Flowers Elena, Flentje Annesa, Levine Jon, Olshen Adam, Hammer Marilyn, Paul Steven, Conley Yvette, Miaskowski Christine, Kober Kord M
1 School of Nursing, University of California, San Francisco, San Francisco, CA, USA.
2 School of Medicine, University of California, San Francisco, San Francisco, CA, USA.
Biol Res Nurs. 2019 Mar;21(2):142-156. doi: 10.1177/1099800418823286. Epub 2019 Jan 31.
Fatigue is the most common symptom associated with cancer and its treatment. Investigation of molecular mechanisms associated with fatigue may identify new therapeutic targets.
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.
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.
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.
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.
疲劳是与癌症及其治疗相关的最常见症状。对与疲劳相关的分子机制进行研究可能会确定新的治疗靶点。
本初步研究的目的是评估接受化疗的乳腺癌女性基因表达与甲基化状态和夜间疲劳严重程度之间的关系。
采用潜在类别分析（LCA）来确定夜间疲劳表型。在该分析中，通过两个阶段对使用LCA确定的最低（即中度，n = 7）和最高（即非常高，n = 29）疲劳严重程度类别进行分析。首先，评估全血中的总共32,609条转录本在不同类别之间的表达水平差异。接下来，对那些显示出差异表达的基因的假定转录因子结合位点内的637个甲基化位点进行评估，以确定不同类别之间的甲基化状态差异。
在中度（确定的最低疲劳严重程度类别）和非常高的夜间疲劳类别之间，共有75个独特基因中的89条转录本存在差异表达。此外，在中度和非常高的夜间疲劳类别之间发现了23个差异甲基化探针和3个差异甲基化区域。
通过对基因表达和甲基化进行多阶段综合分析，在与先前假设的疲劳机制相关的基因调控区域中发现了差异甲基化，这些机制包括炎症、免疫功能、神经传递、昼夜节律、骨骼肌能量、碳水化合物代谢和肾功能以及包括基因转录和细胞周期调控在内的核心生物学过程。
