Proteomics of REPLICANT perfusate detects changes in the metastatic lymph node microenvironment

Abstract

In breast cancer (BC), detecting low volumes of axillary lymph node (ALN) metastasis pre-operatively is difficult and novel biomarkers are needed. We recently showed that patient-derived ALNs can be sustained ex-vivo using normothermic perfusion. We now compare reactive (tumour-free; n = 5) and macrometastatic (containing tumour deposits >2 mm; n = 4) ALNs by combining whole section multiplex immunofluorescence with TMT-labelled LC-MS/MS of the circulating perfusate. Macrometastases contained significantly fewer B cells and T cells (CD4⁺/CD8⁺/regulatory) than reactive nodes (p = 0.02). Similarly, pathway analysis of the perfusate proteome (119/1453 proteins significantly differentially expressed) showed that immune function was diminished in macrometastases in favour of 'extracellular matrix degradation'; only 'neutrophil degranulation' was preserved. Qualitative comparison of the perfusate proteome to that of node-positive pancreatic and prostatic adenocarcinoma also highlighted 'neutrophil degranulation' as a contributing factor to nodal metastasis. Thus, metastasis-induced changes in the REPLICANT perfusate proteome are detectable, and could facilitate biomarker discovery.

Fig. 1. Multiplex immunofluorescence of REPLICANT axillary lymph nodes (ALNs).

Reactive (n = 5) and macrometastatic (n = 4) ALNs were fluorescently stained for CD8, CD4, CD20, FoxP3 and PD-L1; reactive nodes, for CD68 in addition; metastatic nodes, additionally for pan-cytokeratin (pan-CK). Representative images of a reactive (A) and macrometastatic (B) node are shown (x20 magnification; field of view: 670 µm × 500 µm). From left to right, the first panels show immunofluorescent staining; second panels show cell phenotype maps, which were generated algorithmically. In metastatic nodes, the tissue also was segmented (third panel in B) into areas containing mostly cancer cells (‘tumour’; red), stromal regions (‘stroma’; light grey), and areas comprising mainly lymphoid cells (‘lymphoid’; green) for tumour infiltrating lymphocyte (mTILs) and PD-L1 analysis. No statistically significant differences in immune composition were seen between control (fixed at baseline) and perfused nodes (reactive nodes are shown in C, metastatic in D; cell density = total cells/mm²; Wilcoxon test). Subsequent analysis was therefore done on perfused ALNs only. The percentage of mTILs across the whole tissue section of metastatic ALNs (‘whole tumour’), as well as in ‘tumour’, ‘stroma’, and ‘lymphoid’ areas, is shown in E (n = 4). The differences between these regions was statistically significant (p < 0.0001; Kruskal-Wallis test). The regional distribution of regulatory T cells (T-regs) did not differ significantly however (F). The co-localisation of PD-L1 (average signal intensity) with other cell markers is shown in G. 49% (whole tumour) and 30–54% (regional) of the PD-L1 staining did not co-localise with any of the other markers that we had stained for (‘other immune’). Most of the remaining signal was present on T-lymphocytes (36% (whole tumour); 32% (tumour); 46% (stroma); and 37% (lymphoid)), with cancer cells contributing between 5 and 10%, and B cells <5%, to overall intensity. H The average cell density of CD20 ⁺ B cells (p = 0.02), CD8 ⁺ T cells (p = 0.02), CD4 ⁺ T cells (p = 0.02) and T-regs (p = 0.02) was significantly decreased in nodes replaced by macrometastases (latter, Kruskal–Wallis; former three, Mann–Whitney). (Graphs show mean with standard error of the mean (SEM)).

Fig. 2. Hierarchical cluster analysis of the 119 significantly differentially expressed proteins separates reactive from metastatic nodes.

A heat map showing hierarchical clustering of the nine perfusate samples (taken from nine different patients). A clear separation of reactive and metastatic nodes is seen.

Fig. 3. The perfusate proteome reflects the pathophysiology of the axillary lymph node (ALN) from which it derives.

The 57 significantly up-regulated proteins in reactive ALNs (A; n = 5) and the 62 significantly up-regulated proteins in macrometastatic ALNs (B; n = 4) were subjected to pathway analysis in ConsensusPathDB. Reactive ALNs maintained immune function whilst this was lost in macrometastatic nodes, with the notable exception on ‘neutrophil degranulation’. The identification of ‘keratinisation’ in macrometastatic nodes reflects the presence of cancer cells within the node. The other pathways identified in these nodes related to extracellular matrix (ECM) degradation. Histological neutrophil counts (haematoxylin and eosin stained ALN tissue sections) are shown in (C; graph shows mean with standard error of the mean (SEM)).

Fig. 4. Comparison of the perfusate proteome to primary breast cancer (BC) and plasma proteomes yields novel data.

We stratified the TCGA(CPTAC) primary BC proteomics data into three groups according to axillary tumour burden (ATB): those who had a sentinel lymph node biopsy only (SLNB; no/low ATB); those who had a completion clearance (CC; higher burden of ATB than the SLNB group); and those who had an axillary lymph node dissection, and high ATB, at diagnosis (ALND). Of the 10 most abundant reactive proteins, ADD1 (p = 0.01; A) and specific ADD1 phospho-isoforms; ASPN (p = 0.02; B) and PRELP (p = 0.023; B) were significantly up-regulated in the SLNB group, matching our data. No metastatic proteins were found to be significantly differentially expressed. Comparison of the perfusate proteome with BC plasma proteomic studies (C) showed minimal overlap, with APOC3 and KRT9 identified as up-regulated in metastatic nodes/perfusate, and SERPIND1 as up-regulated in reactive nodes/perfusate. (Graphs show median with interquartile range).

Fig. 5. Neutrophil degranulation is recurrently highlighted when the REPLICANT proteome is compared to either pancreatic or prostatic cancer.

Pathway analysis of the commonly expressed proteins obtained from an exclusive comparison of the perfusate proteome to node-positive pancreatic ductal adenocarcinoma (A; 515 commonly expressed proteins) or node-positive prostatic adenocarcinoma (B; 854 commonly expressed proteins) is shown. ‘Neutrophil degranulation’ was consistently identified as being important to lymph node metastasis.

Fig. 6. Neutrophil degranulation and 48 ‘core proteins’ are conserved in lymph node (LN) metastasis, across cancers.

Concurrent comparison of the REPLICANT proteome to node-positive pancreatic and node-positive prostate adenocarcinoma identified 438 commonly expressed proteins. Pathway analysis of these 438 proteins is shown in A. ‘Neutrophil degranulation’ once again was identified as being important to LN metastasis. Certain protein families were also seen to recur across the three datasets (48 ‘core proteins’). Pathway analysis of these ‘core proteins’ is shown in B.