Three tyrosine kinase inhibitors cause cardiotoxicity by inducing endoplasmic reticulum stress and inflammation in cardiomyocytes

Abstract

Background: Tyrosine kinase inhibitors (TKIs) are anti-cancer therapeutics often prescribed for long-term treatment. Many of these treatments cause cardiotoxicity with limited cure. We aim to clarify molecular mechanisms of TKI-induced cardiotoxicity so as to find potential targets for treating the adverse cardiac complications.

Methods: Eight TKIs with different levels of cardiotoxicity reported are selected. Phenotypic and transcriptomic responses of human cardiomyocytes to TKIs at varying doses and times are profiled and analyzed. Stress responses and signaling pathways that modulate cardiotoxicity induced by three TKIs are validated in cardiomyocytes and rat hearts.

Results: Toxicity rank of the eight TKIs determined by measuring their effects on cell viability, contractility, and respiration is largely consistent with that derived from database or literature, indicating that human cardiomyocytes are a good cellular model for studying cardiotoxicity. When transcriptomes are measured for selected TKI treatments with different levels of toxicity in human cardiomyocytes, the data are classified into 7 clusters with mainly single-drug clusters. Drug-specific effects on the transcriptome dominate over dose-, time- or toxicity-dependent effects. Two clusters with three TKIs (afatinib, ponatinib, and sorafenib) have the top enriched pathway as the endoplasmic reticulum stress (ERS). All three TKIs induce ERS in rat primary cardiomyocytes and ponatinib activates the IRE1α-XBP1s axis downstream of ERS in the hearts of rats underwent a 7-day course of drug treatment. To look for potential triggers of ERS, we find that the three TKIs induce transient reactive oxygen species followed by lipid peroxidation. Inhibiting either PERK or IRE1α downstream of ERS blocks TKI-induced cardiac damages, represented by the induction of cardiac fetal and pro-inflammatory genes without causing more cell death.

Conclusions: Our data contain rich information about phenotypic and transcriptional responses of human cardiomyocytes to eight TKIs, uncovering potential molecular mechanisms in modulating cardiotoxicity. ER stress is activated by multiple TKIs and leads to cardiotoxicity through promoting expression of pro-inflammatory factors and cardiac fetal genes. ER stress-induced inflammation is a promising therapeutic target to mitigate ponatinib- and sorafenib-induced cardiotoxicity.

Keywords: Cardiotoxicity; Endoplasmic reticulum stress; Inflammation; Transcriptomics; Tyrosine kinase inhibitor.

Fig. 1

Toxicity of eight TKIs measured by cellular assays, FAERS analysis, and literature review. A–H Cor.4U hiPSC-CMs were treated with TKIs at doses from 0.32 to 10 µM and duration from 1 to 5 days. Fold changes in ATP were calculated relative to vehicle controls at the same time point and shown as a surface plot. Treatments selected for subsequent RNAseq profiling were enclosed in red circles. Toxicity that was significantly different from controls was labeled with red asterisks. I–L Base impedance and extracellular field potential were measured by CardioExcyte 96 microelectrode array in HELP hiPSC-CMs treated with fixed doses of TKIs (afatinib 10 µM, gefitinib 10 µM, crizotinib 3.16 µM, dasatinib 10 µM, nilotinib 10 µM, ponatinib 3.16 µM, sorafenib 10 µM, sunitinib 10 µM) for 24 h. Beat rate (I), amplitude of impedance (J), base impedance (K), and corrected field potential duration (FPDc, L) were calculated for different treatments. Data were presented as mean ± SD of three replicated wells. M–N Mitochondrial oxygen consumption and extracellular acidification were measured in rat cardiomyocytes treated with fixed doses of TKIs (same as in I) for 24 h. A representative experiment from three independent repeats was shown. O–R Basal, maximal, spare, and non-mitochondrial oxygen consumption were derived from the seahorse experiment from M. Data were presented as mean ± SEM of three independent experiments with 5–6 replicated wells each. *p < 0.05, **p < 0.01, ***p < 0.001 versus the DMSO vehicle control group. S Heatmap of reporting odds ratios (RORs) calculated based on the event numbers of cardiotoxicity-related medical terms mined from the FDA adverse events reporting system (FAERS). T Toxicity rankings of eight TKIs based on literature, FAERS, ATP level, mitochondrial respiration and beating properties. Drug with the highest toxicity is on the top

Fig. 2

Major biological processes regulated by different TKIs. A The L- or T-shaped designs that span three doses and three time points for each TKI, selected based on results from Fig. 1A–H; 129 samples with three biological replicates per condition were measured in 3’DGE-UMI RNAseq. B Transcriptome changes induced by eight TKIs over dose and time were grouped into 7 clusters based on tSNE analysis, and the corresponding drugs of each cluster were shown in C. D Expression of top 20 gene markers for each cluster. E In Cluster 0, mitochondrial tRNA genes were expressed at a higher level than the other clusters. F Biological processes enriched for gene markers of Cluster 2. Expression of representative genes in GO term of mitotic nuclear division was shown on the right. G Biological processes enriched for gene markers of Cluster 3. Expression of representative genes in this GO endoplasmic reticulum stress was shown on the right. H Biological processes enriched for gene markers of Cluster 4. Expression of representative genes in GO term of heart contraction was shown on the right. I Biological processes enriched for gene markers of Cluster 6. Expression of representative genes in GO term of response to topologically incorrect protein was shown on the right

Fig. 3

Drug specific effects on transcriptome dominate dose-, time- or toxicity-induced effects. A Transcriptome data were sliced to retain all drug treatments at day 1 with different doses. The orange arrow represents the concentration gradient of data. Red squares denote the doses for six TKIs (labeled in red in B) and blue diamonds denote the doses for two TKIs (labeled in blue in B). B–D Data selected as in A were projected into the tSNE space and shown with the properties of drug, concentration, or toxicity (represented by the ATP fold changes). Darker gray corresponds to higher toxicity. E Transcriptome data were sliced to retain drug treatments at a fixed dose over 5 days. The blue arrow represents the time gradient of data. Red squares denote the time points for six TKIs (labeled in red in F) and blue diamonds denote the time points for two TKIs (labeled in blue in F). F–H Data selected as in E were projected into the tSNE space and shown with the properties of drug, time or toxicity (represented by the ATP fold changes). Toxicity that was significantly different from controls was labeled with red asterisks in H. I Principal component analysis (PCA) of transcriptome changes induced by eight TKIs. J Drug concentration of each condition projected into the PCA space. K Treatment duration of each condition projected into the PCA space. L Toxicity level of each condition defined by the percent ATP of controls projected into the PCA space. Darker gray corresponds to higher toxicity. M–N Expression of genes with top and bottom 30 highest loadings of PC1 and PC2 grouped by drugs

Fig. 4

Afatinib, sorafenib and ponatinib induce ER stress in NRCMs and rat hearts. A Fold changes of ER stress related genes, Atf4 and its targets, Chac1, Ddit3, Trib3;Xbp1s, and its target Dnajb9; Atf6 and its targets Hspa5 and Herpud1, in NRCMs treated with afatinib at 5.62 or 10 µM for 24 h. B Fold changes of ER stress related genes in NRVMs treated with sorafenib at 3.16 or 10 µM for 24 h. C Fold changes of ER stress related genes in NRCMs treated with ponatinib at 1.78 or 5.62 µM for 24 h. D Left: heatmap of gene expression changes from A–C. Right: heatmap of gene expression changes caused by afatinib 5.62 µM, sorafenib 3.16 µM, or ponatinib 1.78 µM at 24 or 72 h. E Phospho-eIF2α (or EIF2S1), XBP1s, ATF6 (cleaved), and GAPDH expression at different time points under afatinib, sorafenib, and ponatinib treatment measured by Western blot. F–H Fold changes of Anp, Dnajb9, and Ddit3 in rat left ventricles from sorafenib or ponatinib gavage for 3 or 7 days. A-C Data were presented as mean ± SEM (n = 3) and analyzed using ANOVA analysis. *p < 0.05, **p < 0.01, ***p < 0.001 versus the DMSO vehicle control group. ^#p < 0.05, ^##p < 0.01, ^###p < 0.001 versus the lower dose. F–H Data were presented as mean ± SEM (n = 8) and analyzed using ANOVA analysis. *p < 0.05, **p < 0.01, ***p < 0.001 versus the vehicle control

Fig. 5

The 3 TKIs induce different levels of lipid peroxidation, ROS, calcium defects, and TNNT2 loss in NRCMs. To measure oxidative stress and cardiotoxic effects induced by TKIs, NRCMs were treated with 10 µM afatinib, 10 µM sorafenib, or 5.62 µM ponatinib and stained with various dyes before quantification by flow cytometry or imaging. A-B Percent of ROS-high cells quantified by flow cytometry and staining with H₂DCFDA after different TKI treatments for 3 or 24 h. C–D Histogram of the ratios between green (oxidized) and red (non-oxidized) fluorescence intensity of C11-bodipy^581/591 in NRCMs under different treatments. Percentages by the condition names were the fraction of cells in the specified gate for each treatment. E Representative fluorescence images of live NRCMs pre-loaded with Calbryte™ 520 AM and treated with the indicated drug from 0 to 3 h. F Integrated density of green fluorescence in E. G Representative immunofluorescence images of TNNT2 (green) and nuclei (blue) in NRCMs treated with TKIs for 24 h. H Integrated density of green fluorescence in G. Data were presented as mean ± SEM (n = 3) and analyzed using ANOVA analysis. *p < 0.05, **p < 0.01, ***p < 0.001 versus the DMSO vehicle control group. Scale bar: 200 µm

Fig. 6

The 3 TKIs cause increased expression of fetal and pro-inflammatory genes through coordinated activation of PERK and IRE1α pathways. A–J Fold changes of Atf4, Xbp1s, Anp, Bnp, Myh6, Nfkb1, Il6, Tnf, Txnip, and Il1b mRNAs in NRCMs treated with 3 TKIs (10 μM afatinib, 10 μM sorafenib, 5.62 μM ponatinib) in combination with or without ISRIB (200 nM) or 4μ8c (10 μM) for 24 h. Data were presented as mean ± SEM (n = 3) and analyzed using ANOVA analysis. *p < 0.05, **p < 0.01, ***p < 0.001 versus the DMSO vehicle control group. ^#p < 0.05, ^##p < 0.01, ^###p < 0.001 versus the TKI treatment alone