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Kinase-substrate Edge Biomarkers Provide a More Accurate Prognostic Prediction in er-negative breast cancer

Genomics, Proteomics & Bioinformatics 2020年第5期18卷 525-538页

作者： Yidi Sun Chen Li Shichao Pang Qianlan Yao Luonan Chen Yixue Li Rong Zeng CAS Key Laboratory of Systems Biology CAS Center for Excellence in Molecular Cell ScienceInstitute of Biochemistry and Cell BiologyShanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China University of Chinese Academy of Sciences Shanghai 200031China Deptartment of Statistics School of Mathematical SciencesShanghai Jiao Tong UniversityShanghai 200240China School of Life Sciences and Biotechnology Shanghai Jiao Tong UniversityShanghai 200240China Department of Life Sciences ShanghaiTech UniversityShanghai 201210China CAS Center for Excellence in Animal Evolution and Genetics Chinese Academy of SciencesKunming 650223China Bio-Med Big Data Center Key Laboratory of Computational BiologyCAS-MPG Partner Institute for Computational BiologyShanghai Institute of Nutrition and HealthShanghai Institutes for Biological SciencesChinese Academy of SciencesShanghai 200031China Collaborative Innovation Center for Genetics and Development Fudan UniversityShanghai 200032China Shanghai Center for Bioinformation Technology Shanghai Academy of Science&TechnologyShanghai 201203China Center for Single-Cell Omics School of Public HealthShanghai Jiao Tong University School of MedicineShanghai 200025China

The estrogen receptor(er)-negative breast cancer subtype is aggressive with few treatment options *** identify specific prognostic factors for er-negative breast cancer,this study included 705,729 and 1034 breast invasive cancer patients from the Surveillance,Epidemiology,and End Results(SEer)and The cancer Genome Atlas(TCGA)databases,*** identify key differential kinase-substrate node and edge biomarkers between er-negative and erpositive breast cancer patients,we adopted a network-based method using correlation coefficients between molecular pairs in the kinase regulatory *** analysis of the clinical and molecular data revealed the significant prognostic power of kinase-substrate node and edge features for both subtypes of breast *** promising kinase-substrate edge features,CSNK1A1-NFATC3 and SRC-OCLN,were identified for more accurate prognostic prediction in ernegative breast cancer patients.

关键词： er-negative breast cancer Edge biomarkers Kinase Substrate Prognostic prediction

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Profile of the breast cancer susceptibility marker rs4245739 identifies a role for miRNAs

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cancer Biology & Medicine 2017年第4期14卷 387-395页

作者： Sumadi Lukman Anwar Wahyu Wulaningsih Johnathan Watkins PILAR Research Network Cambridgeshire CB1 2JD UK Division of Surgical Oncology Department of Surgery Faculty of Medicine Universitas Gadjah Mada Yogyakarta 55281 Indonesia Division of Hemato-Oncology Department of Internal Medicine Faculty of Medicine Universitas Gadjah Mada Yogyakarta 55281 Indonesia MRC Unit for Lifelong Nealth and Ageing University College London London WCIB 5JU UK Institute of Molecular and Mathematical Biomedicine King's College London London SE1 1UL UK

Objective:To determine the influence of the single nucleotide polymorphism(SNP)rs4245739 on the binding and expression of micro RNAs and subsequent MDM4 expression and the correlation of these factors with clinical determinants of er-negative breast ***:Find Tar and miRanda were used to detect the manner in which potential micro RNAs are affected by the SNP rs4245739-flanking *** sequencing data for er-negative breast cancer from The cancer Genome Atlas(TCGA)were used to compare the expression of miR-184,miR-191,miR-193a,miR-378,and MDM4 in different rs4245739 ***:Comparison of er-negative cancer patients with and without the expression of miR-191 as well as profile micro RNAs(miR-184,miR-191,miR-193a and miR-378 altogether)can differentiate the expression of MDM4 among different rs4245739 *** simple genotyping alone did not reveal significant clinical relationships,the combination of genotyping and micro RNA profiles was able to significantly differentiate individuals with larger tumor size and lower number of involved lymph nodes(Per expression and(ii)an expression profile of miRNAs predicted to bind to the SNP *** demonstrate that the application of these two methods,in particular the miRNA profile approach,permits detection of new molecular and clinical features related to the rs4245739 variant in er-negative breast cancer.

关键词： Rs4245739 er-negative breast cancer MDM4 microRNA clinical relevance

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