Literature DB >> 33398005

MCM3 upregulation confers endocrine resistance in breast cancer and is a predictive marker of diminished tamoxifen benefit.

Sanne Løkkegaard1, Daniel Elias1, Carla L Alves1, Martin V Bennetzen2, Anne-Vibeke Lænkholm3, Martin Bak4, Morten F Gjerstorff1, Lene E Johansen1, Henriette Vever1, Christina Bjerre5, Tove Kirkegaard6, Bo Nordenskjöld7, Tommy Fornander8, Olle Stål7, Linda S Lindström9, Laura J Esserman10, Anne E Lykkesfeldt6, Jens S Andersen2, Rikke Leth-Larsen1,11, Henrik J Ditzel12,13,14.   

Abstract

Resistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancer is a major clinical problem with poorly understood mechanisms. There is an unmet need for prognostic and predictive biomarkers to allow appropriate therapeutic targeting. We evaluated the mechanism by which minichromosome maintenance protein 3 (MCM3) influences endocrine resistance and its predictive/prognostic potential in ER+ breast cancer. We discovered that ER+ breast cancer cells survive tamoxifen and letrozole treatments through upregulation of minichromosome maintenance proteins (MCMs), including MCM3, which are key molecules in the cell cycle and DNA replication. Lowering MCM3 expression in endocrine-resistant cells restored drug sensitivity and altered phosphorylation of cell cycle regulators, including p53(Ser315,33), CHK1(Ser317), and cdc25b(Ser323), suggesting that the interaction of MCM3 with cell cycle proteins is an important mechanism of overcoming replicative stress and anti-proliferative effects of endocrine treatments. Interestingly, the MCM3 levels did not affect the efficacy of growth inhibitory by CDK4/6 inhibitors. Evaluation of MCM3 levels in primary tumors from four independent cohorts of breast cancer patients receiving adjuvant tamoxifen mono-therapy or no adjuvant treatment, including the Stockholm tamoxifen (STO-3) trial, showed MCM3 to be an independent prognostic marker adding information beyond Ki67. In addition, MCM3 was shown to be a predictive marker of response to endocrine treatment. Our study reveals a coordinated signaling network centered around MCM3 that limits response to endocrine therapy in ER+ breast cancer and identifies MCM3 as a clinically useful prognostic and predictive biomarker that allows personalized treatment of ER+ breast cancer patients.

Entities:  

Year:  2021        PMID: 33398005     DOI: 10.1038/s41523-020-00210-8

Source DB:  PubMed          Journal:  NPJ Breast Cancer        ISSN: 2374-4677


  47 in total

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Journal:  Bioessays       Date:  2003-02       Impact factor: 4.345

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Journal:  Cancer       Date:  2005-07-15       Impact factor: 6.860

3.  Molecular changes in tamoxifen-resistant breast cancer: relationship between estrogen receptor, HER-2, and p38 mitogen-activated protein kinase.

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Journal:  J Clin Oncol       Date:  2005-03-07       Impact factor: 44.544

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Journal:  J Clin Oncol       Date:  2002-08-15       Impact factor: 44.544

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Journal:  J Clin Oncol       Date:  2002-08-15       Impact factor: 44.544

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Journal:  Eur J Cancer Clin Oncol       Date:  1983-05

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Journal:  Cancer Res       Date:  1995-08-01       Impact factor: 12.701

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Journal:  Cancer Res       Date:  1983-08       Impact factor: 12.701

9.  Estrogen Receptor analyses in the Danish Breast Cancer Cooperative Group. History, methods, prognosis and clinical implications.

Authors:  Maj-Lis M Talman; Birgitte B Rasmussen; Jørn Andersen; Ib J Christensen
Journal:  Acta Oncol       Date:  2008       Impact factor: 4.089

10.  Altered expression of estrogen-regulated genes in a tamoxifen-resistant and ICI 164,384 and ICI 182,780 sensitive human breast cancer cell line, MCF-7/TAMR-1.

Authors:  A E Lykkesfeldt; M W Madsen; P Briand
Journal:  Cancer Res       Date:  1994-03-15       Impact factor: 12.701

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Authors:  Chen Chen; Hong Yu; Qi Li
Journal:  Cells       Date:  2021-10-05       Impact factor: 6.600

2.  Bioinformatics Analysis Reveals MCM3 as an Important Prognostic Marker in Cervical Cancer.

Authors:  Hui Ma; Zhen Liu; Honglin Li; Xuewang Guo; Sujie Guo; Pengpeng Qu; Yuquan Wang
Journal:  Comput Math Methods Med       Date:  2021-10-11       Impact factor: 2.238

3.  Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis.

Authors:  Xiaolu Wu; Ran Li; Qu Xu; Feng Liu; Yue Jiang; Min Zhang; Meiling Tong
Journal:  Sci Rep       Date:  2022-02-15       Impact factor: 4.996

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