SET binding protein 1 (SETBP1) suppresses cell proliferation in estrogen receptor-positive breast cancer.

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Yuki Ando, Takaaki Masuda, Naoki Hayashi, Keisuke Kosai, Shohei Shibuta, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5269021/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 20 Feb, 2025 Read the published version in Breast Cancer → Version 1 posted 5 You are reading this latest preprint version Abstract Background The single nucleotide polymorphism rs6507583 at the promoter of SET binding protein 1 ( SETBP1 ) was implicated in estrogen receptor (ER)-positive breast carcinogenesis. Here, we evaluated the clinical and biological relevance of SETBP1 expression in ER-positive breast cancer (BC). Methods The associations between SETBP1 expression and clinical outcomes in BC patients were analyzed in independent cohorts. The localizations of SETBP1 expression in BC tissues were observed by immunohistochemical staining. Pathway analyses were conducted using TCGA dataset. An in vitro proliferation assay, protein phosphatase 2A (PP2A) activity assay, and gene expression analysis were performed in SETBP1 -knockdown ER-positive BC cells. We investigated the factors influencing SETBP1 mRNA expression using TCGA dataset. rs6507583 presence and SETBP1 mRNA expression in 11 mammary cell lines and 56 BC tissue samples were examined by target sequencing and RT-qPCR, respectively. Results SETBP1 was downregulated in BC cells compared with normal ductal epithelial cells. Low SETBP1 mRNA expression was an independent prognostic factor for poor recurrence-free survival. Pathway analyses revealed an inverse relationship between decreased SETBP1 expression and the expression of E2F, MYC, and G2M checkpoint target genes in BC tissues. SETBP1 knockdown promoted proliferation, inhibition of PP2A activity, and phosphorylation of MAPK in ER-positive BC. Low SETBP1 expression was influenced by high SETBP1 promoter methylation and DNA copy number SETBP1 deletion. SETBP1 expression with rs6507583 was lower than without rs6507583 in BC. Conclusions We demonstrated that low SETBP1 expression could be a poor prognostic biomarker that promotes ER-positive BC proliferation, possibly via phosphorylation of MAPK. SETBP1 ER positive breast cancer proliferation SNP Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Breast cancer (BC) is the most common cancer and the leading cause of cancer-related deaths among women worldwide including Japan [1–3], with approximately 70% of cases being estrogen receptor (ER) positive [4]. BC readily metastasizes, which limits the efficacy of further treatment [5]. A lack of understanding of the mechanism of ER-positive BC progression has hampered the development of efficient strategies to control disease progression and improve clinical outcomes. Thus, identifying driver genes contributing to the progression of ER-positive BC is of immense importance. Single nucleotide polymorphism (SNP)(rs6507583) at the promoter of SET binding protein 1 ( SETBP1 ) was implicated in breast carcinogenesis by BC genome-wide association analysis, and the association was stronger in ER-positive BC [6]. Importantly, it was reported that SNPs regulate the expression of target genes that affect tumorigenesis and the development of various cancers [7,8]. Altered SETBP1 expression by SNPs may contribute to the progression of ER-positive BC. SETBP1 , discovered in 2001 [9], is located at chromosome 18q21.1. SETBP1 encodes a large protein of 1542 amino acids localized in the cell nucleus and cytoplasm [10,11]. SETBP1 was initially found to interact with SE translation (SET ) and with a small protein inhibitor of the tumor suppressor protein phosphatase 2A (PP2A) [12]. SETBP1 expression has been investigated in various diseases, including malignancies such as non-small cell lung cancer [11], hematologic malignancies [13], colorectal cancers [14], ovarian cancers [15], triple-negative BC [16], and gastric cancers [17,18], suggesting that SETBP1 functions either as an oncogene or a tumor suppressor depending on the cancer. However, the clinical and biological significance of SETBP1 in the development of ER-positive BC remains unknown. Here, we analyzed the expression of SETBP1 in human ER-positive BC and determined the relationship between SETBP1 expression and survival in ER-positive BC patients. Furthermore, we sought to determine the biological role of SETBP1 in the progression of ER-positive BC. Materials and Methods Public datasets Data from The Cancer Genome Atlas database (TCGA) via Broad Institute’s Firehose ( http://gdac.broadinstitute.org/ ), Cancer Cell Line Encyclopedia (CCLE) via the Cancer Dependency Portal (DepMap) ( https://depmap.org/portal/ccle/ ), the Molecular Taxonomy of Breast Cancer International Consortium dataset (METABRIC) via cBioportal ( https://www.cbioportal.org/study/summary?id=brca_metabric ), and GSE19615 via PrognoScan analysis ( http://dna00.bio.kyutech.ac.jp/PrognoScan/ ) were analyzed in this study. We obtained mRNA expression data from the TCGA dataset (1093 tumor tissues, 112 non-cancerous tissues), METABRIC dataset (1959 tumor tissue), GSE19615 dataset (115 tumor tissue), and CCLE dataset (47 cell lines). DNA copy number and methylation data were obtained from 313 tumor tissues and mutation data from 945 tumor tissues in the TCGA dataset. There were TCGA sequencing data were normalized with quantile normalization[19]. The prognostic value of SET mRNA expression in BC was assessed according to relapse-free survival using the Kaplan–Meier plotter ( http://kmplot.com/analysis/ ), an online database that includes gene expression and clinical data. Our patient cohort and sample collection As the first dataset, 56 BC patients who underwent breast resection at the Kyushu University Beppu Hospital and its affiliated hospitals between 1990 and 1996 were enrolled in this study. As the second dataset, 55 BC patients who underwent breast resection at Kyushu University Beppu Hospital and its affiliated hospitals between 2016 and 2022 were enrolled in this study. Tissue samples from resected tumors for RNA extraction were immediately stored in RNAlater (Ambion, Austin, TX, USA), frozen in liquid nitrogen, and stored at − 80°C until RNA extraction. Tissue samples from resected tumors for DNA extraction were immediately frozen in liquid nitrogen and stored at − 80°C until DNA extraction. Corresponding non-cancerous breast tissues were also collected. Registration of clinicopathological characteristics and a prognostic follow-up were conducted after surgery. Written informed consent was obtained from each patient. The study design was approved by the institutional review boards and the ethics committee of the Kyushu University Institutional Review Board (approval number: 24121-00). RNA extraction Total RNA was extracted from frozen tissue samples and cell lines using Isogen (Nippon Gene, Tokyo, Japan), as described previously [20]. Reverse-transcription quantitative PCR (RT-qPCR) RT was performed using M-MLV reverse transcriptase (Invitrogen, Carlsbad, CA, USA) as described previously [21]. Quantitative polymerase chain reaction (qPCR) was performed using the LightCycler 480 SYBR Green I Master Mix (Roche, Basel, Switzerland) as described previously [22]. The primers used for SETBP1 were 5′-GCTTACAACTGCCCTGACCT-3′ (sense) and 5′-AAGTTTCCTCCTTCCAGGGC-3′ (antisense), and those used for 18s were 5′-AGCCACATCGCTCAGACAC-3′ (sense) and 5′-GCC CAATACG ACCAAATCC-3′ (antisense). The expression level of SETBP1 mRNA was normalized to that of 18s . Immunohistochemical analysis Immunohistochemical analysis of SETBP1 expression was performed using formalin-fixed paraffin-embedded surgical sections obtained from patients with ER-positive BC as described previously [23]. The primary rabbit polyclonal antibody against SETBP1 (bs-4944R; Bioss, Woburn, MA, USA) was used at a dilution of 1:1000. SET (ab1183; Abcam, Cambridge, UK) at a dilution of 1:500. Tumor histology was independently reviewed by two researchers, including an experienced pathologist (T.T.) Cell lines and cell culture The human BC cell lines MDA-MB-468, HCC-1954, MCF10A, SKBR-3 (all from ATCC), MDA-MB-361, ZR-75-1, MDA-MB-231 (all from KAC), MCF7, and MRK-nu1 (both from Japanese Collection of Research Bioresources Cell Bank), and the non-cancer HuMEC cells (Kurabo Industries Ltd.) were used in this study. The MDA-MB-468, HCC-1954, ZR-75-1, MDA-MB-231, and SKBR-3 cell lines were cultured in RPMI1640; the MCF7 and MDA-MB-361 cell lines were cultured in D-MEM, and MRK-nu1 and HuMEC cells were cultured in DM160, with all media supplemented with 10% fetal bovine serum (FBS). HuMEC cells were cultured using the MammaryLife Comp kit (Kurabo Industries Ltd., Osaka, Japan). MCF10A cells were cultured in MEGM (Lonza, Basel, Switzerland) supplemented with 100 ng/ml cholera toxin. All cells were cultured at 37°C in a humidified atmosphere containing 5% CO 2 . DNA extraction DNA was extracted from tumor and normal tissue samples and from cell lines using the AllPrep DNA/RNA Mini Kit (Qiagen, Hidden, Germany) according to the manufacturer’s instructions. DNA sequencing First, we amplified the extracted DNA, targeting a specific region of interest, using PCR. For amplification, we utilized the primers 5’-GTAAGATCCGAAGTGGTGGCA-3′ (sense) and 5′-TTACACGCAGTCCCAGTTCA-3′ (antisense). The PCR conditions were as follows: an initial denaturation at 94°C for 2 minutes, followed by 35 cycles of denaturation at 98°C for 10 seconds, and extension at 68°C for 1 minute. After amplification, the PCR products were checked on an agarose gel, and the band corresponding to the target was excised and purified from the gel. Direct sequencing of these purified PCR products was conducted by FASMAC, using the Sanger sequencing method, as described previously [24,25]. Gene set enrichment analysis (GSEA) The associations between SETBP1 expression and previously defined gene sets were analyzed by GSEA using BC expression profiles from the appropriate TCGA dataset. The biologically defined gene sets were obtained from the Molecular Signatures Database v5.2 ( http://software.broadinstitute.org/gsea/msigdb/index.jsp ). Gene Ontology (GO) analysis To determine the biological implications of low SETBP1 expression, GO analysis was conducted using DAVID Bioinformatics Resources 6.8 ( https://david.ncifcrf.gov/tools.jsp ). This tool provided a comprehensive set of functional annotations for the evaluated genes, allowing us to categorize them into corresponding biological processes, cellular components, and molecular functions. The significance of the enriched GO terms was determined using the modified Fisher’s exact test, with P < 0.05 considered significant. siRNA-mediated knockdown experiments Human SETBP1 -specific and negative control siRNAs were purchased from Thermo Fisher and Santa Cruz Biotechnology (Santa Cruz, CA, USA), respectively. The BC cell lines were transfected with siRNA oligonucleotides using Lipofectamine RNAiMAX (Thermo Fisher) according to the manufacturer's instructions. Western blot analysis Western blot analysis was performed as described previously [20]. The following antigen-specific antibodies were used: primary mouse polyclonal antibody against SETBP1 (bs-4944R; Bioss) at a dilution of 1:1000, primary rabbit polyclonal antibody against SET (ab1183; Abcam) at a dilution of 1:2000, a mixture of three specific rabbit monoclonal primary antibodies against phospho-cdk2 Tyr15, phospho-Histone H3 Ser10, and β-actin (ab136810; Abcam) at a dilution of 1:250, primary rabbit polyclonal antibody against p44/42 MAPK (k1/2) (#9102S; Cell Signaling Technology, Danvers, MA, USA) at a dilution of 1:1000, primary rabbit polyclonal antibody against phospho-p44/42 MAPK (k1/2) (#9101S; Cell Signaling Technology) at a dilution of 1:1000, primary mouse polyclonal antibody against PP2A C subunit (05-421; Millipore, Billerica, MA, USA) at a dilution of 1:1000, and primary mouse polyclonal antibody against β-actin (Santa Cruz Biotechnology) at a dilution of 1:10,000. Colony formation assay The colony formation assay was performed as described previously [26]. For siRNA-mediated knockdown of SETBP1 , cells were plated at a density of 500/well (MCF7) or 2 × 10 4 /well (MDA-MB-361) in 6-well plates and incubated at 37°C under 5% CO2. After 14 days, the colonies were stained using the Differential Quick Stain Kit (Sysmex) according to the manufacturer’s instructions. Visible colonies were photographed using the FUSION SOLO S. Colony counts were determined using ImageJ software (version 1.80, NIH, Bethesda, MD, USA). PP2A phosphatase activity assay The protein phosphatase activity in each cell lysate was determined by measuring the generation of free phosphatase from threonine phosphopeptide using the malachite green–phosphate complex assay, according to the instructions of the manufacturer (Upstate Biotechnology, Lake Placid, NY, USA). In brief, PP2A-specific reaction buffer (Millipore) containing 750 mM phosphopeptide substrate was added to cell lysates prepared in a low-detergent lysis buffer. After incubation for 10 min at 30°C, the malachite dye was added, and free phosphate was measured by optical density at 655 nm. Statistical analysis Associations between variables were analyzed using Student’s t - test, the Mann–Whitney U test, or Fisher’s exact test. The degree of linearity was assessed using Pearson’s correlation coefficient. Recurrence-free survival (RFS) was estimated using the Kaplan–Meier method, and survival curves were compared using the log-rank test. Data analyses were conducted using JMP Pro version 17 software (SAS Institute) and R software version 4.3.1 (The R Foundation). Two-sided P values < 0.05 were deemed statistically significant. Results Downregulation of SETBP1 in BC SETBP1 mRNA expression was significantly lower in BC tissues compared with normal breast tissues in the TCGA dataset ( P < 0.05) (Fig. 1 A). In 71.4% of cases, SETBP1 mRNA expression was lower in BC tissues than in normal breast tissues, according to RT-qPCR, in our BC cohort (Fig. 1 B). Regarding ER status, SETBP1 mRNA expression was lower in tumor tissues than in normal breast tissues in 61.3% of ER-positive cases and 94.4% of ER-negative cases (Fig. 1 C). ER-positive tumor tissues had significantly higher SETBP1 mRNA expression compared with ER-negative tumor tissues in the TCGA dataset (Fig. 1 D). Immunohistochemical analysis showed that SETBP1 was highly expressed in the normal epithelial cells of ER-positive BC (Fig. 1 E). These results indicate that SETBP1 is downregulated in BC tumor cells. RFS curves of BC patients according to SETBP1 mRNA expression We assessed the prognostic and clinical significance of SETBP1 mRNA expression in BC. First, we evaluated the RFS rates according to SETBP1 mRNA expression in patients with BC. In the univariate analysis, tumor size (≥ 2 cm) ( P < 0.05), menopause ( P < 0.05), and low SETBP1 mRNA expression ( P < 0.05) were significantly associated with a lower RFS rate (Table 1 ). The multivariate analysis indicated that tumor size (≥ 2 cm) ( P < 0.05), menopause ( P < 0.05), and low SETBP1 mRNA expression ( P < 0.05) were independent predictors of a poor prognosis in BC (Table 1 ). The RFS rate was significantly lower in the low than high SETBP1 mRNA expression group in the METABRIC and GSE19615 datasets ( P < 0.01 and P < 0.05, respectively; Fig. 2 A). Furthermore, the RFS rate was lower in the low than high SETBP1 mRNA expression group in ER-positive BC cases in the METABRIC and GSE1965 datasets ( P < 0.05 and P = 0.076, respectively; Fig. 2 B). In the ER-negative BC cases, there was no significant difference in the RFS rate between the high and low SETBP1 mRNA expression groups in the METABRIC and GSE1965 datasets ( P = 0.46 and P = 0.14, respectively; Fig. 2 B). Table 1 Univariate and multivariate analyses of the clinicopathological factors affecting disease-free survival in the METABRIC dataset Variable HR Univariate (95% CI) P -value HR Multivariate (95% CI) P -value Menopause (Post/Pre) 1.35 1.17–1.56 < 0.05 1.37 1.17–1.58 < 0.05 ER status (+/-) 1.01 0.88–1.16 0.88 PgR status (+/-) 0.96 0.85–1.07 0.45 HER2 status (+/-) 1.07 0.88–1.03 0.48 Tumor size (≥ 2/<2 cm) 1.19 1.06–1.33 < 0.05 1.17 1.04–1.31 < 0.05 Lymph node metastasis (+/-) 1.10 0.97–1.23 0.18 SETBP1 expression (low/high) 1.25 1.11–1.40 < 0.05 1.26 1.10–1.45 < 0.05 ER, Estrogen Receptor; PgR, Progesterone Receptor; CI, confidential interval; HR, hazard ratio. Table 2 : Correlations between SETBP1 mRNA expression in tumor tissues and clinicopathological factors in breast cancer (A) Our cohort Variable TN (n =15) Number (%) P -value Age (y) Mean ± SD 56.5 ± 1.5 55.3 ± 2.7 0.66 Menopause Pre 5 (14.3) 5 (41.7) 0.06 Post 30 (85.7) 7 (58.3) Tumor size (cm) <2 24 (64.9) 7 (58.3) 0.47 ≥2 13 (35.1) 5 (41.7) ER status + 20 (51.3) 12 (92.3) <0.01 - 19 (48.7) 1 ( 7.7) PgR status + 16 (41.0) 12 (92.3) <0.01 - 23 (59.0) 1 ( 7.7) Lymphatic invasion 0 24 (64.9) 4 (30.8) <0.05 1–3 13 (35.1) 9 (69.2) Vascular invasion 0 33 (89.2) 11 (84.6) 0.96 1–3 4 (10.8) 2 (13.4) Lymph node metastasis + 21 (51.2) 9 (60.0) 0.33 - 20 (48.8) 6 (40.0) Distant metastasis + 2 (4.9) 0 (0) 0.53 - 39 (95.1) 15 (100) (B) METABRIC dataset Variable Low expression (n = 980) High expression (n = 979) P -value Age (y) Mean ± SD 60.0 ± 0.4 62.1 ± 0.4 <0.05 Tumor size (cm) <2 385 456 <0.01 ≥2 586 509 ER status + 621 871 <0.01 - 359 108 PgR status + 386 642 <0.01 - 594 337 HER2 status + 180 67 <0.01 - 800 912 Histological grade 1, 2 322 608 <0.01 3 632 316 Menopause Pre 233 190 <0.05 Post 747 789 Lymph node metastasis + 505 398 <0.01 - 442 541 Stage 1 336 407 <0.01 2 228 200 3 133 79 ER, Estrogen Receptor; PgR, Progesterone Receptor; SD, standard deviation These results suggest that low SETBP1 expression indicates a poor prognosis in patients with ER-positive BC. Clinicopathologic significance of SETBP1 mRNA expression in BC We analyzed the associations between SETBP1 mRNA expression and clinicopathologic factors in BC patients at our hospital (Table 2 A). We divided the patients into two groups: the T N group ( SETBP1 mRNA expression was higher in BC than normal breast tissues). We found higher frequencies of ER-negative and PgR-negative statuses, but a lower frequency of lymphatic invasion, in the T N group. In the METABRIC dataset, low SETBP1 mRNA expression was associated with an older age, large tumor size, ER-negative, PgR-negative, and HER2-negative statuses, high histological grade, menopause, lymph node metastasis, and TNM stage (Table 2 B). These results suggest that low SETBP1 mRNA expression is positively associated with malignant phenotypes. Pathway analysis of SETBP1 in ER-positive BC To explore oncogenic pathways associated with SETBP1 expression in ER-positive BC, we performed GSEA using TCGA dataset. SETBP1 expression was negatively correlated with the expression of E2F, MYC, and G2M checkpoint target geneset in ER-positive BC (Fig. 3 A). E2F, MYC, and G2M checkpoint-related genes play important roles in various biological processes, including cell proliferation and cell cycle [27] [28] [29]. Next, we performed GO analysis and observed downregulation of many genes involved in cell cycle-related and MAPK-related pathways (Fig. 3 B). The results of the GSEA and GO analyses motivated us to investigate whether SETBP1 regulates tumor proliferation, cell cycle progression, and activation of the MAPK pathway in ER-positive BC. Increased proliferation of ER-positive BC cells in vitro by SETBP1 knockdown We performed a colony formation assay using a knockdown system in two ER-positive BC cell lines, MCF7 and MDA-MB-361, to clarify the relationship between SETBP1 and proliferative capacity. We found that SETBP1 knockdown significantly reduced the proliferation of MCF7 and MDA-MB-361 cells (Fig. 3 C, 3 D). Activation of cell cycle progression by SETBP1 knockdown We evaluated the expression of histone H3 pSer10 (marker of cell cycle arrest at G2/M [30]) and CDK2 pTyr15 (marker of cell cycle arrest at G1/S [31]) in SETBP1- knockdown ER-positive BC cells (Fig. 4 A). The expression of both markers was suppressed, suggesting that SETBP1 knockdown promotes cell cycle progression. Suppressed PP2A activity and increased MAPK phosphorylation by SETBP1 knockdown SETBP1 has been reported to form a complex with SET and PP2A [32]. PP2A is considered a tumor suppressor protein since its inactivation is mediated primarily by increased expression of its endogenous inhibitors, such as SET and cellular inhibitor of phosphatase 2A [33]. However, it is unknown if the expression of SETBP1, which binds to and functions with SET, affects the activation of PP2A. Thus, we performed a PP2A activity assay using SETBP1 -knockdown cells. PP2A activity was significantly suppressed in SETBP1 -knockdown ER-positive BC cells compared with control siRNA ER-positive BC cells (Fig. 4 B). Activation of PP2A has been reported to inhibit phosphorylation of MAPK [34]. Therefore, we hypothesized that low SETBP1 expression may activate the MAPK signaling pathway by inactivating PP2A activity in ER-positive BC cells. As expected, the ER-positive BC cell lines MCF7 and MDA-MB-361 with SETBP1 knockdown showed increased phosphorylation levels of MAPK compared with control cells(Fig. 4 A). These results suggest that SETBP1 knockdown facilitates cell proliferation possibly via inactivation of PP2A, followed by activation of MAPK signaling in ER-positive BC cells. Potential factors responsible for the downregulated SETBP1 expression Since DNA methylation, DNA copy number alterations, SNPs, and gene mutations are well-known factors that regulate gene expression [7,35,36], we investigated the relationship between each of these factors and SETBP1 expression in BC. To do this, the SETBP1 mRNA level was divided into high and low groups based on the median value. First, we evaluated the relationship between the SETBP1 promoter methylation rate and mRNA expression. The promoter methylation rate was significantly higher in the low than high SETBP1 mRNA expression groups (68.1% vs. 33.3%, P < 0.05, Fig. 5 A). The SETBP1 promoter methylation rate was negatively correlated with SETBP1 mRNA expression in the TCGA dataset (R = − 0.50, P < 0.01, Fig. 5 A). When comparing ER-positive and ER-negative tumors from the TCGA dataset, the SETBP1 promoter methylation rate was significantly lower in ER-positive BC (Supplementary Fig. 1A). Second, the relationship between the SETBP1 DNA copy number status and gene expression level was assessed. The rate of SETBP1 deletion was significantly higher in the low than high SETBP1 mRNA expression groups (41.4% vs. 11.9%, P < 0.05, Fig. 5 B). Compared with the diploid cases, cases with SETBP1 deletion had lower SETBP1 mRNA expression ( P < 0.05). Regarding ER status, the ER-positive BC cases had a lower rate of SETBP1 deletion (Supplementary Fig. 1B). Next, we examined the relationship between the SETBP1 rs6507583 SNP and SETBP1 mRNA expression in 55 ER-positive BC cases from our BC cohort. rs6507583 was detected in only one case, and this case also showed the lowest SETBP1 expression level (Fig. 5 C). Next, we investigated the rs6507583 SNP in human mammary cell lines and found that 2 of the 10 cell lines possessed rs6507583. The SETBP1 expression level was lower in the two cell lines with rs6507583 (MRK-nu1 and SKBR-3 cells) than in the cell lines without this SNP (Fig. 5 D). Interestingly, SKBR-3 cells, possessing rs6507583, had low SETBP1 mRNA expression with a low promoter methylation rate, whereas MDA-MB-231 cells, which lack rs6507583, had low SETBP1 mRNA expression with a high promoter methylation rate. This suggests that the rs6507583 SNP and promoter methylation rate strongly contribute to the low SETBP1 expression (Fig. 5 E). Finally, the mutation rate in SETBP1 was examined. The frequency of mutations in SETBP1 was only 1.1% in the TCGA dataset in all BC cases (Fig. 5 F). The ER-positive and ER-negative cases had a comparable rate of mutations (Supplementary Fig. 1C). These results suggest that the low expression of SETBP1 may be induced by the high promoter methylation rate, genomic deletions, and the rs6507583 SNP in BC. Discussion In this study, we found that low SETBP1 expression contributed to the proliferation of ER-positive BC cells possibly by inducing MAPK phosphorylation. Furthermore, low SETBP1 expression predicted a poor prognosis in ER-positive BC patients. To the best of our knowledge, this is the first study to provide evidence that SETBP1 has a tumor suppressive role in ER-positive BC. Our hospital cohort and the METABRIC dataset demonstrated that SETBP1 expression was negatively associated with several malignant phenotypes, including tumor size, lymph node metastasis, histological grade, and TNM stage. Additionally, low SETBP1 expression was associated with poor prognosis in ER-positive BC. Our biological analysis indicated that low SETBP1 expression accelerated cell proliferation, partly via cell cycle progression, in ER-positive BC. Furthermore, decreased SETBP1 mRNA expression was attributed to DNA copy number deletion, increased promoter methylation, and the SNP rs6507583. These findings provide clinical and biological evidence that SETBP1 plays a tumor-suppressive role in ER-positive BC. Interestingly, low SETBP1 expression in triple-negative BC has been reported to be associated with good prognosis [16]. Our study also showed that low SETBP1 expression was not associated with a poor prognosis in ER-negative BC. These findings suggest SETBP1 may have different functions in BC depending on ER status. SETBP1 mRNA expression was significantly higher in ER-positive BC than in ER-negative BC. We found that SETBP1 mRNA expression was decreased due to DNA copy number deletion, increased promoter methylation rate, and the rs6507583 SNP. ER-negative BC exhibited multiple factors contributing to the lower SETBP1 expression compared with ER-positive BC (Supplementary Fig. 1A, 1B). Our in vitro analysis revealed that SETBP1 knockdown inhibited PP2A activity and increased MAPK phosphorylation, thereby enhancing cell cycle progression and proliferation in ER-positive BC cells. However, previous studies reported that SETBP1 overexpression leads to formation of the SETBP1/SET/PP2A complex, resulting in PP2A inhibition and subsequent cell proliferation in colorectal cancer, ovarian cancer, and acute myeloid leukemia [13,14,37]. These contradictory findings suggest that the role of SETBP1 in tumor progression varies depending on tissue type. Further research is needed to elucidate the tissue-dependent mechanisms of SETBP1 function. ER-positive BC is treated effectively with endocrine therapies (ET) [37]. Low expression of SETBP1 may lead to activation of the MAPK pathway downstream of the ER [38], potentially diminishing the efficacy of ET. ER-positive BC cases with low SETBP1 expression may benefit from combining ET and MAPK inhibitors [39]. In summary, we demonstrated that SETBP1 inhibits tumor progression and is a prognostic biomarker in ER-positive BC. Declarations Acknowledgments The authors would like to thank M. Kasagi, S. Sakuma, T. Fukuda, N. Mishima, T. Kawano, and M. Utou for their technical assistance. This work was supported in part by the following grants and foundations: Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Science Research (grant numbers: 19K09176, 19H03715, 20H05039, 20K08930, 20K17556, 21K07179, 22K02903, 22K09006, 23K06765, 23K08074, 24K11766, 24K10384, and 24K02523); OITA Cancer Research Foundation; AMED (grant numbers: 23ck0106825h001, 23ck0106800h001, 22ama221501h0001, 21ck0106690s0201, 20cm0106475h0001, 20ck0106547h0001, and 20ck0106541h0001); Takeda Science Foundation; and The Princess Takamatsu Cancer Research Fund. Disclosure Statement One of the co-authors of this manuscript, Takaaki Masuda, serves as the editor of Breast Cancer . To maintain a fair and unbiased review process, the editorial office has ensured that Takaaki Masuda was not involved in the peer review or decision-making process for this manuscript. 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Identification of ARL4C as a Peritoneal Dissemination-Associated Gene and Its Clinical Significance in Gastric Cancer. Ann Surg Oncol. 2018;25:745–53. Nambara S, Masuda T, Nishio M, Kuramitsu S, Tobo T, Ogawa Y, et al. Antitumor effects of the antiparasitic agent ivermectin via inhibition of Yes-associated protein 1 expression in gastric cancer. Oncotarget. 2017;8:107666–77. Shimizu D, Masuda T, Sato K, Tsuruda Y, Otsu H, Kuroda Y, et al. CRMP5-associated GTPase (CRAG) Is a candidate driver gene for colorectal cancer carcinogenesis. Anticancer Res. 2019;39:99–106. Kobayashi-Ishihara M, Terahara K, Martinez JP, Yamagishi M, Iwabuchi R, Brander C, et al. HIV LTR-Driven Antisense RNA by Itself Has Regulatory Function and May Curtail Virus Reactivation From Latency. Front Microbiol. 2018;9:1066. Hashimoto M, Masuda T, Nakano Y, Tobo T, Saito H, Koike K, et al. Tumor suppressive role of the epigenetic master regulator BRD3 in colorectal cancer. Cancer Sci [Internet]. 2024; Available from: http://dx.doi.org/10.1111/cas.16129 Koike K, Masuda T, Sato K, Fujii A, Wakiyama H, Tobo T, et al. GET4 is a novel driver gene in colorectal cancer that regulates the localization of BAG6, a nucleocytoplasmic shuttling protein. Cancer Sci. 2022;113:156–69. Johnson J, Thijssen B, McDermott U, Garnett M, Wessels LFA, Bernards R. Targeting the RB-E2F pathway in breast cancer. Oncogene. 2016;35:4829–35. Prall OW, Rogan EM, Musgrove EA, Watts CK, Sutherland RL. c-Myc or cyclin D1 mimics estrogen effects on cyclin E-Cdk2 activation and cell cycle reentry. Mol Cell Biol. 1998;18:4499–508. Stark GR, Taylor WR. Analyzing the G2/M checkpoint. Methods Mol Biol. 2004;280:51–82. Hans F, Dimitrov S. Histone H3 phosphorylation and cell division. Oncogene. 2001;20:3021–7. Fagundes R, Teixeira LK. Cyclin E/CDK2: DNA Replication, Replication Stress and Genomic Instability. Front Cell Dev Biol. 2021;9:774845. Oaks J, Ogretmen B. Regulation of PP2A by Sphingolipid Metabolism and Signaling. Front Oncol. 2014;4:388. Kauko O, Westermarck J. Non-genomic mechanisms of protein phosphatase 2A (PP2A) regulation in cancer. Int J Biochem Cell Biol. 2018;96:157–64. Zheng H-Y, Shen F-J, Tong Y-Q, Li Y. PP2A Inhibits Cervical Cancer Cell Migration by Dephosphorylation of p-JNK, p-p38 and the p-ERK/MAPK Signaling Pathway. Curr Med Sci. 2018;38:115–23. Ried T, Meijer GA, Harrison DJ, Grech G, Franch-Expósito S, Briffa R, et al. The landscape of genomic copy number alterations in colorectal cancer and their consequences on gene expression levels and disease outcome. Mol Aspects Med. 2019;69:48–61. Jovanovic J, Rønneberg JA, Tost J, Kristensen V. The epigenetics of breast cancer. Mol Oncol. 2010;4:242–54. Cardoso F, Harbeck N, Fallowfield L, Kyriakides S, Senkus E, ESMO Guidelines Working Group. Locally recurrent or metastatic breast cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol. 2012;23 Suppl 7:vii11-9. Arpino G, Wiechmann L, Osborne CK, Schiff R. Crosstalk between the estrogen receptor and the HER tyrosine kinase receptor family: molecular mechanism and clinical implications for endocrine therapy resistance. Endocr Rev. 2008;29:217–33. Hotokezaka H, Sakai E, Kanaoka K, Saito K, Matsuo K-I, Kitaura H, et al. U0126 and PD98059, specific inhibitors of MEK, accelerate differentiation of RAW264.7 cells into osteoclast-like cells. J Biol Chem. 2002;277:47366–72. Supplementary Files SupFig1.tif Supplementary Figure 1. Comparison of factors affecting low SETBP 1 expression according to ER status. A. Comparison of SETBP1 promoter methylation rates in the TCGA dataset according to ER status. B. Comparison of SETBP1 DNA copy number abnormalities in the TCGA dataset according to ER status. C. Frequency of SETBP1 mutations among BC cases according to ER status in the TCGA dataset. Cite Share Download PDF Status: Published Journal Publication published 20 Feb, 2025 Read the published version in Breast Cancer → Version 1 posted Editorial decision: Minor Revision 01 Dec, 2024 Reviewers agreed at journal 10 Nov, 2024 Reviewers invited by journal 08 Nov, 2024 Editor assigned by journal 21 Oct, 2024 First submitted to journal 20 Oct, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5269021","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":375715683,"identity":"98b8da05-2ad9-457a-8711-68544621eb6a","order_by":0,"name":"Yuki Ando","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBACCQhlw8PP3gCkDSyI1pImI9lzAKRFgmgth20MZiQg8fEByRm5xx78YEjjMZB8fnXDjwIJBv727gS8WqQl8tINe4B+MZfOKbvZA3SYxJmzG/BqkZPIMZPgAdpiOTsn7QYPUIuBRC5hLZJ/GA7zGNw8k3bzDzFapIFapHlAWm6wH7tNlC2SPe/SjWUM0ngke3LYbssYSPAQ9IvE8dxjD99U2Njzsx9/dvPNHxs5/vZe/FoYGHjYgDEIZkBIAsphWsCA/QERqkfBKBgFo2AkAgCP7kA21U8GsQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0006-2561-8028","institution":"Kyushu University Beppu Hospital: Kyushu Daigaku Byoin Beppu Byoin","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yuki","middleName":"","lastName":"Ando","suffix":""},{"id":375715684,"identity":"ef164fe7-42c4-49e5-8f37-7eb1794b9151","order_by":1,"name":"Takaaki Masuda","email":"","orcid":"","institution":"Kochi University: Kochi Daigaku","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Takaaki","middleName":"","lastName":"Masuda","suffix":""},{"id":375715685,"identity":"dceb0241-aeb4-4633-a942-b96f13399b64","order_by":2,"name":"Naoki Hayashi","email":"","orcid":"","institution":"Kyushu University Beppu Hospital: Kyushu Daigaku Byoin Beppu Byoin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Naoki","middleName":"","lastName":"Hayashi","suffix":""},{"id":375715686,"identity":"d60249ab-b950-47f2-9f8d-68c87506e83b","order_by":3,"name":"Keisuke Kosai","email":"","orcid":"","institution":"Kyushu University Beppu Hospital: Kyushu Daigaku Byoin Beppu Byoin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Keisuke","middleName":"","lastName":"Kosai","suffix":""},{"id":375715687,"identity":"61d58f49-fbb3-48ac-ae65-e66b98e4ca82","order_by":4,"name":"Shohei Shibuta","email":"","orcid":"","institution":"Kyushu University Beppu Hospital: Kyushu Daigaku Byoin Beppu Byoin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shohei","middleName":"","lastName":"Shibuta","suffix":""},{"id":375715688,"identity":"48a83467-0a2e-498d-bf65-fa5c2e8fbf2e","order_by":5,"name":"Yuya Ono","email":"","orcid":"","institution":"Kyushu University Beppu Hospital: Kyushu Daigaku Byoin Beppu Byoin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuya","middleName":"","lastName":"Ono","suffix":""},{"id":375715689,"identity":"c2b6b963-9618-48d0-80fa-94af1c3f83e7","order_by":6,"name":"Hajime Ohtsu","email":"","orcid":"","institution":"Kyushu University Beppu Hospital: Kyushu Daigaku Byoin Beppu Byoin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hajime","middleName":"","lastName":"Ohtsu","suffix":""},{"id":375715690,"identity":"e65986fa-384a-4a5f-8d3a-1c67da884e81","order_by":7,"name":"Yuichi Hisamatsu","email":"","orcid":"","institution":"Kyushu University Faculty of Medicine Graduate School of Medical Science: Kyushu Daigaku Igakubu Daigakuin Igakukei Gakufu Daigakuin Igaku Kenkyuin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yuichi","middleName":"","lastName":"Hisamatsu","suffix":""},{"id":375715691,"identity":"4532a9b0-e29f-455c-8002-a32cc9359fb6","order_by":8,"name":"Tomoharu Yoshizumi","email":"","orcid":"","institution":"Kyushu University Faculty of Medicine Graduate School of Medical Science: Kyushu Daigaku Igakubu Daigakuin Igakukei Gakufu Daigakuin Igaku Kenkyuin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tomoharu","middleName":"","lastName":"Yoshizumi","suffix":""},{"id":375715692,"identity":"395eb80b-1d3b-45c1-9a34-38c34f6e1777","order_by":9,"name":"Koshi Mimori","email":"","orcid":"","institution":"Kyushu University Beppu Hospital: Kyushu Daigaku Byoin Beppu Byoin","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Koshi","middleName":"","lastName":"Mimori","suffix":""}],"badges":[],"createdAt":"2024-10-15 13:18:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5269021/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5269021/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12282-025-01667-w","type":"published","date":"2025-02-20T15:57:21+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":71055726,"identity":"bede02ed-1e68-42f1-87c0-1bcc9a6daa71","added_by":"auto","created_at":"2024-12-10 16:10:56","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":470189,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eSETBP1\u003c/em\u003e expression in breast cancer tissues. A. \u003cem\u003eSETBP1 \u003c/em\u003emRNA expression in tumor tissues (T) and non-cancerous tissues (N) from a TCGA dataset. B. Waterfall plot showing the ratio of T to N in all BC cases. C. Waterfall plot showing the ratio of T to N according to ER status. Left: ER-positive BC. Right: ER-negative BC. D. \u003cem\u003eSETBP1 \u003c/em\u003emRNA expression in T and N in our BC cohort and in tumor tissues according to ER status in the TCGA data. E. Immunohistochemical staining of SETBP1 in T and N. N, normal tissue; T, tumor tissue.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-5269021/v1/37762f5b0f20f6127547d041.png"},{"id":71055725,"identity":"36aee4ff-3038-4769-b253-72cd622e5cac","added_by":"auto","created_at":"2024-12-10 16:10:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":197253,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier analysis of RFS in BC patients from the METABRIC and\u003c/p\u003e\n\u003cp\u003eGSE19615 datasets. A. All BC cases in the METABRIC (left) and GSE19615 (right) datasets. B. ER-positive (top left) and -negative (top right) BC cases in METABRIC and ER-positive (bottom left) and -negative (bottom right) BC cases in GSE19615.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-5269021/v1/80f6cd56131961fb2138734a.png"},{"id":71054290,"identity":"cdce0415-1d40-44cf-951e-1234857f3047","added_by":"auto","created_at":"2024-12-10 16:02:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":672907,"visible":true,"origin":"","legend":"\u003cp\u003eAssociation of low expression of \u003cem\u003eSETBP1\u003c/em\u003e with cell growth in ER-positive breast cancer. A. Gene set enrichment analysis using TCGA dataset. B. GO analysis using the TCGA dataset. C.\u003cem\u003e SETBP1\u003c/em\u003e mRNA expression using RT-qPCR and SETBP1 protein expression using western blot analysis in \u003cem\u003eSETBP1-\u003c/em\u003eknockdown and control cells. D. Colony formation assays using \u003cem\u003eSETBP1\u003c/em\u003e-knockdown MCF7 and MDA-MB-361 cells. *\u003cem\u003eP\u003c/em\u003e\u0026lt;0.05\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-5269021/v1/33c1d2171d961cfb5f5b0b10.png"},{"id":71054289,"identity":"cf5c89e5-cabf-483d-8309-a441e078fe43","added_by":"auto","created_at":"2024-12-10 16:02:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":285370,"visible":true,"origin":"","legend":"\u003cp\u003eIncreased phosphorylation of MAPK and PP2A activity by\u003cem\u003e SETBP1\u003c/em\u003e knockdown in ER-positive BC cells. A. Expression levels of SET, PP2A, MAPK, phosphorylated MAPK, H3pSer10, and CDK2pTyr15 in \u003cem\u003eSETBP1-\u003c/em\u003eknockdown and control cells (negative control). B. PP2A activity of \u003cem\u003eSETBP1\u003c/em\u003e-knockdown and negative control cells.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-5269021/v1/717bc5472b50ad4cc364c40a.png"},{"id":71054292,"identity":"51fda75f-2aca-4b4c-b455-32c6809a426e","added_by":"auto","created_at":"2024-12-10 16:02:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":284871,"visible":true,"origin":"","legend":"\u003cp\u003ePotential factors responsible for the downregulation of \u003cem\u003eSETBP1 \u003c/em\u003eexpression\u003cem\u003e. \u003c/em\u003eA. Left: relationship between \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression and \u003cem\u003eSETBP1\u003c/em\u003e promoter methylation rate in the TCGA dataset. Right: correlation between \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression and \u003cem\u003eSETBP1\u003c/em\u003e promoter methylation rate in the TCGA dataset.\u003cem\u003e R\u003c/em\u003e is the Pearson correlation coefficient. B. Left: relationship between \u003cem\u003eSETBP1\u003c/em\u003emRNA expression and \u003cem\u003eSETBP1\u003c/em\u003e DNA copy number in the TCGA dataset. Right: relationship between \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression and \u003cem\u003eSETBP1\u003c/em\u003e DNA copy number in the TCGA dataset. C. Relationship between the rs6507583 SNP and \u003cem\u003eSETBP1\u003c/em\u003emRNA expression in our BC cohort. D. Relationship between the rs6507583 SNP and \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression in BC cell lines. E. Relationship between the \u003cem\u003eSETBP1\u003c/em\u003epromoter methylation rate and \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression in BC cell lines. F. Frequency of \u003cem\u003eSETBP1\u003c/em\u003e mutations among all BC cases in the TCGA dataset.\u003c/p\u003e","description":"","filename":"Fig5.png","url":"https://assets-eu.researchsquare.com/files/rs-5269021/v1/93ad4720991f18376826f81b.png"},{"id":77052743,"identity":"8f12d79f-f418-4ee7-8266-d340b90b1266","added_by":"auto","created_at":"2025-02-24 16:24:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2883792,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5269021/v1/b82a42b8-d006-4f2c-ac2c-60435ca4e930.pdf"},{"id":71054293,"identity":"92b68552-a244-4a5a-b018-5dc4c6a0f981","added_by":"auto","created_at":"2024-12-10 16:02:57","extension":"tif","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":26133728,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplementary Figure 1\u003c/strong\u003e. Comparison of factors affecting low \u003cem\u003eSETBP\u003c/em\u003e1 expression according to ER status. A. Comparison of \u003cem\u003eSETBP1 \u003c/em\u003epromoter methylation rates in the TCGA dataset according to ER status. B. Comparison of \u003cem\u003eSETBP1\u003c/em\u003e DNA copy number abnormalities in the TCGA dataset according to ER status. C. Frequency of \u003cem\u003eSETBP1\u003c/em\u003emutations among BC cases according to ER status in the TCGA dataset.\u003c/p\u003e","description":"","filename":"SupFig1.tif","url":"https://assets-eu.researchsquare.com/files/rs-5269021/v1/11293bffdd155877f2976530.tif"}],"financialInterests":"","formattedTitle":"SET binding protein 1 (SETBP1) suppresses cell proliferation in estrogen receptor-positive breast cancer.","fulltext":[{"header":"Background","content":"\u003cp\u003eBreast cancer (BC) is the most common cancer and the leading cause of cancer-related deaths among women worldwide including Japan [1\u0026ndash;3], with approximately 70% of cases being estrogen receptor (ER) positive [4]. BC readily metastasizes, which limits the efficacy of further treatment [5]. A lack of understanding of the mechanism of ER-positive BC progression has hampered the development of efficient strategies to control disease progression and improve clinical outcomes. Thus, identifying driver genes contributing to the progression of ER-positive BC is of immense importance.\u003c/p\u003e \u003cp\u003eSingle nucleotide polymorphism (SNP)(rs6507583) at the promoter of SET binding protein 1 (\u003cem\u003eSETBP1\u003c/em\u003e) was implicated in breast carcinogenesis by BC genome-wide association analysis, and the association was stronger in ER-positive BC [6]. Importantly, it was reported that SNPs regulate the expression of target genes that affect tumorigenesis and the development of various cancers [7,8]. Altered \u003cem\u003eSETBP1\u003c/em\u003e expression by SNPs may contribute to the progression of ER-positive BC.\u003c/p\u003e \u003cp\u003e \u003cem\u003eSETBP1\u003c/em\u003e, discovered in 2001 [9], is located at chromosome 18q21.1. \u003cem\u003eSETBP1\u003c/em\u003e encodes a large protein of 1542 amino acids localized in the cell nucleus and cytoplasm [10,11]. SETBP1 was initially found to interact with SE translation (SET\u003cem\u003e)\u003c/em\u003e and with a small protein inhibitor of the tumor suppressor protein phosphatase 2A (PP2A) [12].\u003c/p\u003e \u003cp\u003eSETBP1 expression has been investigated in various diseases, including malignancies such as non-small cell lung cancer [11], hematologic malignancies [13], colorectal cancers [14], ovarian cancers [15], triple-negative BC [16], and gastric cancers [17,18], suggesting that SETBP1 functions either as an oncogene or a tumor suppressor depending on the cancer. However, the clinical and biological significance of SETBP1 in the development of ER-positive BC remains unknown.\u003c/p\u003e \u003cp\u003eHere, we analyzed the expression of SETBP1 in human ER-positive BC and determined the relationship between SETBP1 expression and survival in ER-positive BC patients. Furthermore, we sought to determine the biological role of SETBP1 in the progression of ER-positive BC.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePublic datasets\u003c/h2\u003e \u003cp\u003eData from The Cancer Genome Atlas database (TCGA) via Broad Institute\u0026rsquo;s Firehose (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://gdac.broadinstitute.org/\u003c/span\u003e\u003cspan address=\"http://gdac.broadinstitute.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), Cancer Cell Line Encyclopedia (CCLE) via the Cancer Dependency Portal (DepMap) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://depmap.org/portal/ccle/\u003c/span\u003e\u003cspan address=\"https://depmap.org/portal/ccle/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), the Molecular Taxonomy of Breast Cancer International Consortium dataset (METABRIC) via cBioportal (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.cbioportal.org/study/summary?id=brca_metabric\u003c/span\u003e\u003cspan address=\"https://www.cbioportal.org/study/summary?id=brca_metabric\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), and GSE19615 via PrognoScan analysis (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dna00.bio.kyutech.ac.jp/PrognoScan/\u003c/span\u003e\u003cspan address=\"http://dna00.bio.kyutech.ac.jp/PrognoScan/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) were analyzed in this study. We obtained mRNA expression data from the TCGA dataset (1093 tumor tissues, 112 non-cancerous tissues), METABRIC dataset (1959 tumor tissue), GSE19615 dataset (115 tumor tissue), and CCLE dataset (47 cell lines). DNA copy number and methylation data were obtained from 313 tumor tissues and mutation data from 945 tumor tissues in the TCGA dataset. There were TCGA sequencing data were normalized with quantile normalization[19].\u003c/p\u003e \u003cp\u003eThe prognostic value of \u003cem\u003eSET\u003c/em\u003e mRNA expression in BC was assessed according to relapse-free survival using the Kaplan\u0026ndash;Meier plotter (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://kmplot.com/analysis/\u003c/span\u003e\u003cspan address=\"http://kmplot.com/analysis/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), an online database that includes gene expression and clinical data.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOur patient cohort and sample collection\u003c/h3\u003e\n\u003cp\u003eAs the first dataset, 56 BC patients who underwent breast resection at the Kyushu University Beppu Hospital and its affiliated hospitals between 1990 and 1996 were enrolled in this study. As the second dataset, 55 BC patients who underwent breast resection at Kyushu University Beppu Hospital and its affiliated hospitals between 2016 and 2022 were enrolled in this study. Tissue samples from resected tumors for RNA extraction were immediately stored in RNAlater (Ambion, Austin, TX, USA), frozen in liquid nitrogen, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until RNA extraction. Tissue samples from resected tumors for DNA extraction were immediately frozen in liquid nitrogen and stored at \u0026minus;\u0026thinsp;80\u0026deg;C until DNA extraction. Corresponding non-cancerous breast tissues were also collected. Registration of clinicopathological characteristics and a prognostic follow-up were conducted after surgery. Written informed consent was obtained from each patient. The study design was approved by the institutional review boards and the ethics committee of the Kyushu University Institutional Review Board (approval number: 24121-00).\u003c/p\u003e\n\u003ch3\u003eRNA extraction\u003c/h3\u003e\n\u003cp\u003eTotal RNA was extracted from frozen tissue samples and cell lines using Isogen (Nippon Gene, Tokyo, Japan), as described previously [20].\u003c/p\u003e\n\u003ch3\u003eReverse-transcription quantitative PCR (RT-qPCR)\u003c/h3\u003e\n\u003cp\u003eRT was performed using M-MLV reverse transcriptase (Invitrogen, Carlsbad, CA, USA) as described previously [21]. Quantitative polymerase chain reaction (qPCR) was performed using the LightCycler 480 SYBR Green I Master Mix (Roche, Basel, Switzerland) as described previously [22]. The primers used for \u003cem\u003eSETBP1\u003c/em\u003e were 5\u0026prime;-GCTTACAACTGCCCTGACCT-3\u0026prime; (sense) and 5\u0026prime;-AAGTTTCCTCCTTCCAGGGC-3\u0026prime; (antisense), and those used for \u003cem\u003e18s\u003c/em\u003e were 5\u0026prime;-AGCCACATCGCTCAGACAC-3\u0026prime; (sense) and 5\u0026prime;-GCC CAATACG ACCAAATCC-3\u0026prime; (antisense). The expression level of \u003cem\u003eSETBP1\u003c/em\u003e mRNA was normalized to that of \u003cem\u003e18s\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003eImmunohistochemical analysis\u003c/h3\u003e\n\u003cp\u003eImmunohistochemical analysis of \u003cem\u003eSETBP1\u003c/em\u003e expression was performed using formalin-fixed paraffin-embedded surgical sections obtained from patients with ER-positive BC as described previously [23]. The primary rabbit polyclonal antibody against SETBP1 (bs-4944R; Bioss, Woburn, MA, USA) was used at a dilution of 1:1000. SET (ab1183; Abcam, Cambridge, UK) at a dilution of 1:500. Tumor histology was independently reviewed by two researchers, including an experienced pathologist (T.T.)\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCell lines and cell culture\u003c/h2\u003e \u003cp\u003eThe human BC cell lines MDA-MB-468, HCC-1954, MCF10A, SKBR-3 (all from ATCC), MDA-MB-361, ZR-75-1, MDA-MB-231 (all from KAC), MCF7, and MRK-nu1 (both from Japanese Collection of Research Bioresources Cell Bank), and the non-cancer HuMEC cells (Kurabo Industries Ltd.) were used in this study. The MDA-MB-468, HCC-1954, ZR-75-1, MDA-MB-231, and SKBR-3 cell lines were cultured in RPMI1640; the MCF7 and MDA-MB-361 cell lines were cultured in D-MEM, and MRK-nu1 and HuMEC cells were cultured in DM160, with all media supplemented with 10% fetal bovine serum (FBS). HuMEC cells were cultured using the MammaryLife Comp kit (Kurabo Industries Ltd., Osaka, Japan). MCF10A cells were cultured in MEGM (Lonza, Basel, Switzerland) supplemented with 100 ng/ml cholera toxin. All cells were cultured at 37\u0026deg;C in a humidified atmosphere containing 5% CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDNA extraction\u003c/h3\u003e\n\u003cp\u003eDNA was extracted from tumor and normal tissue samples and from cell lines using the AllPrep DNA/RNA Mini Kit (Qiagen, Hidden, Germany) according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003ch3\u003eDNA sequencing\u003c/h3\u003e\n\u003cp\u003eFirst, we amplified the extracted DNA, targeting a specific region of interest, using PCR. For amplification, we utilized the primers 5\u0026rsquo;-GTAAGATCCGAAGTGGTGGCA-3\u0026prime; (sense) and 5\u0026prime;-TTACACGCAGTCCCAGTTCA-3\u0026prime; (antisense). The PCR conditions were as follows: an initial denaturation at 94\u0026deg;C for 2 minutes, followed by 35 cycles of denaturation at 98\u0026deg;C for 10 seconds, and extension at 68\u0026deg;C for 1 minute. After amplification, the PCR products were checked on an agarose gel, and the band corresponding to the target was excised and purified from the gel. Direct sequencing of these purified PCR products was conducted by FASMAC, using the Sanger sequencing method, as described previously [24,25].\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eGene set enrichment analysis (GSEA)\u003c/h2\u003e \u003cp\u003eThe associations between \u003cem\u003eSETBP1\u003c/em\u003e expression and previously defined gene sets were analyzed by GSEA using BC expression profiles from the appropriate TCGA dataset. The biologically defined gene sets were obtained from the Molecular Signatures Database v5.2 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://software.broadinstitute.org/gsea/msigdb/index.jsp\u003c/span\u003e\u003cspan address=\"http://software.broadinstitute.org/gsea/msigdb/index.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eGene Ontology (GO) analysis\u003c/h2\u003e \u003cp\u003eTo determine the biological implications of low \u003cem\u003eSETBP1\u003c/em\u003e expression, GO analysis was conducted using DAVID Bioinformatics Resources 6.8 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://david.ncifcrf.gov/tools.jsp\u003c/span\u003e\u003cspan address=\"https://david.ncifcrf.gov/tools.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). This tool provided a comprehensive set of functional annotations for the evaluated genes, allowing us to categorize them into corresponding biological processes, cellular components, and molecular functions. The significance of the enriched GO terms was determined using the modified Fisher\u0026rsquo;s exact test, with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered significant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003esiRNA-mediated knockdown experiments\u003c/h2\u003e \u003cp\u003eHuman \u003cem\u003eSETBP1\u003c/em\u003e-specific and negative control siRNAs were purchased from Thermo Fisher and Santa Cruz Biotechnology (Santa Cruz, CA, USA), respectively. The BC cell lines were transfected with siRNA oligonucleotides using Lipofectamine RNAiMAX (Thermo Fisher) according to the manufacturer's instructions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eWestern blot analysis\u003c/h2\u003e \u003cp\u003eWestern blot analysis was performed as described previously [20]. The following antigen-specific antibodies were used: primary mouse polyclonal antibody against SETBP1 (bs-4944R; Bioss) at a dilution of 1:1000, primary rabbit polyclonal antibody against SET (ab1183; Abcam) at a dilution of 1:2000, a mixture of three specific rabbit monoclonal primary antibodies against phospho-cdk2 Tyr15, phospho-Histone H3 Ser10, and β-actin (ab136810; Abcam) at a dilution of 1:250, primary rabbit polyclonal antibody against p44/42 MAPK (k1/2) (#9102S; Cell Signaling Technology, Danvers, MA, USA) at a dilution of 1:1000, primary rabbit polyclonal antibody against phospho-p44/42 MAPK (k1/2) (#9101S; Cell Signaling Technology) at a dilution of 1:1000, primary mouse polyclonal antibody against PP2A C subunit (05-421; Millipore, Billerica, MA, USA) at a dilution of 1:1000, and primary mouse polyclonal antibody against β-actin (Santa Cruz Biotechnology) at a dilution of 1:10,000.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eColony formation assay\u003c/h2\u003e \u003cp\u003eThe colony formation assay was performed as described previously [26]. For siRNA-mediated knockdown of \u003cem\u003eSETBP1\u003c/em\u003e, cells were plated at a density of 500/well (MCF7) or 2 \u0026times; 10\u003csup\u003e4\u003c/sup\u003e/well (MDA-MB-361) in 6-well plates and incubated at 37\u0026deg;C under 5% CO2. After 14 days, the colonies were stained using the Differential Quick Stain Kit (Sysmex) according to the manufacturer\u0026rsquo;s instructions. Visible colonies were photographed using the FUSION SOLO S. Colony counts were determined using ImageJ software (version 1.80, NIH, Bethesda, MD, USA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePP2A phosphatase activity assay\u003c/h2\u003e \u003cp\u003eThe protein phosphatase activity in each cell lysate was determined by measuring the generation of free phosphatase from threonine phosphopeptide using the malachite green\u0026ndash;phosphate complex assay, according to the instructions of the manufacturer (Upstate Biotechnology, Lake Placid, NY, USA). In brief, PP2A-specific reaction buffer (Millipore) containing 750 mM phosphopeptide substrate was added to cell lysates prepared in a low-detergent lysis buffer. After incubation for 10 min at 30\u0026deg;C, the malachite dye was added, and free phosphate was measured by optical density at 655 nm.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAssociations between variables were analyzed using Student\u0026rsquo;s t\u003cem\u003e-\u003c/em\u003etest, the Mann\u0026ndash;Whitney U test, or Fisher\u0026rsquo;s exact test. The degree of linearity was assessed using Pearson\u0026rsquo;s correlation coefficient. Recurrence-free survival (RFS) was estimated using the Kaplan\u0026ndash;Meier method, and survival curves were compared using the log-rank test. Data analyses were conducted using JMP Pro version 17 software (SAS Institute) and R software version 4.3.1 (The R Foundation). Two-sided \u003cem\u003eP\u003c/em\u003e values\u0026thinsp;\u003cem\u003e\u0026lt;\u0026thinsp;0.05\u003c/em\u003e were deemed statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eDownregulation of\u003c/b\u003e \u003cb\u003eSETBP1\u003c/b\u003e \u003cb\u003ein BC\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was significantly lower in BC tissues compared with normal breast tissues in the TCGA dataset (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA). In 71.4% of cases, \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was lower in BC tissues than in normal breast tissues, according to RT-qPCR, in our BC cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB). Regarding ER status, \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was lower in tumor tissues than in normal breast tissues in 61.3% of ER-positive cases and 94.4% of ER-negative cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC). ER-positive tumor tissues had significantly higher \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression compared with ER-negative tumor tissues in the TCGA dataset (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD). Immunohistochemical analysis showed that SETBP1 was highly expressed in the normal epithelial cells of ER-positive BC (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThese results indicate that \u003cem\u003eSETBP1\u003c/em\u003e is downregulated in BC tumor cells.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRFS curves of BC patients according to\u003c/b\u003e \u003cb\u003eSETBP1\u003c/b\u003e \u003cb\u003emRNA expression\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe assessed the prognostic and clinical significance of \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression in BC. First, we evaluated the RFS rates according to \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression in patients with BC. In the univariate analysis, tumor size (\u0026ge;\u0026thinsp;2 cm) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), menopause (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and low \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were significantly associated with a lower RFS rate (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The multivariate analysis indicated that tumor size (\u0026ge;\u0026thinsp;2 cm) (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), menopause (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and low \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) were independent predictors of a poor prognosis in BC (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The RFS rate was significantly lower in the low than high \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression group in the METABRIC and GSE19615 datasets (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Furthermore, the RFS rate was lower in the low than high \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression group in ER-positive BC cases in the METABRIC and GSE1965 datasets (\u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.05 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.076, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). In the ER-negative BC cases, there was no significant difference in the RFS rate between the high and low \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression groups in the METABRIC and GSE1965 datasets (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.46 and \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.14, respectively; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate analyses of the clinicopathological factors affecting disease-free survival in the METABRIC dataset\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnivariate (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMultivariate (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMenopause\u003c/p\u003e \u003cp\u003e(Post/Pre)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.17\u0026ndash;1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.17\u0026ndash;1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eER status (+/-)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.88\u0026ndash;1.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePgR status (+/-)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.85\u0026ndash;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHER2 status (+/-)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.88\u0026ndash;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size (\u0026ge;\u0026thinsp;2/\u0026lt;2 cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.06\u0026ndash;1.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.04\u0026ndash;1.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymph node metastasis (+/-)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.97\u0026ndash;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSETBP1\u003c/em\u003e expression (low/high)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.11\u0026ndash;1.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.10\u0026ndash;1.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eER, Estrogen Receptor; PgR, Progesterone Receptor; CI, confidential interval; HR, hazard ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e: Correlations between \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression in tumor tissues and clinicopathological factors in breast cancer\u003c/p\u003e\n\u003cp\u003e(A)\u0026nbsp;Our cohort\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 29.0749%;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 27.0925%;\"\u003e\n \u003cp\u003eT\u0026lt;N (n =41)\u003c/p\u003e\n \u003cp\u003eNumber (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 27.0925%;\"\u003e\n \u003cp\u003eT\u0026gt;N (n =15)\u003c/p\u003e\n \u003cp\u003eNumber (%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e56.5 \u0026plusmn; 1.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e55.3 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003eMenopause\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003ePre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e5 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e5 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; Post\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e30 (85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e7 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eTumor size (cm)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026lt;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e24 (64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e7 (58.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026ge;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e13 (35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e5 (41.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eER status\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e20 (51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e12 (92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e19 (48.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e1 ( 7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003ePgR status\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e16 (41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e12 (92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e23 (59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e1 ( \u0026nbsp;7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eLymphatic invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e24 (64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e4 (30.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; 1\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e13 (35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e9 (69.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eVascular invasion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e33 (89.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e11 (84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; 1\u0026ndash;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e4 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e2 (13.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eLymph node metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e21 (51.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e9 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e20 (48.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e6 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 100%;\"\u003e\n \u003cp\u003eDistant metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; +\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e2 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 29.0749%;\"\u003e\n \u003cp\u003e\u0026nbsp; -\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e39 (95.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27.0925%;\"\u003e\n \u003cp\u003e15 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16.7401%;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e(B) METABRIC dataset\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 113px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eLow expression (n = 980)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eHigh expression (n = 979)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003eAge (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp; Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e60.0 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e62.1 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003eTumor size (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026lt;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026ge;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e509\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003eER status\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e621\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e871\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e359\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003ePgR status\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e386\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e642\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e337\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003eHER2 status\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e800\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003eHistological grade\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1, 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e322\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e632\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003eMenopause\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003ePre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e190\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003ePost\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e747\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e789\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003eLymph node metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e505\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e398\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e541\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" style=\"width: 454px;\"\u003e\n \u003cp\u003eStage\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e336\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e407\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e228\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eER, Estrogen Receptor; PgR, Progesterone Receptor; SD, standard deviation\u003c/p\u003e\u003cp\u003eThese results suggest that low \u003cem\u003eSETBP1\u003c/em\u003e expression indicates a poor prognosis in patients with ER-positive BC.\u003c/p\u003e \u003cp\u003e \u003cb\u003eClinicopathologic significance of\u003c/b\u003e \u003cb\u003eSETBP1\u003c/b\u003e \u003cb\u003emRNA expression in BC\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe analyzed the associations between \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression and clinicopathologic factors in BC patients at our hospital (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). We divided the patients into two groups: the T\u0026thinsp;\u0026lt;\u0026thinsp;N group (\u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was lower in BC than normal breast tissues) and T\u0026thinsp;\u0026gt;\u0026thinsp;N group (\u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was higher in BC than normal breast tissues). We found higher frequencies of ER-negative and PgR-negative statuses, but a lower frequency of lymphatic invasion, in the T\u0026thinsp;\u0026lt;\u0026thinsp;N than T\u0026thinsp;\u0026gt;\u0026thinsp;N group. In the METABRIC dataset, low \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was associated with an older age, large tumor size, ER-negative, PgR-negative, and HER2-negative statuses, high histological grade, menopause, lymph node metastasis, and TNM stage (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003eThese results suggest that low \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression is positively associated with malignant phenotypes.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePathway analysis of\u003c/b\u003e \u003cb\u003eSETBP1\u003c/b\u003e \u003cb\u003ein ER-positive BC\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo explore oncogenic pathways associated with \u003cem\u003eSETBP1\u003c/em\u003e expression in ER-positive BC, we performed GSEA using TCGA dataset. \u003cem\u003eSETBP1\u003c/em\u003e expression was negatively correlated with the expression of E2F, MYC, and G2M checkpoint target geneset in ER-positive BC (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). E2F, MYC, and G2M checkpoint-related genes play important roles in various biological processes, including cell proliferation and cell cycle [27] [28] [29]. Next, we performed GO analysis and observed downregulation of many genes involved in cell cycle-related and MAPK-related pathways (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe results of the GSEA and GO analyses motivated us to investigate whether SETBP1 regulates tumor proliferation, cell cycle progression, and activation of the MAPK pathway in ER-positive BC.\u003c/p\u003e \u003cp\u003e \u003cb\u003eIncreased proliferation of ER-positive BC cells in vitro by\u003c/b\u003e \u003cb\u003eSETBP1\u003c/b\u003e \u003cb\u003eknockdown\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe performed a colony formation assay using a knockdown system in two ER-positive BC cell lines, MCF7 and MDA-MB-361, to clarify the relationship between \u003cem\u003eSETBP1\u003c/em\u003e and proliferative capacity. We found that \u003cem\u003eSETBP1\u003c/em\u003e knockdown significantly reduced the proliferation of MCF7 and MDA-MB-361 cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC, \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003cb\u003eActivation of cell cycle progression by\u003c/b\u003e \u003cb\u003eSETBP1\u003c/b\u003e \u003cb\u003eknockdown\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe evaluated the expression of histone H3 pSer10 (marker of cell cycle arrest at G2/M [30]) and CDK2 pTyr15 (marker of cell cycle arrest at G1/S [31]) in \u003cem\u003eSETBP1-\u003c/em\u003eknockdown ER-positive BC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). The expression of both markers was suppressed, suggesting that \u003cem\u003eSETBP1\u003c/em\u003e knockdown promotes cell cycle progression.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSuppressed PP2A activity and increased MAPK phosphorylation by\u003c/b\u003e \u003cb\u003eSETBP1\u003c/b\u003e \u003cb\u003eknockdown\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSETBP1 has been reported to form a complex with SET and PP2A [32]. PP2A is considered a tumor suppressor protein since its inactivation is mediated primarily by increased expression of its endogenous inhibitors, such as SET and cellular inhibitor of phosphatase 2A [33]. However, it is unknown if the expression of SETBP1, which binds to and functions with SET, affects the activation of PP2A. Thus, we performed a PP2A activity assay using \u003cem\u003eSETBP1\u003c/em\u003e-knockdown cells. PP2A activity was significantly suppressed in \u003cem\u003eSETBP1\u003c/em\u003e-knockdown ER-positive BC cells compared with control siRNA ER-positive BC cells (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Activation of PP2A has been reported to inhibit phosphorylation of MAPK [34]. Therefore, we hypothesized that low \u003cem\u003eSETBP1\u003c/em\u003e expression may activate the MAPK signaling pathway by inactivating PP2A activity in ER-positive BC cells. As expected, the ER-positive BC cell lines MCF7 and MDA-MB-361 with \u003cem\u003eSETBP1\u003c/em\u003e knockdown showed increased phosphorylation levels of MAPK compared with control cells(Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003eThese results suggest that \u003cem\u003eSETBP1\u003c/em\u003e knockdown facilitates cell proliferation possibly via inactivation of PP2A, followed by activation of MAPK signaling in ER-positive BC cells.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePotential factors responsible for the downregulated\u003c/b\u003e \u003cb\u003eSETBP1\u003c/b\u003e \u003cb\u003eexpression\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSince DNA methylation, DNA copy number alterations, SNPs, and gene mutations are well-known factors that regulate gene expression [7,35,36], we investigated the relationship between each of these factors and \u003cem\u003eSETBP1\u003c/em\u003e expression in BC. To do this, the \u003cem\u003eSETBP1\u003c/em\u003e mRNA level was divided into high and low groups based on the median value.\u003c/p\u003e \u003cp\u003eFirst, we evaluated the relationship between the \u003cem\u003eSETBP1\u003c/em\u003e promoter methylation rate and mRNA expression. The promoter methylation rate was significantly higher in the low than high \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression groups (68.1% vs. 33.3%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The \u003cem\u003eSETBP1\u003c/em\u003e promoter methylation rate was negatively correlated with SETBP1 mRNA expression in the TCGA dataset (R\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.50, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). When comparing ER-positive and ER-negative tumors from the TCGA dataset, the \u003cem\u003eSETBP1\u003c/em\u003e promoter methylation rate was significantly lower in ER-positive BC (Supplementary Fig.\u0026nbsp;1A).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSecond, the relationship between the \u003cem\u003eSETBP1\u003c/em\u003e DNA copy number status and gene expression level was assessed. The rate of \u003cem\u003eSETBP1\u003c/em\u003e deletion was significantly higher in the low than high \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression groups (41.4% vs. 11.9%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Compared with the diploid cases, cases with \u003cem\u003eSETBP1\u003c/em\u003e deletion had lower \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Regarding ER status, the ER-positive BC cases had a lower rate of \u003cem\u003eSETBP1\u003c/em\u003e deletion (Supplementary Fig.\u0026nbsp;1B).\u003c/p\u003e \u003cp\u003eNext, we examined the relationship between the \u003cem\u003eSETBP1\u003c/em\u003e rs6507583 SNP and \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression in 55 ER-positive BC cases from our BC cohort. rs6507583 was detected in only one case, and this case also showed the lowest \u003cem\u003eSETBP1\u003c/em\u003e expression level (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eC). Next, we investigated the rs6507583 SNP in human mammary cell lines and found that 2 of the 10 cell lines possessed rs6507583. The \u003cem\u003eSETBP1\u003c/em\u003e expression level was lower in the two cell lines with rs6507583 (MRK-nu1 and SKBR-3 cells) than in the cell lines without this SNP (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eD). Interestingly, SKBR-3 cells, possessing rs6507583, had low \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression with a low promoter methylation rate, whereas MDA-MB-231 cells, which lack rs6507583, had low \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression with a high promoter methylation rate. This suggests that the rs6507583 SNP and promoter methylation rate strongly contribute to the low \u003cem\u003eSETBP1\u003c/em\u003e expression (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003eFinally, the mutation rate in \u003cem\u003eSETBP1\u003c/em\u003e was examined. The frequency of mutations in \u003cem\u003eSETBP1\u003c/em\u003e was only 1.1% in the TCGA dataset in all BC cases (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eF). The ER-positive and ER-negative cases had a comparable rate of mutations (Supplementary Fig.\u0026nbsp;1C).\u003c/p\u003e \u003cp\u003eThese results suggest that the low expression of \u003cem\u003eSETBP1\u003c/em\u003e may be induced by the high promoter methylation rate, genomic deletions, and the rs6507583 SNP in BC.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we found that low SETBP1 expression contributed to the proliferation of ER-positive BC cells possibly by inducing MAPK phosphorylation. Furthermore, low SETBP1 expression predicted a poor prognosis in ER-positive BC patients. To the best of our knowledge, this is the first study to provide evidence that SETBP1 has a tumor suppressive role in ER-positive BC.\u003c/p\u003e \u003cp\u003eOur hospital cohort and the METABRIC dataset demonstrated that SETBP1 expression was negatively associated with several malignant phenotypes, including tumor size, lymph node metastasis, histological grade, and TNM stage. Additionally, low \u003cem\u003eSETBP1\u003c/em\u003e expression was associated with poor prognosis in ER-positive BC. Our biological analysis indicated that low \u003cem\u003eSETBP1\u003c/em\u003e expression accelerated cell proliferation, partly via cell cycle progression, in ER-positive BC. Furthermore, decreased \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was attributed to DNA copy number deletion, increased promoter methylation, and the SNP rs6507583. These findings provide clinical and biological evidence that SETBP1 plays a tumor-suppressive role in ER-positive BC.\u003c/p\u003e \u003cp\u003eInterestingly, low \u003cem\u003eSETBP1\u003c/em\u003e expression in triple-negative BC has been reported to be associated with good prognosis [16]. Our study also showed that low \u003cem\u003eSETBP1\u003c/em\u003e expression was not associated with a poor prognosis in ER-negative BC. These findings suggest SETBP1 may have different functions in BC depending on ER status.\u003c/p\u003e \u003cp\u003e \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was significantly higher in ER-positive BC than in ER-negative BC. We found that \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was decreased due to DNA copy number deletion, increased promoter methylation rate, and the rs6507583 SNP. ER-negative BC exhibited multiple factors contributing to the lower \u003cem\u003eSETBP1\u003c/em\u003e expression compared with ER-positive BC (Supplementary Fig.\u0026nbsp;1A, 1B).\u003c/p\u003e \u003cp\u003eOur in vitro analysis revealed that \u003cem\u003eSETBP1\u003c/em\u003e knockdown inhibited PP2A activity and increased MAPK phosphorylation, thereby enhancing cell cycle progression and proliferation in ER-positive BC cells. However, previous studies reported that SETBP1 overexpression leads to formation of the SETBP1/SET/PP2A complex, resulting in PP2A inhibition and subsequent cell proliferation in colorectal cancer, ovarian cancer, and acute myeloid leukemia [13,14,37]. These contradictory findings suggest that the role of SETBP1 in tumor progression varies depending on tissue type. Further research is needed to elucidate the tissue-dependent mechanisms of SETBP1 function.\u003c/p\u003e \u003cp\u003eER-positive BC is treated effectively with endocrine therapies (ET) [37]. Low expression of \u003cem\u003eSETBP1\u003c/em\u003e may lead to activation of the MAPK pathway downstream of the ER [38], potentially diminishing the efficacy of ET. ER-positive BC cases with low \u003cem\u003eSETBP1\u003c/em\u003e expression may benefit from combining ET and MAPK inhibitors [39].\u003c/p\u003e \u003cp\u003eIn summary, we demonstrated that \u003cem\u003eSETBP1\u003c/em\u003e inhibits tumor progression and is a prognostic biomarker in ER-positive BC.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank M. Kasagi, S. Sakuma, T. Fukuda, N. Mishima, T. Kawano, and M. Utou for their technical assistance.\u0026nbsp;This work was supported in part by the following grants and foundations: Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Science Research (grant numbers: 19K09176, 19H03715, 20H05039, 20K08930, 20K17556, 21K07179, 22K02903, 22K09006, 23K06765, 23K08074, 24K11766, 24K10384, and 24K02523); OITA Cancer Research Foundation; AMED (grant numbers: 23ck0106825h001, 23ck0106800h001, 22ama221501h0001, 21ck0106690s0201, 20cm0106475h0001, 20ck0106547h0001, and 20ck0106541h0001); Takeda Science Foundation; and The Princess Takamatsu Cancer Research Fund.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOne of the co-authors of this manuscript, Takaaki Masuda, serves as the editor of\u0026nbsp;\u003cem\u003eBreast Cancer\u003c/em\u003e. To maintain a fair and unbiased review process, the editorial office has ensured that Takaaki Masuda was not involved in the peer review or decision-making process for this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm that they have no conflicts of interest with respect to the work described in this manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71:209\u0026ndash;49.\u003c/li\u003e\n\u003cli\u003eNational Cancer Center Japan. [cited 2024 Apr 29]. Available from: https://ganjoho.jp/reg_stat/statistics/stat/cancer/14_breast.html\u003c/li\u003e\n\u003cli\u003eKajiwara Y, Takahashi A, Ueno H, Kakeji Y, Hasegawa H, Eguchi S, et al. 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Ann Oncol. 2012;23 Suppl 7:vii11-9.\u003c/li\u003e\n\u003cli\u003eArpino G, Wiechmann L, Osborne CK, Schiff R. Crosstalk between the estrogen receptor and the HER tyrosine kinase receptor family: molecular mechanism and clinical implications for endocrine therapy resistance. Endocr Rev. 2008;29:217\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eHotokezaka H, Sakai E, Kanaoka K, Saito K, Matsuo K-I, Kitaura H, et al. U0126 and PD98059, specific inhibitors of MEK, accelerate differentiation of RAW264.7 cells into osteoclast-like cells. J Biol Chem. 2002;277:47366\u0026ndash;72.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"breast-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brca","sideBox":"Learn more about [Breast Cancer](http://link.springer.com/journal/12282)","snPcode":"12282","submissionUrl":"https://www.editorialmanager.com/brca/default2.aspx","title":"Breast Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"SETBP1, ER positive, breast cancer, proliferation, SNP","lastPublishedDoi":"10.21203/rs.3.rs-5269021/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5269021/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe single nucleotide polymorphism rs6507583 at the promoter of SET binding protein 1 (\u003cem\u003eSETBP1\u003c/em\u003e) was implicated in estrogen receptor (ER)-positive breast carcinogenesis. Here, we evaluated the clinical and biological relevance of \u003cem\u003eSETBP1\u003c/em\u003e expression in ER-positive breast cancer (BC).\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe associations between SETBP1 expression and clinical outcomes in BC patients were analyzed in independent cohorts. The localizations of \u003cem\u003eSETBP1\u003c/em\u003e expression in BC tissues were observed by immunohistochemical staining. Pathway analyses were conducted using TCGA dataset. An in vitro proliferation assay, protein phosphatase 2A (PP2A) activity assay, and gene expression analysis were performed in \u003cem\u003eSETBP1\u003c/em\u003e-knockdown ER-positive BC cells. We investigated the factors influencing \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression using TCGA dataset. rs6507583 presence and \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression in 11 mammary cell lines and 56 BC tissue samples were examined by target sequencing and RT-qPCR, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSETBP1 was downregulated in BC cells compared with normal ductal epithelial cells. Low \u003cem\u003eSETBP1\u003c/em\u003e mRNA expression was an independent prognostic factor for poor recurrence-free survival. Pathway analyses revealed an inverse relationship between decreased \u003cem\u003eSETBP1\u003c/em\u003e expression and the expression of E2F, MYC, and G2M checkpoint target genes in BC tissues. \u003cem\u003eSETBP1\u003c/em\u003e knockdown promoted proliferation, inhibition of PP2A activity, and phosphorylation of MAPK in ER-positive BC. Low \u003cem\u003eSETBP1\u003c/em\u003e expression was influenced by high \u003cem\u003eSETBP1\u003c/em\u003e promoter methylation and DNA copy number \u003cem\u003eSETBP1\u003c/em\u003e deletion. \u003cem\u003eSETBP1\u003c/em\u003e expression with rs6507583 was lower than without rs6507583 in BC.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e\u003c/p\u003e \u003cp\u003eWe demonstrated that low \u003cem\u003eSETBP1\u003c/em\u003e expression could be a poor prognostic biomarker that promotes ER-positive BC proliferation, possibly via phosphorylation of MAPK.\u003c/p\u003e","manuscriptTitle":"SET binding protein 1 (SETBP1) suppresses cell proliferation in estrogen receptor-positive breast cancer.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-10 16:02:51","doi":"10.21203/rs.3.rs-5269021/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor Revision","date":"2024-12-02T03:10:28+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2024-11-10T11:51:53+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-08T10:59:49+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-21T14:54:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Breast Cancer","date":"2024-10-20T04:46:27+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"breast-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"brca","sideBox":"Learn more about [Breast Cancer](http://link.springer.com/journal/12282)","snPcode":"12282","submissionUrl":"https://www.editorialmanager.com/brca/default2.aspx","title":"Breast Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"ad28636b-03fb-485f-b072-f4b9fe914c44","owner":[],"postedDate":"December 10th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-24T16:05:37+00:00","versionOfRecord":{"articleIdentity":"rs-5269021","link":"https://doi.org/10.1007/s12282-025-01667-w","journal":{"identity":"breast-cancer","isVorOnly":false,"title":"Breast Cancer"},"publishedOn":"2025-02-20 15:57:21","publishedOnDateReadable":"February 20th, 2025"},"versionCreatedAt":"2024-12-10 16:02:51","video":"","vorDoi":"10.1007/s12282-025-01667-w","vorDoiUrl":"https://doi.org/10.1007/s12282-025-01667-w","workflowStages":[]},"version":"v1","identity":"rs-5269021","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5269021","identity":"rs-5269021","version":["v1"]},"buildId":"omnImTCwR2MFx8CMYfrG7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}