Abstract
Background/Aim: Patients’ age may influence the response to chemotherapy and the clinical course of breast carcinoma. This study aimed to compare the spatial transcriptomic profiles between younger (≤50 years) and older (>50 years) patients with hormone receptor (HR)-positive breast carcinoma. Patients and Methods: Seven cases of breast carcinoma were included. We performed digital spatial profiling and bioinformatic analysis to investigate the spatial transcriptomes of the epithelial and stromal compartments. Results: In the epithelial compartment of three young-age breast carcinoma (YABC) cases, we found 21 up-regulated and 7 down-regulated genes. The top two most up-regulated genes were serpin peptidase inhibitor clade A member 1 and serine protease. The gene ontology enrichment analysis revealed a significant up-regulation of genes defining ribosomal structures and functions in YABCs. The gene set enrichment analysis revealed that gene sets defining early and late responses to estrogen, response to interferon-α, and tumor necrosis factor-α signaling were significantly enriched in YABCs. Conclusion: We described for the first time the age-related differences in spatially resolved transcriptomic profiles and up-regulated transcriptional pathways of HR-positive breast carcinoma. Our observations highlight the critical need for age-specific treatment strategies for breast carcinoma management.
Breast carcinoma is one of the most common malignancies and the second leading cause of carcinoma-related mortality in women worldwide (1). There have been substantial improvements in the development of new diagnostic technologies and novel therapeutic strategies; however, the global incidence and mortality rates of breast carcinoma have steadily increased over the last several decades (2). Many researchers focus on advancing our understanding of how to prevent, detect, and treat breast carcinoma and identify people with a higher risk of breast carcinoma recurrence.
Breast carcinoma is a heterogeneous group of malignant tumors originating from the epithelial cells lining the lactiferous ducts (3). The heterogeneity of breast carcinoma has long been noted in both histology and clinical behavior, and these differences have served as the basis for disease classification (3). Breast carcinoma was recently classified into various molecular subtypes based on the expression status of the hormone receptor (HR) and human epidermal growth factor receptor (HER2), both of which are significant determinants that profoundly impact patient outcomes and therapeutic strategies (4, 5). Among the molecular subtypes, HR-positive breast carcinomas represent the largest proportion.
Although breast carcinoma is most common in postmenopausal women, approximately 20% of cases occur in premenopausal women <50 years, with HR-positive breast carcinoma comprising the majority in this younger demographic (6). Young-age breast carcinoma (YABC) often presents with higher rates of recurrence and mortality (7, 8). Specifically, women <40 years diagnosed with breast carcinoma tend to have tumors with larger sizes, higher histological grades, and positive lymph node metastasis (9). Nevertheless, studies on the clinicopathological and molecular features of HR-positive YABC are scarce.
Treatment strategies for HR-positive breast carcinoma include chemotherapy and endocrine therapy. Gene expression assays, such as Oncotype DX (Exact Sciences, Marlborough, MA, USA), aid in determining the necessity of adjuvant chemotherapy (10, 11). For instance, the Trial Assigning Individualized Options for Treatment study indicated that for patients with HR-positive, node-negative breast carcinoma with Oncotype DX Recurrence Score (ORS) below 26, chemotherapy offers little to no survival benefit, particularly in those >50 years old (12). In contrast, chemoendocrine therapy may be considered for patients >50 years with ORS between 16 and 25 (13). The survival benefit of adjuvant chemotherapy for YABC is not fully understood, particularly whether it is related to an indirect effect on ovarian suppression.
Digital spatial profiling (DSP) can quantify RNA transcripts in formalin-fixed paraffin-embedded (FFPE) tissue samples using barcoded DNA oligonucleotides attached to in situ hybridization probes via an ultraviolet (UV)-photocleavable linker (14). Regions of interest (ROIs) are exposed to UV light that cleaves the linker and releases the barcoded oligonucleotides for capture. This high-plex spatially resolved RNA detection allows for transcriptomic characterization in spatially distinct areas. Some spatial transcriptomic studies have recently been reported in breast carcinoma (15-18); however, only a few studies have analyzed the differences in gene expression between age groups of patients with HR-positive breast carcinoma. This study aimed to analyze the spatial transcriptomic profiles of younger and older patients with HR-positive breast carcinoma using DSP technology. Such clinicopathological and genetic insights could significantly contribute to the understanding and management of breast carcinoma across different age groups.
Patients and Methods
Case selection and clinicopathological data collection. This study was performed in accordance with the principles of the Declaration of Helsinki. The study protocol was reviewed and approved by the Institutional Review Board of the Kangbuk Samsung Hospital (Seoul, Republic of Korea; protocol number: 2024-02-034; approval date: March 8, 2024). Between March 2019 and September 2022, we collected tissue samples from seven patients with HR-positive, HER2-negative, node-negative breast carcinoma. The patients were categorized into two groups: three patients <50 years (young-age group; YAG) and four patients ≥50 years (old-age group; OAG). Two board-certified breast pathologists thoroughly examined all available hematoxylin and eosin (H&E)-stained slides and confirmed that all were cases of invasive breast carcinoma. They also reviewed the electronic medical records and pathology reports to collect the following clinicopathological information: tumor size, histological grade, lymph node status, estrogen receptor (ER) expression status, progesterone receptor (PR) expression status, HER2 expression status, Ki-67 labeling index, mitotic count, and ORS. The expression statuses of HRs and Ki-67 were determined by immunostaining (19-23). ER and PR immunoreactivities were analyzed using the Allred scoring system (24). For both proteins, Allred scores of 0-2, 3-4, and 5-8 were interpreted as negative, weakly positive, and strongly positive, respectively. To estimate the Ki-67 labeling index, three 20× objective fields were digitally captured using the GenASis Capture and Analysis Platform (Applied Spectral Imaging, Carlsbad, CA, USA), and the index was measured using a GenASis HiPath system (Applied Spectral Imaging) (1, 25).
Tissue microarray (TMA) technique. TMA blocks were constructed as previously described (25-27). The two most representative tumor areas were marked on all H&E-stained slides and the corresponding FFPE tissue blocks. Two 3-mm diameter tissue cores were taken from marked tumor areas in each block and manually assembled into recipient TMA blocks. Each core had more than 70% of the tumor volume. For recipient blocks, holes for array cores at 2-mm intervals were created using an X-Y position guide. The obtained tissue core was transferred into holes in the recipient block. Finally, a pair of TMA blocks was constructed for each case.
DSP technique. Four-micrometer-thick FFPE tissue sections from TMA blocks were profiled using the Technology Access Program (NanoString Technologies, Seattle, WA, USA). In each TMA core, circular ROIs were selected based on two visualization markers, pan-cytokeratin (CK) and smooth muscle actin (SMA), representing the epithelial and stromal compartments, respectively. The ROIs were subsequently segmented into two CK-positive and SMA-positive clusters (Figure 1). UV exposure of each ROI liberated the barcodes (indexing oligonucleotides) from the DSP probes, and the probes were then quantified using the NanoString nCounter system (NanoString Technologies). Using the GeoMx DSP Analysis Suite (NanoString Technologies), quality control and normalization were performed according to the manufacturer’s recommendations (28). Briefly, the binding density of probe tags, positive control normalization, minimum nuclei, and surface area count were assessed through quality control. Normalization was carried out using three housekeeping proteins (histone H3, S6, and glyceraldehyde 3-phosphate dehydrogenase), and relative protein expression data were obtained separately from the CK-positive and SMA-positive compartments and exported from the GeoMx DSP Analysis Suite (NanoString Technologies). DSP with the NanoString Whole Transcriptome Atlas Panel (NanoString Technologies) was then conducted on each compartment.
Regions of interest obtained from multilabel immunofluorescence staining of invasive breast carcinoma. (A-C) Case 1. (D-F) Case 2. (G-I) Case 5. (J-L) Case 6. The epithelial and stromal compartments express pan-cytokeratin (green) and smooth muscle actin (red), respectively.
Differentially expressed genes (DEGs). All statistical analyses were performed using R software (version 4.3.1, R Foundation for Statistical Computing, Vienna, Austria). DEG analysis was conducted using the DESeq2 package. The raw data were processed to identify DEGs, applying a threshold of absolute log2 fold change (FC) >1.0 and an adjusted p-value <0.05. For visualization, the ComplexHeatmap package was employed to generate a heatmap of the DEGs, with data scaled by Z-score for enhanced visualization. Both rows (representing genes) and columns (samples) were clustered to identify patterns. The EnhancedVolcano package facilitated the creation of a volcano plot, juxtaposing statistical significance (p-value) against the magnitude of change (FC), enabling rapid identification of genes with significant and large FCs.
Gene ontology (GO) enrichment analysis. GO enrichment analysis was performed to identify enriched GO terms within the categories of cellular component, biological process, and molecular function, using the enrichGO function from the clusterProfiler package and the org.Hs.eg.db from the OrgDb package. The GO terms with a p-value <0.05 were considered statistically significant.
Gene set enrichment analysis (GSEA). To assess the enrichment of specific gene sets in our dataset, we performed GSEA using the fgsea package. We utilized the MSigDB hallmark gene sets. An adjusted p<0.05 was used as the cutoff value for assessing the statistical significance of the estimates.
Results
Table I summarizes the baseline clinicopathological characteristics of the seven patients with HR-positive, HER2-negative, node-negative breast carcinoma. The three YAG patients (cases 1-3) were between 32 and 47 years old, whereas the OAG comprised four patients (cases 4-7) aged between 57 and 68 years. All patients were histo-pathologically diagnosed with invasive carcinoma of no special type. The tumor size ranged from 1.5 to 2 cm (mean=1.7 cm; median=1.7 cm). All cases exhibited high Allred scores of ER (mean=8.0; median=8.0) and PR (mean=6.9; median=7.0), lack of HER2 immunoreactivity, and Ki-67 labeling indices ≤10%. None of the cases showed lymph node metastasis or histological grade 3. The ODSs ranged between 11 and 20 (mean=15.4; median=16), indicating that all the patients had a low-to-intermediate risk of recurrence.
Baseline clinicopathological characteristics.
Table II summarizes the differences in gene expression between patients in the YAG and OAG. In the epithelial compartments of the YAG, we found 28 significant DEGs, including 21 up-regulated and 7 down-regulated genes. Serpin peptidase inhibitor clade A member 1 (SERPINA1), serine protease (PRSS23), and protein-glucosylgala-ctosylhydro-xylysine glucosidase (PGGHG) showed the highest FCs (3.69, 3.24, and 2.37, respectively) in the YAG. The average expression levels of these genes in the YAG were 9.74, 6.82, and 6.96, respectively, while those in the OAG were 5.33, 4.29, and 4.47, respectively. Ribosomal protein 3 (RPG3) was also up-regulated in the epithelial compartments of the YAG (FC=1.51). In contrast, clusterin (CLU), cellular retinoic acid binding protein 2 (CRABP2), and immunoglobulin heavy constant gamma 2 (IGHG2) were the three most down-regulated genes (FCs=−3.13, −2.36, and −2.12, respectively) in the epithelial compartment of the YAG. The average expression levels of CLU, CRABP2, and IGHG2 in the YAG were 4.54, 5.54, and 4.03, respectively, while those in the OAG were 7.70, 7.76, and 5,70, respectively. Interestingly, we identified SERPINA1 as a significant DEG in both the epithelial and stromal compartments. In the stromal compartment of the YAG, SERPINA1 was significantly up-regulated, with an average expression level and FC of 7.51 and 2.46, respectively. The immunoglobulin kappa constant was significantly down-regulated in the stromal component of the YAG (average expression level of YAG=6.67; average expression level of OAG=9.77; FC=−2.76). Figure 2 and Figure 3 depict heatmaps (Figure 2) and volcano plots (Figure 3) of DEGs identified in the epithelial and stromal compartments of breast carcinoma.
Differentially expressed genes in the epithelial and stromal compartments of young-age breast carcinoma.
Heatmaps of differentially expressed genes in the (A) epithelial and (B) stromal compartments across different age groups. The normalized expression values are presented as z-scores to enhance comparative analysis, with the color gradients indicating the degree of expression (red for high expression and blue for low expression). The epithelial compartment heatmap was generated using genes with an absolute fold change (aFC) of >1 and an adjusted p-value of <0.05. The stromal compartment heatmap was generated using genes with an aFC>1 and a p<0.01.
Volcano plots of differentially expressed genes in the (A) epithelial and (B) stromal compartments across different age groups. Each dot represents a gene; its location indicates the fold change of gene expression and its statistical significance. For the epithelial compartment, genes with an absolute fold change (aFC) >1 and an adjusted p-value of <0.05 are shown. For the stromal compartment, genes with an aFC>1 and a p<0.01 are shown. The red dots represent up-regulated genes in the younger and older age groups in the right and left upper corners, respectively.
To elucidate the functional implications of the identified genes in each compartment of the YAG, we conducted a GO enrichment analysis (Table III). We observed significant enrichments in several GO terms related to the cellular component, biological process, and molecular function, including ribosomal structures and functions, cell adhesion, and cytoplasmic translation. The most significantly enriched terms with counts of ≥12 were associated with cytoplasmic translation (counts=16; p<0.00001), cytosolic ribosome (counts=14; p<0.00001), ribosomal subunit (counts=14; p<0.00001), structural constituent of ribosome (counts=14; p<0.00001), ribosome (counts=14; p<0.00001), focal adhesion (counts=12; p<0.00001), and cell-substrate junction (counts=12; p<0.00001). In contrast, the analysis yielded minimal enrichment in the stromal compartment, with counts ranging between 1 and 4 (data not shown).
Enriched gene ontology categories of up-regulated genes in the epithelial compartment of young-age breast carcinoma.
Table IV summarizes the top enriched hallmark gene sets in the YAG. GSEA revealed several hallmark gene sets that were significantly up-regulated or down-regulated in the YAG. We noted that two pathways indicative of both early and late estrogen signaling, HALLMARK_ESTROGEN_RESPONSE_ LATE [adjusted p=0.0129; normalized enrichment score (NES)=2.2009] and HALLMARK_ESTROGEN_RESPONSE_ EARLY (adjusted p=0.0129; NES=2.0281), were significantly enriched in the epithelial compartment. In particular, the HALLMARK_ESTROGEN_RESPONSE_LATE pathway featured key genes, such as SERPINA1 and PRSS23. Two pathways related to immune response and signaling, HALLMARK_INTERFERON_ALPHA_RESPONSE (adjusted p=0.0129; NES=2.0643) and HALLMARK_TNFA_ SIGNALING_VIA_NFKB (adjusted p=0.0129; NES=1.9563), were also significantly enriched. Furthermore, HALLMARK_KRAS_SIGNALING_UP was identified as a significantly up-regulated pathway (adjusted p=0.0129; NES=1.8937). In contrast, the HALLMARK_MYOGENESIS pathway (adjusted p=0.0453; NES=−1.6193), featured by key genes, such as CLU and cyclin-dependent kinase inhibitor 1A, and HALLMARK_GLYCOLYSIS pathway (adjusted =0.0452; NES=−1.4812) exhibited a significant down-regulation in the epithelial compartment of the YAG. GSEA of the stromal compartment further revealed positive enrichment of HALLMARK_OXIDATIVE_PHOSPHORYLATION (adjusted p=0.0247; NES=2.0084) and HALLMARK_ESTROGEN_ RESPONSE_LATE pathways (adjusted p=0.0247; NES=1.9087), which also highlighted SERPINA1 among the key genes. In contrast, the HALLMARK_EPITHELIAL_ MESENCHYMAL_TRANSITION (adjusted p=0.0247, NES=− 2.8875) and HALLMARK_ANGIOGENESIS (adjusted p=0.0304, NES=−1.9787) pathways were negatively enriched in the stromal compartment. Figure 4 and Figure 5 demonstrate the results of GSEA for hallmark pathways that were significantly up-regulated or down-regulated in the epithelial (Figure 4) and stromal (Figure 5) compartments of the YAG, respectively.
Top enriched hallmark gene sets in the epithelial and stromal compartments of young-age breast carcinoma.
Gene set enrichment analysis of hallmark pathways in the epithelial compartment. (A) Pink and blue bars represent up-regulated and down-regulated hallmark pathways in the younger age group, respectively. The length of each bar indicates the normalized enrichment score. (B and C) The gene sets most (B) up-regulated and (C) down-regulated in the younger age group are HALLMARK_ESTROGEN_RESPONSE_LATE and HALLMARK_MYOGENESIS, respectively. The bars at the bottom and top of the panels are the corresponding genes of certain gene sets.
Gene set enrichment analysis of hallmark pathways in the stromal compartment. (A) Pink and blue bars represent up-regulated and down-regulated hallmark pathways in the younger age group, respectively. The length of each bar indicates the normalized enrichment score. (B and C) The gene sets most (B) up-regulated and (C) down-regulated in the younger age group are HALLMARK_OXIDATIVE_PHOSPHORYLATION and HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION, respectively. The bars at the bottom and top of the panels are the corresponding genes of certain gene sets.
Discussion
This study presents interesting perspectives by highlighting transcriptomic differences between the YAG and OAG in HR-positive breast carcinoma. We employed spatial transcriptomics to explore the age-related differences in gene expression profiles for the first time. Our results indicate the importance of recognizing distinct biological mechanisms in age-stratified breast carcinoma research, facilitating further investigations into age-specific therapeutic strategies.
The significant up-regulation of PRSS23 and SERPINA1 in the epithelial compartment of YABC underscores the impact of patients’ age on the biological characteristics of breast carcinoma. Some previous studies have demonstrated that PRSS23 is up-regulated by ERα and associated with the proliferation of breast carcinoma cells, indicating that PRSS23 over-expression is associated with ERα-positive breast carcinoma and potentially influences DNA replication and cellular proliferation (29, 30). Chan et al. (31) emphasized that SERPINA1, a direct ER target gene, exhibits increased expression associated with the enhanced overall survival of patients with ER-positive breast carcinoma in The Cancer Genome Atlas cohort, indicating that a high expression of SERPINA1 is a promising predictive marker for a better clinical outcome of patients with ER-positive breast carcinoma. Our GSEA results confirmed that the pathways related to estrogen signaling are significantly enriched in YABC, with PRSS23 and SERPINA1 identified as key genes of these pathways. This finding emphasizes the clinical significance of patients’ age and the estrogen signaling pathway in breast carcinoma.
The enrichment of ribosome-related genes in the epithelial compartment of the YAG indicates the vital role of these genes in the development and progression of YABC. Beyond their primary functions in protein synthesis, ribosomal proteins are involved in various extraribosomal processes of breast carcinoma cells, including the regulation of cellular proliferation and tumor growth (32). Notably, we found that RPS3 was significantly up-regulated in YABC. This finding agrees with previous data demonstrating that RPS3 plays a role in enhancing the expression of the X-linked inhibitor of apoptosis, which is the most potent inhibitor of cell death pathways and is linked to chemotherapy resistance, aggressive clinical behavior, and shorter survival of breast carcinoma (33). The transcriptomic characterization and expression profiles of the ribosome-related genes in YABC may provide a better understanding of their oncogenic functions in breast carcinoma (34).
From a therapeutic perspective, the relationship between the estrogen signaling pathway and chemosensitivity in breast carcinoma has been reported (35). Sarhadi et al. (35) performed gene enrichment analysis to identify the most affected pathways and functional gene sets in chemoresistant and chemosensitive breast carcinoma samples. In the latter phenotype, epithelium development (biological process), growth factor binding (molecular function), extracellular matrix (cellular component), and HALLMARK_ESTROGEN_ RESPONSE_EARLY (hallmark) were the most significantly enriched gene sets. In line with these data, we found that two hallmark pathways, HALLMARK_ESTROGEN_RESPO NSE_LATE and HALLMARK_ESTROGEN_RESPONSE_EARLY, were significantly enriched in the epithelial compartment of YABC. In this context, our findings raise the possibility that patients’ age could have a substantial influence on treatment outcomes, emphasizing the essence of integrating age-related factors into the process of deciding treatment plans for patients with breast carcinoma.
Accumulated evidence has shown the interactions between estrogen signals and immune cells within the tumor microenvironment. The clinicopathological significance of estrogen reactivity in immune and autoimmune responses has been documented (36, 37). This includes the influence of estrogen on the size, maturation, and functionality of T cells, notably leading to a decrease in pro-inflammatory cytokine production in CD4+ helper T type 1 cells and an increase in anti-inflammatory cytokine activity in CD4+ helper T type 2 cells. Moreover, the ERα pathway plays a role in controlling the activation and survival of B cells (37). Takeshita et al. (36) demonstrated that breast carcinoma with increased estrogen reactivity features reduced immune cytolytic activity and lower levels of immunostimulatory cells, highlighting a complex relationship between estrogen signaling and immune surveillance within the tumor microenvironment.
Study limitations. We employed a rigorous research design, standardizing various clinical parameters among participants to reduce confounding variables. Despite these efforts, the limited number of cases in each age group may present a notable limitation. Furthermore, we enrolled patients with breast carcinoma who underwent surgery exclusively from a single institution. We acknowledge that the primary drawback of single-center or single-laboratory studies is their potentially limited external validity. Future investigations with larger YABC cohorts are warranted to validate our findings and enhance the reliability of age-related differences in spatially resolved transcriptomic profiles.
Conclusion
In conclusion, we demonstrated significant differences in gene expression and transcriptional pathways between younger and older patients with HR-positive breast carcinoma. Our observations highlight the critical need for age-specific treatment strategies for breast carcinoma management.
Acknowledgements
This work was supported by the Samsung Medical Center Grant (SMO1240641), the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (2023R1A 2C2006223), and the Medical Research Funds from Kangbuk Samsung Hospital.
Footnotes
Authors’ Contributions
All Authors made substantial contributions to the conceptualization and design of this study, collection, interpretation, and validation of the data, drafting of the manuscript, critical revision of the manuscript, and approval of the final version to be published.
Conflicts of Interest
None of the Authors have any conflicts of interest or financial ties to declare regarding this study.
- Received March 28, 2024.
- Revision received April 10, 2024.
- Accepted April 11, 2024.
- Copyright © 2024 The Author(s). Published by the International Institute of Anticancer Research.
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY-NC-ND) 4.0 international license (https://creativecommons.org/licenses/by-nc-nd/4.0).
