Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Mar;21(2):142-156.
doi: 10.1177/1099800418823286. Epub 2019 Jan 31.

A Pilot Study Using a Multistaged Integrated Analysis of Gene Expression and Methylation to Evaluate Mechanisms for Evening Fatigue in Women Who Received Chemotherapy for Breast Cancer

Elena Flowers  1 , Annesa Flentje  1 , Jon Levine  2 , Adam Olshen  2 , Marilyn Hammer  3 , Steven Paul  1 , Yvette Conley  4 , Christine Miaskowski  1 , Kord M Kober  1
Affiliations

A Pilot Study Using a Multistaged Integrated Analysis of Gene Expression and Methylation to Evaluate Mechanisms for Evening Fatigue in Women Who Received Chemotherapy for Breast Cancer

Elena Flowers et al. Biol Res Nurs. 2019 Mar.

Abstract

Context: Fatigue is the most common symptom associated with cancer and its treatment. Investigation of molecular mechanisms associated with fatigue may identify new therapeutic targets.

Objective: The objective of this pilot study was to evaluate the relationships between gene expression and methylation status and evening fatigue severity in women with breast cancer who received chemotherapy.

Methods: Latent class analysis (LCA) was used to identify evening fatigue phenotypes. In this analysis, the lowest (i.e., moderate, n = 7) and highest (i.e., very high, n = 29) fatigue-severity classes identified using LCA were analyzed via two stages. First, a total of 32,609 transcripts from whole blood were evaluated for differences in expression levels between the classes. Next, 637 methylation sites located within the putative transcription factor binding sites for those genes demonstrating differential expression were evaluated for differential methylation state between the classes.

Results: A total of 89 transcripts in 75 unique genes were differentially expressed between the moderate (the lowest fatigue-severity class identified) and very high evening fatigue classes. In addition, 23 differentially methylated probes and three differentially methylated regions were found between the moderate and very high evening fatigue classes.

Conclusions: Using a multistaged integrated analysis of gene expression and methylation, differential methylation was identified in the regulatory regions of genes associated with previously hypothesized mechanisms for fatigue, including inflammation, immune function, neurotransmission, circadian rhythm, skeletal muscle energy, carbohydrate metabolism, and renal function as well as core biological processes including gene transcription and the cell-cycle regulation.

Keywords: breast cancer; chemotherapy; fatigue; gene expression; integrated genomic analysis; methylation.

PubMed Disclaimer

Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Hypothesized mechanisms to explain fatigue severity (Panel A; Flowers et al., 2018). In Panel B, the potential relationships between differentially methylated genes identified in this study and hypothesized mechanisms of fatigue are shown in bold font and shapes. The interrelationships between components related to fatigue in Panel A are not shown.
Figure 2.
Figure 2.
Screenshot of the University of California Santa Cruz Genome browser displaying the region on chromosome 20 of the hg19 (genome reference consortium Version 37) assembly of the human genome that includes the defensin beta 124 and RRAD and GEM-Like GTPase 1 genes, the region identified in this study as differentially methylated, and the locations of the methylation probe included in the analysis. Assembly tracks show scale, chromosome, position of the region, and gaps in the assembly. The gene models are provided by the RefSeq. The gene models depict exons as solid blocks connected by lines in introns with arrows showing the direction of transcription. Putative regulatory regions are identified by the layered H3K4Me1, layered H3K27Ac, transcription factor Chromatin Immunoprecipitation Sequencing (ChIP-seq), DNase hypersensitivity clusters, and CpG island (i.e., 5'—C—phosphate—G—3' linear DNA sequence) tracks. Predicted recombination rates and DNA repeat elements in the region are displayed in the final tracks.
Figure 3.
Figure 3.
Protein–protein interaction network of predicted functional partners for the chromosome 2 open reading frame 88 gene (C2orf88). Network interaction representation for C2orf88 was generated by the STRING database (Szklarczyk et al., 2017). Nodes represent all proteins produced by a single protein-coding gene locus. Edges represent specific or meaningful associations. Node size: protein of unknown 3D structure (small), protein of known or predicted 3D structure (large). Color of the edges connecting the nodes represents the types of evidence supporting the connections (colors visible in online version of article only): predicted gene neighborhood (green), predicted gene fusions (red), known interactions from experimental evidence (pink), co-expression (black), and text mining (green).
See this image and copyright information in PMC

Similar articles

See all similar articles

Cited by

See all "Cited by" articles

References

    1. Ali M. Rincon-Arano H. Zhao W. Rothbart S. B. Tong Q. Parkhurst S. M.…Kutateladze T. G. (2013). Molecular basis for chromatin binding and regulation of MLL5. Proceedings of the National Academy of Sciences USA, 110, 11296–11301. - PMC - PubMed
    1. Ames R. S. Sarau H. M. Chambers J. K. Willette R. N. Aiyar N. V. Romanic A. M.…Douglas S. A. (1999). Human urotensin-II is a potent vasoconstrictor and agonist for the orphan receptor GPR14. Nature, 401, 282–286. - PubMed
    1. Amro A., Waldum-Grevbo B., von der Lippe N., Brekke F. B., Miaskowski C., Os I. (2016). Symptom clusters from dialysis to renal transplantation: A five-year longitudinal study. Journal of Pain and Symptom Management, 51, 512–519. - PubMed
    1. Andersen J. S., Wilkinson C. J., Mayor T., Mortensen P., Nigg E. A., Mann M. (2003). Proteomic characterization of the human centrosome by protein correlation profiling. Nature, 426, 570–574. - PubMed
    1. Argiropoulos B., Humphries R. K. (2007). Hox genes in hematopoiesis and leukemogenesis. Oncogene, 26, 6766. - PubMed

Publication types

Substances