Skip to main content
NCBI home page
Journal of Cardiothoracic Surgery logoLink to Journal of Cardiothoracic Surgery
. 2026 Jun 14;21:617. doi: 10.1186/s13019-026-04419-9

Identification of TGF-β1 as a key regulator in DOX-induced cardiotoxicity

Cong Mao 1,2,#, Zhuo Zhang 1,2,#, Dabao Xiao 1,2, Junru He 1,2, Xu Leng 1,2, Wenzhen Zhao 1,2, Mengya Zeng 1,4,✉, Keyan Zhong 3,✉, Yuewu Chen 1,4,✉
PMCID: PMC13495333  PMID: 42289684

Abstract

Background

Doxorubicin (DOX) is a widely used chemotherapeutic agent, but its severe cardiotoxicity limits its clinical application. Many biological processes and molecular mechanisms have been implicated in DOX-induced cardiotoxicity. However, the mechanisms underlying DOX-induced cardiotoxicity remain largely unknown. This study aimed to identify key regulatory genes and select targeted drugs for DOX-induced cardiotoxicity.

Methods

RNA-seq analysis was used to identify differentially expressed genes (DEGs) in DOX-treated cardiomyocytes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was used to elucidate the biological significance of the DEGs. Protein-protein interaction (PPI) network and maximum clique centrality (MCC) algorithm in Cytoscape software were used to identify central regulatory genes. Gene Set Enrichment Analysis (GSEA) was used to verify the key gene involved in DOX-induced cardiotoxicity. Molecular docking analysis was used to identify the inhibitors of the key gene. Cell Counting Kit-8 (CCK-8) assay, Western blot, creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH) detection kits, and Hematoxylin and Eosin (HE) staining were used to investigate the protective effect of SB-431,542 against DOX-induced cardiomyocyte injury.

Results

RNA-seq analysis revealed significant transcriptional changes. Upregulated genes wereassociated with oxidative stress and apoptosis, while downregulated genes were linked to disrupted signaling pathways. Differential expression analysis identified interleukin-6 (Il6), transforming growth factor-beta 1 (TGF-β1), intercellular adhesion molecule-1 (Icam1), serine peptidase inhibitor clade E member 1 (Serpine1), and angiotensinogen (Agt) as central regulators of DOX-induced cellular responses. Functional enrichment analysis highlighted the involvement of mitogen-activated protein kinase (MAPK), receptor for advanced glycation endproducts (RAGE), and TGF-β signaling pathways. Further analysis identified TGF-β1 as a key regulatory hub connecting the MAPK pathway and protein-protein interaction networks. GSEA confirmed TGF-β pathway enrichment, emphasizing its role in inflammation, fibrosis, and oxidative stress. Notably, SB-431,542, a TGF-β receptor kinase inhibitor, mitigated DOX-induced apoptosis, improved cell viability, and ameliorated DOX-induced cardiotoxicity by inhibiting the phosphorylation of Smad2/3.

Conclusion

Our study identifies TGF-β1 as a central regulator of DOX-induced cardiotoxicity and highlights SB-431,542 as a promising therapeutic agent for mitigating cardiomyocyte apoptosis by targeting Smad2/3. Our study suggests that TGF-β1 may serve as a potential therapeutic target for reducing DOX-induced cardiotoxicity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13019-026-04419-9.

Keywords: TGF-β1, SB-431542, Cardiomyocyte apoptosis, Smad2/3, Doxorubicin cardiotoxicity

Background

Doxorubicin (DOX), an anthracycline chemotherapy agent, is widely used to treat various cancers, including breast cancer, leukemia, and sarcoma [1]. However, its clinical application is limited by dose-dependent cardiotoxicity. Dexrazoxane (DEX) is the only drug approved by the Food and Drug Administration (FDA) that can relieve DOX-induced cardiotoxicity. However, the clinical use of DEX is limited by its myelosuppressive effects [2, 3]. Therefore, developing highly efficient and low-toxicity therapeutic drugs is crucial for alleviating DOX-induced cardiotoxicity.

Over the past decades, numerous biological processes and molecular mechanisms have been implicated in DOX-induced cardiotoxicity, including reactive oxygen species (ROS) generation, calcium overload, mitochondrial dysfunction, apoptosis, pyroptosis, ferroptosis, and autophagy [4–6]. Among these, apoptosis plays a pivotal role. Studies have shown that inhibiting apoptosis through pharmacological or genetic interventions significantly reduces DOX-induced myocardial injury. For instance, overexpression of anti-apoptotic genes such as B-cell lymphoma 2 (Bcl-2) or inhibition of pro-apoptotic genes such as Bcl-2-associated X protein (Bax) mitigates DOX-induced cardiomyocyte damage [7]. However, the specific molecular pathways and key regulatory factors involved remain incompletely understood. Therefore, elucidating the molecular network that governs DOX-induced apoptosis is crucial for developing strategies to mitigate its cardiotoxicity.

In this study, RNA-seq was performed to identify differentially expressed genes in DOX-treated cardiomyocytes. Bioinformatic analysis and Gene Set Enrichment Analysis (GSEA)were conducted to determine key regulatory genes. Molecular docking was then used to select an inhibitor targeting the identified key gene. Finally, in vitro and in vivo experiments were carried out to validate the inhibitor’s effects on DOX-induced cardiomyocyte injury.

Methods

Cell culture and treatment

The cardiac muscle cell line H9c2 was obtained from the Cell Bank of the Shanghai Institute of Cell Biology, Chinese Academy of Sciences. Cells were cultured in dulbecco’s modified eagle medium (DMEM) supplemented with 100 µg/mL streptomycin, 100 U/mL penicillin G, and 10% fetal bovine serum at 37 °C in a 5% CO₂ incubator.

For RNA sequencing (RNA-seq) analysis: H9c2 cells were divided into two groups: (A) Control (Ctrl), treated with vehicle for 24 h; (B) DOX, treated with 1 µM DOX (Selleck, S1208, Shanghai, China) for 24 h [8, 9]. For SB-431,542 concentration screening: Cells were seeded in 96-well plates at 5 × 103 cells/mL and treated with 0, 5, 10, 15, and 20 µM SB-431,542 (MCE, HY-10431, Shanghai, China) for 24 h [10]. Cell viability was assessed using the Cell Counting Kit 8 (CCK-8) assay (Beyotime, C0038, Shanghai, China), and the maximum non-toxic concentration was chosen for subsequent experiments. For the effect of SB-431,542 on DOX-induced cell injury: H9c2 cells were divided into four groups: the Ctrl group, the SB-431,542 group treated with 15 µM SB-431,542, the DOX group treated with 1 µM DOX, and the DOX + SB-431,542 group co-treated with 1 µM DOX and 15 µM SB-431,542. All cells were incubated at 37 °C in 5% CO2 for 24 h before further detection.

RNA sequencing (RNA-seq)

Total RNA was extracted using TRIzol reagent and assessed for purity (NanoDrop, OD260/280 > 1.8) and integrity (Agilent 2100 Bioanalyzer, RIN > 7). RNA was fragmented at 94 °C for 5–7 min and reverse-transcribed into cDNA using SuperScript™ II. cDNA synthesis was followed by one-step synthesis and end repair using E. coli DNA polymerase I and RNase H, with mRNA enrichment performed using Dynabeads Oligo (dT). Libraries were quality-checked (Agilent 2100 Bioanalyzer), quantified (Qubit Fluorometer), and sequenced on an Illumina NovaSeq™ 6000 platform with a 150 bp paired-end strategy.

Data analysis of RNA-seq

Fastp software (https://github.com/OpenGene/fastp) were used to remove the reads that contained adaptor contamination, low quality bases and undetermined bases with default parameter. Then sequence quality was also verified using fastp. We used HISAT2 (https://ccb.jhu.edu/software/hisat2) to map reads to the reference genome of Rattus norvegicus Rnor-6.0. The mapped reads of each sample were assembled using StringTie (https://ccb.jhu.edu/software/stringtie) with default parameters. Then, all transcriptomes from all samples were merged to reconstruct a comprehensive transcriptome using gffcompare (https://github.com/gpertea/gffcompare/). After the final transcriptome was generated, StringTie was used to estimate the expression levels of all transcripts. StringTie was used to perform expression level for mRNAs by calculating FPKM. The differentially expressed mRNAs were selected with fold change > 2 or fold change < 0.5 and with parametric F-test comparing nested linear models (P value < 0.05) by R package edgeR (https://bioconductor.org/packages/release/bioc/html/edgeR.html).

Bioinformatic analysis of differentially expressed genes

Differentially expressed genes (DEGs) were analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment using the ClusterProfiler R package (v4.0.2) [11]. Protein-protein interaction (PPI) networks were constructed using the STRING database [12] and visualized with Cytoscape (v3.8.2) [13]. Based on the maximum clique centrality (MCC) algorithm in cytoHubba, the top 5 hub genes were identified and ranked from the PPI network [14]. Genes overlapping across significant pathways and hub gene analyses were designated as key regulatory genes.

GSEA analysis

GSEA was conducted to explore the signaling pathways in which the key gene might be involved. An adjusted p-value < 0.05 was considered statistically significant.

Protocols for animal experiment

Healthy C57BL/6 male mice (weight 25–30 g, 10–12 weeks old) were purchased from Guangdong Medical Laboratory Animal Center (Guangzhou, China). Mice were kept under a 12 h light/dark cycle at 25 ℃, water and food were freely accessible. The mice were acclimatized for one week before the experiment. The mice were randomly divided into four groups (n = 10 per group): Ctrl mice were injected with an appropriate amount of sterilized water; the SB-431,542 group received intraperitoneal injection of SB-431,542 at 10 mg/kg body weight [15]; the DOX group was given a single intraperitoneal injection of DOX at 15 mg/kg body weight together with an equal volume of DMSO; the DOX + SB-431,542 group was co-treated with SB-431,542 and DOX. After 7 days of injection, all mice were anesthetized by intraperitoneal injection of 2% tribromoethanol (Macklin, Shanghai, China), and blood samples and heart tissue were collected for further analyses.

All animal experimental procedures approved by the Institutional Animal Care and Use Committee (Approval Number: IACUC-HHGPHCM-2508001), and were performed in accordance with the Guide for the Care and Use of Laboratory Animals (2011 edition).

Measurement of serum creatine kinase-MB (CK-MB) and lactate dehydrogenase (LDH)

Blood samples were collected and centrifuged for 10 min at 3000 rpm to obtain serum. The concentration of CK-MB and LDH in serum was measured by commercially available kits from Rayto Life Technology (Shenzhen, China) according to the manufacturer’s instructions.

Hematoxylin and eosin (HE) staining

The Heart tissues were collected and fixed in 4% paraformaldehyde for 24 h, embedded in paraffin after dehydration, sliced to 5 μm, and subsequently stained with HE (Beyotime, Shanghai, China) according to the manufacturer’s instructions.

Western blot

Total protein was extracted from H9c2 cells using Radio immunoprecipitation assay (RIPA) lysis buffer (Beyotime, Shanghai, China). A 30 µg protein sample was separated on a 12% Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) gel and transferred onto a 0.22 μm Polyvinylidene difluoride (PVDF) membrane (Millipore, MA, USA). After blocking with 5% milk at room temperature, the membrane was incubated overnight at 4 °C with primary antibodies against p53 (1:1000, Proteintech, 10442-1-AP, Wuhan, China), p53 (1:1000, CST, 2524, MA, USA), Caspase-3 (1:1000, CST, 9662 S), cleaved- Caspase-3 (1:1000, CST, 9664 S), phospho-Smad2/3 (p-Smad2/3) (1:1000, CST, 8828), Smad2/3 (1:1000, CST, 8685), and GAPDH (1:1000, Proteintech, 60004-1-Ig) as a loading control. Protein bands were detected using an enhanced chemiluminescent detection kit (NCM Biotech, Suzhou, China), and densitometric analysis was performed using Tanon imaging software (Shanghai, China). All experiments were repeated at least three times.

RNA extraction and quantitative real-time polymerase chain reaction (qRT-PCR) analysis

Total RNA in H9c2 cardiomyocytes was extracted using Trizol reagent (Tiangen, Beijing, China) according to the manufacturer’s instructions. In short, 2000 ng of total RNA was reverse transcribed to cDNA using the FastKing gDNA Dispelling RT SuperMix kit (Tiangen, KR116, Beijing, China). Then, the cDNA was subjected to qRT-PCR using SYBR Green (Bio-Rad, 1725124, California, USA) according to the manufacturer’s instructions. GAPDH was used as a normalizing control. The mRNA level of TGF-β1 was calculated using the 2−ΔΔCt analytical method. The sequences of primers were listed in Table 1. All experiments were repeated at least three times.

Table 1.

Primer sequences used in this study

PCR Primers Sequence
Rat- TGF-β1-F 5’- CCTGGACACACAGTACAGCA-3’
Rat- TGF-β1-R 5’- TTGCGACCCACGTAGTAGAC-3’
Rat-GAPDH-F 5’-ACAGCAACAGGGTGGTGGAC − 3’
Rat-GAPDH-R 5’-TTTGAGGGTGCAGCGAACTT − 3’
Open in a new tab

Molecular docking analysis

The crystal structure of TGF-β receptor 1 (TGF-β-R1) (Protein Data Bank (PDB) ID: 3TZM) was gained from the PDB (www.rcsb.org) and prepared using PyMOL software (version 2.6.0a0). The solvent and organic molecules were removed to ensure a clean protein structure for further analysis. The 3D structures of candidate compounds were obtained from PubChem (https://pubchem.ncbi.nlm.nih.gov). Molecular docking was performed using AutoDock Vina to determine the specific binding modes between TGF-β-R1 and the candidate compounds. The docked complexes were analyzed for key interactions and binding energies.

Statistical analysis

Data were presented as mean ± Standard deviation (SD). A two-tailed Student’s t-test was used for comparisons between two groups, while one-way analysis of variance (ANOVA) followed by Tukey’s post hoc test was applied for multiple-group comparisons. P-value < 0.05 was considered statistically significant. Statistical analyses were conducted using SPSS 23.0.

Results

Overview of differentially expressed genes in DOX-treated cardiomyocytes

To identify DEGs in DOX-treated cardiomyocytes, RNA-seq analysis was performed on control and DOX-treated samples. Principal component analysis (PCA) revealed a distinct separation between the two groups along the first principal component (PC1), which explained 97% of the variance (Fig. 1A). This clustering highlights the substantial transcriptional changes induced by DOX treatment. Mean-average (MA) plots (Fig. 1B, C) showed a significant number of DEGs, which were identified based on |log2 fold change| > 1.5 and an adjusted P-value < 0.05. A total of 2,377 DEGs were detected, with 968 upregulated and 1,409 downregulated (Fig. 1D, E). Notably, upregulated genes, such as cytochrome P450 family 26 subfamily b polypeptide 1 (Cyp26b1), alcohol dehydrogenase iron containing 1 (Adhfe1), and t-complex 11 like 2 (Tcp11l2) were associated with oxidative stress and apoptosis, consistent with DOX-induced cardiotoxicity. Conversely, significantly downregulated genes, including gap junction protein alpha 5 (Gja5), dual specificity phosphatase 27 (Dusp27), and insulin-like growth factor binding protein 5 (Igfbp5), suggested potential disruptions in cellular signaling pathways. These results provide a foundation for further mechanistic investigation.

Fig. 1.

Fig. 1

Open in a new tab

Differential gene expression analysis in DOX-treated cardiomyocytes. (A) PCA showing distinct separation between the control and DOX-treated groups. (B) MA plots of DEGs in the control group. (C) MA plot of DEGs in the DOX group, with blue dots representing genes with significant expression changes. (D) Scatter plot showing differentially expressed genes in the DOX group. (E) Hierarchical clustering of differentially expressed genes in the DOX group

Functional enrichment analysis of differentially expressed genes

To elucidate the biological significance of the DEGs, GO and KEGG enrichment analyses were performed. For cellular component (CC), DEGs were significantly enriched in motile cilium (Fig. 2A); regarding biological process (BP), they were primarily enriched in pattern specification process, regionalization, and developmental maturation (Fig. 2B); the molecular function (MF) terms associated with these DEGs included potassium ion transmembrane transport and voltage-gated potassium channel activity (Fig. 2C). KEGG pathway analysis revealed significant enrichment in the mitogen-activated protein kinase (MAPK) signaling pathway (adjusted P-value < 0.01) (Fig. 2D), a key pathway involved in DOX-induced cardiomyocyte stress and apoptosis [16–18]. The above results suggest that DEGs play crucial roles in DOX-induced cardiotoxicity.

Fig. 2.

Fig. 2

Open in a new tab

GO and KEGG pathway enrichment analysis of DEGs. (A) GO enrichment analysis of cellular components (CC). (B) Biological process (BP) analysis. (C) Molecular function (MF) analysis of DEGs in the DOX group relative to the control group. (D) KEGG pathway analysis

Identification of hub genes and key pathways

To identify central regulatory genes, a PPI network was constructed using STRING and visualized with Cytoscape. Global network analysis revealed intricate connections among DEGs, forming dense clusters of core genes (Fig. 3A). Molecular complex detection (MCODE) plug-in in Cytoscape identified key hub genes, including interleukin-6 (Il6), TGF-β1, intercellular adhesion molecule-1 (Icam1), serine peptidase inhibitor clade E member 1 (Serpine1), and angiotensinogen (Agt), which are involved in oxidative stress, inflammation, and endothelial dysfunction (Fig. 3B). Ranking by MCC scores confirmed Il6 and TGF-β1 as the most prominent hub genes (Fig. 3C). ClueGo analysis indicated significant involvement in biological processes such as the positive regulation of ROS metabolism, nitric oxide biosynthesis, and fibroblast proliferation (Fig. 3D). This analysis also revealed significant enrichment in the receptor for advanced glycation endproducts (RAGE) signaling pathway (Fig. 3D, E). Collectively, these results indicate that Il6, TGF-β1, Icam1, Serpine1, and Agt are potential regulators in DOX-induced cardiotoxicity.

Fig. 3.

Fig. 3

Open in a new tab

PPI network and identification of hub genes. (A) Global PPI network constructed using STRING and visualized with Cytoscape. (B) The module with the highest score, where red nodes represent key hub genes. (C) The ladder graph of hub genes. (D) The ClueGo analysis of hub genes. (E) The hub genes among the cross-pathway DEGs

Identification of TGF-β1 as a key regulator in DOX-induced cardiotoxicity

To determine the key gene involved in DOX-induced cardiotoxicity, we intersected genes from the MAPK signaling pathway with the results of MCC algorithm analysis. As shown in Fig. 4A, TGF-β1 was the only overlapping gene, suggesting its central role in this pathological process. To further explore the functional enrichment of TGF-β1, a GSEA was conducted. TGF-β1 was found to be enriched in a total of 43 signaling pathways, with Fig. 4B displaying 10 representative pathways. Notably, TGF-β1 was again found to be involved in TGF-β signaling pathway in DOX-treated cardiomyocytes, as demonstrated by GSEA analysis (Fig. 4C). In addition, the mRNA level of TGF-β1 was significantly increased in DOX-treated cardiomyocytes (Fig. 4D). These results suggest that TGF-β1 may serve as a key regulator of DOX-induced cardiotoxicity.

Fig. 4.

Fig. 4

Open in a new tab

Analysis of hub genes and GSEA validation. (A) Venn diagram of overlapping genes between MAPK pathway-related genes and hub genes identified through MCC network analysis. (B) Ridge plot showing enriched pathways. (C) GSEA analysis of the TGF-β signaling pathway, with p-value = 0.03876. (D) The mRNA level of TGF-β1 was determined by qRT-PCR analysis (n = 3). All data are presented as the mean ± SD. *P < 0.05

Screening of TGF-β1 inhibitors

To evaluate TGF-β1 as a potential therapeutic target for DOX-induced cardiotoxicity, we screened compounds that inhibit its activity. Although no direct TGF-β1 inhibitors were identified, we found that the TGF-β receptor kinase inhibitor SB-431,542 has been reported to inhibit TGF-β-induced transcription, gene expression, apoptosis, and growth inhibition. Molecular docking analysis demonstrated that SB-431,542 directly binds to TGF-β-R1 (Fig. 5A-C); the binding energy was − 11.6 kcal/mol, which was significantly lower than the binding threshold of -5 kcal/mo. Functional experiments using SB-431,542 were conducted to further explore the role of TGF-β1 in DOX-induced cardiotoxicity.

Fig. 5.

Fig. 5

Open in a new tab

Screening and validation of TGF-β-R1 inhibitors. (A) 3D structure of the TGF-β-R1 protein. (B) Chemical structure of SB-431,542. (C) Docking model showing SB-431,542 binding within the ATP-binding pocket of TGF-β-R1. The compound forms hydrogen bonds with key residues Lys-213 and Asp-351, with a binding energy of -11.6 kcal/mol, indicating strong affinity and potential inhibitory activity

SB-431,542 attenuated DOX-induced cardiomyocyte injury

To investigate the protective effect of SB-431,542 against DOX-induced cardiomyocyte injury, cell viability was assessed in H9c2 cardiomyocytes using the CCK-8 assay. The results showed that 5, 10, and 15 µM SB-431,542 had no significant effect on H9c2 viability, whereas 20 µM exhibited mild cytotoxicity (Fig. 6A). Based on these findings, 15 µM SB-431,542 was selected for subsequent experiments. Compared with the control group, DOX treatment significantly reduced cardiomyocyte viability, whereas SB-431,542 mitigated this decrease (Fig. 6B). These findings suggest that the TGF-β receptor kinase inhibitor SB-431,542 alleviates DOX-induced cardiomyocyte injury.

Fig. 6.

Fig. 6

Open in a new tab

SB-431,542 attenuates DOX-induced cardiomyocyte injury. (A) The viability of H9c2 cardiomyocytes after treatment with different concentrations of SB-431,542 were detected by the CCK-8 kit (n = 3). *P < 0.05, ns = not significant, compared with ctrl. (B) The viability of H9c2 cardiomyocytes after DOX treatment and SB-431,542 intervention were determined by the CCK-8 kit (n = 3). (C) The expression levels of apoptosis marker proteins (Caspase-3, Cleaved-Caspase-3, p53) in H9c2 cardiomyocytes were detected by Western blot (n = 3). (D) The expression levels of Smad2/3 and p-Smad2/3 in H9c2 cardiomyocytes were detected by Western blot (n = 3). All data are presented as the mean ± SD. *P < 0.05, **P < 0.01, ns = not significant

To confirm the role of SB-431,542 in DOX-induced cardiomyocyte injury, we performed Western blot analysis to detect changes in apoptotic markers in H9c2 cardiomyocytes after DOX and SB-431,542 treatment. The results showed that, compared with the control group, the protein levels of cleaved-caspase-3 and p53 were significantly increased in H9c2 cardiomyocytes after DOX treatment, whereas SB-431,542 inhibited the DOX-induced increase in cleaved-caspase-3 and p53 expression (Fig. 6C). Furthermore, SB-431,542 also inhibits the DOX-induced increase in the expression level of phospho-Smad2/3 (p-Smad2/3) (Fig. 6D). The above results suggest that the TGF-β receptor kinase inhibitor SB-431,542 reduces DOX-induced cardiomyocyte apoptosis by inhibiting Smad2/3 phosphorylation.

SB-431,542 prevented DOX-induced cardiac injury

To verify the protective role of SB-431,542 in DOX-induced cardiotoxicity, we detected the effect of SB-431,542 on cardiac function in DOX-treated mice (Fig. 7A). Our results showed that SB-431,542 significantly decreased the serum concentrations of CK-MB and LDH (Fig. 7B, C), and alleviated DOX-induced cardiac injury (Fig. 7D) induced by DOX. Furthermore, SB-431,542 inhibited the DOX-induced increase in cleaved-caspase-3, p53 and p-Smad2/3 expression (Fig. 7E, F). These results suggested that SB-431,542 exerted a protective role in DOX-induced cardiac injury by inhibiting the phosphorylation of Smad2/3.

Fig. 7.

Fig. 7

Open in a new tab

SB-431,542 inhibits DOX-induced cardiac injury. (A) Schematic diagram for the establishment of the animal model. The concentration of CK-MB (B) and LDH (C) in serum were measured by CK-MB and LDH detection kits (n = 5). (D) Representative images of HE staining of mouse heart tissues. Scale bar: 50 μm. (E) The expression levels of apoptosis marker proteins (Caspase-3, Cleaved-Caspase-3, p53) in mouse heart tissues were detected by Western blot (n = 5). (F) The expression levels of Smad2/3 and p-Smad2/3 in mouse heart tissues were detected by Western blot (n = 5). All data are presented as the mean ± SD. *P < 0.05, **P < 0.01

Discussion

DOX is a widely used and effective antitumor drug; however, its clinical application is limited by cumulative and irreversible cardiotoxicity [9, 19, 20]. Extensive studies have shown that DOX-induced cardiotoxicity involves multiple molecular mechanisms, including the overproduction of ROS, calcium overload, mitochondrial dysfunction, apoptosis, pyroptosis, ferroptosis, and autophagy [21, 22]. Among these, apoptosis is considered a key contributor to this process. For instance, DOX can trigger the release of cytochrome c from mitochondria, activating caspase cascades and ultimately leading to apoptotic cell death, thereby exacerbating cardiac dysfunction [23]. Given the critical role of apoptosis in DOX-induced cardiotoxicity and the limitations of current therapeutic agents, it is crucial to explore novel therapeutic targets that modulate apoptotic signaling to protect cardiomyocytes from DOX-induced damage.

In the present study, we identified 2,377 DEGs in DOX-treated cardiomyocytes. These DEGs were predominantly associated with oxidative stress, apoptosis, and abnormal signaling pathways, all of which are closely linked to DOX-induced cardiotoxicity. Furthermore, KEGG pathway enrichment analysis revealed that many DEGs were clustered in the MAPK signaling pathway. Previous studies have demonstrated that activation of p38 MAPK and c-Jun N-terminal kinase (JNK) by DOX promotes cardiomyocyte apoptosis and mediates inflammatory responses, while dysregulation of extracellular signal-regulated kinase (ERK) further impairs cell survival and contractility [24–27]. These findings highlight the central role of MAPK-related pathways in DOX-induced cardiotoxicity.

To identify core targets of DOX-induced cardiotoxicity, we constructed a PPI network and performed topological analyses, which revealed 5 hub genes, with Il6 and TGF-β1 emerging as the most prominent. By intersecting MAPK pathway-related genes with the MCC algorithm, TGF-β1 was the only overlapping gene, suggesting it may be a key regulator of DOX-induced cardiotoxicity. Additionally, GSEA analyses confirmed that TGF-β1 plays a central role in DOX-induced cardiotoxicity. TGF-β1 is a pleiotropic cytokine involved in various biological processes, including fibrosis, inflammation, and apoptotic signaling [28–30]. Although direct evidence specifically related to DOX-induced cardiac injury is limited, a growing literature suggests that TGF-β1 may exacerbate DOX-induced cardiomyocyte damage by enhancing cardiac fibrosis and modulating interconnected signaling cascades. For example, TGF-β1 regulates extracellular matrix remodeling and stimulates fibroblast proliferation, contributing to adverse cardiac remodeling [31]. Moreover, in annulus fibrosus cells, TGF-β1 can reduce autophagy and apoptosis induced by oxidative stress through the ERK signaling pathway [32]. However, the precise role of TGF-β1 in DOX-induced cardiotoxicity requires further investigation.

To verify the potential of TGF-β1 as a therapeutic target for DOX-induced cardiotoxicity, we screened compounds that inhibit TGF-β1. Although we did not identify specific TGF-β1 inhibitors, we found that the TGF-β receptor kinase inhibitor SB-431,542 was effective. Molecular docking confirmed the effective binding between SB-431,542 and TGF-β-R1. Previous studies have reported that SB-431,542 effectively inhibits TGF-β-mediated transcriptional regulation, gene expression, and apoptosis [33, 34]. In line with these findings, our results showed that SB-431,542 treatment significantly alleviated DOX-induced cardiomyocyte apoptosis, as evidenced by improved cell viability and decreased expression of cleaved caspase-3 and p53. A recent study has proven that TGF-β1/Smad signaling pathway mediates the DOX-induced cardiotoxicity [35]. In addition, as the downstream effectors of TGF-β1, Smad2 and Smad3 play pivotal roles in mediating cell fibrosis, apoptosis, and inflammation [35, 36]. We therefore investigated whether the protective role of SB-431,542 in DOX-induced cardiac injury was mediated by Smad2 and Smad3. Our results suggested that SB-431,542 exerted a protective role in DOX-induced cardiac injury by inhibiting the phosphorylation of Smad2/3.

While earlier studies primarily focused on SB-431,542’s anti-fibrotic and anti-inflammatory effects downstream of TGF-β1 signaling [37, 38], our data underscore its direct cytoprotective role in counteracting DOX-mediated apoptotic pathways. This discrepancy highlights the broad spectrum of TGF-β signaling in cardiology and reinforces the clinical potential of targeting TGF-β1/TGF-β-R1 axis in DOX-induced cardiac injury.

Overall, our findings not only identify TGF-β1 as a pivotal molecular mediator in DOX-induced cardiotoxicity but also provide experimental evidence supporting SB-431,542 as a potential therapeutic agent. These results lay the foundation for further in-depth studies and the development of targeted strategies to mitigate cardiotoxic risks while preserving DOX’s antineoplastic efficacy.

However, the present study has some limitations: First, the inhibition or gene knockdown experiments should be carried out to validate the role of TGF-β1 in DOX-induced cardiotoxicity. Second, the protective role of SB-431,542 in DOX-induced cardiac injury should be confirmed on primary cardiomyocytes in further research.

Conclusion

In conclusion, our study identifies TGF-β1 as a central regulator of DOX-induced cardiotoxicity and highlights SB-431,542 as a promising therapeutic agent for mitigating cardiomyocyte apoptosis. The protective role of SB-431,542 in DOX-induced cardiac injury was mediated by Smad2 and Smad3. Targeting TGF-β signaling axis may offer a novel strategy to enhance the clinical safety of DOX in cancer treatment.

Supplementary Information

Supplementary Material 1. (569.2KB, pdf)

Acknowledgements

We would like to thank all the colleagues in our research team for technical support.

Abbreviations

DOX

Doxorubicin

RNA-seq

RNA sequencing

DEGs

Differentially expressed genes

KEGG

Kyoto encyclopedia of genes and genomes

PPI

Protein-protein interaction

MCC

Maximum clique centrality

GSEA

Gene set enrichment analysis

CCK-8

Cell counting kit-8

CK-MB

Creatine kinase-MB

LDH

Lactate dehydrogenase

HE

Hematoxylin and eosin

RIPA

Radio immunoprecipitation assay

ROS

Reactive oxygen species

TGF-β-R1

TGF-β receptor 1

TGF-β1

Transforming growth factor-beta 1

MAPK

Mitogen-activated protein kinase

RAGE

Receptor for advanced glycation endproducts

DEX

Dexrazoxane

FDA

Food and drug administration

Bax

Bcl-2-associated X protein

DMEM

Dulbecco’s modified eagle medium

GO

Gene ontology

PCA

Principal component analysis

PC1

Principal component 1

MA

Mean-average

MCODE

Molecular complex detection

Il6

Interleukin-6

Icam1

Intercellular adhesion molecule-1

Serpine1

Serine peptidase inhibitor clade E member 1

Agt

Angiotensinogen

RIPA

Radio immunoprecipitation assay

SDS-PAGE

Sodium dodecyl sulfate-polyacrylamide gel electrophoresis

PVDF

Polyvinylidene difluoride

qRT-PCR

Quantitative real-time polymerase chain reaction

PDB

Protein data bank

SD

Standard deviation

ANOVA

Analysis of variance

BP

Biological process

CC

Cellular component

MF

Molecular function

Author contributions

CM, ZZ, KZ and YC conceived and designed the study. CM, ZZ and DX performed the experiments. CM, ZZ, JH, XL, WZ and MZ conducted the data analysis and plotted the graphs for figures. MZ and KZ interpreted the results of experiments. CM, KZ, and YC wrote the manuscript. All authors read and approved the final manuscript.

Funding

This work was supported by the National Natural Science Foundation of China (Grant Number: 82360063) and the Hainan Provincial Natural Science Foundation of China (High-level Talent Project) (Grant Number: 821RC1127). The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.

Data availability

RNA-seq data have been deposited in the NCBI SRA database (Accession number: PRJNA1327474). To access the data go to page [https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA990838](https:/www.ncbi.nlm.nih.gov/sra/?term=PRJNA990838) , data will be available as soon as the article is published online. The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.

Declarations

Ethics approval and consent to participate

All animal experimental procedures approved by the Institutional Animal Care and Use Committee (Approval Number: IACUC-HHGPHCM-2508001), and were performed in accordance with the Guide for the Care and Use of Laboratory Animals (2011 edition).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Cong Mao and Zhuo Zhang contributed equally to this work.

Contributor Information

Mengya Zeng, Email: zmyalucky@hainmc.edu.cn.

Keyan Zhong, Email: hy0308016@hainmc.edu.cn.

Yuewu Chen, Email: eyuewu@126.com.

References

  • 1.Antoniak S, Phungphong S, Cheng Z, Jensen BC. Novel Mechanisms of Anthracycline-Induced Cardiovascular Toxicity: A Focus on Thrombosis, Cardiac Atrophy, and Programmed Cell Death. Front Cardiovasc Med. 2021;8:817977. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Shu G, Chen K, Li J, Liu B, Chen X, Wang J, et al. Galangin alleviated Doxorubicin-induced cardiotoxicity by inhibiting ferroptosis through GSTP1/JNK pathway. Phytomedicine. 2024;134:155989. [DOI] [PubMed] [Google Scholar]
  • 3.Zhang L, Kong HW, Song XY, Sheng LS, Huang NN, Liu Y, et al. Danggui buxue decoction attenuates doxorubicin-induced cardiotoxicity by inhibiting ZBP1-mediated PANoptosis in vivo and in vitro. Phytomedicine. 2025;145:157037. [DOI] [PubMed] [Google Scholar]
  • 4.Li Y, Yan J, Yang P. The mechanism and therapeutic strategies in doxorubicin-induced cardiotoxicity: Role of programmed cell death. Cell Stress Chaperones. 2024;29(5):666–80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Arrigoni R, Jirillo E, Caiati C. Pathophysiology of Doxorubicin-Mediated Cardiotoxicity. Toxics. 2025;13(4):277. [DOI] [PMC free article] [PubMed]
  • 6.Al Khafaji AT, Barakat AM, Shayyal AJ, Taan AA, Aboqader Al-Aouadi RF. Managing Doxorubicin Cardiotoxicity: Insights Into Molecular Mechanisms and Protective Strategies. J Biochem Mol Toxicol. 2025;39(2):e70155. [DOI] [PubMed] [Google Scholar]
  • 7.Zhang Y, Liu S, Ma JL, Chen C, Huang P, Ji JH, et al. Apocynum venetum leaf extract alleviated doxorubicin-induced cardiotoxicity through the AKT/Bcl-2 signaling pathway. Phytomedicine. 2022;94:153815. [DOI] [PubMed] [Google Scholar]
  • 8.Wen SY, Ali A, Huang IC, Liu JS, Chen PY, Padma Viswanadha V, et al. Doxorubicin induced ROS-dependent HIF1alpha activation mediates blockage of IGF1R survival signaling by IGFBP3 promotes cardiac apoptosis. Aging. 2023;15(1):164–78. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Lin Z, Wu C, Song D, Zhu C, Wu B, Wang J, et al. Sarmentosin alleviates doxorubicin-induced cardiotoxicity and ferroptosis via the p62-Keap1-Nrf2 pathway. Redox Rep. 2024;29(1):2392329. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Wang S, Sun A, Li L, Zhao G, Jia J, Wang K, et al. Up-regulation of BMP-2 antagonizes TGF-beta1/ROCK-enhanced cardiac fibrotic signalling through activation of Smurf1/Smad6 complex. J Cell Mol Med. 2012;16(10):2301–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47(D1):D607–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY. cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol. 2014;8(Suppl 4):S11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Chang H, Shen Q, Tan Y, Tong J, Zhang Z, Ouyang W, et al. Red light promotes dermis-epidermis remodeling via TGFbeta and AKT-mediated collagen dynamics in naturally aging mice. Zool Res. 2025;46(5):967–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Xie L, Xue F, Cheng C, Sui W, Zhang J, Meng L, et al. Cardiomyocyte-specific knockout of ADAM17 alleviates doxorubicin-induced cardiomyopathy via inhibiting TNFalpha-TRAF3-TAK1-MAPK axis. Signal Transduct Target Ther. 2024;9(1):273. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Chen Y, Tu Y, Cao J, Wang Y, Ren Y. Rhein Alleviates Doxorubicin-Induced Myocardial Injury by Inhibiting the p38 MAPK/HSP90/c-Jun/c-Fos Pathway-Mediated Apoptosis. Cardiovasc Toxicol. 2024;24(11):1139–50. [DOI] [PubMed] [Google Scholar]
  • 18.Li S, Liu H, Lin Z, Li Z, Chen Y, Chen B, et al. Isoorientin attenuates doxorubicin-induced cardiac injury via the activation of MAPK, Akt, and Caspase-dependent signaling pathways. Phytomedicine. 2022;101:154105. [DOI] [PubMed] [Google Scholar]
  • 19.Dabour MS, Abdelgawad IY, Sadaf B, Daniel MR, Grant MKO, Seelig D, et al. Losmapimod ameliorates doxorubicin-induced cardiotoxicity through attenuating senescence and inflammatory pathways. Biomed Pharmacother. 2024;179:117288. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Liu D, Cheng X, Wu H, Song H, Bu Y, Wang J, et al. CREG1 attenuates doxorubicin-induced cardiotoxicity by inhibiting the ferroptosis of cardiomyocytes. Redox Biol. 2024;75:103293. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Tai P, Chen X, Jia G, Chen G, Gong L, Cheng Y, et al. WGX50 mitigates doxorubicin-induced cardiotoxicity through inhibition of mitochondrial ROS and ferroptosis. J translational Med. 2023;21(1):823. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Zha W, Zhao Q, Xiao Y, Gan Y, Wei J, Yu M, et al. Mitochonic acid 5 rescues cardiomyocytes from doxorubicin-induced toxicity via repressing the TNF-α/NF-κB/NLRP3-mediated pyroptosis. Int Immunopharmacol. 2023;123:110736. [DOI] [PubMed] [Google Scholar]
  • 23.Christidi E, Brunham LR. Regulated cell death pathways in doxorubicin-induced cardiotoxicity. Cell Death Dis. 2021;12(4):339. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Wen SY, Tsai CY, Pai PY, Chen YW, Yang YC, Aneja R, et al. Diallyl trisulfide suppresses doxorubicin-induced cardiomyocyte apoptosis by inhibiting MAPK/NF-κB signaling through attenuation of ROS generation. Environ Toxicol. 2018;33(1):93–103. [DOI] [PubMed] [Google Scholar]
  • 25.Kitakata H, Endo J, Ikura H, Moriyama H, Shirakawa K, Katsumata Y et al. Therapeutic Targets for DOX-Induced Cardiomyopathy: Role of Apoptosis vs. Ferroptosis. Int J Mol Sci. 2022;23(3):1414. [DOI] [PMC free article] [PubMed]
  • 26.Hu YH, Liu J, Lu J, Wang PX, Chen JX, Guo Y, et al. sFRP1 protects H9c2 cardiac myoblasts from doxorubicin-induced apoptosis by inhibiting the Wnt/PCP-JNK pathway. Acta Pharmacol Sin. 2020;41(9):1150–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Lavoie H, Gagnon J, Therrien M. ERK signalling: a master regulator of cell behaviour, life and fate. Nat Rev Mol Cell Biol. 2020;21(10):607–32. [DOI] [PubMed] [Google Scholar]
  • 28.Ying H, Fang M, Hang QQ, Chen Y, Qian X, Chen M. Pirfenidone modulates macrophage polarization and ameliorates radiation-induced lung fibrosis by inhibiting the TGF-beta1/Smad3 pathway. J Cell Mol Med. 2021;25(18):8662–75. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Lei Z, Tang R, Wu Y, Mao C, Xue W, Shen J et al. TGF-beta1 induces PD-1 expression in macrophages through SMAD3/STAT3 cooperative signaling in chronic inflammation. JCI Insight. 2024;9(7):e165544. [DOI] [PMC free article] [PubMed]
  • 30.Liu Y, Lin S, Wang J, Jiang J, Shu A, Zhou M. TGF-beta1 inhibits apoptosis of cardiomyocytes H9c2 by regulating autophagy and ERK pathway. Gen Physiol Biophys. 2024;43(6):525–34. [DOI] [PubMed] [Google Scholar]
  • 31.Narikawa M, Umemura M, Tanaka R, Fujita T, Yokoyama U, Ishigami T, et al. Acute Hyperthermia Inhibits TGF-β1-induced Cardiac Fibroblast Activation via Suppression of Akt Signaling. Sci Rep. 2018;8(1):6277. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Ni B, Shen H, Wang W, Lu H, Jiang L. TGF-β1 reduces the oxidative stress-induced autophagy and apoptosis in rat annulus fibrosus cells through the ERK signaling pathway. J Orthop Surg Res. 2019;14(1):241. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Halder SK, Beauchamp RD, Datta PK. A specific inhibitor of TGF-beta receptor kinase, SB-431542, as a potent antitumor agent for human cancers. Neoplasia. 2005;7(5):509–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Yadav P, Kundu P, Pandey VK, Amin PJ, Nair J, Shankar BS. Effects of prolonged treatment of TGF-betaR inhibitor SB431542 on radiation-induced signaling in breast cancer cells. Int J Radiat Biol. 2022;98(11):1630–44. [DOI] [PubMed] [Google Scholar]
  • 35.Zhou S, Meng Z, Lu L, Xie J, Li L, Cheng H, et al. ELABELA-32 Alleviates Doxorubicin-Induced Chronic Cardiotoxicity by Inhibiting the TGF-beta/Smad Signaling Pathway. Cardiovasc Toxicol. 2025;25(7):1009–21. [DOI] [PubMed] [Google Scholar]
  • 36.Hao M, Jiao K. Jatrorrhizine reduces myocardial infarction-induced apoptosis and fibrosis through inhibiting p53 and TGF-beta1/Smad2/3 pathways in mice. Acta Cir Bras. 2022;37(7):e370705. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Lee AJ, Mahoney CM, Cai CC, Ichinose R, Stefani RM, Marra KG, et al. Sustained Delivery of SB-431542, a Type I Transforming Growth Factor Beta-1 Receptor Inhibitor, to Prevent Arthrofibrosis. Tissue Eng Part A. 2021;27(21–22):1411–21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Xia Y, Jiang C, Yang M, Liu T, Zou X, Li C, et al. SB431542 alleviates lupus nephritis by regulating B cells and inhibiting the TLR9/TGFbeta1/PDGFB signaling. J Autoimmun. 2022;132:102894. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (569.2KB, pdf)

Data Availability Statement

RNA-seq data have been deposited in the NCBI SRA database (Accession number: PRJNA1327474). To access the data go to page [https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA990838](https:/www.ncbi.nlm.nih.gov/sra/?term=PRJNA990838) , data will be available as soon as the article is published online. The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors.

Articles from Journal of Cardiothoracic Surgery are provided here courtesy of BMC

RESOURCES