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SMC6 expression & outcome of breast cancer
For correspondence: Prof Maria A Nagai, Department of Radiology and Oncology, Laboratory of Molecular Genetics, Centro de Investigação Translacionalem Oncologia- CTO and Comprehensive Center for Precision Oncology, Instituto do Câncer do Estado de São Paulo (ICESP), Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, 01246-000, Brazil e-mail: nagai@usp.br
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Received: ,
Accepted: ,
Abstract
Background & objectives
Genetic instability is frequent in tumour cells and might occur due to an imbalance of homologous recombination (HR). HR is a crucial mechanism of DNA double-strand break (DSB) repair that depends on the formation and resolution of Holliday junctions for genomic stability maintenance. The SMC6 complex with SMC5 is involved in DSB repair. We sought to investigate the association between SMC6 expression, genomic instability, and prognosis of breast cancer.
Methods
This was an observational retrospective cohort study. We assessed SMC6 expression and copy number variation (CNV) data measured by qRT-PCR and whole-genome comparative genomic hybridization in 33 women with breast cancer who are non-carriers of BRCA1/BRCA2 mutations. According to nuclear staining, the SMC6 protein expression was evaluated on a tissue microarrayer containing 481 samples classified as SMC6low (negative/weak) or SMC6high (moderate/strong).
Results
SMC6low tumours tend to show higher CNV. SMC6high group presented poorer disease-free survival than the SMC6low group (P=0.050), mainly for the luminal subtype (P=0.005). SMC6low/ERpos were protective biomarkers for recurrence.
Interpretation & Conclusions
There is a possible association between SMC6 expression and relapse of breast cancer, also suggesting that SMC6 abnormal expression may indicate tumour genetic instability in breast cancer.
Keywords
Biomarker
breast cancer
expression
genomic instability
prognosis
SMC6
Genomic integrity is the key to the correct functioning of cell proliferation and tissue homeostasis. The normal cell has mechanisms that guarantee the stability of its genetic content. In cancer, one of the hallmarks is genomic instability, represented mainly by chromosomal instability leading to chromosomal rearrangements, translocations, duplications, and aneuploidy1,2. In breast cancer, some genes involved in the maintenance of genomic integrity are frequently mutated and associated with a higher risk of disease development, such as BRCA1/2, TP53, ATM, PIK3CA, CHEK2, and RAD513-6.
Cells have several mechanisms to preserve the integrity of the genome. Homologous recombination (HR), the exchange of DNA fragments with similar or identical nucleotide sequences, is a normal process responsible for the genetic variability during meiosis. It is also one of the primary DNA double-strand break repair mechanisms (DSB) using sister chromatids as a repair template during the cell division process, thus being an essential mechanism for maintaining genomic stability. For HR repair to take place after DSB, intermediate bonds can be formed and resolved, which join homologous DNA strands called Holliday Junctions (HJ), allowing DNA synthesis and DSB repair7,8.
One of the genes involved in the DSB process is the structural maintenance of chromosomes (SMC6; also known as SMC6L1). The SMC6 belongs to the family of the same name whose members (SMC1-6) act as complexes in different processes such as DNA repair, genetic recombination, chromosome condensation, and sister-chromatid cohesion, to guarantee chromosomal homeostasis. The SMC family members assemble into three distinct complexes: cohesins complex - SMC1/3, acting on the cohesion of sister chromatids; cohesins complex- SMC2/4, involved in the condensation of chromosomes; and the SMC5/6 complex, evolutionarily conserved in eukaryotes, acting in the repair of DNA lesions9,10. The protein encoded by SMC6 has been shown to act in a complex with SMC5, facilitating the repair of DSB by HR and acting in different processes of maintenance of genomic integrity11,12. SMC6 is located on chromosome 2p24.2, adjacent to the GEN1 (GEN1 Holliday junction 5’ flap endonuclease) gene in head-to-head orientation, sharing the intergenic promoter region, which corresponds to the organisation observed in gene pairs with bidirectional promoters13. GEN1 encodes a monomeric endonuclease that cleaves symmetrically at the Holliday junction, producing duplexes that will be ligated by resolving the junction of DNA molecules14,15.
To date, there is no comprehensive report concerning the prognostic value of SMC6 on for prognosis of breast cancer. We evaluated the pattern of SMC6 expression and its prognostic value in breast cancer and explore the association with genomic imbalance.
Materials & Methods
This retrospective cohort study was undertaken by the department of Radiology and Oncology, Faculdade de Medicina da Universidade de São Paulo (FMUSP), Brazil. The study was conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and its subsequent amendments, as outlined in the Brazilian national resolution 466/12 (Resolução do Conselho Nacional de Saúde n° 466/12). The ethical approval was obtained from the Institutional Ethics Committees (Faculdade de Medicina da Universidade de São Paulo and Fundação Antonio Prudente - Hospital AC Camargo). The written informed consent was obtained from all the study participants.
Participants and tumour samples
The study cohort comprised of 481 formalin-fixed paraffin-embedded (FFPE) breast cancer samples assembled in tissue micro-array (TMA) slides from the department of Pathological Anatomy, AC Camargo Cancer Center, and from the department of Pathology da Faculdade de Medicina da Universidade de São Paulo (FMUSP), São Paulo, Brazil. The mean age of participants was 56 yr (26-91 yr), 82.5 per cent of (n=399) tumours were oestrogen receptor-positive, 73.1 (n=354) per cent were progesterone receptor-positive, and 16.4 per cent (n=79) were HER2-positive.
To explore the association between SMC6 expression and genomic instability, an independent cohort, also from AC Camargo Cancer Center, São Paulo, Brazil, composed of 33 breast cancer samples from women who were non-carriers of BRCA1/BRCA2 mutations, was accessed by CGH array.
TMA assembly, immunohistochemical performance, and assessment
The HE-stained slides were reviewed for the construction of the breast tissue microarrays, and core biopsies of selected areas of the donor block were taken as duplicates using a tissue microarrayer (TMA). For immunohistochemistry, TMA was deparaffinized and rehydrated using xylene, serial dilutions of ethanol (100, 85, and 70%), and distilled water. Antigen retrieval was performed by using 10 mM citrate buffer pH 6.0, in a steamer, and the endogenous peroxidase activity blockage was performed with three per cent hydrogen peroxide in phosphate-buffered saline (PBS) pH 7.4, followed by PBS washes. The primary monoclonal antibody used was SMC6 (43-Q) sc-101015 Santa Cruz (1:10).
Blinded image-based quantitative digital analysis was conducted on QuPath software (Quantitative Pathology & Bioimage Analysis, v0.2.0-m1, University of Edinburgh, UK)16. After the nuclear intensity threshold was set up, categorizing intensities as negative, weak, moderate, or strongly positive, the QuPath unsupervised algorithm automatically calculated each core H-score. For further analysis, only those samples with more than 10 per cent of representative tumour cells were considered.
RT-PCR
For mRNA quantification by qRT-PCR, 10 µg of total RNA was reverse transcribed using a high-capacity cDNA archive kit (Applied Biosystems). PCR amplification was performed using an applied biosystems PRISM 7500 Sequence Detector, using the Power SYBR® Green PCR Master Mix (Thermo Fisher Scientific, Waltham, MA, EUA). According to the manufacturer’s instructions, PCR reactions were carried out in a total volume of 12.5 μL. Experiments were performed in duplicate. The relative expression was calculated by 2−ΔΔCT.17
CGH array
The CGH was performed in a microarray (array-CGH) using a 180 K whole-genome platform. Briefly, samples were labeled with Cy3- and Cy5-deoxycytidine triphosphates by random priming. After purification, hybridization, and washing, images of the arrays were scanned using feature extraction software (Agilent Technologies, Santa Clara, CA, EUA). We applied the genomic workbench software (Agilent Technologies, Santa Clara, CA, EUA) for calling DNA CNV using the aberration detection method, two statistical algorithms with a sensitivity threshold of 6.7.
Statistical analysis
The best SMC6 H-score cutoff value was adjusted by the ROC curve. IHQ categorical data was evaluated by Pearson’s chi-square test. Non-categorical variables were analysed by the Mann-Whitney U test. Overall and disease-free intervals were calculated from the date of diagnosis to the date of last follow up or disease recurrence, respectively, and adjusted for 120 months. Cumulative overall survival (OS) and disease-free survival (DFS) probabilities were estimated by the Kaplan-Meier method, Survival curves were compared using the log-rank test. All statistical analyses were performed using IBM SPSS Statistics (version 25.0; SPSS Inc., Chicago, IL, USA).
Results
SMC6 expression and prognostic association
The digital image analysis confirmed the predominance of nuclear staining in accordance with its cohesion function, with some cases presenting cytoplasmic staining (Fig. 1). The SMC6 intensities were heterogeneous among the 481 cases. According to the adjusted cutoff value, n=269 (55.5%) of the cases were classified as SMC6low. Tumour features and association with SMC6 expression are shown in table.
- A representative panel of SMC6 immunohistochemistry of breast tumour specimens. Tumour samples were classified as (A) low and (B) high expression according to SMC6 nuclear staining.
| Variable | Categories (n) | SMC6 n (%) | P value | |
|---|---|---|---|---|
| low | high | |||
| Oestrogen receptor | ERneg (84) | 60 (12.5) | 24 (5.0) | 0.001 |
| ERpos (395) | 205 (42.8) | 190 (39.7) | ||
| Progesterone receptor | PRneg(129) | 83 (17.3) | 46 (9.6) | 0.018 |
| PRpos (352) | 184 (38.3) | 168 (34.9) | ||
| HER2 | Neg (392) | 216 (46.1) | 176 (37.5) | 0.765 |
| Pos (77) | 41 (8.7) | 36 (7.7) | ||
| Tumour, node metastasis stage | Early (329) | 178 (41.3) | 151 (35.0) | 0.507 |
| Late (102) | 59 (13.7) | 43 (10.0) | ||
| Tumour size (T) | T1+ T2 (390) | 214 (48.4) | 176 (39.8) | 0.151 |
| T3+ T4 (52) | 34 (7.7) | 18 (4.1) | ||
| Lymph node status (pN) | pN0 (253) | 138 (32.3) | 115 (26.9) | 0.717 |
| pN+ (174) | 98 (20.0) | 76 (17.8) | ||
| Bloom-Richardson grading | I+ II (275) | 135 (33.9) | 140 (35.2) | 0.196 |
| III (123) | 69 (17.3) | 54 (13.6) | ||
| Nuclear grade | I+ II (166) | 73 (17.8) | 93 (22.6) | 0.007 |
| III (145) | 141 (34.3) | 104 (25.3) | ||
No association was observed between long-term overall survival and SMC6 expression (Fig. 2A and B). On the other hand, SMC6high expression was slightly related to poor disease-free survival (P=0.050, Fig. 2C). A stronger association was observed in SMC6high luminal breast cancer patients and worse DFS (P=0.005, Fig. 2D). The ER expression is a well-known prognostic marker and can also stratify patients in this cohort (Fig. 3A and 3B). The SMC6low/ERnegative group of patients has a higher risk of death (P=0.002, HR 2.51, 95% CI 1.41-4.47, Fig. 3C). Regarding DFS, the SMC6low/ERpositive patients have a protective effect compared with all the other groups Fig. 3D.
- Outcome curves of breast cancer patients according to SMC6 protein expression - Kaplan-Meier Overall (A and B) and Disease-free (C and D) survival curves in groups of low and high SMC6 expression. A and C- entire breast cancer cohort; B and D - Luminal breast cancer patients. Log-rank test was performed for the comparison between groups. HR, hazard ratio; sig, significance; SR, survival rate.
- Outcome curves of breast cancer patients according to co-expression of SMC6 protein and oestrogen receptor- Kaplan-Meier overall (A) and disease-free (B) survival curves in groups of oestrogen receptor positive or negative, and groups of co-expression (C and D). Log-rank test was performed for the comparison between groups.
SMC6 expression and genomic instability
To minimise the interference of commonly known breast cancer mutated genes related to DNA repair, we selected 33 primary breast cancer patients with no BRCA1 or BRCA2 mutations and explored copy number variation (CNV) by whole-genome comparative genomic hybridization (CGH). In this population, we assessed the pattern of SMC6 mRNA expression. The median relative SMC6 expression was 13.31 (range 0 – 108) and was used as a cutoff to categorise low or high-expression groups. The median CNV events in the entire population were 49 (range 3-168). We found that the median CNV events were greater in the SMC6low group, 75.5 (range 24–130, n=16), than in the SMC6high group, 32 (range 3–168, n=17). Although not significant, we observe a trend to accumulate more CNV events per genome in the group of low SMC6 expression (P=0.087). A representative CNV profile in each group of SMC6 expression is represented in figure 4.
- Genome-wide copy number profiles of breast cancer samples stratified by SMC6 expression level. (A) Cutout of the representative copy number profile of breast cancer samples. Top panels: CGH-Array landscape of SMC6low tumours. Bottom panels: CGH-Array landscape of SMC6high tumours. Each vertical line represents a chromosome boundary (chromosomes 1–22, X, Y), and log₂ copy number ratios are plotted for each probe. Points above the light grey threshold line indicate gains, and those below the dark grey threshold line indicate losses, as defined by Nexus Copy Number software (BioDiscovery). Images were created and adapted from Nexus Copy Number software. (B) SMC6 expression measured by qRT-PCR and copy number variation (CNV) per sample. SMC6 mRNA levels are represented as 2^(−ΔΔCT), normalized to an internal control. CNV burden is displayed as the total number of CNV events detected per sample. The dotted horizontal line marks the median SMC6 expression used to define ‘high’ and ‘low’ expression groups. (C) Distribution of CNV events stratified by SMC6 expression levels. Boxplots illustrate CNV burden for the two expression groups. Individual sample points are overlaid to show dispersion. The box represents the interquartile range and the median.
Discussion
Here, we provided the first large-scale evaluation of SMC6 protein expression in breast cancer and its potential prognostic value. We observed distinct patterns of SMC6 expression across tumour samples and identified associations between SMC6 status and key clinicopathological features, including hormone receptor status and tumour grade. Moreover, differences in genomic imbalance patterns between SMC6 expression groups suggest that SMC6 may participate in pathways linked to genome maintenance.
SMC6 expression has been associated with the tumorigenic process in hepatocellular carcinomas (HCC) (Livingston et al, 2017)18, in pancreatic adenocarcinoma19, and sarcomas20. However, there are no systematic studies evaluating the prognostic value of SMC6 in breast cancer. In a recent study, genetic alterations affecting SMC5/6 complex components have been identified as prevalent in breast cancer, and amplification of SMC5/6 complex genes was associated with higher aneuploidy and ploidy scores and poor patient survival21. Although not directly comparable, as these authors do not evaluate SMC6 mRNA or protein expression, these findings, taken together, warrant new experimental and clinical studies to understand better the role of the SMC5/SMC6 complex in breast cancer physiopathology. Pei et al (2024)22 conducted an in silico evaluation of the role and potential clinical value of mRNA expression of the SMC family members in breast cancer. They found elevated SMC6 mRNA expression in breast cancer tumours compared to normal tissue, which was negatively correlated with promoter methylation and the immunopheno score22. SMC4 mRNA was found to be upregulated and associated with poor survival in breast cancer patients, and high SMC4 expression levels were found to be associated with worse survival in ER/PR-positive patients23. Here, we found an association between high SMC6 expression and oestrogen receptor positivity. The role of cohesin complexes in mediating gene regulation has been well documented, although several questions remain, especially regarding the roles of the different members of the SMC family24. Cohesins are important for oestrogen receptor transactivation. Schmidt et al (2010)25 identified thousands of genomic sites shared by cohesin and oestrogen receptor alpha (ER). They showed that oestrogen-regulated genes in breast cancer cells are preferentially bound by both ER and cohesin. Cohesins have also been associated with anti-oestrogen agents. Knockdown of NIPBL, SMC3, and RAD21 reduced tamoxifen sensitivity in MCF7 cells26. Taken together, these finding suggest that members of the SMC family, such as SMC6, could serve as useful biomarkers to identify patients with ER-positive tumours who should be treated with a more aggressive therapeutic protocol.
The strengths of this study include the use of a well-characterised breast cancer cohort and the integration of protein expression, molecular data, and genome-wide copy number profiling. Another strength of this study is the use of automated image analysis software based on machine learning for protein quantification, which reduces observer-dependent variability and increases reproducibility. However, our study has limitations, particularly regarding the CGH-array analyses, which were performed in a small subset of patients, limiting conclusions about genomic instability patterns. Additionally, we are aware that immunocytochemical analysis of molecularly characterised patients would be essential to validate and complement the real-time PCR results, thereby strengthening the biological relevance of the findings.
In conclusion, our findings provide new insights into the potential role of SMC6 as a biomarker in breast cancer. However, further clinical and experimental studies are required to evaluate the functional role and prognostic and predictive value of SMC6 in breast cancer.
Acknowledgment
Authors acknowledge Dr(s) de Toledo Osório CAB, de Andrade VP (Department of Pathological Anatomy, A.C. Camargo Cancer Center) and de Mello E [Department of Pathology, Instituto do Câncer do Estado de São Paulo (ICESP), Hospital das Clinicas, Faculdade de Medicina da Universidade de São Paulo (HCFMUSP)] for the production and availability of breast cancer TMA slides. Authors are also thankful to Ms. Nonogaki S (Department of Pathological Anatomy, A.C. Camargo Cancer Center) for the immunohistochemistry of all TMA slides.
Financial support & sponsorship
This study received the funding support from Fundação de Amparo a Pesquisa do Estadode São Paulo (FAPESP; 2019/05252-4).
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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