Circadian oscillations persist in low malignancy breast cancer cells.
Sujeewa S Lellupitiyage DonHui-Hsien LinJessica J FurtadoMaan QraitemStephanie R TaylorMichelle E FarkasPublished in: Cell cycle (Georgetown, Tex.) (2019)
Epidemiological studies have shown that humans with altered circadian rhythms have higher cancer incidence, with breast cancer being one of the most cited examples. To uncover how circadian disruptions may be correlated with breast cancer and its development, prior studies have assessed the expression of BMAL1 and PER2 core clock genes via RT-qPCR and western blot analyses. These and our own low-resolution data show that BMAL1 and PER2 expression are suppressed and arrhythmic. We hypothesized that oscillations persist in breast cancer cells, but due to limitations of protocols utilized, cannot be observed. This is especially true where dynamic changes may be subtle. In the present work, we generated luciferase reporter cell lines representing high- and low-grade breast cancers to assess circadian rhythms. We tracked signals for BMAL1 and PER2 to determine whether and to what extent oscillations exist and provide initial correlations of circadian rhythm alterations with breast cancer aggression. In contrast to previous studies, where no oscillations were apparent in any breast cancer cell line, our luminometry data reveal that circadian oscillations of BMAL1 and PER2 in fact exist in the low-grade, luminal A MCF7 cells but are not present in high-grade, basal MDA-MB-231 cells. To our knowledge, this is the first evidence of core circadian clock oscillations in breast cancer cells. This work also suggests that circadian rhythms are further disrupted in more aggressive/high tumor grades of breast cancer, and that use of real time luminometry to study additional representatives of breast and other cancer subtypes is merited.
Keyphrases
- low grade
- breast cancer cells
- high grade
- working memory
- induced apoptosis
- papillary thyroid
- poor prognosis
- cell cycle arrest
- genome wide
- childhood cancer
- big data
- healthcare
- oxidative stress
- atrial fibrillation
- risk factors
- magnetic resonance
- magnetic resonance imaging
- gene expression
- computed tomography
- cell death
- blood pressure
- crispr cas
- artificial intelligence
- machine learning
- endoplasmic reticulum stress
- young adults
- cell proliferation
- lymph node metastasis
- signaling pathway