This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.The 120th amino acid in the DNA-binding domain of p53 is a lysine residue. This site is known to provide an important acetylation modification that enables p53 to function as a transcription factor, regulating its sequence-specific DNA-binding ability and the transcription of downstream target genes involved in growth arrest or apoptosis (1-9). Acetylation of lysine 120 is a key regulatory mechanism that plays an essential role in mediating p53’s pro-apoptotic function (8, 10). Mutations at this site may therefore directly affect the activity of p53 due to the lack of acetylation. The TP53 c.359A>G mutation, which replaces lysine with arginine, has been identified in several cancers (11-16), and the loss of this acetylation event is likely involved in disrupting p53’s tumor suppressor function, contributing to tumorigenesis. Despite this, a mouse model harboring this mutation exhibits a phenotype indistinguishable from wild-type (WT) mice, and the putative tumorigenic potential of this mutation has not been elucidated (4). To investigate this issue, we previously created cells with the TP53 c.359A>G mutation using a bacterial artificial chromosome (BAC)-based homologous recombination system in human induced pluripotent stem cells (hiPSCs), which revealed that the mutation severely impairs normal splicing of TP53 mRNA by creating a novel splice donor site (5).
Using TP53 c.359A>G-mutant hiPSCs, we aimed to restore the normal splicing pattern and assess the effects of splicing correction, proposing RNA therapy to mask the cryptic splice donor caused by the mutation. Antisense Morpholino Oligomers (AMOs), well-known splicing modulators, are short oligonucleotides consisting of approximately 25 nucleotides (17, 18). Their structure consists of nucleic acid bases positioned on the backbone of morpholine rings. This unique structure confers significant stability against nuclease degradation while maintaining sequence-specific binding to the target RNA, effectively modulating mRNA translation or splicing. Given their ability to target cryptic splice donor or acceptor sites and intervene in premature mRNA processing, AMO’s are ideal for correcting the cryptic splice donor site created by the TP53 c.359A>G mutation (5). In this study, we explored the therapeutic potential of AMOs by evaluating the restoration of tumor suppressor functions, such as cell growth inhibition and apoptosis induction, in mutant p53 proteins. Since p53 mediates cellular responses like apoptosis and growth inhibition under genotoxic stress (e.g., doxorubicin treatment), we examined the potential of AMO-based primary treatment by analyzing the effects of the mutant p53 protein following drug treatment.
To determine whether the function of the p53 protein encoded by the TP53 c.359A>G mutation is restored, RNA expression must be recovered sufficiently for translation. We previously screened for effective AMOs that could restore major TP53 transcripts by masking the cryptic splicing donor site caused by the mutation (5) (Fig. 1A). Based on this RNA therapeutic approach, we aimed to identify effective combination therapies using sequential treatment with doxorubicin, a chemotherapy drug. Doxorubicin is a potent chemotherapeutic agent that inhibits cancer cell growth or induces apoptosis through p53 activation by inducing DNA damage (19, 20). However, doxorubicin has limitations in stabilizing the mutant p53 protein, which has extremely low quantitative expression due to the TP53 c.359A>G mutation, as it increases the stability of p53, maintaining its basal level. Therefore, to identify the activity and function of the mutant p53 protein in response to genotoxic stress, transcript restoration by AMO is required. We confirmed the expression levels of each variant using a probe that could specifically detect variant 1 derived from the authentic splicing donor (aSD-V1) located between exon 4 and intron 4 of TP53, and variant 2 derived from the cryptic splicing donor (cSD-V2) created by the mutation (Fig. 1B). As shown in Fig. 1C, normal TP53 transcripts were unaffected by AMO, whereas aSD-V1, which showed low expression due to the TP53 c.359A>G mutation, was considerably increased by AMO. However, similar to normal TP53 transcripts, genotoxic stress did not further influence the AMO-mediated restoration of mutant transcripts. In TP53 c.359A> G-mutant cells, AMO-restored TP53 transcripts resulted in significant p53 protein synthesis through translation. Restoration of the transcript pool enabled a quantitative increase in p53 protein levels in response to the sequential administration of doxorubicin (Fig. 1D). This enhanced protein is a p53 K120R mutant encoded by TP53 c.359A>G. Generally, p53 is a transcription factor that determines cell fate, such as cell growth inhibition or apoptosis, by regulating target gene expression; however, mutations can alter its function as a transcriptional regulator (21, 22). In this context, the expression of some target proteins was confirmed. While the p53 K120R mutant protein normally regulated the expression of Mdm2 and PUMA, which are related to cell survival and apoptosis, it exhibited a serious defect in regulating p21 expression, a key gene in cell growth inhibition (Fig. 1D). These findings suggest functional alterations in p53 K120R, characterized by the retention of apoptotic capacity and loss of cell growth inhibition function, but also indicate that not all target genes are dependent on p53 K120R transcriptional regulation. To further understand the impact of p53 K120R on transcriptional regulation, we performed a comprehensive whole-transcriptome analysis to investigate the dependence of target genes on the p53 K120R protein.
To comprehensively analyze the transcriptional impacts of the p53 K120R mutation and its recovery with AMO, we generated RNA-seq datasets to examine the expression profiles of cells harboring either mutant or WT-p53 under treatment with AMO and/or doxorubicin. The expression level of CDKN1A, a representative p53 target gene, was downregulated in mutant p53 cells compared to WT and increased by doxorubicin; however, the expression levels of BBC3 or MDM2 were not enhanced by AMO to the level of WT in mutant p53 cells (Fig. 2A). To systematically analyze the effects of the p53 K120R mutation, we performed differential gene expression analysis (Fig. 2B) and identified 825 significantly downregulated genes (Supplementary Table 1). Among these, 84 genes consistently increased expression after doxorubicin treatment under all conditions (Fig. 2C). Pathway analysis of these genes revealed enrichment in the p53 signaling pathway, confirming that the mutation substantially altered p53 target gene behavior (Fig. 2D).
Further analysis of AMO treatment on these 84 genes showed that AMO treatment significantly enhanced their expression in response to doxorubicin in p53 mutant cells but not in WT cells (Fig. 3A). We defined the recovery effects of AMO treatment based on expression levels in p53 mutant cells compared to WT cells. Using the median recovery effect as a threshold, these genes were divided into two groups: BBC3 and MDM2 were categorized as the high-recovery group, while CDKN1A was in the low-recovery group (Fig. 3B). Pathway analysis of each group indicated that genes involved in apoptotic processes were predominantly enriched in the high-recovery group, whereas genes associated with cell cycle arrest were enriched in the low-recovery group (Fig. 3C). These genes, whether involved in apoptotic processes or cell cycle arrest, showed distinct clustering based on recovery and mutation effects (Fig. 3D). For example, in response to doxorubicin, AMO treatment significantly increased the expression of PMAIP1, which encodes NOXA, similar to the increase observed for BBC3 (Supplementary Fig. 1). Conversely, it resulted in only a minor recovery in the expression of PLK2, similar to changes observed in CDKN1A. These findings suggest that AMO treatment selectively restores p53 function, with a more pronounced recovery observed in proapoptotic genes than in those associated with cell cycle control.
To ensure compatibility with the comprehensive analysis results, we evaluated the expression of several p53 target genes, including CDKN1A, BBC3, and MDM2. As shown in the expression patterns of target genes regulated by p53 K120R in Fig. 1D and Fig. 2A, p53 K120R consistently exerted or did not exert an influence on their transcript expression. In the absence of AMO treatment, even if genotoxic stress was induced, the p53 protein was insufficient to perform its role as a transcriptional regulator. In contrast, compared to normal p53, AMO-mediated restoration of major TP53 transcripts contributed to a quantitative increase in p53 K120R protein and enhanced transcript expression of pro-apoptotic BBC3 and cell survival-related MDM2 as a synergistic effect of genotoxic stress (Fig. 4B, C). However, the expression of CDKN1A, a cell cycle arrest gene, did not significantly increase (Fig. 4A). These findings suggest that the p53 K120R mutant protein selectively regulates the expression of typical p53 target genes. Since p53 primarily exerts its function by regulating target gene expression, selective regulation of target genes leads to corresponding functional changes.
The impairment of gene expression related to cell growth arrest ultimately manifests as a failure to regulate cell growth arrest. Following doxorubicin treatment, the positivity rate for Ki67, a proliferation marker, was significantly reduced in normal p53 cells. However, despite the restoration of p53 expression levels by AMO treatment, Ki67 positivity was retained in p53 mutant cells (Fig. 4D, E). This reflects a defect in the cell growth inhibition function of p53 K120R due to the loss of regulatory function of cell growth-related target genes. In contrast, under conditions that induce apoptosis, p53 K120R mutant cells exhibited a partial apoptotic response to genotoxic stress, sensitized by AMO treatment (Fig. 4F, G). This indicates that the p53 K120R protein restored by AMO retains some degree of pro-apoptotic function. These findings suggest that the significant impairment of cell cycle arrest gene expression and the retention of pro-apoptotic gene expression may indicate that lysine 120 acetylation plays a more important role in regulating cell cycle-related genes than apoptosis-related genes. Thus, a synergistic effect may be achieved by sequentially administering AMO as an RNA therapeutic agent and doxorubicin as a chemical therapeutic to restore the function of p53 K120R.
Given that p53 mutations can have wide-ranging functional consequences, understanding their complex impacts requires multilevel analyses of the genome, transcriptome, and proteome. Recent large-scale proteogenomic studies provided valuable insights for assessing the functional impact of proteins and acetylation markers (23). These proteogenomic resources are also invaluable for examining posttranslational modifications, such as acetylation defects linked to cancer (24). Future research should leverage these datasets to deepen our understanding of K120R-related biological effects.
Understanding the properties of normal and mutant amino acids can help predict functional changes in mutant proteins. Lysine and arginine are both positively charged polar amino acids, suggesting that the lysine-to-arginine substitution in p53 K120R is a conservative change (25, 26). This implies that the p53 K120R mutation likely retains its tumor suppressor functions. Indeed, previous studies on the tumorigenic potential of the mouse p53 K117R mutation, which corresponds to human p53 K120R, reported no tumor formation (4). However, lysine 120 of p53 is an important acetylation site linked to p53 activation, suggesting that the functions of p53 K120R are unlikely to be identical to those of WT-p53. Due to these differences between the WT and mutant proteins, the p53 K120R mutant exhibited impaired transcriptional induction of the CDKN1A gene and compromised growth arrest, implying that acetylation of lysine 120 may be crucial for the cell growth inhibitory function of p53. Studies on the tumorigenic impact of the p53 K120R mutant protein, particularly the potential link between lysine 120 acetyl defects and tumor formation, suggest that targeting this site may be beneficial for therapy. Nonetheless, prior to functional characterization of the mutant protein by artificially expressing p53 K120R in cancer cell lines, studies targeting mutant TP53 mRNA are essential for restoring p53 function. Cell-based mutation studies may vary across cell types, but our model endogenously expressed TP53 transcripts using a gene knock-in approach, rather than artificially expressing a mutant gene. Therefore, TP53 c.359A>G-mutant hiPSCs not only complement previous cancer cell line-based studies but also provide important insights into determining therapeutic targets at the RNA level for restoring p53 function prior to doxorubicin-induced p53 activation as a chemical therapeutic.
Human iPSCs (hiPSCs) were cultured in the mTeSRTM Plus medium (STEMCELL Technologies). hiPSCs were differentiated into myoblasts using the Skeletal Muscle Differentiation Kit (Amsbio), and into the endoderm lineage using the STEMdiffTM Definitive Endoderm Kit (STEMCELL Technologies), respectively.
AMO (sequence: ACCTGGCTGTCCCAGAATGCAAGAA) was purchased from GeneTool. To introduce this into hiPSCs, the 40 μM AMO transfection was performed using a Gene Pulser XcellTM Electroporation System (BioRad) under the following conditions: 250 V and 200 μF.
Cellular RNA was isolated using the RNeasy Mini Kit (QIAGEN Germany, Hilden) according to the manufacturer’s instructions. cDNA was synthesized from 1 μg of total RNA using the Superscript III First Strand Synthesis System (Invitrogen). Quantitative PCR was performed using Power SYBR Green PCR Master Mix (Applied Biosystems), TaqManTM Gene Expression Master Mix, and the QuantStudioTM 6 Flex Real-Time PCR System (Applied Biosystems). Primer sequences are listed in Supplementary Table 2.
RNA-seq data were obtained with n = 1 for each specific condition without replicates, including WT or mutant TP53, control, AMO, and treatment with DMSO or doxorubicin, resulting in eight cases. The RNA Integrity Number (RIN) of each sample was > 7.0 (Supplementary Table 3). cDNA libraries were constructed using the QuantSeq 3’ mRNA-Seq Library Prep Kit (Lexogen, Inc., Vienna, Austria) and sequenced on a NextSeq 500 (Illumina Inc., San Diego, CA, USA) to generate single-end 75 bp reads according to the manufacturer’s instructions. The reads were trimmed for adapters and low-quality bases using bbduk (v.39.01), mapped to the reference genome using STAR (v.2.7.10b), and quantified using HTSeq-count (v.2.0.2).
Bioinformatics analysis of the RNA-seq data was performed using R (v4.3.1). Differential gene expression analysis was conducted using the DESeq2 package (v1.42.2), and the mutation effect of TP53 c.359A>G was calculated as fold change by comparing the TP53 mutation (control condition) to WT (both control and AMO conditions), specifically in cases with DMSO. The recovery effect of AMO was calculated as a ratio by comparing the TP53 mutation to WT, specifically in AMO-treated cases with DMSO. Genes were categorized into high and low expression groups based on the median value of the recovery effect. Pathway enrichment analysis was conducted using the enrichment package (v3.2).
Nitrocellulose membranes were probed with primary antibodies against p53 (Santa Cruz Biotechnology; Cat# sc-6243), p21 (Cell signaling Technology; Cat#12D1), PUMA (Santa Cruz Biotechnology; Cat# sc-374223), MDM2 (Santa Cruz Biotechnology; Cat# sc-13161), and β-actin (Santa Cruz Biotechnology; Cat# sc-47778). After incubation with goat anti-rabbit (Cat# ADI-SAB-300-J) and anti-mouse (Cat# ADI-SAB-100-J) IgG-horseradish peroxidase (Enzo Life Sciences), the blots were developed using enhanced chemiluminescence detection (Thermo Scientific). Immunoreactivity was evaluated using the ImageQuant LAS 4000 Analysis System (GE Healthcare).
WT and TP53 c.359A>G AMO-transfected hiPSCs were treated with 0.2 μM doxorubicin for 6 h. The cells were processed using an Annexin V-FITC Apoptosis Detection Kit (BD Pharmingen) according to the manufacturer’s instructions and analyzed with a BD FACSCalibur flow cytometer (BD Biosciences).
Myoblasts were transfected with 20 μM AMO for 48 h using Endo-porter, following the manufacturer’s instructions (Gene Tools). They were pre-treated with 0.2 μM doxorubicin for 4 h, and the medium was then replaced with fresh medium without DOX. After 24 h, cells were fixed with 4% paraformaldehyde (PFA, Biosesang) and stained with the following primary antibodies: Ki67 (1:1000), Abcam ab16667; p53 (1:200), Santa Cruz sc-126) and fluorescent secondary antibodies: Alexa Fluor 488 goat anti-mouse IgG (1:1000), Thermo Fisher A11001; Alexa Fluor 594 goat anti-rabbit IgG (1:1000), Thermo Fisher A11012. Images were captured using an EVOS M5000 imaging system (Thermo Fisher Scientific).
Endodermal lineage cells were transfected with 20 μM AMO and pre-treated with 0.2 μM doxorubicin for 12 h. The medium was then replaced with fresh medium containing 10 μM EdU (no doxorubicin). EdU-incorporated cells were detected via fluorescence imaging 24 h later using the Click-iT Plus EdU imaging kit (Invitrogen) following the manufacturer’s instructions.
Statistical analyses were performed using Prism version 8 (GraphPad Software, Inc.). The numbers of replicates is reported in the figure legends. All data were expressed as means ± SEM from at least three independent experiments. Statistical significance was obtained by one-way ANOVA test or an unpaired Student’s t-test.
The RNA-seq data are publicly available in the Gene Expression Omnibus (GEO) under the accession number GSE274604.
This study was funded by the Korea Institute of Oriental Medicine (grant numbers KSN20233302 and KSN2021240).
The authors have no conflicting interests.
Fig. 1. Restoration of TP53 expression by AMO treatment. (A) AMO masks the cryptic splicing donor site caused by the TP53 c.359A>G mutation (5). (B) Annealing positions of primer pairs and probes specifically detect the two variants in the TaqMan assay. (C) Recovery of the major TP53 variant after AMO treatment. Data are presented as mean ± SEM (n = 3), ****P < 0.0001, **P < 0.01. (D) Expression patterns of the p53 protein and its target proteins following AMO treatment. AMO, antisense morpholino oligomer. Ctrl, control. WT, wild-type. aSD-V1: authentic spliced donor-derived variant 1. cSD-V2: cryptic splice donor-derived variant 2. DOXO, δoxorubicin. ND, not detected. See Supplementary Table 1 for Fig. 1B.
Fig. 2. Transcriptional impact of TP53 c.359A>G mutation and AMO treatment. (A) Expression levels of key p53 target genes CDKN1A, BBC3, and MDM2 under different conditions. Expression levels are calculated as log2-transformed Transcripts Per Million (TPM) ＋ 1. (B) A volcano plot shows differential gene expression analysis of μutation effects. Genes significantly differentially expressed (P < 0.05) with fold-changes >1.5 (upregulated) or <−1.5 (downregulated) are shown in red or blue, respectively. Key p53 target genes are highlighted. (C) A Venn diagram displays the overlap of genes whose expression was increased by DOXO treatment across four conditions, derived from the 825 genes significantly downregulated by the mutation. (D) Pathway enrichment analysis of 84 selected genes using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Significance is calculated using the −log10 value of the adjusted P-value. AMO, antisense morpholino oligomer. Ctrl, control. DOXO, doxorubicin.
Fig. 3. Distinct effects of AMO on p53 target gene expression. (A) The ratio of expression levels of the 84 selected genes in TP53 μutant versus WT cells under AMO conditions. Statistical significance was evaluated using an unpaired Student’s t-test. (B) Recovery effects of the 84 selected genes categorized into high and low groups based on the median, as indicated by a dashed line. (C) Pathway enrichment analysis of the high-(left) and low-(right) recovery groups using the Gene Ontology (GO) database, with distinct pathways enriched in the low recovery group. Significance is calculated using the −log10 value of the adjusted P-value. (D) Clustering of genes based on mutation and recovery effects. Genes involved in apoptotic processes and cell cycle arrest are colored differently. AMO, antisense morpholino oligomer.
Fig. 4. Regulation of p53 target genes by AMO and its effects on p53 function. (A, B, C) Expression patterns of p53 target genes induced by AMO: CDKN1A (A), BBC3 (B), and MDM2 (C). Data are presented as mean ± SEM (n=3), ****P < 0.0001, ***P < 0.001, #P > 0.05. (D, E) Representative immunofluorescence images show the effect of AMO on the growth of myoblasts (D) and endodermal lineage cells (E) stained for Ki67, a cell proliferation marker. (F, G) Analysis of the effect of AMO on apoptosis using flow cytometry. Scale bars: 100 μm (D) or 200 μm (E). Each dot represents one biological replicate (n = 2).
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Funding Information Korea Institute of Oriental Medicine |
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