The footprint of the ageing stroma in older patients with breast cancer

This study was approved by the ethics committee of the University Hospitals Leuven (Leuven, Belgium) in accordance with the International Conference on Harmonisation Harmonised Tripartite Guideline for Good Clinical Practice. Candidate patients were selected using the following criteria: (1) aged <45 years or ≥80 years, (2) no neo-adjuvant chemotherapy treatment or hormone treatment before surgery, (3) surgery for early triple-negative breast cancer (defined as oestrogen receptor [ER] and progesterone receptor [PR] <1% and human epidermal growth factor receptor 2 [HER2] <2+ by immunohistochemistry or fluorescent in situ hybridisation-negative) with fresh frozen resection specimens available (stored at −80 °C at the pathology department of the University Hospitals Leuven) and (4) no chronic inflammatory diseases to exclude confounding variables.

For each candidate patient, one section of the frozen tumour material was obtained for hematoxylin and eosin (H&E) staining. H&E-stained sections were evaluated for tumoural and stromal content and used to localise the best areas for stromal microdissection (see Fig. 1 as an example). Only tumour tissue blocks consisting of invasive tumour with representative carcinoma-associated stromal fields to allow laser capture microdissection (LSM) were selected. We selected tumours with a very low amount of or absent tumour-infiltrating lymphocytes to prevent bias in the gene expression analyses. On the basis of the above criteria, 17 female patients with breast cancer (9 young patients <45 years old at diagnosis and 8 old patients ≥80 years old at diagnosis) were included in the study.

Prior to LCM, tumour slides were stained with cresyl violet following a procedure optimised for maximising RNA yield. Briefly, tumour slides were taken from −80 °C and were fixed into a 95% ethanol solution for 30 seconds. Next, they were transferred to ethanol solutions with progressively decreasing concentrations (75%, 50%) for 30 seconds each. Then, cresyl violet dye (cresyl violet acetate pure high-purity biological stain, catalogue number AC229630050; Acros Organics, Geel, Belgium) at a concentration of 0.2% was applied for 30–60 seconds, after which dehydration of the tissue was achieved by rinsing the slides with increasing concentrations of ethanol (50%, 75%, 95%, 100%, 100%) for 15 seconds each.

After the staining procedure, LCM was accomplished within 30 minutes by using a laser microscope (LMD6500; Leica Microsystems). Dissected stromal pieces were immediately collected in an RNase/DNase-free capture vial containing 25 μl of stabilising RNA extraction buffer. During dissection, care was taken to avoid blood vessels, zones containing infiltrating immune cells, or fatty tissue. Dissection was restricted to fields contained within the perimeter of the invasive tumour or at the invasive front of the tumour, but in direct relationship with invasive epithelial nests. Pictures were taken before and after the dissection procedure (see Fig. 2 as an example). After finishing dissection for one tumour slide, 25 μl of RNA extraction buffer was added to the capture vial, and lysis was performed for 30 minutes at 42 °C. The obtained lysate was stored at −80 °C until further RNA extraction. For each patient, several tumour slides were laser-dissected using this procedure (seven to ten slides per patient according to size and amount of stromal fields within the tumour tissue).

RNA isolation was performed using the Arcturus PicoPure RNA extraction kit (PicoPure^TM Frozen RNA Isolation Kit, catalogue number KIT0202/KIT0204; Arcturus, Mountain View, CA, USA) according to the manufacturer’s protocol. Briefly, lysates from the same tumour were combined, and after addition of 50 μl of ethanol 70%, the pooled samples were passed onto pre-conditioned RNA extraction columns. After centrifugation and washing, DNase was applied onto the column to eliminate residual DNA (RNase-Free DNase Set, catalogue number 79254; QIAGEN, Hilden, Germany). After a washing step, the purified RNA was eluted from the column using 11 μl of elution buffer. Samples were subsequently tested for RNA quality (RNA Quality Indicator) on the Experion™ system (Bio-Rad Laboratories, Hercules, CA, USA) using high-sensitivity RNA chips, and concentrations were measured using the NanoDrop 2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA). The quality of the RNA varied between samples, which is a known limitation of the LSM procedure [45] (see Additional file 1). Prior to microarray analysis, RNA was pre-amplified using the Ovation PicoSL WTA System V2 (catalogue number 3312-24; NuGEN, Leek, The Netherlands). The Ribo-SPIA (single-primer isothermal amplification) technology implemented in this procedure is ideal for amplification of partially degraded and compromised RNA samples, contributes minimal coverage bias, and is highly reproducible [46]. The procedure is widely used in LCM projects and does not introduce significant bias into relative gene expression values [47, 48]. A clean-up step using the MinElute Reaction Cleanup Kit (catalogue number 28204; QIAGEN) was also incorporated into the amplification procedure. After NuGEN pre-amplification of the RNA samples, quantitative reverse transcription-polymerase chain reaction assessment of common housekeeping genes showed that the amplification procedure had resulted in highly concentrated complementary DNA fragments with sufficient size to be recognised by the primers (data not shown).

Gene expression was analysed using Human Genome U133Plus2 microarray chips (Affymetrix, Santa Clara, CA, USA) at the J.C. Heuson Breast Cancer Translational Research Laboratory (Jules Bordet Institute, Brussels, Belgium) according to the manufacturer’s instructions. Standard quality assessments were conducted on the resulting files, and all samples passed quality assurance for further analysis. Expression values were computed using the frozen robust multi-array analysis (fRMA) normalisation method (‘frma’ package in Bioconductor) [49]. When multiple probe sets mapped to the same official gene symbol, we computed their average value. The expression data are available from the Gene Expression Omnibus (GEO) repository under accession number [GEO:GSE90521].

For the purpose of the present study, 17 female patients (9 young patients <45 years old at diagnosis and 8 old patients aged ≥80 years at diagnosis) with available fresh frozen breast cancer resection specimens and with sufficient stroma to allow laser microdissection were selected. Extreme age categories were chosen to maximise the probability of detecting significant age-related differences. All patients underwent surgery for early breast cancer at the Multidisciplinary Breast Center (University Hospitals Leuven, Belgium) between 2000 and 2011. All patients had invasive ductal carcinomas >1.5 cm and were negative for ER, PR and HER2. Additional patient and tumour characteristics are summarised in Table 1. The choice of triple-negative breast cancers was made to exclude cancer-related confounding factors as much as possible.

A differential gene expression analysis using a 1.5-fold up- or down-regulation as the cut-off revealed 120 genes that were up-regulated in older subjects’ stromal samples and 107 genes that were down-regulated in older subjects’ stromal samples compared with younger subjects (Table 2). Heat maps constructed using the 25 top up- and down-regulated genes are shown in Fig. 3.

We used publicly available data sets ([GEO:GSE5847] [9], 34 samples; [GEO:GSE4823] [7], 33 samples; [GEO:GSE14548] [8], 9 samples) to validate our findings because of the limited size of our study group. We found a significant overlap for ten genes, of which five showed higher expression in older patients (p < 0.01) and five showed lower expression in older patients (p < 0.01). Venn diagrams depicting the overlapping genes are shown in Fig. 4; gene details are listed in Table 3.

Next, we performed GSEA to measure the expression of pre-defined gene sets related to specific biological processes. The resulting ES, which ranges from −1 to 1, reflects the enrichment in genes of a given reference class among the top up- or down-regulated genes from the individual gene ranking. Plots are shown in Figs. 5 and 6. The genes that were included in each GSEA, with respective literature references, are listed in Table 4.

In the individual gene expression analysis, no significant difference was found for genes known to be associated with senescence, such as CDKN1A, CDKN2A, TP53, GLB1 or the retinoblastoma (RB) genes. Nevertheless, the enrichment analysis for this gene set resulted in an ES of −0.53, suggesting enrichment of senescence genes in the stroma of older patients, although statistical significance was not reached (p = 0.09) (Fig. 5a). The lack of significance might be due to the small sample size of the reference classes.

None of the three most important components of the DNA damage response, namely ATM, NBN (NBS1) and CHK2, were differentially expressed between young and old stromal tissues. Similar results were found when we applied GSEA to the DNA damage response gene set. The estimated gene score was 0.57, which did not reach statistical significance (p = 0.10) (Fig. 5b).

Several genes involved in the SASP showed a deregulated gene expression profile, suggesting an enrichment of SASP in the stroma of older patients, including CXCL2 (over-expressed in older stromal tissues; fold change 1.59), TNFRSF11B (over-expressed in older stromal tissues; fold change 2.11) and CCL8 (down-regulated in older stromal tissues; fold change −1.61). Of interest, GSEA confirmed a significant enrichment in SASP-related genes within the stroma of older patient samples with an ES of −0.21 (p = 0.04) (Fig. 6a).

None of the genes described to be involved in the AST showed a relevant difference in gene expression between young and old stroma at the individual gene level. However, when compiling them together in the GSEA, we found a highly significant enrichment of autophagy genes in the stroma of older patient samples (ES −0.42; p < 0.01) (Fig. 6b).