Identifying a Serum Exosomal-Associated lncRNA/circRNA-miRNA-mRNA Network in Coronary Heart Disease

Background. Accumulating evidence supports the importance of noncoding RNAs and exosomes in coronary heart disease (CHD). However, exosomal-associated competing endogenous RNA- (ceRNA-) mediated regulatory mechanisms in CHD are largely unexplored. The present study aimed to explore exosomal-associated ceRNA networks in CHD. Methods. Data from 6 CHD patients and 32 normal controls were downloaded from the ExoRBase database. CHD and normal controls were compared by screening differentially expressed mRNAs (DEMs), lncRNAs (DELs), and circRNAs (DECs) in serum exosomes. MicroRNAs (miRNAs) targeting DEMs were predicted using the Targetscan and miRanda databases, and miRNAs targeted by DELs and DECs were predicted using the miRcode and starBase databases, respectively. The biological functions and related signaling pathways of DEMs were analyzed using the David and KOBAS databases. Subsequently, a protein-protein interaction (PPI) network was established to screen out on which hub genes enrichment analyses should be performed, and a ceRNA network (lncRNA/circRNA-miRNA-mRNA) was constructed to elucidate ceRNA axes in CHD. Results. A total of 312 DEMs, 43 DELs, and 85 DECs were identified between CHD patients and normal controls. Functional enrichment analysis showed that DEMs were significantly enriched in “chromatin silencing at rDNA,” “telomere organization,” and “negative regulation of gene expression, epigenetic.” PPI network analysis showed that 25 hub DEMs were closely related to CHD, of which ubiquitin C (UBC) was the most important. Hub genes were mainly enriched in “cellular protein metabolic process” functions. The exosomal-associated ceRNA regulatory network incorporated 48 DEMs, 73 predicted miRNAs, 10 DELs, and 15 DECs. The LncRNA/circRNA-miRNA-mRNA interaction axes (RPL7AP11/hsa-miR-17-5p/UBC and RPL7AP11/hsa-miR-20b-5p/UBC) were obtained from the network. Conclusions. Our findings provide a novel perspective on the potential role of exosomal-associated ceRNA network regulation of the pathogenesis of CHD.

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Identifying Serum Exosomal-Associated lncRNA/circRNA-miRNA-mRNA Network in Coronary Heart Disease

10.21203/rs.3.rs-131078/v1 ◽

2020 ◽

Author(s):

Jia Mao ◽

Yufei Zhou ◽

Licheng Lu ◽

Ping Zhang ◽

Runhua Ren ◽

...

Keyword(s):

Coronary Heart Disease ◽

Heart Disease ◽

Regulation Of Gene Expression ◽

Cellular Protein ◽

Functional Enrichment ◽

Signal Pathways ◽

Ppi Network ◽

Hub Genes ◽

Cerna Network ◽

Normal Controls

Abstract Background: Accumulating evidence has indicated that the importance of noncoding RNAs and exosomes in coronary heart disease (CHD). However, the exosomal-associated competing endogenous RNA (ceRNA)-mediated regulatory mechanism in CHD is still unknown. The present study aimed to explore exosomal-associated ceRNA network in CHD.Methods: The dataset, including 6 CHD patients and 32 normal controls, were downloaded from the ExoRBase database. Differentially expressed mRNAs (DEMs), lncRNAs (DELs) and circRNAs (DECs) in the serum exosomes between CHD and normal controls were screened. MicroRNAs (miRNAs) targeting DEMs were predicted by Targetscan and miRanda, miRNAs targeting DELs and DECs were predicted with miRcode and starBase, respectively. The biological functions and related signal pathways of DEMs were analyzed using David and KOBAS database. Subsequently, the protein-protein interaction (PPI) network was established to screen out hub genes, enrichment analyses of hub genes were performed and the ceRNA network (lncRNA/circRNA-miRNA-mRNA) was constructed to elucidate ceRNA axes in CHD.Results: A total of 312 DEMs, 43 DELs and 85 DECs were identified between CHD patients and normal controls. Functional enrichment analysis showed that DEMs were significantly enriched in “chromatin silencing at rDNA”, “telomere organization”, “negative regulation of gene expression, epigenetic”. The PPI network analysis showed that 25 hub DEMs were closely related to CHD, of which, ubiquitin C (UBC) was the most important. The biological function of hub genes showed that they were mainly enriched in “cellular protein metabolic process”. The exosomal-associated ceRNA regulatory network incorporated 48 DEMs, 72 predicted miRNAs, 10 DELs and 15 DECs. LncRNA/circRNA-miRNA-mRNA interaction axes (RPL7AP11/hsa-miR-17-5p/UBC, RPL7AP11/hsa-miR-20b-5p/UBC) were obtained from the network. Conclusions: Our findings have provided a novel perspective on the potential roles of exosomal-associated ceRNA network regulating the pathogenesis of CHD.

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Identifying Serum Exosomal-Associated lncRNA/circRNA-miRNA-mRNA Network in Coronary Heart Disease

10.21203/rs.3.rs-131078/v2 ◽

2021 ◽

Author(s):

Jia Mao ◽

Yufei Zhou ◽

Licheng Lu ◽

Ping Zhang ◽

Runhua Ren ◽

...

Keyword(s):

Coronary Heart Disease ◽

Heart Disease ◽

Regulation Of Gene Expression ◽

Cellular Protein ◽

Functional Enrichment ◽

Signal Pathways ◽

Ppi Network ◽

Hub Genes ◽

Cerna Network ◽

Normal Controls

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Abstract 62: Molecular Basis of Regulatory Variation at Coronary Heart Disease-Associated Loci

Arteriosclerosis Thrombosis and Vascular Biology ◽

10.1161/atvb.35.suppl_1.62 ◽

2015 ◽

Vol 35 (suppl_1) ◽

Author(s):

Clint L Miller ◽

Milos Pjanic ◽

Jonathan D Lee ◽

Boxiang Liu ◽

William J Greenleaf ◽

...

Keyword(s):

Coronary Heart Disease ◽

Heart Disease ◽

Chromatin Immunoprecipitation ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Regulatory Mechanisms ◽

Tgf Beta ◽

Genome Wide ◽

Context Specific ◽

Accessible Chromatin

Genome-wide association studies have identified 46 replicated genetic loci for coronary heart disease (CHD), and 104 loci associated at a 5% false discovery rate. However, the regulatory mechanisms of these associations largely remain elusive. Given that the majority of these CHD-associated loci reside in non-coding regions, they are predicted to function via context-specific gene regulation. Recent high-throughput assays of regulatory function include the assay for transposase-accessible chromatin using sequencing (ATAC-seq) and chromatin immunoprecipitation-sequencing (ChIP-seq). ATAC-seq utilizes a Tn5 transposase to fragment and tag accessible DNA sequences, which are often coupled to transcription factor occupancy identified by ChIP-seq. Importantly, this assay may reveal the spatio-temporal regulatory profiles in limited numbers of primary cells. Using ATAC-seq in human coronary artery smooth muscle cells (HCASMC) we identified 147,173 accessible chromatin peaks in control versus 198,976 peaks in TGF-beta-stimulated cells (136,446 shared peaks). Using de novo motif enrichment analysis we identified significant enrichment of specific AP-1 family members (29.2% vs. 5.1% background), chromatin remodeling, and SMC differentiation transcription factors. Using functional enrichment analysis of ChIP-seq and CHD-overlapping regions we observed enrichment of the hypoxia inducible factor 1 (HIF-1) and TGF-beta signaling pathways (1.5x10 -22 and 5.6x10 -18 , respectively) and relevant phenotypes, including cell migration and blood vessel morphology. Finally, we utilized these regulatory maps to explore the causal mechanisms underlying CHD-associated variants at four loci using haplotype-specific chromatin immunoprecipitation (haploChIP) and luciferase reporter assays. Taken together, these results suggest that genome-wide approaches such as ATAC-seq can be leveraged to map context-specific regulatory mechanisms of non-coding variants associated with complex diseases such as CHD, and reveal new biological and molecular insights into targeting heritable disease risk.

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Integrated analysis identifies a pathway-related competing endogenous RNA network in the progression of pancreatic cancer

BMC Cancer ◽

10.1186/s12885-020-07470-4 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Fuqiang Zu ◽

Peng Liu ◽

Huaitao Wang ◽

Ting Zhu ◽

Jian Sun ◽

...

Keyword(s):

Pancreatic Cancer ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Tumor Formation ◽

Functional Enrichment ◽

Integrated Analysis ◽

Competing Endogenous Rna ◽

Hub Genes ◽

Cerna Network ◽

Competing Endogenous Rna Network

Abstract Background It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression. Methods We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC. Results A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC. Conclusion Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

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Xiaoyu Xiezhuo Drink Protects against Ischemia-Reperfusion Acute Kidney Injury in Aged Mice through Inhibiting the TGF-β1/Smad3 and HIF1 Signaling Pathways

BioMed Research International ◽

10.1155/2021/9963732 ◽

2021 ◽

Vol 2021 ◽

pp. 1-19

Author(s):

Qingqing Ye ◽

Hongbo Chen ◽

Hongzhen Ma ◽

Xiaojun Xiang ◽

Shouci Hu ◽

...

Keyword(s):

Drug Targets ◽

Ischemia Reperfusion ◽

Kidney Injury ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Ppi Network ◽

Hub Genes ◽

Aged Mice ◽

Tgf Β1

Acute kidney injury (AKI) is responsible for significant mortality among hospitalized patients that is especially troubling aged people. An effective self-made Chinese medicine formula, Xiaoyu Xiezhuo Drink (XXD), displayed therapeutic effects on AKI. However, the compositions and underlying mechanisms of XXD remain to be elucidated. In this study, we used the ultra-high-performance liquid chromatography method coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS) to investigate the chemical components in XXD. Then, the absorbable components of XXD were identified based on the five principles and inputted into the SwissTargetPrediction and STITCH databases to identify the drug targets. AKI-related targets were collected from the GenCLiP 3, GeneCards, and DisGeNET databases. The crossover genes of XXD and AKI were identified for functional enrichment analysis. The protein-protein interaction (PPI) network of crossover genes was constructed, followed by the identification of hub genes. Subsequently, the effects and potential mechanisms of XXD on AKI predicted by the network pharmacology and bioinformatics analyses were experimentally validated in ischemia-reperfusion (I/R) injury-induced AKI aged mouse models. A total of 122 components in XXD were obtained; among them, 58 components were found that could be absorbed in the blood. There were 800 potential drug targets predicted from the 58 absorbable components in AKI which shared 36 crossover genes with AKI-related targets. The results of functional enrichment analysis indicated that crossover genes mostly associated with the response to oxidative stress and the HIF1 signaling pathway. In the PPI network analysis, 12 hub genes were identified, including ALB, IL-6, TNF, TP53, VEGFA, PTGS2, TLR4, NOS3, EGFR, PPARG, HIF1A, and HMOX1. In AKI aged mice, XXD prominently alleviated I/R injury-induced renal dysfunction, abnormal renal pathological changes, and cellular senescence, inflammation, and oxidative damage with a reduction in the expression level of the inflammatory mediator, α-SMA, collagen-1, F4/80, TP53, VEGFA, PTGS2, TLR4, NOS3, EGFR, PPARG, HIF1A, ICAM-1, TGF-β1, Smad3, and p-Smad3 and an increase of nephridial tissue p-H3, Ki67, HMOX1, MMP-9, and Smad7 levels. In summary, our findings suggest that XXD has renoprotective effects against AKI in aged mice via inhibiting the TGF-β1/Smad3 and HIF1 signaling pathways.

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Identification of Potentially Functional Circular RNAs hsa_circ_0070934 and hsa_circ_0004315 as Prognostic Factor of Hepatocellular Carcinoma by Integrated Bioinformatics Analysis

10.21203/rs.3.rs-948198/v1 ◽

2021 ◽

Author(s):

Pejman Morovat ◽

Saman Morovat ◽

Arash M. Ashrafi ◽

Shahram Teimourian

Keyword(s):

Gene Expression ◽

Hepatocellular Carcinoma ◽

Prognostic Factor ◽

Sequence Data ◽

Functional Enrichment ◽

Differentially Expressed ◽

Circular Rnas ◽

Ppi Network ◽

Hub Genes ◽

Cerna Network

Abstract Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, which has a high mortality rate and poor treatment outcomes with yet unknown molecular basis. It seems that gene expression plays a pivotal role in the pathogenesis of the disease. Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in various malignancies by acting as competitive endogenous RNAs (ceRNAs). However, the potential pathogenesis roles of the ceRNA network among circRNA/miRNA/mRNA in HCC are unclear. In this study, first, the HCC circRNA expression data were obtained from three Gene Expression Omnibus microarray datasets (GSE164803, GSE94508, GSE97332), and the differentially expressed circRNAs (DECs) were identified using R limma package. Also, the liver hepatocellular carcinoma (LIHC) miRNA and mRNA sequence data were retrieved from TCGA, and differentially expressed miRNAs (DEMIs) and mRNAs (DEGs) were determined using the R DESeq2 package. Second, CSCD website was used to uncover the binding sites of miRNAs on DECs. The DECs' potential target miRNAs were revealed by conducting an intersection between predicted miRNAs from CSCD and downregulated DEMIs. Third, some related genes were uncovered by intersecting targeted genes predicted by miRWalk and targetscan online tools with upregulated DEGs. The ceRNA network was then built using the Cytoscape software. The functional enrichment and the overall survival time of these potential targeted genes were analyzed, and a PPI network was constructed in the STRING database. Network visualization was performed by Cytoscape, and ten hub genes were detected using the CytoHubba plugin tool. Four DECs (hsa_circ_0000520, hsa_circ_0008616, hsa_circ_0070934, hsa_circ_0004315) were obtained and six miRNAs (hsa-miR-542-5p, hsa-miR-326, hsa-miR-511-5p, hsa-miR-195-5p, hsa-miR-214-3p, and hsa-miR-424-5p) which are regulated by the above DECs were identified. Then 543 overlapped genes regulated by six miRNAs mentioned above were predicted. Functional enrichment analysis showed that these genes are mostly associated with cancer regulation functions. Ten hub genes (TTK،AURKB, KIF20A، KIF23، CEP55، CDC6، DTL، NCAPG، CENPF، PLK4) have been screened from the PPI network of the 204 survival-related genes. KIF20A, NCAPG, TTK, PLK4, and CDC6 were selected for the highest significant p-values. In the end, a circRNA-miRNA-mRNA regulatory axis was established for five final selected hub genes. This study implies the potential pathogenesis of the obtained network and proposes that the two DECs (has_circ_0070934 and has_circ_0004315) may be important prognostic factor for HCC.

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Using Weighted Gene Co-Expression Network Analysis to Identify Key Genes Related to the Onset of Preeclampsia

10.21203/rs.3.rs-87182/v1 ◽

2020 ◽

Author(s):

Xinyang Shen ◽

Zhijian Wang ◽

Zhirui Zeng ◽

Zhenqin Huang ◽

Xiaowei Huang ◽

...

Keyword(s):

Enrichment Analysis ◽

Diagnostic Value ◽

Functional Enrichment ◽

Immune Response Gene ◽

Control Group ◽

Ppi Network ◽

Hub Genes ◽

Ontology Term ◽

Gene Data ◽

Core Genes

Abstract Background: Preeclampsia is a form of hypertension in pregnancy, which induced by complicated factors. However, the pathogenesis of the disease is unclear. The present study was aimed to discover the critical biomarkers associated with the occurrence and development of preeclampsia. Methods：Gene data profile GSE75010 was downloaded from the Gene Expression Omnibus (GEO) database and used as discovery cohort to establish a WGCNA network determining significant modules which associated with clinical traits. Subsequently, functional enrichment analysis, pathway analysis and protein-protein interaction (PPI) network construction were performed on the core genes in significant modules to identify hub genes. Then, gene data profile GSE25906 was used as verified cohort to determine their diagnostic value of hub genes. The protein expression levels of these hub genes in preeclampsia and control placental tissues were verified using immunohistochemistry method. Finally, GSEA was performed to analyze their enrichment pathways. Results: Total 33 co-expression modules were identified after the establishment of WGCNA, of which 4 gene modules were identified as significant modules because they were related to multiple (>3) clinical traits. Total 75 core genes in significant modules were analyzed, and results showed that they were mainly enriched in adaptive immune response (Gene Ontology term) and platelet activation (Kyoto Encyclopedia of Genes and Genomes term). Finally, a total of 5 genes including TYROBP, PLEK, LCP2, HCK, ITGAM were identified as hub genes which scored high in PPI network and had high diagnostic value. Furthermore, the protein level of these 5 genes in placental tissues of preeclampsia was lower than that of the control group. Moreover, these 5 genes were all enriched in 17 pathways, including autoimmunity pathway. Conclusions：These 5 genes (TYROBP, PLEK, LCP2, HCK, ITGAM) may be closely related to the pathogenesis of preeclampsia, which may also help the diagnosis and therapy of preeclampsia.

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Construction of Circular RNA–MicroRNA–Messenger RNA Regulatory Network of Recurrent Implantation Failure to Explore Its Potential Pathogenesis

Frontiers in Genetics ◽

10.3389/fgene.2020.627459 ◽

2021 ◽

Vol 11 ◽

Author(s):

Jiahuan Luo ◽

Li Zhu ◽

Ning Zhou ◽

Yuanyuan Zhang ◽

Lirong Zhang ◽

...

Keyword(s):

Messenger Rna ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Implantation Failure ◽

Ppi Network ◽

Recurrent Implantation Failure ◽

Hub Genes ◽

Hub Gene ◽

Gene Regulatory

Background: Many studies on circular RNAs (circRNAs) have recently been published. However, the function of circRNAs in recurrent implantation failure (RIF) is unknown and remains to be explored. This study aims to determine the regulatory mechanisms of circRNAs in RIF.Methods: Microarray data of RIF circRNA (GSE147442), microRNA (miRNA; GSE71332), and messenger RNA (mRNA; GSE103465) were downloaded from the Gene Expression Omnibus (GEO) database to identify differentially expressed circRNA, miRNA, and mRNA. The circRNA–miRNA–mRNA network was constructed by Cytoscape 3.8.0 software, then the protein–protein interaction (PPI) network was constructed by STRING database, and the hub genes were identified by cytoHubba plug-in. The circRNA–miRNA–hub gene regulatory subnetwork was formed to understand the regulatory axis of hub genes in RIF. Finally, the Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the hub genes were performed by clusterProfiler package of Rstudio software, and Reactome Functional Interaction (FI) plug-in was used for reactome analysis to comprehensively analyze the mechanism of hub genes in RIF.Results: A total of eight upregulated differentially expressed circRNAs (DECs), five downregulated DECs, 56 downregulated differentially expressed miRNAs (DEmiRs), 104 upregulated DEmiRs, 429 upregulated differentially expressed genes (DEGs), and 1,067 downregulated DEGs were identified regarding RIF. The miRNA response elements of 13 DECs were then predicted. Seven overlapping miRNAs were obtained by intersecting the predicted miRNA and DEmiRs. Then, 56 overlapping mRNAs were obtained by intersecting the predicted target mRNAs of seven miRNAs with 1,496 DEGs. The circRNA–miRNA–mRNA network and PPI network were constructed through six circRNAs, seven miRNAs, and 56 mRNAs; and four hub genes (YWHAZ, JAK2, MYH9, and RAP2C) were identified. The circRNA–miRNA–hub gene regulatory subnetwork with nine regulatory axes was formed in RIF. Functional enrichment analysis and reactome analysis showed that these four hub genes were closely related to the biological functions and pathways of RIF.Conclusion: The results of this study provide further understanding of the potential pathogenesis from the perspective of circRNA-related competitive endogenous RNA network in RIF.

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Integrated analysis identifies a pathway-related competing endogenous RNA network in the progression of Pancreatic cancer

10.21203/rs.3.rs-36637/v3 ◽

2020 ◽

Author(s):

Fuqiang Zu ◽

Peng Liu ◽

Huaitao Wang ◽

Ting Zhu ◽

Jian Sun ◽

...

Keyword(s):

Pancreatic Cancer ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Tumor Formation ◽

Functional Enrichment ◽

Integrated Analysis ◽

Competing Endogenous Rna ◽

Hub Genes ◽

Cerna Network ◽

Competing Endogenous Rna Network

Abstract Background: It is well acknowledged that cancer-related pathways play pivotal roles in the progression of pancreatic cancer (PC). Employing Integrated analysis, we aim to identify the pathway-related ceRNA network associated with PC progression.Methods: We divided eight GEO datasets into three groups according to their platform, and combined TCGA and GTEx databases as a group. Additionally, we screened out the differentially expressed genes (DEGs) and performed functional enrichment analysis in each group, and recognized the top hub genes in the most enriched pathway. Furthermore, the upstream of miRNAs and lncRNAs were predicted and validated according to their expression and prognostic roles. Finally, the co-expression analysis was applied to identify a pathway-related ceRNA network in the progression of PC.Results: A total of 51 significant pathways that common enriched in all groups were spotted. Enrichment analysis indicated that pathway in cancer was greatly linked with tumor formation and progression. Next, the top 20 hug genes in this pathway were recognized, and stepwise prediction and validation from mRNA to lncRNA, including 11 hub genes, 4 key miRNAs, and 2 key lncRNAs, were applied to identify a meaningful ceRNA network according to ceRNA rules. Ultimately, we identified the PVT1/miR-20b-/CCND1 axis as a promising pathway-related ceRNA axis in the progression of PC.Conclusion: Overall, we elucidate the pathway-related ceRNA regulatory network of PVT1/miR-20b-/CCND1 in the progression of PC, which can be considered as therapeutic targets and encouraging prognostic biomarkers for PC.

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Identification Of Putative Gene Signatures Associated With Diagnosis And Prognosis Of Breast Cancer

Clinical & Investigative Medicine ◽

10.25011/cim.v44i3.37194 ◽

2021 ◽

Vol 44 (3) ◽

pp. E45-54

Author(s):

Chao Tan ◽

Fang Zuo ◽

Mingqian Lu ◽

Sai Chen ◽

Zhenzhen Tian ◽

...

Keyword(s):

Risk Model ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Support Vector ◽

Ppi Network ◽

Hub Genes ◽

Putative Gene ◽

Network Analyses ◽

Cluster 2

Purpose: This study aimed to identify potential diagnostic and therapeutic biomakers for the development ofbreast cancer (BC). Methods: GSE86374 dataset containing 159 samples was acquired from the Gene Expression Omnibus (GEO) database followed by differentially expressed genes (DEGs) identification and cluster analysis. Corresponding functional enrichment and protein-protein interaction (PPI) network analyses were performed to identify hub genes. Prognostic evaluation using clinical information obtained from TCGA database and hub genes was conducted to screen for crucial indicators for BC progression. The risk model was established and validated. Results: In total, 186 DEGs were identified and grouped into four clusters: 96 in cluster 1; 69 in cluster 2; 16 in cluster 3; and 5 in cluster 4. Functional enrichment analysis showed that DEGs, including ADH1B in cluster 1, were dramatically enriched in the tyrosine and drug metabolism pathways, while genes in cluster 2, including SPP1 and RRM2, played crucial roles in PI3K-Akt and p53 signalling pathway. SPP1 and RRM2 served as hub genes in the PPI network, resulting in an support vector machine classifier with good accuracy and specificity.Ad ditionally, the results of prognostic analysis suggest that age, metastasis stage, SPP1 and ADH1B were correlated with risk of BC, which was validated by using the established risk model analysis. Conclusion: SPP1, RRM2 and ADH1B appear to play vital roles in the development of BC. Age and TNM stage were also preferentially associated with risk of developing BC. Evaluation of the risk model based on larger sample size and further experimental validation are required.

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