miR-381-3p suppresses breast cancer progression by inhibition of epithelial-mesenchymal transition

The effect of miR-381 on proliferation and prognosis of breast cancer by altering CCNA2 expression

BACKGROUND

MiR-381 can regulate the expression of cyclin A2 (CCNA2) to inhibit the proliferation and migration of bladder cancer cells, but whether miR-381 has the same function in breast cancer is not well know.

METHODS

The over express or silence miR-381 expressing cell lines were constructed by lentivirus infection to reveal the biological functions of miR-381 in vitro. The expression of miR-381 and CCNA2 in 162 breast cancer patients were detected to further reveal their impact and predictive value on progression-free survival (PFS) and overall survival (OS).

RESULTS

After transfection of MDA-MB-231 and MCF-7 cells with miR-381 mimics, the expression of miR-381 was effectively up-regulated and CCNA2 was effectively down-regulated, while the opposite results were observed in tumour cell which transfected with miR-381 inhibitors. After transfection of cell lines with miR-381 mimics, tumour cell activity was significantly reduced, while the opposite results were observed in tumour cell which transfected with miR-381 inhibitors. The area under curves (AUCs) of miRNA-381 and CCNA2 for predicting PFS and OS were 0.711, 0.695, 0.694 and 0.675 respectively. Cox regression analysis showed that miRNA-381 ≥ 1.65 2-ΔΔCt and CCNA ≥ 2.95 2-ΔΔCt were the influence factors of PFS and OS, the hazard ratio (HR) values were 0.553, 2.075, 0.462 and 2.089, respectively.

CONCLUSION

miR-381 inhibitors breast cancer cells proliferation and migration by down-regulating the expression of CCNA2, both of them can predict the prognosis of breast cancer.

EIF4A3-mediated oncogenic circRNA hsa_circ_0001165 advances esophageal squamous cell carcinoma progression through the miR-381-3p/TNS3 pathway

Esophageal squamous cell carcinoma (ESCC) remains a major clinical challenge due to its poor prognosis and the scarcity effective therapeutic targets. Circular RNAs (circRNAs) are crucial in cancer progression. In this study, high-throughput sequencing was employed to profile ESCC tissues, revealing that hsa_circ_0001165 is notably elevated in both ESCC tumor samples and cell lines, with its expression is positively associated with patients' TNM staging. Knockdown of hsa_circ_0001165 resulted in reduced malignant biological behavior of ESCC cells in vitro and also inhibited tumor growth in vivo. Mechanism experimental analysis found that hsa_circ_0001165 expression is positively enhanced by eukaryotic translation initiation factor 4A3 (EIF4A3). Hsa_circ_0001165 acts as a miRNA sponge for miR-381-3p, increasing the expression of tensin-3 (TNS3) through a series of related mechanism assays include dual-luciferase reporter gene, RNA Immunoprecipitation and RNA-pulldown. The downregulation in miR-381-3p expression was observed in ESCC tissues, and the cell proliferation, invasion, and migration of ESCC were suppressed. The upregulated expression of hsa_circ_0001165 modulates the miR-381-3p/TNS3 axis and promotes aggressive phenotypes of ESCC. Hsa_circ_0001165 is regarded as a encouraging biomarker and potential therapeutic target for ESCC, presenting innovative options for both diagnostic and treatment approaches.

Advances in applications of artificial intelligence algorithms for cancer-related miRNA research

MiRNAs are a class of small non-coding RNAs, which regulate gene expression post-transcriptionally by partial complementary base pairing. Aberrant miRNA expressions have been reported in tumor tissues and peripheral blood of cancer patients. In recent years, artificial intelligence algorithms such as machine learning and deep learning have been widely used in bioinformatic research. Compared to traditional bioinformatic tools, miRNA target prediction tools based on artificial intelligence algorithms have higher accuracy, and can successfully predict subcellular localization and redistribution of miRNAs to deepen our understanding. Additionally, the construction of clinical models based on artificial intelligence algorithms could significantly improve the mining efficiency of miRNA used as biomarkers. In this article, we summarize recent development of bioinformatic miRNA tools based on artificial intelligence algorithms, focusing on the potential of machine learning and deep learning in cancer-related miRNA research.

Serum Exosome-Derived microRNA-193a-5p and miR-381-3p Regulate Adenosine 5'-Monophosphate-Activated Protein Kinase/Transforming Growth Factor Beta/Smad2/3 Signaling Pathway and Promote Fibrogenesis

INTRODUCTION

Liver fibrosis results from chronic liver injury and inflammation, often leading to cirrhosis, liver failure, portal hypertension, and hepatocellular carcinoma. Progress has been made in understanding the molecular mechanisms underlying hepatic fibrosis; however, translating this knowledge into effective therapies for disease regression remains a challenge, with considerably few interventions having entered clinical validation. The roles of exosomes during fibrogenesis and their potential as a therapeutic approach for reversing fibrosis have gained significant interest. This study aimed to investigate the association between microRNAs (miRNAs) derived from serum exosomes and liver fibrosis and to evaluate the effect of serum exosomes on fibrogenesis and fibrosis reversal, while identifying the underlying mechanism.

METHODS

Using serum samples collected from healthy adults and paired histologic patients with advanced fibrosis or cirrhosis, we extracted human serum exosomes by ultrahigh-speed centrifugation. Transcriptomic analysis was conducted to identify dysregulated exosome-derived miRNAs. Liver fibrosis-related molecules were determined by qRT-PCR, Western blot, Masson staining, and immunohistochemical staining. In addition, we analyzed the importance of serum exosome-derived miRNA expression levels in 42 patients with advanced fibrosis or cirrhosis.

RESULTS

Exosome-derived miR-193a-5p and miR-381-3p were associated with fibrogenesis, as determined by transcriptomic screening. Compared with healthy control group, the high expression of serum exosome-derived miR-193a-5p and miR-381-3 in chronic hepatitis B (n = 42) was closely associated with advanced liver fibrosis and cirrhosis. In vitro , exosome-derived miRNA-193a-5p and miR-381-3p upregulated the expression of α-smooth muscle actin, collagen 1a1, and tissue inhibitors of metalloproteinase 1 in the human hepatic stellate cell line at both mRNA and protein levels.

DISCUSSION

Serum exosome-derived miR-193a-5p and miR-381-3p regulated the adenosine 5'-monophosphate-activated protein kinase/transforming growth factor beta/Smad2/3 signaling pathway and promoted fibrogenesis.

A serum miRNAs signature for early diagnosis of bladder cancer

BACKGROUND

Bladder cancer accounts for the most common type of urologic malignancy and presents high recurrence rate after surgical resection and adjuvant intravesical therapy. We aim to search for an early diagnostic biomarker in serum for bladder cancer in this study.

METHODS

The expression profiles of miRNAs in serum samples of 112 bladder cancer patients and 112 healthy controls were detected with real-time polymerase chain reaction (RT-qPCR). Receiver operating characteristic (ROC) curve and area under curve (AUC) analysis were performed to assess the diagnostic efficiency of miRNAs. Stepwise logic regression analysis was used to construct a diagnostic signature with highest sensitivity and specificity. Bioinformatics analysis was applied to explore the potential biological functions and mechanisms of candidate miRNAs.

RESULTS

Five miRNAs including miR-451a, miR-381-3p, miR-223-3p, miR-142-5p and miR-27b-3p were found differentially expressed in serum samples of bladder patients and healthy subjects. The diagnostic signature was constructed with miR-27b-3p, miR-381-3p and miR-451a. AUC of the three-miRNA signature was 0.894 (0.837-0.936, p < 0.001). The sensitivity and specificity of this signature were 86.90% and 77.38%, respectively, indicating that this signature has a good ability to diagnose bladder cancer.

CONCLUSION

The three-miRNA signature we constructed has favorable diagnostic capacity and may be a promising non-invasive biomarker in the early diagnosis of bladder cancer.KEY MESSAGESThere is still no clinical utilization of serum miRNAs in the early detection of bladder cancer.We screened and constructed a three-miRNA signature with the sensitivity of 86.90% and specificity of 77.38% which may be a promising non-invasive biomarker in the early diagnosis of bladder cancer.

Inhaled seralutinib exhibits potent efficacy in models of pulmonary arterial hypertension

BACKGROUND

Signalling through platelet-derived growth factor receptor (PDGFR), colony-stimulating factor 1 receptor (CSF1R) and mast/stem cell growth factor receptor kit (c-KIT) plays a critical role in pulmonary arterial hypertension (PAH). We examined the preclinical efficacy of inhaled seralutinib, a unique small-molecule PDGFR/CSF1R/c-KIT kinase inhibitor in clinical development for PAH, in comparison to a proof-of-concept kinase inhibitor, imatinib.

METHODS

Seralutinib and imatinib potency and selectivity were compared. Inhaled seralutinib pharmacokinetics/pharmacodynamics were studied in healthy rats. Efficacy was evaluated in two rat models of PAH: SU5416/Hypoxia (SU5416/H) and monocrotaline pneumonectomy (MCTPN). Effects on inflammatory/cytokine signalling were examined. PDGFR, CSF1R and c-KIT immunohistochemistry in rat and human PAH lung samples and microRNA (miRNA) analysis in the SU5416/H model were performed.

RESULTS

Seralutinib potently inhibited PDGFRα/β, CSF1R and c-KIT. Inhaled seralutinib demonstrated dose-dependent inhibition of lung PDGFR and c-KIT signalling and increased bone morphogenetic protein receptor type 2 (BMPR2). Seralutinib improved cardiopulmonary haemodynamic parameters and reduced small pulmonary artery muscularisation and right ventricle hypertrophy in both models. In the SU5416/H model, seralutinib improved cardiopulmonary haemodynamic parameters, restored lung BMPR2 protein levels and decreased N-terminal pro-brain natriuretic peptide (NT-proBNP), more than imatinib. Quantitative immunohistochemistry in human lung PAH samples demonstrated increased PDGFR, CSF1R and c-KIT. miRNA analysis revealed candidates that could mediate seralutinib effects on BMPR2.

CONCLUSIONS

Inhaled seralutinib was an effective treatment of severe PAH in two animal models, with improved cardiopulmonary haemodynamic parameters, a reduction in NT-proBNP, reverse remodelling of pulmonary vascular pathology and improvement in inflammatory biomarkers. Seralutinib showed greater efficacy compared to imatinib in a preclinical study.

lncRNA SNHG15 as a ceRNA modulates Osteoclast Differentiation, Proliferation, and Metastasis by Sponging miR-381-3p/NEK2 Axis

Background

A growing number of studies have shown that long noncoding RNAs play an important role in osteoclast differentiation. However, there are few studies on the roles of lncRNA small nucleolar RNA host gene 15 (SNHG15) in osteoclast differentiation.

Methods

The expressions of SNHG15, miR-381-3p, and never in mitosis-related kinase 2 (NEK2) mRNA were detected by real-time quantitative polymerase chain reaction (RT-qPCR); Western blot detected NEK2 and osteoclast markers (Cathepsin K, CTSK), matrix metalloproteinase 9 (MMP9), nuclear factor of activated T cell 2 (NFAT2), and tartrate-resistant acid phosphatase (TRAP) protein levels; cell proliferation was detected by Cell Counting Kit-8 (CCK-8), and the formation of osteoclasts was observed by TRAP staining; the F-actin skeleton was stained with tetramethylrhodamine isothiocyanate (TRITC) phalloidin; cell migration rate was detected by Transwell; dual-luciferase reporter gene assay and RNA-binding protein immunoprecipitation (RIP) assay verified the targeting relationship between miR-381-3p, SNHG15, and NEK2.

Results

The expression of SNHG15 was increased in THP-1 cells stimulated by macrophage colony-stimulating factor (M-CSF)/receptor activator of nuclear factor-kappa B ligand (RANKL). Overexpression of SNHG15 significantly promoted the proliferation, migration, osteoclast differentiation, and expression of osteoclast markers CTSK, MMP9, NFAT2, and TRAP of THP-1 cells induced by M-CSF/RANKL. Knockdown of SNHG15 reversed this effect. Overexpression of SNHG15 downregulated the inhibitory effect of overexpression of miR-381-3p on the proliferation, migration, and differentiation of THP-1 cells induced by M-CSF/RANKL. Knockdown of miR-381-3p reversed the inhibitory effect of knockdown of NEK2 on the proliferation, migration, and differentiation of THP-1 cells induced by M-CSF/RANKL.

Conclusion

SNHG15 acted as a ceRNA promoted the proliferation, migration, and differentiation of THP-1 cells induced by M-CSF/RANKL through sponging miR-381-3p to promote the expression of NEK2.

The Role of MicroRNA in the Regulation of Tumor Epithelial–Mesenchymal Transition

Consistently, the high metastasis of cancer cells is the bottleneck in the process of tumor treatment. In this process of metastasis, a pivotal role is executed by epithelial–mesenchymal transition (EMT). The epithelial-to-mesenchymal transformation was first proposed to occur during embryonic development. Later, its important role in explaining embryonic developmental processes was widely reported. Recently, EMT and its intermediate state were also identified as crucial drivers in tumor progression with the gradual deepening of research. To gain insights into the potential mechanism, increasing attention has been focused on the EMT-related transcription factors. Correspondingly, miRNAs target transcription factors to control the EMT process of tumor cells in different types of cancers, while there are still many exciting and challenging questions about the phenomenon of microRNA regulation of cancer EMT. We describe the relevant mechanisms of miRNAs regulating EMT, and trace the regulatory roles and functions of major EMT-related transcription factors, including Snail, Twist, zinc finger E-box-binding homeobox (ZEB), and other families. In addition, on the basis of the complex regulatory network, we hope that the exploration of the regulatory relationship of non-transcription factors will provide a better understanding of EMT and cancer metastasis. The identification of the mechanism leading to the activation of EMT programs during diverse disease processes also provides a new protocol for the plasticity of distinct cellular phenotypes and possible therapeutic interventions. Here, we summarize the recent progress in this direction, with a promising path for further insight into this fast-moving field.

Discovering Common miRNA Signatures Underlying Female-Specific Cancers via a Machine Learning Approach Driven by the Cancer Hallmark ERBB

Big data processing, using omics data integration and machine learning (ML) methods, drive efforts to discover diagnostic and prognostic biomarkers for clinical decision making. Previously, we used the TCGA database for gene expression profiling of breast, ovary, and endometrial cancers, and identified a top-scoring network centered on the ERBB2 gene, which plays a crucial role in carcinogenesis in the three estrogen-dependent tumors. Here, we focused on microRNA expression signature similarity, asking whether they could target the ERBB family. We applied an ML approach on integrated TCGA miRNA profiling of breast, endometrium, and ovarian cancer to identify common miRNA signatures differentiating tumor and normal conditions. Using the ML-based algorithm and the miRTarBase database, we found 205 features and 158 miRNAs targeting ERBB isoforms, respectively. By merging the results of both databases and ranking each feature according to the weighted Support Vector Machine model, we prioritized 42 features, with accuracy (0.98), AUC (0.93–95% CI 0.917–0.94), sensitivity (0.85), and specificity (0.99), indicating their diagnostic capability to discriminate between the two conditions. In vitro validations by qRT-PCR experiments, using model and parental cell lines for each tumor type showed that five miRNAs (hsa-mir-323a-3p, hsa-mir-323b-3p, hsa-mir-331-3p, hsa-mir-381-3p, and hsa-mir-1301-3p) had expressed trend concordance between breast, ovarian, and endometrium cancer cell lines compared with normal lines, confirming our in silico predictions. This shows that an integrated computational approach combined with biological knowledge, could identify expression signatures as potential diagnostic biomarkers common to multiple tumors.

Identification and Validation of miRNA-TF-mRNA Regulatory Networks in Uterine Fibroids

Uterine fibroids (UF) are the most common benign gynecologic tumors and lead to heavy menstrual bleeding, severe anemia, abdominal pain, and infertility, which seriously harm a women’s health. Unfortunately, the regulatory mechanisms of UF have not been elucidated. Recent studies have demonstrated that miRNAs play a vital role in the development of uterine fibroids. As a high-throughput technology, microarray is utilized to identify differentially expressed genes (DEGs) and miRNAs (DEMs) between UF and myometrium. We identified 373 candidate DEGs and the top 100 DEMs. Function enrichment analysis showed that candidate DEGs were mainly enriched in biological adhesion, locomotion and cell migration, and collagen-containing extracellular matrix. Subsequently, protein-protein interaction (PPI) networks are constructed to analyze the functional interaction between DEGs and screen hub DEGs. Subsequently, the expression levels of hub DEGs were validated by real-time PCR of clinical UF samples. The DGIdb database was used to select candidate drugs for hub DEGs. Molecular docking was applied to test the affinity between proteins and drugs. Furthermore, target genes for 100 candidate DEMs were predicted by miRwalk3.0. After overlapping with 373 candidate DEGs, 28 differentially expressed target genes (DEGTs) were obtained. A miRNA-mRNA network was constructed to investigate the interactions between miRNA and mRNA. Additionally, two miRNAs (hsa-miR-381-3p and hsa-miR-181b-5p) were identified as hub DEMs and validated through RT-PCR. In order to better elucidate the pathogenesis of UF and the synergistic effect between miRNA and transcription factor (TF), we constructed a miRNA-TF-mRNA regulatory network. Meanwhile, in vitro results suggested that dysregulated hub DEMs were associated with the proliferation, migration, and apoptosis of UF cells. Our findings provided a novel horizon to reveal the internal mechanism and novel targets for the diagnosis and treatment of UF.

miR-381-3p Involves in Glioma Progression by Suppressing Tumor-Promoter Factor ANTXR1

Accumulating studies revealed association between development of glioma and miRNA dysregulation. A case in point is miR-381-3p, but its mechanism in glioma is unclear yet. In this work, we confirmed that overexpressed miR-381-3p repressed biological functions of glioma cells. Additionally, we also discovered that upregulated anthrax toxin receptor 1 (ANTXR1) was negatively mediated by miR-381-3p. We further proved that miR-381-3p-targeted ANTXR1 was able to counteract the suppression of miR-381-3p on biological functions of glioma. We concluded that miR-381-3p and ANTXR1 were both important factors in modulating glioma progression. miR-381-3p/ANTXR1 axis is expected to be a molecular target for glioma.

Circular RNA circVAPA contributes to non-small-cell lung cancer progression via miR-342-3p-dependent regulation of ZEB2

BACKGROUND

Accumulating evidence demonstrated that circular RNAs (circRNAs) play pivotal regulatory roles in the pathology of cancers. Disclosing the roles and molecular mechanisms of circRNAs in tumorigenesis and development is essential to identify novel diagnostic and therapeutic targets. In this study, we explored the role of circVAPA in non-small-cell lung cancer (NSCLC) progression and its associated mechanism.

METHODS

The expression level of RNA was analyzed by real-time quantitative polymerase chain reaction (RT-qPCR). Cell proliferation was assessed by MTT assay and colony-forming assay. Cell apoptosis was analyzed by flow cytometry. Cell migration and invasion were assessed by transwell assays. Dual-luciferase reporter, RNA pull-down, and RNA immunoprecipitation (RIP) assays were used to test the intermolecular interactions. The role of circVAPA was assessed in vivo. And xenograft tumor tissues were analyzed by immunohistochemistry (IHC) staining.

RESULTS

CircVAPA expression was upregulated in NSCLC tissues and cell lines, and a high level of circVAPA was associated with a poor prognosis of NSCLC patients. CircVAPA silencing suppressed the proliferation, migration, and invasion and induced the apoptosis of NSCLC cells. CircVAPA served as a molecular sponge for microRNA-342-3p (miR-342-3p). miR-342-3p interference largely reversed circVAPA knockdown-mediated anti-tumor effects in NSCLC cells. Zinc finger E-box-binding homeobox 2 (ZEB2) was a target of miR-342-3p, and miR-342-3p overexpression suppressed the malignant behaviors of NSCLC cells largely by downregulating ZEB2. CircVAPA silence repressed xenograft tumor growth in vivo, and IHC assay confirmed that circVAPA silence restrained the proliferation and metastasis but induced the apoptosis of NSCLC cells in vivo.

CONCLUSION

CircVAPA contributes to the progression of NSCLC by binding to miR-342-3p to upregulate ZEB2. CircVAPA/miR-342-3p/ZEB2 axis might be a novel potential target for NSCLC treatment.

Identification of a novel glycolysis-related signature to predict the prognosis of patients with breast cancer

Background

Breast cancer (BC) has a high incidence and mortality rate in females. Its conventional clinical characteristics are far from accurate for the prediction of individual outcomes. Therefore, we aimed to develop a novel signature to predict the survival of patients with BC.

Methods

We analyzed the data of a training cohort from the Cancer Genome Atlas (TCGA) database and a validation cohort from the Gene Expression Omnibus (GEO) database. After the applications of Gene Set Enrichment Analysis (GSEA) and Cox regression analyses, a glycolysis-related signature for predicting the survival of patients with BC was developed; the signature contained AK3, CACNA1H, IL13RA1, NUP43, PGK1, and SDC1. Furthermore, on the basis of expression levels of the six-gene signature, we constructed a risk score formula to classify the patients into high- and low-risk groups. The receiver operating characteristic (ROC) curve and the Kaplan-Meier curve were used to assess the predicted capacity of the model. Later, a nomogram was developed to predict the outcomes of patients with risk score and clinical features over a period of 1, 3, and 5 years. We further used Human Protein Atlas (HPA) database to validate the expressions of the six biomarkers in tumor and sample tissues, which were taken as control.

Results

We constructed a six-gene signature to predict the outcomes of patients with BC. The patients in the high-risk group showed poor prognosis than those in the low-risk group. The area under the curve (AUC) values were 0.719 and 0.702, showing that the prediction performance of the signature is acceptable. Additionally, Cox regression analysis revealed that these biomarkers could independently predict the prognosis of BC patients with BC without being affected by clinical factors. The expression levels of all six biomarkers in BC tissues were higher than that in normal tissues; however, AK3 was an exception.

Conclusion

We developed a six-gene signature to predict the prognosis of patients with BC. Our signature has been proved to have the ability to make an accurate prediction and might be useful in expanding the hypothesis in clinical research.

Comprehensive analysis of the cancer driver genes in breast cancer demonstrates their roles in cancer prognosis and tumor microenvironment

Background

Breast cancer is the most common malignancy in women. Cancer driver gene-mediated alterations in the tumor microenvironment are critical factors affecting the biological behavior of breast cancer. The purpose of this study was to identify the expression characteristics and prognostic value of cancer driver genes in breast cancer.

Methods

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets are used as the training and test sets. Classified according to cancer and paracancerous tissues, we identified differentially expressed cancer driver genes. We further screened prognosis-associated genes, and candidate genes were submitted for the construction of a risk signature. Functional enrichment analysis and transcriptional regulatory networks were performed to search for possible mechanisms by which cancer driver genes affect breast cancer prognosis.

Results

We identified more than 200 differentially expressed driver genes and 27 prognosis-related genes. High-risk group patients had a lower survival rate compared to the low-risk group (P<0.05), and risk signature showed high specificity and sensitivity in predicting the patient prognosis (AUC 0.790). Multivariate regression analysis suggested that risk scores can independently predict patient prognosis. Further, we found differences in PD-1 expression, immune score, and stromal score among different risk groups.

Conclusion

Our study confirms the critical prognosis role of cancer driver genes in breast cancer. The cancer driver gene risk signature may provide a novel biomarker for clinical treatment strategy and survival prediction of breast cancer.

Over-expression of SRD5A3 and its prognostic significance in breast cancer

Objective

The study aimed to compare the Steroid 5 alpha-reductase 3 (SRD5A3) expression levels in breast cancer (BC) and normal tissues, to investigate the prognostic value of SRD5A3 mRNA expression in BC patients and to identify the SRD5A3-related signaling pathways using bioinformatics approaches.

Methods

We evaluated the expression levels of SRD5A3 and survival data in BC patients using different bioinformatic databases. Further, Cox regression analysis was conducted to predict the independent prognostic factors for BC. Moreover, the association of SRD5A3 with clinicopathological factors was measured through LinkedOmics database. And the potential role of SRD5A3 was determined by Gene Ontology and KEGG pathway enrichment analysis. Finally, protein network of SRD5A3 was constructed and genetic alterations were analyzed.

Results

Bioinformatic data indicated that both mRNA and protein expression levels of SRD5A3 were higher in BC group than those in the normal group (P < 0.05). Besides, BC patients with higher SRD5A3 mRNA expression levels had a lower overall survival (all P < 0.05). Cox regression analysis further demonstrated the independent prognostic value of SRD5A3 in BC (P = 0.015). SRD5A3 mRNA expression was significantly associated with N stage (P < 0.001), age (P < 0.05), and histologic subtype (P < 0.001) but had no significant relationship with other clinical characteristics (all P > 0.05). Moreover, the functional enrichment analysis revealed that the SRD5A3 was involved in metabolism-related pathways (all P < 0.05).

Conclusions

SRD5A3 was highly expressed in BC tissues and high SRD5A3 expression was related to poorer prognosis. SRD5A3 serves as an oncogene and might function as a potential biomarker for prognosis and a therapeutic target for BC.