Analysis of lncRNA-miRNA-mRNA expression pattern in heart tissue after total body radiation in a mouse model

Abstract

Background: Radiation therapy is integral to effective thoracic cancer treatments, but its application is limited by sensitivity of critical organs such as the heart. The impacts of acute radiation-induced damage and its chronic effects on normal heart cells are highly relevant in radiotherapy with increasing lifespans of patients. Biomarkers for normal tissue damage after radiation exposure, whether accidental or therapeutic, are being studied as indicators of both acute and delayed effects. Recent research has highlighted the potential importance of RNAs, including messenger RNAs (mRNAs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) as biomarkers to assess radiation damage. Understanding changes in mRNA and non-coding RNA expression will elucidate biological pathway changes after radiation.

Methods: To identify significant expression changes in mRNAs, lncRNAs, and miRNAs, we performed whole transcriptome microarray analysis of mouse heart tissue at 48 h after whole-body irradiation with 1, 2, 4, 8, and 12 Gray (Gy). We also validated changes in specific lncRNAs through RT-qPCR. Ingenuity Pathway Analysis (IPA) was used to identify pathways associated with gene expression changes.

Results: We observed sustained increases in lncRNAs and mRNAs, across all doses of radiation. Alas2, Aplnr, and Cxc3r1 were the most significantly downregulated mRNAs across all doses. Among the significantly upregulated mRNAs were cell-cycle arrest biomarkers Gdf15, Cdkn1a, and Ckap2. Additionally, IPA identified significant changes in gene expression relevant to senescence, apoptosis, hemoglobin synthesis, inflammation, and metabolism. LncRNAs Abhd11os, Pvt1, Trp53cor1, and Dino showed increased expression with increasing doses of radiation. We did not observe any miRNAs with sustained up- or downregulation across all doses, but miR-149-3p, miR-6538, miR-8101, miR-7118-5p, miR-211-3p, and miR-3960 were significantly upregulated after 12 Gy.

Conclusions: Radiation-induced RNA expression changes may be predictive of normal tissue toxicities and may indicate targetable pathways for radiation countermeasure development and improved radiotherapy treatment plans.

Keywords: Biomarkers; Heart; Normal tissue injury; Radiation; lncRNA; mRNA; miRNA.

Fig. 1

Radiation-induced gene expression profiles in mouse heart tissue. Whole genome microarray analysis was performed on all samples. A linear model was fit to each probe to evaluate differential expression of irradiated samples compared to controls. Criteria of |log₂Fold Change (FC)| > 1 and Benajmini-Hochberg adjusted (B-H) p-value < 0.05 relative to controls were used to determine significance and differential expression. A Heatmap displays expression patterns, represented by z-score, of all differentially expressed mRNAs across all doses and controls. B Venn diagram shows dose distribution and overlap of differentially expressed mRNAs across all doses. C The number of down-regulated versus up-regulated mRNAs at each dose are shown in the table. D Examples of significant linearly up- and down-regulated mRNAs are shown to display the dose response to radiation in heart tissue samples

Fig. 2

Radiation-induced long non-coding RNA expression profiles in mouse heart tissue. Whole genome microarray data was filtered to include only probes that correspond to transcripts of lncRNAs. A linear model was fit to each lncRNA probe to assess differential expression of irradiated compared to control samples using criteria of |log₂FC| > 2 and B-H p-value < 0.05. A Heatmap displays expression patterns, represented by z-score, of all differentially expressed lncRNAs across all doses and controls. B Venn diagram shows dose distribution and overlap of differentially expressed lncRNAs across all doses. C The table shows the number of down- versus up-regulated lncRNAs at each dose. D Examples of significant linearly up- and down-regulated lncRNAs are shown to display the dose response of lncRNAs to radiation in heart tissue samples. E RT-qPCR validation was performed on significantly up-regulated lncRNAs that were previously reported in the blood [44]

Fig. 3

Radiation-induced microRNA expression profiles in mouse heart tissue. Microarray analysis was performed for all samples, and a linear model was fit to each miRNA probe to assess differential expression of irradiated samples compared to controls. Criteria of |log₂FC| > 2 and B-H p-value < 0.05 relative to controls were used to determine significance and differential expression. A Heatmap displays expression patterns, represented by z-score, of all differentially expressed miRNAs across all doses and controls. B Venn diagram shows dose distribution and overlap of differentially expressed miRNAs across all doses. C The number of down-regulated versus up-regulated miRNAs at each dose are shown in the table. D Examples of significant linearly up- and down-regulated miRNAs are shown to display the dose response to radiation in heart tissue samples

Fig. 4

Significant dysregulation of canonical pathways observed through changes in expression of the mRNA targets of differentially expressed miRNAs. Experimentally verified and differentially expressed mRNA targets of differentially expressed miRNAs were analyzed using IPA to predict effects of miRNA-mRNA pairs on canonical pathways. A Heatmap displays canonical pathways that were predicted to be significantly dysregulated (B-H p-value < 0.01 across all doses) based upon differentially expressed mRNA targets. A positive z-score indicates predicted activation of the pathway based on gene expression and a negative z-score indicates predicted deactivation of the pathway based on gene expression. Pathways are hierarchically clustered by z-score. B Fold changes of inversely correlated miRNA-mRNA target pairs with involvement in the significantly dysregulated pathways. Three miRNAs had two mRNA targets each that were inversely correlated across all doses and significant in at least one condition

Fig. 5

Predicted canonical pathway dysregulation in mouse heart samples based on all differentially expressed mRNAs. IPA was used to perform pathway analysis on all differentially expressed mRNAs to predict pathway involvement, independent of the target relationship with differentially expressed miRNAs. A Heatmap displays the top 35 most significantly dysregulated pathways (B-H p-value < 0.01). A positive z-score indicates predicted activation of the pathway based on gene expression and a negative z-score indicates predicted deactivation of the pathway based on gene expression. Pathways are hierarchically clustered by z-score. B Heatmap shows the log₂FC of the 78 differentially expressed genes with involvement in the cluster of activated pathways. C Heatmap shows the log₂FC of 79 differentially expressed genes with involvement in the cluster of most deactivated pathways

Fig. 6

Differentially expressed genes involved in metabolic pathways suggest impact of radiation on metabolism in the heart. Differentially expressed genes with involvement in metabolic signaling pathways were identified using IPA. A Heatmap displays the log₂FC of the genes at each dose. B Cartoon depicts changes predicted based upon the genes shown in (A). Red arrows indicate increased gene expression. Green arrows indicate decreased expression of gene. Light blue indicates no significant change to gene expression