization. C, survival plot analysis based on the selected expression of proteins in lymph nodes affected by melanoma. sEV, small extracellular vesicle.