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Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy

From an epidemiological standpoint, disruptions to circadian rhythms have been shown to contribute to the development of various disease pathologies, including breast cancer. However, it is unclear how altered circadian rhythms are related to malignant transformations at the molecular level. In this...

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Autores principales: Lin, Hui-Hsien, Qraitem, Maan, Lian, Yue, Taylor, Stephanie R., Farkas, Michelle E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449806/
https://www.ncbi.nlm.nih.gov/pubmed/30943793
http://dx.doi.org/10.1177/1534735419836494
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author Lin, Hui-Hsien
Qraitem, Maan
Lian, Yue
Taylor, Stephanie R.
Farkas, Michelle E.
author_facet Lin, Hui-Hsien
Qraitem, Maan
Lian, Yue
Taylor, Stephanie R.
Farkas, Michelle E.
author_sort Lin, Hui-Hsien
collection PubMed
description From an epidemiological standpoint, disruptions to circadian rhythms have been shown to contribute to the development of various disease pathologies, including breast cancer. However, it is unclear how altered circadian rhythms are related to malignant transformations at the molecular level. In this article, a series of isogenic breast cancer cells representing disease progression was used to investigate the expression patterns of core circadian clock proteins BMAL1 and PER2. Our model is indicative of 4 stages of breast cancer and includes the following cells: MCF10A (non-malignant), MCF10AT.Cl2 (pre-malignant), MCF10Ca1h (well-differentiated, malignant), and MCF10Ca1a (poorly differentiated, malignant). While studies of circadian rhythms in cancer typically use low-resolution reverse transcription polymerase chain reaction assays, we also employed luciferase reporters BMAL1:Luc and PER2:Luc in real-time luminometry experiments. We found that across all 4 cancer stages, PER2 showed relatively stable oscillations compared with BMAL1. Period estimation using both wavelet-based and damped-sine-fitting methods showed that the periods are distributed over a wide circadian range and there is no clear progression in mean period as cancer severity progresses. Additionally, we used the K-nearest neighbors algorithm to classify the recordings according to cancer line, and found that cancer stages were largely differentiated from one another. Taken together, our data support that there are circadian discrepancies between normal and malignant cells, but it is difficult and insufficient to singularly use period evaluations to differentiate them. Future studies should employ other progressive disease models to determine whether these findings are representative across cancer types or are specific to this series.
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spelling pubmed-64498062019-04-16 Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy Lin, Hui-Hsien Qraitem, Maan Lian, Yue Taylor, Stephanie R. Farkas, Michelle E. Integr Cancer Ther Research Article From an epidemiological standpoint, disruptions to circadian rhythms have been shown to contribute to the development of various disease pathologies, including breast cancer. However, it is unclear how altered circadian rhythms are related to malignant transformations at the molecular level. In this article, a series of isogenic breast cancer cells representing disease progression was used to investigate the expression patterns of core circadian clock proteins BMAL1 and PER2. Our model is indicative of 4 stages of breast cancer and includes the following cells: MCF10A (non-malignant), MCF10AT.Cl2 (pre-malignant), MCF10Ca1h (well-differentiated, malignant), and MCF10Ca1a (poorly differentiated, malignant). While studies of circadian rhythms in cancer typically use low-resolution reverse transcription polymerase chain reaction assays, we also employed luciferase reporters BMAL1:Luc and PER2:Luc in real-time luminometry experiments. We found that across all 4 cancer stages, PER2 showed relatively stable oscillations compared with BMAL1. Period estimation using both wavelet-based and damped-sine-fitting methods showed that the periods are distributed over a wide circadian range and there is no clear progression in mean period as cancer severity progresses. Additionally, we used the K-nearest neighbors algorithm to classify the recordings according to cancer line, and found that cancer stages were largely differentiated from one another. Taken together, our data support that there are circadian discrepancies between normal and malignant cells, but it is difficult and insufficient to singularly use period evaluations to differentiate them. Future studies should employ other progressive disease models to determine whether these findings are representative across cancer types or are specific to this series. SAGE Publications 2019-04-03 /pmc/articles/PMC6449806/ /pubmed/30943793 http://dx.doi.org/10.1177/1534735419836494 Text en © The Author(s) 2019 http://www.creativecommons.org/licenses/by-nc/4.0/ This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (http://www.creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Research Article
Lin, Hui-Hsien
Qraitem, Maan
Lian, Yue
Taylor, Stephanie R.
Farkas, Michelle E.
Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy
title Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy
title_full Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy
title_fullStr Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy
title_full_unstemmed Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy
title_short Analyses of BMAL1 and PER2 Oscillations in a Model of Breast Cancer Progression Reveal Changes With Malignancy
title_sort analyses of bmal1 and per2 oscillations in a model of breast cancer progression reveal changes with malignancy
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6449806/
https://www.ncbi.nlm.nih.gov/pubmed/30943793
http://dx.doi.org/10.1177/1534735419836494
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