Targeting of BUB1b Gene Expression in Sentinel Lymph Node Biopsies of Invasive Breast Cancer in Iranian Female Patients

Mansouri, Neda; Movafagh, Abolfazl; Sayad, Arezou; Pour, Atefeh Heidary; Taheri, Mohammad; Soleimani, Shahrzad; Shargh, Shohreh Alizadeh; Azargashb, Eznollah; Bazmi, Haleh; Moradi, Hossein Allah; Zandnia, Fatemeh; Hashemi, Mehrdad; Massoudi, Nilofar; Mortazavi-Tabatabaei, Seyed Abdolreza

doi:10.7314/apjcp.2016.17.s3.317

Cited by 16 publications

(9 citation statements)

References 11 publications

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“…Our validation showed that the expression patterns of BUB1B, CCNB1, CDC20, COL10A1, CYCS, EEF1A2, gap junction protein beta 2 (GJB2), KPNA2, PTTG1, RAB31, TTK, UBE2C, ELF5 and STAC2 were the same in all individual patients. These genes have been reported as cancer-related for breast cancer [23–25, 37–45].…”

Section: Discussionmentioning

confidence: 99%

Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer

et al. 2019

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Background Exploration of the genes with abnormal expression during the development of breast cancer is essential to provide a deeper understanding of the mechanisms involved. Transcriptome sequencing and bioinformatics analysis of invasive ductal carcinoma and paracancerous tissues from the same patient were performed to identify the key genes and signaling pathways related to breast cancer development. Methods Samples of breast tumor tissue and paracancerous breast tissue were obtained from 6 patients. Sequencing used the Illumina HiSeq platform. All. Only perfectly matched clean reads were mapped to the reference genome database, further analyzed and annotated based on the reference genome information. Differentially expressed genes (DEGs) were identified using the DESeq R package (1.10.1) and DEGSeq R package (1.12.0). Using KOBAS software to execute the KEGG bioinformatics analyses, enriched signaling pathways of DEGs involved in the occurrence of breast cancer were determined. Subsequently, quantitative real time PCR was used to verify the accuracy of the expression profile of key DEGs from the RNA-seq result and to explore the expression patterns of novel cancer-related genes on 8 different clinical individuals. Results The transcriptomic sequencing results showed 937 DEGs, including 487 upregulated and 450 downregulated genes in the breast cancer specimens. Further quantitative gene expression analysis was performed and captured 252 DEGs (201 downregulated and 51 upregulated) that showed the same differential expression pattern in all libraries. Finally, 6 upregulated DEGs (CST2, DRP2, CLEC5A, SCD, KIAA1211, DTL) and 6 downregulated DEGs (STAC2, BTNL9, CA4, CD300LG, GPIHBP1 and PIGR), were confirmed in a quantitative real time PCR comparison of breast cancer and paracancerous breast tissues from 8 clinical specimens. KEGG analysis revealed various pathway changes, including 20 upregulated and 21 downregulated gene enrichment pathways. The extracellular matrix–receptor (ECM-receptor) interaction pathway was the most enriched pathway: all genes in this pathway were DEGs, including the THBS family, collagen and fibronectin. These DEGs and the ECM-receptor interaction pathway may perform important roles in breast cancer. Conclusion Several potential breast cancer-related genes and pathways were captured, including 7 novel upregulated genes and 76 novel downregulated genes that were not found in other studies. These genes are related to cell proliferation, movement and adhesion. They may be important for research into breast cancer mechanisms, particularly CST2 and CA4. A key signaling pathway, the ECM-receptor interaction signal pathway, was also identified as possibly involved in the development of breast cancer. Electronic supplementary material The online version of this article (10.1186/s11658-019-0162-0) contains supplementary material, which is available to authorized user...

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Section: Discussionmentioning

confidence: 99%

Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer

et al. 2019

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“…Aberrant expression or mutations of BUB1B can cause aneuploidy. Several studies have revealed that BUB1B overexpression is associated with the progression and recurrence of bladder cancer, 36 gastric cancer, 37 breast cancer, 38 , 39 prostate cancer, 40 and other malignancies. There is currently no clear evidence for the relationship between BUB1B and lung cancer.…”

Section: Discussionmentioning

confidence: 99%

Integrated analysis reveals key genes with prognostic value in lung adenocarcinoma

Song

Tan

Xin-huai

et al. 2018

CMAR

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BackgroundLung cancer is one of the most common malignant tumors. Despite advances in lung cancer therapies, prognosis of non-small-cell lung cancer is still unfavorable. The aim of this study was to identify the prognostic value of key genes in lung tumorigenesis.MethodsDifferentially expressed genes (DEGs) were screened out by GEO2R from three Gene Expression Omnibus cohorts. Common DEGs were selected for Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology enrichment analysis. Protein– protein interaction networks were constructed by the STRING database and visualized by Cytoscape software. Hub genes, filtered from the CytoHubba, were validated using the Gene Expression Profiling Interactive Analysis database, and their genomic alterations were identified by performing the cBioportal. Finally, overall survival analysis of hub genes was performed using Kaplan–Meier Plotter.ResultsFrom three datasets, 169 DEGs (70 upregulated and 99 downregulated) were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that upregulated DEGs were significantly enriched in cell cycle, p53 pathway, and extracellular matrix–receptor interactions; the downregulated DEGs were significantly enriched in PPAR pathway and tyrosine metabolism. The protein–protein interaction network consisted of 71 nodes and 305 edges, including 49 upregulated and 22 downregulated genes. The hub genes, including AURKB, BUB1B, KIF2C, HMMR, CENPF, and CENPU, were overexpressed compared with the normal group by Gene Expression Profiling Interactive Analysis analysis, and associated with reduced overall survival in lung cancer patients. In the genomic alterations analysis, two hotspot mutations (S2021C/F and E314K/V) were identified in Pfam protein domains.ConclusionDEGs, including AURKB, BUB1B, KIF2C, HMMR, CENPF, and CENPU, might be potential biomarkers for the prognosis and treatment of lung adenocarcinoma.

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“…Overexpression of BUB1B in prostate cancer cells promotes cell proliferation and migration [ 16 ]. BUB1B was expressed higher in invading metastasized breast cancer cells than in those without metastasis [ 17 ]. BUB1B localizes to centrosomes, physically interacts with PLK1 and inhibits the phosphorylation and kinase activity of PLK1 during interphase [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

Comprehensive analysis of differentially expressed genes associated with PLK1 in bladder cancer

Zhang

Gao

et al. 2017

BMC Cancer

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BackgroundThe significance of PLK1 (polo-like kinase 1) has become increasingly essential as both a biomarker and a target for cancer treatment. Here, we aimed to determine the downstream genes of PLK1 and their effects on the carcinogenesis and progression of bladder cancer.MethodsSpecific siRNA was utilized to silence the target gene expression. The cell proliferation, invasion and migration of bladder cancer cells by MTT assay, BrdU assay and transwell assay. The differential expression genes were identified using Affymetrix HTA2.0 Array. The KEGG, GO and STRING analysis were used to analyze the signaling pathway and protein-protein interaction. Spearman analysis was used to analyze the correlation between protein and protein, between protein and clincopathologic characteristics.ResultsPLK1 siRNA hindered the proliferation, invasion and migration of bladder cancer cells, as determined by the MTT, BrdU and transwell assays. A total of 561 differentially expressed genes were identified using an Affymetrix HTA2.0 Array in PLK1 knockdown T24 cells. According to KEGG, GO and STRING analysis, five key genes (BUB1B, CCNB1, CDC25A, FBXO5, NDC80) were determined to be involved in cell proliferation, invasion and migration. PLK1 knockdown decreased BUB1B, CCNB1, CDC25A and NDC80 expressions but increased FBXO5 expression. BUB1B, CCNB1, CDC25A and NDC80 were positively correlated with cell proliferation, invasion, migration and PLK1 expression in tissues, but FBXO5 was negatively correlated with each of those factors. The results showed that the five genes expressions were significantly correlation with the PLK1 expression in normal bladder tissues and bladder cancer tissues. Four of them (BUB1B, CCNB1, CDC25A, NDC80) were obviously positive correlations with pT stage and metastasis. But FBXO5 was negative correlated with pT stage and metastasis. Furthermore, significant correlations were found between CCNB1 or CDC25A or NDC80 and histological grade; between BUB1B or NDC80 and recurrence.ConclusionFive downstream genes of PLK1 were associated with the regulation of cell proliferation, invasion and migration in bladder cancer. Furthermore, these genes may play important roles in bladder cancer and become important biomarkers and targets for cancer treatment.Electronic supplementary materialThe online version of this article (10.1186/s12885-017-3884-2) contains supplementary material, which is available to authorized users.

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Targeting of BUB1b Gene Expression in Sentinel Lymph Node Biopsies of Invasive Breast Cancer in Iranian Female Patients

Cited by 16 publications

References 11 publications

Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer

Transcriptome profiling revealed multiple genes and ECM-receptor interaction pathways that may be associated with breast cancer

Integrated analysis reveals key genes with prognostic value in lung adenocarcinoma

Comprehensive analysis of differentially expressed genes associated with PLK1 in bladder cancer

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