In silico analysis of the molecular mechanism of postmenopausal osteoporosis

MiR-331-3p facilitates osteoporosis and may promote osteoporotic fractures by modulating NRP2 expression

BACKGROUND

Osteoporosis (OP) is a high-incidence bone disease that is prone to osteoporotic fractures (OF), so it has attracted widespread attention.

AIM

This study investigated the specific expression and role of miR-331 in patients with OP and OF. The findings have profound implications for the clinical prevention and treatment of these conditions.

METHODS

The study included 60 OP patients, 46 OF patients, and 40 healthy controls. The expression level of miR-331-3p was detected using RT-qPCR. BMP2 was used to stimulate differentiation in MC3T3-E1 cells. After induction, the expression activity of osteogenic differentiation-related gene markers was detected using RT-qPCR. The target gene analysis was conducted using a luciferase reporter assay.

RESULTS

The levels of miR-331-3p were significantly elevated, while NRP2 levels were significantly reduced in OF patients. Post-surgery, miR-331-3p levels decreased over time. MiR-331-3p was found to negatively regulate the luciferase activity of NPR2 in MC3T3-E1 cells. Furthermore, overexpression of miR-331-3p inhibited cell proliferation and decreased the levels of osteoblast differentiation markers.

CONCLUSION

The up-regulation of miR-331-3p can promote OP and might also encourage the occurrence of OF by regulating NRP2. However, this needs further verification.

Comparisons of gene expression between peripheral blood mononuclear cells and bone tissue in osteoporosis

Osteoporosis (OP) is one of the major public health problems in the world. However, the biomarkers between the peripheral blood mononuclear cells (PBMs) and bone tissue for prognosis of OP have not been well characterized. This study aimed to explore the similarities and differences of the gene expression profiles between the PBMs and bone tissue and identify potential genes, transcription factors (TFs) and hub proteins involved in OP. The patients were enrolled as an experimental group, and healthy subjects served as normal controls. Human whole-genome expression chips were used to analyze gene expression profiles from PBMs and bone tissue. And the differentially expressed genes (DEGs) were subsequently studied using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. The above DEGs were constructed into protein-protein interaction network. Finally, TF-DEGs regulation networks were constructed. Microarray analysis revealed that 226 DEGs were identified between OP and normal controls in the PBMs, while 2295 DEGs were identified in the bone tissue. And 13 common DEGs were obtained by comparing the 2 tissues. The Gene Ontology analysis indicated that DEGs in the PBMs were more involved in immune response, while DEGs in bone were more involved in renal response and urea transmembrane transport. And the Kyoto Encyclopedia of Genes and Genomes analysis indicated almost all of the pathways in the PBMs were overlapped with those in the bone tissue. Furthermore, protein-protein interaction network presented 6 hub proteins: PI3K1, APP, GNB5, FPR2, GNG13, and PLCG1. APP has been found to be associated with OP. Finally, 5 key TFs were identified by TF-DEGs regulation networks analysis (CREB1, RUNX1, STAT3, CREBBP, and GLI1) and were supposed to be associated with OP. This study enhanced our understanding of the pathogenesis of OP. PI3K1, GNB5, FPR2, GNG13, and PLCG1 might be the potential targets of OP.

Circulating miRNAs associated with bone mineral density in healthy adult baboons

MicroRNAs (miRNAs) regulate gene expression post-transcriptionally and circulate in the blood, making them attractive biomarkers of disease state for tissues like bone that are challenging to interrogate directly. Here, we report on five miRNAs-miR-197-3p, miR-320a, miR-320b, miR-331-5p, and miR-423-5p-associated with bone mineral density (BMD) in 147 healthy adult baboons. These baboons ranged in age from 15 to 25 years (45-75 human equivalent years) and 65% were female with a broad range of BMD values including a minority of osteopenic animals. miRNAs were generated via RNA sequencing from buffy coats collected at necropsy and areal BMD (aBMD) measured postmortem via dual-energy X-ray absorptiometry (DXA) of the lumbar vertebrae. Differential expression analysis controlled for the underlying pedigree structure of these animals to account for genetic variation which may drive miRNA abundance and aBMD values. While many of these miRNAs have been associated with the risk of osteoporosis in humans, this finding is of interest because the cohort represents a model of normal aging and bone metabolism rather than a disease cohort. The replication of miRNA associations with osteoporosis or other bone metabolic disorders in animals with healthy aBMD suggests an overlap in normal variation and disease states. We suggest that these miRNAs are involved in the regulation of cellular proliferation, apoptosis, and protein composition in the extracellular matrix throughout life; and age-related dysregulation of these systems may lead to disease. These miRNAs may be early indicators of progression to disease in advance of clinically detectible osteoporosis.

Identification of ferroptosis-associated biomarkers for the potential diagnosis and treatment of postmenopausal osteoporosis

OBJECTIVE

Postmenopausal osteoporosis (PMOP) is one of the most commonly occurring conditions worldwide and is characterized by estrogen deficiency as well as persistent calcium loss with age. The aim of our study was to identify significant ferroptosis-associated biomarkers for PMOP.

METHODS AND MATERIALS

We obtained our training dataset from the Gene Expression Omnibus (GEO) database using GSE56815 expression profiling data. Meanwhile, we extracted ferroptosis-associated genes for further analysis. Differentially expressed ferroptosis-associated genes (DEFAGs) between OP patients and normal controls were selected using the "limma" package. We established a ferroptosis-associated gene signature using training models, specifically, random forest (RF) and support vector machine (SVM) models. It was further validated in another dataset (GSE56814) which also showed a high AUC: 0.98, indicating high diagnostic value. Using consensus clustering, the OP patient subtypes were identified. A ferroptosis associated gene (FAG)-Scoring scheme was developed by PCA. The important candidate genes associated with OP were also compared between different ferrclusters and geneclusters.

RESULTS

There were significant DEFAGs acquired, of which five (HMOX1, HAMP, LPIN1, MAP3K5, FLT3) were selected for establishing a ferroptosis-associated gene signature. Analyzed from the ROC curve, our established RF model had a higher AUC value than the SVM model (RF model AUC:1.00). Considering these results, the established RF model was chosen to be the most appropriate training model. Later, based on the expression levels of the five DEFAGs, a clinical application nomogram was established. The OP patients were divided into two subtypes (ferrcluster A, B and genecluster A, B, respectively) according to the consensus clustering method based on DEFAGs and differentially expressed genes (DEGs). Ferrcluster B and genecluster B had higher ferroptosis score than ferrcluster A and genecluster A, respectively. The expression of COL1A1 gene was significantly higher in ferrcluster B and gencluster B compared with ferrcluster A and gencluster A, respectively, while there is no statistical difference in term of VDR gene, COL1A2 genes, and PTH gene expressions between ferrcluster A and B, together with gencluster A and B.

CONCLUSIONS

On the basis of five explanatory variables (HMOX1, HAMP, LPIN1, MAP3K5 and FLT3), we developed a diagnostic ferroptosis-associated gene signature and identified two differently categorized OP subtypes that may potentially be applied for the early diagnosis and individualized treatment of PMOP. The ER gene, VDR gene, IL-6 gene, COL1A1 and COL1A2 genes, and PTH gene are important candidate gene of OP, however, more studies are still anticipated to further elucidate the relationship between these genes and ferroptosis in OP.

Identification of Potential Osteoporosis miRNA Biomarkers Using Bioinformatics Approaches

Osteoporosis is a degenerative osteoarthropathy commonly found in old people and postmenopausal women. Many studies showed that microRNAs (miRNAs) can regulate the expression of osteoporosis-related genes and are abnormally expressed in patients with osteoporosis. miRNAs therefore have the potential to serve as biomarkers of osteoporosis. In this study, the limma package was used for the differential expression analysis of mRNA expression profiles and 357 significantly differentially expressed genes (DEGs) were obtained. Metascape was used for functional enrichment analysis of DEGs. The result revealed that DEGs were mainly enriched in signaling pathways like MAPK6/MAPK4. Based on the STRING database, the protein-protein interaction (PPI) network of DEGs was constructed. MCODE was used to analyze the functional subsets, and a key functional subset composed of 9 genes was screened out. In addition, the miRNA-mRNA regulatory interaction network (RegIN) was analyzed by the CyTargetLinker plugin, which generated 55 miRNA-mRNA regulatory interactions. Through literature searching, the osteoporosis-related gene FOXO1 in the key functional subset was determined to be the main object of the study. In qRT-PCR assay, the expression of the predicted miRNAs was tested in peripheral blood mononuclear cells of mice with osteoporosis, in which 13 miRNAs were remarkably highly expressed. All in all, this study, based on bioinformatics analysis and testing assay of miRNA expression, determined the potential biomarkers of osteoporosis.

Identification of Potential Therapeutic Targets and Molecular Regulatory Mechanisms for Osteoporosis by Bioinformatics Methods

BACKGROUND

Osteoporosis is characterized by low bone mass, deterioration of bone tissue structure, and susceptibility to fracture. New and more suitable therapeutic targets need to be discovered.

METHODS

We collected osteoporosis-related datasets (GSE56815, GSE99624, and GSE63446). The methylation markers were obtained by differential analysis. Degree, DMNC, MCC, and MNC plug-ins were used to screen the important methylation markers in PPI network, then enrichment analysis was performed. ROC curve was used to evaluate the diagnostic effect of osteoporosis. In addition, we evaluated the difference in immune cell infiltration between osteoporotic patients and control by ssGSEA. Finally, differential miRNAs in osteoporosis were used to predict the regulators of key methylation markers.

RESULTS

A total of 2351 differentially expressed genes and 5246 differentially methylated positions were obtained between osteoporotic patients and controls. We identified 19 methylation markers by PPI network. They were mainly involved in biological functions and signaling pathways such as apoptosis and immune inflammation. HIST1H3G, MAP3K5, NOP2, OXA1L, and ZFPM2 with higher AUC values were considered key methylation markers. There were significant differences in immune cell infiltration between osteoporotic patients and controls, especially dendritic cells and natural killer cells. The correlation between MAP3K5 and immune cells was high, and its differential expression was also validated by other two datasets. In addition, NOP2 was predicted to be regulated by differentially expressed hsa-miR-3130-5p.

CONCLUSION

Our efforts aim to provide new methylation markers as therapeutic targets for osteoporosis to better treat osteoporosis in the future.

The Role of Chronic Inflammatory Bone and Joint Disorders in the Pathogenesis and Progression of Alzheimer's Disease

Late-onset Alzheimer's Disease (LOAD) is a devastating neurodegenerative disorder that causes significant cognitive debilitation in tens of millions of patients worldwide. Throughout disease progression, abnormal secretase activity results in the aberrant cleavage and subsequent aggregation of neurotoxic Aβ plaques in the cerebral extracellular space and hyperphosphorylation and destabilization of structural tau proteins surrounding neuronal microtubules. Both pathologies ultimately incite the propagation of a disease-associated subset of microglia-the principle immune cells of the brain-characterized by preferentially pro-inflammatory cytokine secretion and inhibited AD substrate uptake capacity, which further contribute to neuronal degeneration. For decades, chronic neuroinflammation has been identified as one of the cardinal pathophysiological driving features of AD; however, despite a number of works postulating the underlying mechanisms of inflammation-mediated neurodegeneration, its pathogenesis and relation to the inception of cognitive impairment remain obscure. Moreover, the limited clinical success of treatments targeting specific pathological features in the central nervous system (CNS) illustrates the need to investigate alternative, more holistic approaches for ameliorating AD outcomes. Accumulating evidence suggests significant interplay between peripheral immune activity and blood-brain barrier permeability, microglial activation and proliferation, and AD-related cognitive decline. In this work, we review a narrow but significant subset of chronic peripheral inflammatory conditions, describe how these pathologies are associated with the preponderance of neuroinflammation, and posit that we may exploit peripheral immune processes to design interventional, preventative therapies for LOAD. We then provide a comprehensive overview of notable treatment paradigms that have demonstrated considerable merit toward treating these disorders.

Searching for valuable differentially expressed miRNAs in postmenopausal osteoporosis by RNA sequencing

AIM

Postmenopausal osteoporosis is a systemic and chronic bone disease in women. In order to understand the pathological mechanism of postmenopausal osteoporosis, we aimed to find the potential differentially expressed miRNAs in the disease.

METHODS

Firstly, RNA sequencing was used to identify differentially expressed miRNAs, followed by the construction of the miRNA-target mRNA regulatory network. Then, Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes were used to analyze the biological function of target mRNAs. Finally, electronic validation of identified differentially expressed miRNAs and target mRNAs was performed.

RESULTS

A total of 33 differentially expressed miRNAs (18 upregulated and 15 downregulated miRNAs) and 6820 miRNA-mRNA pairs were identified. Among which, seven miRNAs with high degree including hsa-miR-17-5p, hsa-miR-1-3p, hsa-miR-193b-3p, hsa-miR-125b-5p, hsa-miR-10b-5p, hsa-miR-100-5p and hsa-miR-30a-3p were obtained in the miRNA-mRNA regulatory network. TGF-beta was the most significantly enriched signaling pathway of target mRNAs. The electronic validation result of hsa-miR-1-3p, hsa-miR-193b-3p, hsa-miR-10b-5p, hsa-miR-100-5p, hsa-miR-133b, hsa-miR-708-5p, CRK, RAB5C, CCND1 and PCYOX1 was consisted with the RNA sequencing analysis.

CONCLUSION

Dysfunctional miRNAs may play significant roles in postmenopausal osteoporosis.

MicroRNA Alterations for Diagnosis, Prognosis, and Treatment of Osteoporosis: A Comprehensive Review and Computational Functional Survey

Osteoporosis (OP) is a systemic bone disease with a series of clinical symptoms. The use of screening biomarkers in OP management is therefore of clinical significance, especially in the era of precision medicine and intelligent healthcare. MicroRNAs (miRNAs) are small, non-coding RNAs with the potential to regulate gene expression at the post-transcriptional level. Accumulating evidence indicates that miRNAs may serve as biomarkers for OP prediction and prevention. However, few studies have emphasized the role of miRNAs in systems-level pathogenesis during OP development. In this article, literature-reported OP miRNAs were manually collected and analyzed based on a systems biology paradigm. Functional enrichment studies were performed to decode the underlying mechanisms of miRNAs in OP etiology and therapeutics in three-dimensional space, i.e., integrated miRNA–gene–pathway analysis. In particular, interactions between miRNAs and three well-known OP pathways, i.e., estrogen–endocrine, WNT/β-catenin signaling, and RANKL/RANK/OPG, were systematically investigated, and the effects of non-genetic factors on personalized OP prevention and therapy were discussed. This article is a comprehensive review of OP miRNAs, and bridges the gap between an understanding of OP pathogenesis and clinical translation.

Medical Treatment for Osteoporosis: From Molecular to Clinical Opinions

Osteoporosis is a major concern all over the world. With aging, a gradual loss of bone mass results in osteopenia and osteoporosis. Heritable factors account for 60–80% of optimal bone mineralization. Modifiable factors, such as weight-bearing exercise, nutrition, body mass, and hormonal milieu, play an important role in the development of osteopenia and osteoporosis in adulthood. Currently, anti-resorptive agents, including estrogen, bisphosphonates, and selective estrogen receptor modulators (SERMs), are the drugs of choice for osteoporosis. Other treatments include parathyroid hormone (PTH) as well as the nutritional support of calcium and vitamin D. New treatments such as tissue-selective estrogen receptor complexes (TSECs) are currently in use too. This review, which is based on a systematic appraisal of the current literature, provides current molecular and genetic opinions on osteoporosis and its medical treatment. It offers evidence-based information to help researchers and clinicians with osteoporosis assessment. However, many issues regarding osteoporosis and its treatment remain unknown or controversial and warrant future investigation.

Identification of hub genes associated with postmenopausal osteoporosis by Gibbs sampling method

Underlying pivotal pathways were identified to reveal potential key genes correlated with postmenopausal osteoporosis (PMOP). The pathways were enriched by Kyoto Encyclopedia of Genes and Genomes (KEGG) with genes intersection greater than 5 based on gene expression profile data, and the acquired pathways were then transformed to Markov chain (MC). Gibbs sampling was conducted to obtain a new MC. Moreover, the average probabilities of each pathway in normal and PMOP were computed via an MC Monte Carlo (MCMC) algorithm, and differential pathways were identified based on probabilities more than 0.7. In addition, frequencies of appearance of pathway genes were counted via MCMC and the hub genes were achieved with the probabilities of gene expression efficiencies in two states. Judging by the gene intersection more than 5, overall 280 pathways were determined. After Gibbs sampling, 2 differential pathways were obtained on the basis of probabilities more than 0.7. Moreover, the hub genes comprising TNNC1, MYL2, and TTN were achieved according to probabilities more than 0.7. The identified pathways and the three hub genes probably are useful for developing approaches for the diagnosis and treatment of PMOP in future preclinical and clinical applications.

Potential Novel Prediction of TMJ-OA: MiR-140-5p Regulates Inflammation Through Smad/TGF-β Signaling

Temporomandibular joint osteoarthritis (TMJ-OA), mainly exhibit extracellular matrix loss and condylar cartilage degradation, is the most common chronic and degenerative maxillofacial osteoarthritis; however, no efficient therapy for TMJ-OA exists due to the poor understanding of its pathological progression. MicroRNA (miR)-140-5p is a novel non-coding microRNAs (miRNAs) that expressed in osteoarthritis specifically. To investigate the molecular mechanisms of miR-140-5p in TMJ-OA, primary mandibular condylar chondrocytes (MCCs) from C57BL/6N mice were treated with interleukins (IL)-1β or transfected with miR-140-5p mimics or inhibitors, respectively. The expression of matrix metallopeptidase (MMP)-13, miR-140-5p, nuclear factor (NF)-kB, Smad3 and transforming growth factor (TGF)-β3 were examined by western blotting or quantitative reverse-transcription polymerase chain reaction (qRT-PCR). The interaction between the potential binding sequence of miR-140-5p and the 3'-untranslated region (3'UTR) of Smad3 mRNA was testified by dual-luciferase assay. Small Interfering RNA of Smad3 (Si-Smad3) was utilized to further identify the role of Smad3 mediated by miR-140-5p. The data showed MMP13, miR-140-5p and NF-kB increased significantly in response to IL-1β inflammatory response in MCCs, meanwhile, Smad3 and TGF-β3 reduced markedly. Moreover, transfection of miR-140-5p mimics significantly suppressed the expression of Smad3 and TGF-β3 in MCCs, while miR-140-5p inhibitors acted in a converse manner. As the luciferase reporter of Smad3 mRNA observed active interaction with miR-140-5p, Smad3 was identified as a direct target of miR-140-5p. Additionally, the expression of TGF-β3 was regulated upon the activation of Smad3. Together, these data suggested that miR-140-5p may play a role in regulating mandibular condylar cartilage homeostasis and potentially serve as a novel prognostic factor of TMJ-OA-like pathology.

Identification of gene biomarkers in patients with postmenopausal osteoporosis

Postmenopausal osteoporosis (PMOP) is a major public health concern worldwide. The present study aimed to provide evidence to assist in the development of specific novel biomarkers for PMOP. Differentially expressed genes (DEGs) were identified between PMOP and normal controls by integrated microarray analyses of the Gene Expression Omnibus (GEO) database, and the optimal diagnostic gene biomarkers for PMOP were identified with LASSO and Boruta algorithms. Classification models, including support vector machine (SVM), decision tree and random forests models, were established to test the diagnostic value of identified gene biomarkers for PMOP. Functional annotations and protein‑protein interaction (PPI) network constructions were also conducted. Integrated microarray analyses (GSE56815, GSE13850 and GSE7429) of the GEO database were employed, and 1,320 DEGs were identified between PMOP and normal controls. An 11‑gene combination was also identified as an optimal biomarker for PMOP by feature selection and classification methods using SVM, decision tree and random forest models. This combination was comprised of the following genes: Dehydrogenase E1 and transketolase domain containing 1 (DHTKD1), osteoclast stimulating factor 1 (OSTF1), G protein‑coupled receptor 116 (GPR116), BCL2 interacting killer, adrenoceptor β1 (ADRB1), neogenin 1 (NEO1), RB binding protein 4 (RBBP4), GPR87, cylicin 2, EF‑hand calcium binding domain 1 and DEAH‑box helicase 35. RBBP4 (degree=12) was revealed to be the hub gene of this PMOP‑specific PPI network. Among these 11 genes, three genes (OSTF1, ADRB1 and NEO1) were speculated to serve roles in PMOP by regulating the balance between bone formation and bone resorption, while two genes (GPR87 and GPR116) may be involved in PMOP by regulating the nuclear factor‑κB signaling pathway. Furthermore, DHTKD1 and RBBP4 may be involved in PMOP by regulating mitochondrial dysfunction and interacting with ESR1, respectively. In conclusion, the findings of the current study provided an insight for exploring the mechanism and developing novel biomarkers for PMOP. Further studies are required to test the diagnostic value for PMOP prior to use in a clinical setting.

MicroRNA and Human Bone Health

The small non‐coding microRNAs (miRNAs) are post‐transcription regulators that modulate diverse cellular process in bone cells. Because optimal miRNA targeting is essential for their function, single‐nucleotide polymorphisms (SNPs) within or proximal to the loci of miRNA (miR‐SNPs) or mRNA (PolymiRTS) could potentially disrupt the miRNA‐mRNA interaction, leading to changes in bone metabolism and osteoporosis. Recent human studies of skeletal traits using miRNA profiling, genomewide association studies, and functional studies started to decipher the complex miRNA regulatory network. These studies have indicated that miRNAs may be a promising bone marker. This review focuses on human miRNA studies on bone traits and discusses how genetic variants affect bone metabolic pathways. Major ex vivo investigations using human samples supported with animal and in vitro models have shed light on the mechanistic role of miRNAs. Furthermore, studying the miRNAs’ signatures in secondary osteoporosis and osteoporotic medications such as teriparatide (TPTD) and denosumab (DMab) have provided valuable insight into clinical management of the disease. © 2018 The Authors. JBMR Plus Published by Wiley Periodicals, Inc. on behalf of the American Society for Bone and Mineral Research

MicroRNA-214-5p/TGF-β/Smad2 signaling alters adipogenic differentiation of bone marrow stem cells in postmenopausal osteoporosis

Postmenopausal osteoporosis (OPM) is a common type of osteoporosis in females. It is a systemic, chronic bone disease that presents as microstructure degradation of osseous tissue, decreased bone mineral density and increased osteopsathyrosis caused by hypoovarianism and reduced estrogen levels in the body following menopause. In the present study, the role of microRNA (miR)-214-5p in the regulation of the expression of bone marrow stem cells (BMSCs) was investigated, and its molecular mechanism of osteogenic induction in vitro was assessed. When dexamethasone-induced adipogenic differentiation was performed, miR-214-5p expression was increased compared with the control group, as determined by RT-qPCR. Furthermore, oil red O staining, RT-qPCR and western blot analysis demonstrated that overexpression of miR-214-5p promoted adipogenic differentiation, inhibited alkaline phosphatase (ALP), runt-related transcription factor 2 (Runx2), osteocalcin (OC) and collagen α-1 (I) chain (COL1A1) mRNA expression, and suppressed transforming growth factor (TGF)-β, phosphorylated (p)-Smad2 and collagen type IV α1 chain (COL4A1) protein expression in BMSCs. Additionally, downregulation of miR-214-5p increased the ALP, Runx2, OC and COL1 mRNA expression and increased TGF-β, Smad2 and COL4A1 protein expression in BMSCs. Furthermore, a TGF-β inhibitor was employed to inhibit TGF-β expression in BMSCs following miR-214-5p downregulation, which led to reduced Smad2, TGF-β and COL4A1 protein expression, and ALP, Runx2, OC and COL1 mRNA expression was also reduced, compared with the miR-214-5p downregulation only group. It was demonstrated that miR-214-5p may weaken osteogenic differentiation of BMSCs through regulating COL4A1. In conclusion, the results of the present study indicated that miR-214-5p may promote the adipogenic differentiation of BMSCs through regulation of the TGF-β/Smad2/COL4A1 signaling pathway, and potentially may be used to develop a novel drug for postmenopausal osteoporosis.

Identifying dysregulated pathways in postmenopausal osteoporosis through investigation of crosstalk between pathways

The present study aimed to identify potential dysregulated pathways to further reveal the molecular mechanisms of postmenopausal osteoporosis (PMOP) based on pathway‑interaction network (PIN) analysis, which considers crosstalk between pathways. Protein‑protein interaction (PPI) data and pathway information were derived from STRING and Reactome Pathway databases, respectively. According to the gene expression profiles, pathway data and PPI information, a PIN was constructed with each node representing a biological pathway. Principal component analysis was used to compute the pathway activity for each pathway, and the seed pathway was selected. Subsequently, dysregulated pathways were extracted from the PIN based on the seed pathway and the increased classification accuracy, which was measured using the area under the curve (AUC) index according to 5‑fold cross validation. A PIN comprising 2,725 interactions was constructed, which was used to detect dysregulated pathways. Notably, the 'mitotic prometaphase' pathway was selected and defined as a seed pathway. Starting with the seed pathway, network‑based analysis successfully identified one pathway set for PMOP comprising eight dysregulated pathways (such as mitotic prometaphase, resolution of sister chromatid cohesion, mRNA splicing and mRNA splicing‑major) with an AUC score of 0.85, which may provide potential biomarkers for targeted therapy for PMOP.