Overview of distinct 8-oxoguanine profiles of messenger RNA in normal and senescent cancer cells

Background: Cellular senescence plays a key role in the development of cancer, but the underlying mechanisms are unknown. Recently, several recent studies have shown that RNA methylation is closely related to cancer cell aging. 8-Oxoguanine (o⁸G) is an important and widely distributed methylation modification whose role in cancer cell senescence is far from elucidated.

Methods: In this study, senescent cancer cell models (CaCO₂ cells) were constructed by knocking down the ADAR1 gene. RNA immunoprecipitation sequencing was used to identify the o⁸G peaks on messenger RNA (mRNA) of normal CaCO₂ cells and senescent CaCO₂ cells, and the distribution characteristics of mRNA o⁸G modification were identified. Further bioinformatics analysis of the sequencing data was performed to preliminarily elucidate the potential function of the o⁸G-modified mRNA.

Results: There were significant differences in mRNA o⁸G modification distribution between normal and senescent CaCO₂ cells. It is suggested that o⁸G modification may play a key role in inducing cancer cells or promoting cancer cell senescence. Gene ontology (GO) enrichment analysis showed that the mRNAs modified by o⁸G were enriched in Cellular component organization or biogenesis, Focal adhesion, and RNA binding. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the genes modified by o⁸G are concentrated in Focal adhesion signaling pathway, Small cell lung cancer signaling pathway and Proteoglycans in cancer signaling pathway.

Conclusion: This study preliminarily revealed the different distribution patterns of o⁸G modification between normal CaCO₂ cells and senescent CaCO₂ cells. Our study established the link between o⁸G modification and cancer cell senescence, which provides a new insight into the mechanism of cancer cell senescence and a potential therapeutic target for subsequent cancer treatment.

Introduction

Cellular senescence is a state of growth arrest induced by severe injury and stress, accompanied by a hypersecretory phenotype, morphological changes, and telomere dysfunction (Wang et al., 2022). Several inducing conditions, such as activated oncogenes, cytokines, reactive oxygen species, DNA damage, and nucleotide depletion, can trigger cellular senescence (Calcinotto et al., 2019; Chandrasekaran et al., 2017; Herranz and Gil, 2018; van Deursen, 2014). In cancer cells, senescence exhibits two distinct functions of anti-tumor and pro-tumor. For example, senescence can induce growth arrest in cancer cells, but it can also promote cancer progression through senescence-mediated tumorigenesis immune evasion (Schmitt et al., 2022).

Disorders of epigenetic regulation are an important feature of cellular senescence (López-Otín et al., 2013), and most of the epigenetic modifications are reversible relative to the genetic regulation represented by DNA sequences, suggesting that epigenetic regulation can be intervened to delay aging and treat aging-related diseases. Therefore, through the study of epigenetic changes in the aging process, we can better understand how to delay aging through external means. Epigenetic alterations play an important regulatory role in cellular senescence (Sen et al., 2016). However, most studies have focused on, for example, histone modifications (Baell et al., 2018) and DNA methylation (Xie et al., 2018). However, as an important epigenetic regulator, the role of RNA modification in the cellular senescence of cancer cells is still poorly understood, and only a few studies have explored the role of RNA modification in cancer cell senescence. METTL3 plays a key role in replicating senescence of colorectal cancer (CRC) cells, and inhibition of METTL3 or targeted inhibition of CDKN2B methylation can effectively inhibit CRC senescence (Chen et al., 2024). In HeLa cells, METTL3/14 and ADAR1 synergistically increase the translation of p21 in response to oxidative stress, leading to cellular senescence (Li et al., 2017). In addition, there is a study that explores the role of m1 A in cellular senescence. Knockdown of Alkbh3 in NSCLC cells leads to senescence induction and cell cycle arrest, followed by increased expression of cell cycle arrest proteins p27 and p21 (Tasaki et al., 2011).

8-oxoguanine (o⁸G) RNA modification is a new RNA modification that has attracted extensive attention in the field of molecular biology and epitranscriptomics in recent years. This modification involves the guanine nucleotide in the RNA molecule being attacked by reactive oxygen species (ROS) under specific conditions, which in turn converts to o⁸G. While 8-oxoguanine (8-oxo-dG) in DNA has been extensively studied, o⁸G modifications in RNA are more common, as RNA is more susceptible to oxidative damage. This difference may be attributed to the single-stranded nature of RNA and its more dynamic distribution in cells (Hahm et al., 2022).

Recent studies have shown that o⁸G modification is not just a consequence of oxidative damage, it may also play a role in regulating gene expression. For example, it has been found that position-specific o⁸G modifications can occur in the seed region of miRNAs and modulate mRNA stability and translation through specific base pairing (Seok et al., 2020). Determining the distribution of o⁸G within the transcriptome can deepen our understanding of o⁸G.

Methylated RNA immunoprecipitation sequencing (MeRIP-seq) is a commonly used technique for detecting o⁸G modifications. This method breaks down purified total RNA or mRNA into 100–150 nt RNA fragments; Subsequently, RNA fragments were co-incubated with o⁸G-modified antibodies, and the o⁸G-modified RNA fragments were enriched with antibodies for library construction and sequencing. Finally, the o⁸G-modified transcriptome region was obtained by comparison with the control library co-incubated with the o⁸G-modified antibody.

ADAR1 is an important regulator of aging, with knockdown of ADAR1 at the cellular level leading to cellular senescence, and overexpression of ADAR1 prevents senescence from occurring (Hao et al., 2022). In this study, we constructed an ADAR1-deficient colorectal cancer cell line to induce senescence in colorectal cancer cells. MeRIP-seq was performed on normal CaCO₂ cells and senescent CaCO₂ cells induced by ADR1 knockdown, and o⁸G-specific analysis and in-depth bioinformatics analysis were performed on o⁸G mRNA.

The results showed that there were significant differences in the number and distribution of o⁸G between the two groups. The number of o⁸G methylation peaks in normal CaCO₂ cells was much higher than that in ADAR1 knockdown cells, and the distribution of o⁸G methylation peaks was significantly different, involving all chromosomes. Further bioinformatics analysis showed that the two groups of cells with different degrees of o⁸G methylation could cause significantly different changes in cell function. Our study preliminarily suggests an association between CRC and o⁸G modification in mRNA and predicts potential functional changes due to differences in o⁸G modification in mRNA. These results provide a solid foundation for further understanding the mechanism of cancer cell senescence from the perspective of o⁸G modification.

Materials and methods

Establishment of senescent colorectal cancer cell line

ADAR1 is an important regulator of aging, knockdown of ADAR1 can lead to cellular senescence, and overexpression of ADAR1 can prevent senescence from occurring. In the present study, we constructed ADAR1 deletion-induced senescence in colorectal cancer cells. The ADAR1 knockdown lentivirus construction system was obtained from Obio Company (Shanghai, China). CaCO₂ cells were stably transfected with ADAR1 knockdown lentivirus (shADAR1) and a corresponding control (shNC) with an anti-puromycin plasmid. The stably transfected CaCO₂ cell line was treated with puromycin (4 μg/mL) for 14 days for selection. The sequence of shRNA is GCC​CAC​TGT​TAT​CTT​CAC​TTT.

RNA extraction and fragmentation

In this study, we extracted total RNA using Trizol reagent (Invitrogen, CA, United States) and reduced rRNA content using Ribo-Zero rRNA removal kit (Illumina, Inc., CA, United States). The quality of RNA was assessed using the OD260/OD280 ratio. When OD260/OD280 values are in the range of 1.8–2.1, RNA purity is considered to meet the standard, and RNA extracted from all samples in this study meets this standard. In this study, we extracted total RNA using Trizol reagent (Invitrogen, CA, United States) and reduced rRNA content using Ribo-Zero rRNA removal kit (Illumina, Inc., CA, United States). The quality of RNA was assessed using the OD260/OD280 ratio. When OD260/OD280 values are in the range of 1.8–2.1, RNA purity is considered to meet the standard, and RNA extracted from all samples in this study meets this standard.

Library construction and sequencing

Methylated RNA immunoprecipitation sequencing (MeRIP-seq) refers to the procedure previously reported in the literature (Lin et al., 2023). Three biological repeats of immunoprecipitation of o⁸G-containing RNA were performed under each condition and ribosomal RNA (rRNA) was removed from the sample using the GenSeq^® rRNA Removal Kit (GenSeq, Inc.) according to the manufacturer’s instructions. After the samples were qualified, o⁸G RIP kit from GenSeq was used for o⁸G-IP reaction. The process is described as follows: RNA is randomly fragmented into fragments of about 200 nt. Protein A/G magnetic beads and Anti-o⁸G antibody (QED Bioscience, Cat# 12501) were incubated at room temperature for 1 h to bind the antibodies to the magnetic beads. The RNA fragments were then incubated with an antibody bound with magnetic beads at 4°C for 4 h to bind the RNA to the antibody. After incubation, the RNA/antibody complex is cleaned several times. The captured RNA is then eluted from the complex and purified. RNA libraries of purified products were constructed using the GenSeq^® Low Input Whole RNA Library Prep Kit (GenSeq, Inc.) kit, and quality control was performed using the Agilent 2100 bioanalyzer. Finally, the library was sequenced by illumina 6000 with 2 × 150 bases in high throughput.

Identifications and analysis of 8-oxoguanine peaks

Raw reads (Raw Data) are generated after sequencing, image analysis, base recognition, and quality control on an Illumina novaseq 6000 sequenator. Start with the Q30 for quality control. Q30 > 80% indicates good sequencing quality. Then, use cutadapt software (v1.9.3) (Kechin et al., 2017) to remove the low-quality reads and obtain high-quality clean reads. The clean reads of all samples were matched to the reference genome using Hisat2 (Kim et al., 2015) software (v2.0.4). The MACS (Zhang et al., 2008) software was then used to identify the o⁸G-modified gene in each sample. Gene identification of differentially o⁸G modifications was performed using diffReps (Shen et al., 2013) software. Use your own program to screen for peaks located on the exon of the mRNA and annotate accordingly.

Statistical analysis

The o⁸G peaks on the mRNA of the samples in each group were combined to obtain the o⁸G peaks of each group. Use the Bed Tool software to find the common peaks between the two groups. The 50 bp sequences on either side of the apex of the o⁸G peak were scanned using DRAME software (Bailey, 2011) to find meaningful motifs. The E value of the motif is calculated as the enriched P value multiplied by the number of candidate motif for the test, and the enriched P value is calculated using Fisher’s exact test to enrich the motif in the positive sequence. The lower the E value, the higher the confidence level. Methylation fold enrichment (FE) of each mRNA in the sample was collected and log2 converted. The log FE value is used for clustering in the heatmap. The mRNA region in which the o⁸G peak is located in each sample was calculated according to the published method and the results were plotted as a pie chart.

Bioinformatics analysis

Functional analysis (http://www.geneontology.org) of differentially o⁸G-modified coding genes was performed using Gene Ontology (GO) to annotate and speculate on the function of these differentially methylated genes. Pathway analysis of differentially o⁸G-modified coding genes was performed using the Kyoto Encyclopedia of Genes and Genomes (KEGG) (https://david.ncifcrf.gov/) to annotate and speculate on the pathways in which they may be involved. In addition, we used the fold change in enrichment intensity of the two groups of samples in the MeRIP-seq experiment to sequence the signals of all coding genes. We chose FDR < 0.25 as the screening criteria. The technology roadmap is shown in Figure 1.

Figure 1

Figure 1. Flowchart of the study.

Result

Construction of senescent cancer cells by knockdown ADAR1

SAβ-Gal is a commonly used marker of cellular senescence. SA-β-Gal (Senescence-Associated β-Galactosidase) is a β-galactosidase that exhibits increased activity during cellular senescence. By measuring the activity level of SA-β-Gal in cells, the degree of senescence of cells can be assessed. The results of SA-β-Gal showed that CaCO₂ cells senescent compared with normal cells after knockdown of ADAR1, as shown in Supplementary Figure S1.

General features of o⁸G methylation in CaCO₂ cells and sh-ADAR1 CaCO₂ cells

In this study, we found 1,835 clean o⁸G methylation peaks in CaCO₂ cells and 592 clean o⁸G methylation peaks in sh-ADAR1 CaCO₂ cells. We mapped up to 1,279 CaCO₂ annotation genes and 402 sh-ADAR1 CaCO₂ cellular annotation genes. Among them, 2,131 o⁸G modification peaks were found in CaCO₂ cells and sh-ADAR1 CaCO₂ cells, corresponding to 1,478 o⁸G modification genes (Figures 2A,B). We further investigated the distribution of o⁸G peaks on chromosomes using Circos software and found that the number and distribution of o⁸G peaks on each chromosome of CaCO₂ cells and senescent CaCO₂ cells differed, with the most significant differences between chromosomes 1 and 11 (Figure 2C).

Figure 2

Figure 2. Characteristics of o⁸G peaks in CaCO₂ cell and sh-ADAR1 CaCO₂ cell. (A) Venn diagram of o⁸G peaks in CaCO₂ cell and sh-ADAR1 CaCO₂ cell. (B) Venn diagram of o⁸G genes in CaCO₂ cell and sh-ADAR1 CaCO₂ cell. (C) Visualization of o⁸G at the chromosome level in CaCO₂ cell and sh-ADAR1 CaCO₂ cell. (D) Accumulation of the region of average o⁸G peaks along all transcripts in CaCO₂ cell and sh-ADAR1 CaCO₂ cell. (E,F) Pie chart of the source of methylated mRNA in CaCO₂ cell and sh-ADAR1 CaCO₂ cell.

Further analysis of the source of the o⁸G methylation peak revealed that the distribution of the o⁸G modification covered all regions of the mRNA but was enriched in the coding sequence region (CDS) (Figures 2D–F). However, the o⁸G peak in CaCO₂ cells and the o⁸G peak in senescent CaCO₂ cells exhibit different patterns. The number of o⁸G peaks in the start codon (start C) of normal CaCO₂ cells (CaCO₂: 19.46% vs. sh-ADAR1 CaCO₂: 14.86%) and the o⁸G peaks in the 5′ untranslated region (5′ UTR) (CaCO₂: 7.79% vs. sh-ADAR1 CaCO₂: 6.59%) was higher than that of senescent cancer cells.

The number of o⁸G peaks in CDS region of normal CaCO₂ cells (CaCO₂: 50.14%, vs. sh-ADAR1 CaCO₂: 53.89%) and the number of o⁸G peaks in stop codon (stop C) (CaCO₂: 14.39% vs. sh-ADAR1 CaCO₂) were decreased compared with senescent cancer cells. In the meantime, the number of o8G peaks in 3′ untranslated region (3′ UTR) of normal CaCO₂ cells (CaCO₂: 8.23% vs. sh-ADAR1 CaCO₂: 9.46%) were also decreased compared with senescent cancer cells.

o⁸G motif analysis and differential o⁸G methylation analysis

The results showed that GCWGCWGC was the most common and most confident methylation site motif in CaCO₂ cells (p = 1.6e-017), while AGGAGWW is the most common and most confident methylation site motif in sh-ADAR1 CaCO₂ cells (p = 1.8e-016) (Figure 3A). We performed methylation heat mapping and cluster analysis on the total data. The results of cluster analysis showed that there were significant differences in expression among the groups, and the expression was consistent within the groups. These differences are due to a decrease in the level of o⁸G modification due to aging (Figure 3B). In addition, we identified 142 upregulated o⁸G methylation peaks and 1,574 downregulated o⁸G methylation peaks of senescent CaCO₂ compared to normal CaCO₂ cells using DiffReps software (Figure 3C).

Figure 3

Figure 3. Characteristics of altered o⁸G peaks in CaCO₂ cell and sh-ADAR1 CaCO₂ cell. (A) The sequence motif of o⁸G sites in CaCO₂ cell and sh-ADAR1 CaCO₂ cell. (B) Cluster analysis of methylation in CaCO₂ cell and sh-ADAR1 CaCO₂ cell. (C) Volcano plots showing the significantly differential o⁸G peaks. (D) The distributions of altered o⁸G peaks in human chromosomes. (E) The number of o⁸G peaks in CaCO₂ cell and sh-ADAR1 CaCO₂ cell on each mRNA. Most mRNAs have only one methylation peak.

We have listed the top 10 mRNAs with the largest fold change in Tables 1, 2. Dysregulated o⁸G methylation peaks are distributed on all chromosomes, especially on chromosome 1 (Figure 3D). In addition, to determine the number of o⁸G peaks on each mRNA, we calculated the methylation peak and the mRNA corresponding to the methylation peak. The results showed that most of the mRNAs at the methylation site in sh-ADAR1 CaCO₂ cells had only one methylation peak (29.8%), while CaCO₂ cells had a higher proportion of methylation peaks (44.6%). At the same time, the number of mRNAs with three or more methylation peaks on 1 mRNA in sh-ADAR1 CaCO₂ cells was higher than in CaCO₂ cells (p < 0.05) (Figure 3E).

Table 1

Table 1. Top 10 upregulated o8G methylation peaks.

Table 2

Table 2. Top 10 downregulated o⁸G methylation peaks.

Gene ontology (GO) enrichment analysis

To understand the biological function of differentially o⁸G-modified mRNA in sh-ADAR1 CaCO₂ cells and CaCO₂ cells, we performed GO analysis. For genes that are upregulated in o⁸G methylation in sh-ADAR1 CaCO₂ cells, GO analysis showed that these genes are enriched in Cellular component organization or biogenesis (GO terminology: BP), Focal adhesion (GO term: CC), and RNA binding (GO term: MF) (Figures 4A–C). As for genes downregulated by o⁸G modification in sh-ADAR1 CaCO₂ cells, GO analysis showed that these genes were mainly enriched in cellular metabolic process (GO term: BP), intracellular anatomical structure (GO term: CC), and protein binding (GO term: MF) (Figures 4D–F).

Figure 4

Figure 4. Gene ontology analyses of CaCO₂ and shADAR1-CaCO₂ cell. (A) Biological processes, (B) cellular components, and (C) molecular functions of genes annotated by upregulated o⁸G peaks in sh-ADAR1 CaCO₂ cell group. (D) Biological processes, (E) cellular components, and (F) molecular functions of genes annotated by downregulated o⁸G peaks in sh-ADAR1 CaCO₂ cell group. The top ten most significant terms are shown for each analysis.

Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis

To elucidate the biological function of differentially o⁸G-modified mRNAs in sh-ADAR1 CaCO₂ cells and CaCO₂ cells, we performed KEGG pathway analysis on differentially o⁸G-modified mRNAs. KEGG pathway analysis showed that the mRNA upregulated by o⁸G modification in sh-ADAR1 CaCO₂ cells was enriched in Focal adhesion signaling pathway, Regulation of actin cytoskeleton signaling pathway and Small cell lung cancer signaling pathway (Figures 5A,B). mRNA downregulated by o8G was enriched in the Salmonella infection signaling pathway, Proteoglycans in cancer signaling pathway and Adherens junction signaling pathway (Figures 5C,D).

Figure 5

Figure 5. Kyoto Encyclopedia of Genes and Genomes analysis of differentially methylated genes in CaCO₂ and shADAR1-CaCO₂ cell. (A,B) Pathway analysis of up-methylated genes in sh-ADAR1 CaCO₂ cell group. (C,D) Pathway analysis of down-methylated genes in sh-ADAR1 CaCO₂ cell group. The top ten most significant terms are shown for each analysis.

Discussion

As an especially important post-transcriptional modification, RNA modification has been shown to be closely related to cell senescence and the occurrence and progression of cancer (Zhou et al., 2024; Cavinato et al., 2021), but there are few studies on RNA modification and cancer cell senescence. The o⁸G modification is an RNA modification produced by the attack of guanine in mRNA by reactive oxygen species in mammalian cells, which can pair with adenine and induce guanine-thymine (G > T) mutations, which is a modification in pathophysiology that causes disease phenotype through reactive oxygen species oxidation. o⁸G modifications in RNA can cause problems with abnormal quality and translation fidelity (Hahm et al., 2022). Due to the ability of o⁸G·A to base pair, o⁸G alters the structural and functional RNA-RNA interactions, enabling post-transcriptional regulation to be redirected (Seok et al., 2020). Recent studies have shown that tRF-1-AspGTC has o⁸G (5o⁸G) modification on the 5th G in its seed region, so that 5o⁸G tRF-1-AspGTC can retarget new downstream genes WNT5A and CASP (Zhang et al., 2024). At present, the mechanism of oxidative modification of o⁸G RNA, as a new class of RNA modification, is far from elucidated (Eom et al., 2023). In this study, we explored the potential role of o8G modification in senescent cancer cells.

First, our study showed that knockdown of ADAR1 can effectively induce senescence in CRC cells, and knockdown of ADAR1 increases SA-β-gal activity. Next, we used MeRIP-seq to sequence the relevant samples and characterize the o⁸G modification profile of mRNA in CaCO₂ cells and senescent CaCO₂ cells using bioinformatics methods. A total of 2,131 o⁸G modification peaks were found in CaCO₂ cells and senescent CaCO₂ cells, corresponding to 1,478 o⁸G modification genes. A total of 1,835 o⁸G methylation peaks were found in CaCO₂ cells and 592 o⁸G methylation peaks were found in senescent CaCO₂ cells. The number of mRNA o⁸G methylation peaks in CaCO₂ cells were significantly higher than that in senescent CaCO₂ cells. The results of cluster analysis showed that the degree of methylation could clearly distinguish CaCO₂ cells from senescent CaCO₂ cells, which further confirmed the potential relationship between o⁸G and senescent cancer cells. The o⁸G peaks were distributed in all regions of mRNA, and the CDS region had the highest proportion. The o⁸G peaks is also found on all chromosomes, mainly on chromosome 1, chromosome 17 and chromosome 19.

We annotated 1,279 genes with altered o⁸G methylation in CaCO₂ cells and 402 genes with altered o⁸G methylation in senescent CaCO₂ cells. The peak value of mRNA o⁸G modification in CaCO₂ cells was significantly higher than that in senescent CaCO₂ cells. In senescent CaCO₂ cells and normal CaCO₂ cells, the peaks of o⁸G modification on some mRNAs, such as LIF, CAPN2, and HOXB9, can be as high as million-fold.

The number of start codons and o⁸G modifications of 5′ UTR in CaCO₂ cells was higher than that in senescent cancer cells. In the CDS region, the number of stop codons and o⁸G modifications of 3′ UTR was relatively lower than that of senescent cancer cells. The first codon for mRNA translation is called the start codon, and AUG is the most common start codon, which encodes the amino acid methionine (Met) in eukaryotes and formyl methionine (fMet) in prokaryotes. During protein synthesis, the tRNA recognizes the start codon AUG with the help of some initiation factors and initiates the translation of the mRNA. Considering that the stop codon also has o⁸G modification, it is reasonable to suspect that o⁸G modification plays an important regulatory role in mRNA translation. Further research is needed on how specific o⁸G modification sites regulate the translation of specific mRNAs. 3′ UTR plays a key role in post-transcriptional regulation, influencing gene expression and mRNA stability, localization, and the occurrence of post-transcriptional modifications. Depending on the properties of the 3′ UTR, o⁸G modification of the 3′ UTR may affect the binding of non-coding RNAs or RNA-binding proteins (RBPs) to mRNA, thereby regulating mRNA translation and stability.

We used the traditional method of predicting other RNA modifications, such as the m⁵C motif, to predict the possible motif of o⁸G modification, due to the lack of relevant studies on o⁸G, the o⁸G modification motif on the mRNA is still inconclusive, which depends on more sequencing to reveal the characteristics of the motif.

We found that differentially o⁸G-modified transcripts were enriched in a variety of important cell biology processes, such as Cellular component organization or biogenesis, Focal adhesion, and RNA binding, suggest that o⁸G modification may be involved in these biological processes regulating cancer cell base aging. Through KEGG analysis, we found that differentially o⁸G methylated mRNA was enriched in some key cancer-related pathways, such as Small cell lung cancer signaling pathway, Proteoglycans in cancer signaling pathway. It also proves from another aspect that o⁸G modification is closely related to the development of cancer.

In conclusion, our study shows that when cancer cells undergo senescence, their o⁸G modification spectrum changes significantly, and the changes are reflected in two aspects, one is the change in the number of modifications, and the other is the change in the distribution of modifications. We also performed further bioinformatics analysis of mRNA with changes in o⁸G modification and GO and KEGG analyses preliminarily revealed the potential direction of o⁸G modification on the regulation of senescent cancer cells. In follow-up studies, further in-depth analysis of the specific regulatory mechanism of o⁸G modification on cancer cell aging is expected to provide innovative ideas for the treatment of cancer.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ncbi.nlm.nih.gov/geo/, GSE284992.

Ethics statement

Ethical approval was not required for the studies on humans in accordance with the local legislation and institutional requirements because only commercially available established cell lines were used.

Author contributions

JH: Formal Analysis, Funding acquisition, Writing–original draft. YL: Conceptualization, Data curation, Writing–original draft. YZ: Formal Analysis, Writing–review and editing. LW: Conceptualization, Investigation, Writing–review and editing.

Funding

The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This research was supported by TCM science and technology project of Shandong Province (2020Q076).

Acknowledgments

We thank the Cloud-Seq Biotech Ltd. Co. (Shanghai, China) for the MeRIP-Seq service.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcell.2025.1443888/full#supplementary-material

SUPPLEMENTARY FIGURE S1 | β-Gal showed that CaCO₂ cells senescent compared with normal cells after knockdown of ADAR1.

Abbreviations

o⁸G, 8-oxoguanine; m⁵C, 5-methylcytosine; GO, Gene ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; BP, biological processes; MF, molecular functions; CC, cellular components; IP, immunoprecipitation.

References

Baell, J. B., Leaver, D. J., Hermans, S. J., Kelly, G. L., Brennan, M. S., Downer, N. L., et al. (2018). Inhibitors of histone acetyltransferases KAT6A/B induce senescence and arrest tumour growth. Nature 560, 253–257. doi:10.1038/s41586-018-0387-5

PubMed Abstract | CrossRef Full Text | Google Scholar

Bailey, T. L. (2011). DREME: motif discovery in transcription factor ChIP-seq data. Bioinformatics 27, 1653–1659. doi:10.1093/bioinformatics/btr261

PubMed Abstract | CrossRef Full Text | Google Scholar

Calcinotto, A., Kohli, J., Zagato, E., Pellegrini, L., Demaria, M., and Alimonti, A. (2019). Cellular senescence: aging, cancer, and injury. Physiol. Rev. 99, 1047–1078. doi:10.1152/physrev.00020.2018

PubMed Abstract | CrossRef Full Text | Google Scholar

Cavinato, M., Madreiter-Sokolowski, C. T., Büttner, S., Schosserer, M., Zwerschke, W., Wedel, S., et al. (2021). Targeting cellular senescence based on interorganelle communication, multilevel proteostasis, and metabolic control. FEBS J. 288, 3834–3854. doi:10.1111/febs.15631

PubMed Abstract | CrossRef Full Text | Google Scholar

Chandrasekaran, A., Idelchik, M., and Melendez, J. A. (2017). Redox control of senescence and age-related disease. Redox Biol. 11, 91–102. doi:10.1016/j.redox.2016.11.005

PubMed Abstract | CrossRef Full Text | Google Scholar

Chen, Z., Zhou, J., Wu, Y., Chen, F., Li, J., Tao, L., et al. (2024). METTL3 promotes cellular senescence of colorectal cancer via modulation of CDKN2B transcription and mRNA stability. Oncogene 43, 976–991. doi:10.1038/s41388-024-02956-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Eom, S., Peak, J., Park, J., Ahn, S. H., Cho, Y. K., Jeong, Y., et al. (2023). Widespread 8-oxoguanine modifications of miRNA seeds differentially regulate redox-dependent cancer development. Nat. Cell Biol. 25, 1369–1383. doi:10.1038/s41556-023-01209-6

PubMed Abstract | CrossRef Full Text | Google Scholar

Hahm, J. Y., Park, J., Jang, E. S., and Chi, S. W. (2022). 8-oxoguanine: from oxidative damage to epigenetic and epitranscriptional modification. Exp. Mol. Med. 54, 1626–1642. doi:10.1038/s12276-022-00822-z

PubMed Abstract | CrossRef Full Text | Google Scholar

Hao, X., Shiromoto, Y., Sakurai, M., Towers, M., Zhang, Q., Wu, S., et al. (2022). ADAR1 downregulation by autophagy drives senescence independently of RNA editing by enhancing p16(INK4a) levels. Nat. Cell Biol. 24, 1202–1210. doi:10.1038/s41556-022-00959-z

PubMed Abstract | CrossRef Full Text | Google Scholar

Herranz, N., and Gil, J. (2018). Mechanisms and functions of cellular senescence. J. Clin. Invest. 128, 1238–1246. doi:10.1172/jci95148

PubMed Abstract | CrossRef Full Text | Google Scholar

Kechin, A., Boyarskikh, U., Kel, A., and Filipenko, M. (2017). cutPrimers: a new tool for accurate cutting of primers from reads of targeted next generation sequencing. J. Comput. Biol. 24, 1138–1143. doi:10.1089/cmb.2017.0096

PubMed Abstract | CrossRef Full Text | Google Scholar

Kim, D., Langmead, B., and Salzberg, S. L. (2015). HISAT: a fast spliced aligner with low memory requirements. Nat. Methods 12, 357–360. doi:10.1038/nmeth.3317

PubMed Abstract | CrossRef Full Text | Google Scholar

Li, Q., Li, X., Tang, H., Jiang, B., Dou, Y., Gorospe, M., et al. (2017). NSUN2-Mediated m5C methylation and METTL3/METTL14-mediated m6A methylation cooperatively enhance p21 translation. J. Cell. Biochem. 118, 2587–2598. doi:10.1002/jcb.25957

PubMed Abstract | CrossRef Full Text | Google Scholar

Lin, Y., Zhao, Z., Nie, W., Huang, M., Cai, J., Wang, Y., et al. (2023). Overview of distinct 5-methylcytosine profiles of messenger RNA in normal and knock-down NSUN2 colorectal cancer cells. Front. Genet. 14, 1121063. doi:10.3389/fgene.2023.1121063

PubMed Abstract | CrossRef Full Text | Google Scholar

López-Otín, C., Blasco, M. A., Partridge, L., Serrano, M., and Kroemer, G. (2013). The hallmarks of aging. Cell 153, 1194–1217. doi:10.1016/j.cell.2013.05.039

PubMed Abstract | CrossRef Full Text | Google Scholar

Schmitt, C. A., Wang, B., and Demaria, M. (2022). Senescence and cancer – role and therapeutic opportunities. Nat. Rev. Clin. Oncol. 19, 619–636. doi:10.1038/s41571-022-00668-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Sen, P., Shah, P. P., Nativio, R., and Berger, S. L. (2016). Epigenetic mechanisms of longevity and aging. Cell 166, 822–839. doi:10.1016/j.cell.2016.07.050

PubMed Abstract | CrossRef Full Text | Google Scholar

Seok, H., Lee, H., Lee, S., Ahn, S. H., Lee, H. S., Kim, G. W. D., et al. (2020). Position-specific oxidation of miR-1 encodes cardiac hypertrophy. Nature 584, 279–285. doi:10.1038/s41586-020-2586-0

PubMed Abstract | CrossRef Full Text | Google Scholar

Shen, L., Shao, N. Y., Liu, X., Maze, I., Feng, J., and Nestler, E. J. (2013). diffReps: detecting differential chromatin modification sites from ChIP-seq data with biological replicates. PLoS One 8, e65598. doi:10.1371/journal.pone.0065598

PubMed Abstract | CrossRef Full Text | Google Scholar

Tasaki, M., Shimada, K., Kimura, H., Tsujikawa, K., and Konishi, N. (2011). ALKBH3, a human AlkB homologue, contributes to cell survival in human non-small-cell lung cancer. Br. J. Cancer 104, 700–706. doi:10.1038/sj.bjc.6606012

PubMed Abstract | CrossRef Full Text | Google Scholar

van Deursen, J. M. (2014). The role of senescent cells in ageing. Nature 509, 439–446. doi:10.1038/nature13193

PubMed Abstract | CrossRef Full Text | Google Scholar

Wang, L., Lankhorst, L., and Bernards, R. (2022). Exploiting senescence for the treatment of cancer. Nat. Rev. Cancer 22, 340–355. doi:10.1038/s41568-022-00450-9

PubMed Abstract | CrossRef Full Text | Google Scholar

Xie, W., Kagiampakis, I., Pan, L., Zhang, Y. W., Murphy, L., Tao, Y., et al. (2018). DNA methylation patterns separate senescence from transformation potential and indicate cancer risk. Cancer Cell 33, 309–321. doi:10.1016/j.ccell.2018.01.008

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, J., Li, Y., Chen, Y., Jia, Z., He, M., et al. (2024). o(8)G site-specifically modified tRF-1-AspGTC: a novel therapeutic target and biomarker for pulmonary hypertension. Circulation Res. 135, 76–92. doi:10.1161/circresaha.124.324421

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., et al. (2008). Model-based analysis of ChIP-seq (MACS). Genome Biol. 9, R137. doi:10.1186/gb-2008-9-9-r137

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhou, L., Zhong, Y., Wang, F., Guo, Y., Mao, R., Xie, H., et al. (2024). WTAP mediated N6-methyladenosine RNA modification of ELF3 drives cellular senescence by upregulating IRF8. Int. J. Biol. Sci. 20, 1763–1777. doi:10.7150/ijbs.90459

PubMed Abstract | CrossRef Full Text | Google Scholar