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Causal Bayesian gene networks associated with bone, brain and lung metastasis of breast cancer

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Abstract

Using a machine learning method, this study aimed to identify unique causal networks of genes associated with bone, brain, and lung metastasis of breast cancer. Bayesian network analysis identified differentially expressed genes in primary breast cancer tissues, in bone, brain, and lung breast cancer metastatic tissues, and the clinicopathological features of patients obtained from the Gene Expression Omnibus microarray datasets. We evaluated the causal Bayesian networks of breast metastasis to distant sites (bone, brain, or lung) by (i) measuring how well the structures of each specific type of breast cancer metastasis fit the data, (ii) comparing the structures with known experimental evidence, and (iii) reporting predictive capabilities of the structures. We report for the first time that the molecular gene signatures are specific to the different types of breast cancer metastasis. Several genes, including CHPF, ARC, ANGPTL4, NR2E1, SH2D1A, CTSW, POLR2J4, SPTLC1, ILK, ALDH3B1, PDE6A, SCTR, ADM, HEY1, KCNF1, and UVRAG, were found to be predictors of the risk for site-specific metastasis of breast cancer. Expression of POLR2JA, SPTLC1, ILK, ALDH3B1, and the estrogen receptor was significantly associated with breast cancer bone metastasis. Expression of PDE6A and NR2E1 was causally linked to breast cancer brain metastasis. Expression of HEY1, KCNF1, UVRAG, and the estrogen and progesterone receptors was strongly associated with breast cancer lung metastasis. The causal Bayesian network structures of these genes identify potential interactions among the genes in distant metastases of breast cancer, including to the bone, brain, and lung, and may serve as target candidates for treatment of breast cancer metastasis.

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Author notes

  1. Deodutta Roy and Changwon Yoo contributed equally to this work.

Authors and Affiliations

  1. Department of Neurosurgery, Seoul National University Boramae Medical Center, Seoul, Korea

    Sung Bae Park

  2. Department of Surgery, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul, Korea

    Ki-Tae Hwang

  3. Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Korea

    Chun Kee Chung

  4. Department of Neurosurgery, Clinical Research Institute, Seoul National University Hospital, Seoul, Korea

    Chun Kee Chung

  5. Department of Environmental Health Sciences, Stempel College of Public Health and Social Work, Florida International University, Miami, FL, USA

    Deodutta Roy

  6. Department of Biostatistics, Robert Stempel College of Public Health and Social Work, Florida International University, 11200 SW 8th Street AHC5, Miami, FL, 33199, USA

    Changwon Yoo

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  1. Sung Bae Park
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Contributions

SBP has contribution to the design of the work and acquisition, analysis and interpretation of data. And he has drafted the work. KH has drafted the work. CKC has contribution to the design of the work. DR and CY have contribution to the conception of the work, interpretation of data and revised the draft.

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Correspondence to Deodutta Roy or Changwon Yoo.

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Park, S.B., Hwang, KT., Chung, C.K. et al. Causal Bayesian gene networks associated with bone, brain and lung metastasis of breast cancer. Clin Exp Metastasis 37, 657–674 (2020). https://doi.org/10.1007/s10585-020-10060-0

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