scholarly journals Comprehensive Analysis of Aberrantly Expressed Profiles of ncRNAs Revealed lncRNA AGPAT4-IT1 is a Potential Prognostic Marker for Breast Cancer Metastasis

2020 ◽  
Author(s):  
Feng chun Zhang ◽  
ning ning yan ◽  
Ming jun Li ◽  
Ying chun Xu ◽  
Xing ya Li
Keyword(s):  
Breast Cancer ◽  
Prognostic Marker ◽  
Cancer Metastasis ◽  
Breast Cancer Metastasis ◽  
Bioinformatics Analyses ◽  
Functional Roles ◽  
Kaplan Meier ◽  
Non Coding Rnas ◽  
Microarray Analyses ◽  
The Relationship

Abstract Aims: we investigated the relationship between long non-coding RNAs (lncRNAs) and breast cancer lung metastasis (BCLM). Methods: We performed lncRNA microarray analyses to establish the lncRNA profile of BCLM. Bioinformatics analyses were carried out to analyzed functional roles of identified lncRNAs. Kaplan-meier analysis was conducted to determine the relation between lncRNA AGPAT4-IT1 and prognosis of breast cancer. Results: We found 317 upregulated and 166 downregulated lncRNAs in BCLM group. We showed AGPAT4-IT1 was positively correlated with its parental gene APGAT4. Furthermore, we suggested AGPAT4-IT1 were highly expressed in higher tumour grade and predicted poorer prognosis. Conclusions: These findings provide evidence for exploring the mechanisms of BCLM and indicate AGPAT4-IT1 is a prospective prognostic marker for breast cancer metastasis.

Microarray to reveal LncRNA profile and the role of lncCUEDC1 in BCSCs.

2018 ◽  
Vol 36 (5_suppl) ◽  
pp. 3-3
Author(s):  
Fengchun Zhang ◽  
Ying chun Xu ◽  
Ning Yan
Keyword(s):  
Breast Cancer ◽  
Cultured Cells ◽  
Bioinformatics Analyses ◽  
Functional Roles ◽  
Functional Activities ◽  
Non Coding Rnas ◽  
Microarray Analyses ◽  
First Time

3 Background: Recently, a growing amount of reports have shown that long non-coding RNAs (lncRNAs) are involved in breast cancer development, progression and metastasis. However, the correlation between lncRNAs and breast cancer stem cells (BCSCs) has been poorly explored. Methods: We initially isolated BCSCs from mammosphere-cultured cells; then, microarray analyses were carried out to detect the lncRNA signature in BCSCs. In addition, bioinformatics analyses, including Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), were consulted to explore the functional roles of lncRNAs on BCSCs. Results: A total of 142 aberrantly expressed lncRNAs in BCSCs were identified, and of those lncRNAs, 25 were downregulated and 117 were upregulated compared to non-BCSCs. In addition, some of these lncRNAs were randomly selected and verified by RT-PCR and sanger sequencing. Notably, bioinformatics data showed that the lncRNAs that were detected were largely associated with stemness-related signalling pathways. Additionally, an interacting network between lncRNAs and its mRNAs was constructed to further depict the lncRNA functional activities. Furthermore, we found that lncCUEDC1 negatively regulated phenotype and biological functions of BCSCs in vitro. Conclusions: Our work establishes the lncRNAs signature in BCSCs for the first time. These findings provide us with evidence to explore the functionalities of lncRNAs in BCSCs and indicate that lncCUED1 is a prospective target for BCSCs.

scholarly journals LIFR is a breast cancer metastasis suppressor upstream of the Hippo-YAP pathway and a prognostic marker

2012 ◽  
Vol 18 (10) ◽  
pp. 1511-1517 ◽  
Author(s):  
Dahu Chen ◽  
Yutong Sun ◽  
Yongkun Wei ◽  
Peijing Zhang ◽  
Abdol Hossein Rezaeian ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Marker ◽  
Cancer Metastasis ◽  
Breast Cancer Metastasis ◽  
Metastasis Suppressor ◽  
Breast Cancer Metastasis Suppressor

scholarly journals Long non-coding RNAs in breast cancer metastasis

2020 ◽  
Vol 5 (4) ◽  
pp. 208-218 ◽  
Author(s):  
Priya Mondal ◽  
Syed Musthapa Meeran
Keyword(s):  
Breast Cancer ◽  
Cancer Metastasis ◽  
Breast Cancer Metastasis ◽  
Non Coding Rnas

Identification of hub genes to regulate breast cancer metastasis to brain by bioinformatics analyses

2018 ◽  
Vol 120 (6) ◽  
pp. 9522-9531 ◽  
Author(s):  
Dongyang Tang ◽  
Xin Zhao ◽  
Li Zhang ◽  
Zhiwei Wang ◽  
Cheng Wang
Keyword(s):  
Breast Cancer ◽  
Cancer Metastasis ◽  
Breast Cancer Metastasis ◽  
Hub Genes ◽  
Bioinformatics Analyses

scholarly journals Evaluation of the TRIP13 level in breast cancer and insights into potential molecular pathways

2020 ◽  
Author(s):  
Jin Lan ◽  
Jingzhan Huang ◽  
Yuan Gao ◽  
Jingbo Sun ◽  
Longshan Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Therapeutic Target ◽  
Cancer Metastasis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Bioinformatic Analysis ◽  
Breast Cancer Metastasis ◽  
Gene Set Enrichment Analysis ◽  
Protein Protein Interaction ◽  
Kaplan Meier

Abstract Background: TRIP13 is a member belonging to a large AAA+ ATPases protein super family. Emerging evidences had shown that TRIP13 may serve as an oncogene However, the function of TRIP13 in BC has not yet been elucidated. Methods: By utilizing the multiple database across BC, we presented the expression of TRIP13 in BC tissue and normal control. We then verified the expression of TRIP13 in patients with BC by immunohistochemical (IHC) staining. Kaplan-Meier plots were used to perform the survival analysis. Further, gene ontology (GO) analysis, gene set enrichment analysis (GSEA), and PPI (protein-protein interaction) network were performed to explore the biological function and potential regular pathway of TRIP13 in BC. Results: The multiple database and immunohistochemical (IHC) showed that higher TRIP13 expression in BC tissue compared to normal tissue. TRIP13 was highly exprssed in lung metastasis lesion compared with primary tumor in our BALB/C mice 4T1 BC models. Kaplan-Meier plots also revealed that high TRIP13 expression correlated to poor survival in patients with BC. Moreover, GSEA analysis revealed that TRIP13 was primarily enriched in the processes of cell division and proliferation. Finally 10 hub genes with a high score of connectivity were filtered from the PPI network, including MAD2L1, CDC20, CDC5L, CDK1, CCNA2, BUB1B, RAD51, SPO11, KIF11 and AURKB. Conclusion: High TRIP13 expression predicted poor prognosis and contributed tumor growth and metastasis in the BC. Thus, ARL3 may be a prognostic marker and therapeutic target for glioma. TRIP13 may be a favorable biomarker and effective therapeutic target for BC. Keywords: TRIP13; breast cancer; metastasis; bioinformatic analysis, prognosis

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