RNA ac4C modification in cancer: Unraveling multifaceted roles and promising therapeutic horizons.

RNA modifications play a crucial role in cancer development, profoundly influencing various stages of the RNA lifecycle. These stages encompass nuclear processing, nuclear export, splicing, and translation in the cytoplasm. Among RNA modifications, RNA ac4C modification, also known as N4-acetylcytidine, stands out for its unique role in acetylation processes. Specific proteins regulate RNA ac4C modification, maintaining the dynamic and reversible nature of these changes. This review explores the molecular mechanisms and biological functions of RNA ac4C modification. It examines the intricate ways in which RNA ac4C modification influences the pathogenesis and progression of cancer. Additionally, the review provides an integrated overview of the current methodologies for detecting RNA ac4C modification. Exploring the potential applications of manipulating this modification suggests avenues for novel therapeutic strategies, potentially leading to more effective cancer treatments in the future.

Targeting N4-acetylcytidine suppresses hepatocellular carcinoma progression by repressing eEF2-mediated HMGB2 mRNA translation.

BACKGROUND: N4-acetylcytidine (ac4C) represents a novel messenger RNA (mRNA) modification, and its associated acetyltransferase N-acetyltransferase 10 (NAT10) plays a crucial role in the initiation and progression of tumors by regulating mRNA functionality. However, its role in hepatocellular carcinoma (HCC) development and prognosis is largely unknown. This study aimed to elucidate the role of NAT10-mediated ac4C in HCC progression and provide a promising therapeutic approach. METHODS: The ac4C levels were evaluated by dot blot and ultra-performance liquid chromatography-tandem mass spectrometry with harvested HCC tissues. The expression of NAT10 was investigated using quantitative real-time polymerase chain reaction, western blotting, and immunohistochemical staining across 91 cohorts of HCC patients. To explore the underlying mechanisms of NAT10-ac4C in HCC, we employed a comprehensive approach integrating acetylated RNA immunoprecipitation and sequencing, RNA sequencing and ribosome profiling analyses, along with RNA immunoprecipitation, RNA pull-down, mass spectrometry, and site-specific mutation analyses. The drug affinity responsive targets stability, cellular thermal shift assay, and surface plasmon resonance assays were performed to assess the specific binding of NAT10 and Panobinostat. Furthermore, the efficacy of targeting NAT10-ac4C for HCC treatment was elucidated through in vitro experiments using HCC cells and in vivo HCC mouse models. RESULTS: Our investigation revealed a significant increase in both the ac4C RNA level and NAT10 expression in HCC. Notably, elevated NAT10 expression was associated with poor outcomes in HCC patients. Functionally, silencing NAT10 suppressed HCC proliferation and metastasis in vitro and in vivo. Mechanistically, NAT10 stimulates the ac4C modification within the coding sequence (CDS) of high mobility group protein B2 (HMGB2), which subsequently enhances HMGB2 translation by facilitating eukaryotic elongation factor 2 (eEF2) binding to the ac4C sites on HMGB2 mRNA's CDS. Additionally, high-throughput compound library screening revealed Panobinostat as a potent inhibitor of NAT10-mediated ac4C modification. This inhibition significantly attenuated HCC growth and metastasis in both in vitro experiments using HCC cells and in vivo HCC mouse models. CONCLUSIONS: Our study identified a novel oncogenic epi-transcriptome axis involving NAT10-ac4C/eEF2-HMGB2, which plays a pivotal role in regulating HCC growth and metastasis. The drug Panobinostat validates the therapeutic potential of targeting this axis for HCC treatment.

A Review of Research on the Mechanism of Tumor Regulation by N-Acetyltransferase 10.

N-acetyltransferase 10 (NAT10) is an important acetyltransferase that regulates telomerase activity and participates in DNA damage reactions, ribosomal RNA (rRNA) transcriptional activation, cell division, microtubule acetylation, and other important cellular processes. Abnormalities in the expression or distribution of NAT10 result in diseases such as Hutchinson-Gilford progeria syndrome (HGPS) and various tumors, with serious consequences. Remodelin, an inhibitor of NAT10, delays HGPS progression; many studies have been conducted on its role in tumor therapy. A major breakthrough in the study of NAT10 was the discovery of mRNA N4-acetylcytidine (ac4C) modification, which can increase mRNA stability and translation efficiency significantly. In addition, NAT10 modifies the mRNA of ac4C, which is associated with tumor development. Here, we present a review of pertinent studies focusing on NAT10, particularly its role in cancer, to provide researchers with a concise and informative summary of the current state of knowledge about this topic. The conclusions drawn from this review could provide a new direction for tumor treatment.

STM-ac4C: a hybrid model for identification of N4-acetylcytidine (ac4C) in human mRNA based on selective kernel convolution, temporal convolutional network, and multi-head self-attention.

N4-acetylcysteine (ac4C) is a chemical modification in mRNAs that alters the structure and function of mRNA by adding an acetyl group to the N4 position of cytosine. Researchers have shown that ac4C is closely associated with the occurrence and development of various cancers. Therefore, accurate prediction of ac4C modification sites on human mRNA is crucial for revealing its role in diseases and developing new diagnostic and therapeutic strategies. However, existing deep learning models still have limitations in prediction accuracy and generalization ability, which restrict their effectiveness in handling complex biological sequence data. This paper introduces a deep learning-based model, STM-ac4C, for predicting ac4C modification sites on human mRNA. The model combines the advantages of selective kernel convolution, temporal convolutional networks, and multi-head self-attention mechanisms to effectively extract and integrate multi-level features of RNA sequences, thereby achieving high-precision prediction of ac4C sites. On the independent test dataset, STM-ac4C showed improvements of 1.81%, 3.5%, and 0.37% in accuracy, Matthews correlation coefficient, and area under the curve, respectively, compared to the existing state-of-the-art technologies. Moreover, its performance on additional balanced and imbalanced datasets also confirmed the model's robustness and generalization ability. Various experimental results indicate that STM-ac4C outperforms existing methods in predictive performance. In summary, STM-ac4C excels in predicting ac4C modification sites on human mRNA, providing a powerful new tool for a deeper understanding of the biological significance of mRNA modifications and cancer treatment. Additionally, the model reveals key sequence features that influence the prediction of ac4C sites through sequence region impact analysis, offering new perspectives for future research. The source code and experimental data are available at https://github.com/ymy12341/STM-ac4C.

Exploring the impact of N4-acetylcytidine modification in RNA on non-neoplastic disease: unveiling its role in pathogenesis and therapeutic opportunities.

RNA modifications include not only methylation modifications, such as m6A, but also acetylation modifications, which constitute a complex interaction involving "writers," "readers," and "erasers" that play crucial roles in growth, genetics, and disease. N4-acetylcytidine (ac4C) is an ancient and highly conserved RNA modification that plays a profound role in the pathogenesis of a wide range of diseases. This review provides insights into the functional impact of ac4C modifications in disease and introduces new perspectives for disease treatment. These studies provide important insights into the biological functions of post-transcriptional RNA modifications and their potential roles in disease mechanisms, offering new perspectives and strategies for disease treatment.

ac4C-AFL: A high-precision identification of human mRNA N4-acetylcytidine sites based on adaptive feature representation learning.

RNA N4-acetylcytidine (ac4C) is a highly conserved RNA modification that plays a crucial role in controlling mRNA stability, processing, and translation. Consequently, accurate identification of ac4C sites across the genome is critical for understanding gene expression regulation mechanisms. In this study, we have developed ac4C-AFL, a bioinformatics tool that precisely identifies ac4C sites from primary RNA sequences. In ac4C-AFL, we identified the optimal sequence length for model building and implemented an adaptive feature representation strategy that is capable of extracting the most representative features from RNA. To identify the most relevant features, we proposed a novel ensemble feature importance scoring strategy to rank features effectively. We then used this information to conduct the sequential forward search, which individually determine the optimal feature set from the 16 sequence-derived feature descriptors. Utilizing these optimal feature descriptors, we constructed 176 baseline models using 11 popular classifiers. The most efficient baseline models were identified using the two-step feature selection approach, whose predicted scores were integrated and trained with the appropriate classifier to develop the final prediction model. Our rigorous cross-validations and independent tests demonstrate that ac4C-AFL surpasses contemporary tools in predicting ac4C sites. Moreover, we have developed a publicly accessible web server at https://balalab-skku.org/ac4C-AFL/.

Unveiling YWHAH: A potential therapeutic target for overcoming CD8+ T cell exhaustion in colorectal cancer.

Colorectal cancer (CRC) is a significant global health challenge, with increasing rates of incidence and mortality. Despite advancements in immunotherapy, resistance, particularly due to T cell exhaustion, remains a major hurdle. This study explores the role of YWHAH, mediated by N4-acetylcytidine (ac4C) modification, in CRC progression and its impact on CD8+ T cell exhaustion. Analysis of five paired CRC patient tissue samples using acetylated RNA immunoprecipitation and sequencing (acRIP-seq)identified ac4C-modified mRNAs. Functional assays, including cell culture, transfection, qRT-PCR, and immune assays, investigated the influence of YWHAH expression on CRC advancement. Bioinformatics analysis of TCGA data assessed the correlation between YWHAH and immune responses, as well as checkpoint inhibitors. Flow cytometry and Immunohistochemistry validated these findings, complemented by a co-culture experiment involving CD8+ T cells and CRC cell lines (LOVO and HCT116). acRIP-seq revealed YWHAH as a potential driver of CRC progression, exhibiting ac4C modification-mediated stability and upregulation. High YWHAH levels correlated with adverse outcomes and immune evasion in CRC patients, showing strong associations with immune checkpoint proteins and modest correlations with CD8+ T cell infiltration. Co-culture experiments demonstrated YWHAH-induced CD8+ T cell exhaustion, characterized by decreased proliferation and increased exhaustion markers. NAT10-mediated ac4C modification enhanced YWHAH stability in CRC. The involvement of YWHAH in CD8 + T cell exhaustion suggests its potential as a therapeutic target and prognostic marker in CRC immunotherapy, highlighting the intricate interplay between epitranscriptomic modifications, the tumor microenvironment, and immune responses in CRC progression.

TransAC4C-a novel interpretable architecture for multi-species identification of N4-acetylcytidine sites in RNA with single-base resolution.

N4-acetylcytidine (ac4C) is a modification found in ribonucleic acid (RNA) related to diseases. Expensive and labor-intensive methods hindered the exploration of ac4C mechanisms and the development of specific anti-ac4C drugs. Therefore, an advanced prediction model for ac4C in RNA is urgently needed. Despite the construction of various prediction models, several limitations exist: (1) insufficient resolution at base level for ac4C sites; (2) lack of information on species other than Homo sapiens; (3) lack of information on RNA other than mRNA; and (4) lack of interpretation for each prediction. In light of these limitations, we have reconstructed the previous benchmark dataset and introduced a new dataset including balanced RNA sequences from multiple species and RNA types, while also providing base-level resolution for ac4C sites. Additionally, we have proposed a novel transformer-based architecture and pipeline for predicting ac4C sites, allowing for highly accurate predictions, visually interpretable results and no restrictions on the length of input RNA sequences. Statistically, our work has improved the accuracy of predicting specific ac4C sites in multiple species from less than 40% to around 85%, achieving a high AUC > 0.9. These results significantly surpass the performance of all existing models.

No evidence for ac4C within human mRNA upon data reassessment.

Cytidine acetylation (ac4C) of RNA is a post-transcriptional modification catalyzed by Nat10. Recently, an approach termed RedaC:T was employed to map ac4C in human mRNA, relying on detection of C>T mutations in WT but not in Nat10-KO cells. RedaC:T suggested widespread ac4C presence. Here, we reanalyze RedaC:T data. We find that mismatch signatures are not reproducible, as C>T mismatches are nearly exclusively present in only one of two biological replicates. Furthermore, all mismatch types-not only C>T-are highly enriched in WT samples, inconsistent with an acetylation signature. We demonstrate that the originally observed enrichment in mutations in one of the WT samples is due to its low complexity, resulting in the technical amplification of all classes of mismatch counts. Removal of duplicate reads abolishes the skewed mismatch patterns. These analyses account for the irreproducible mismatch patterns across samples while failing to find evidence for acetylation of RedaC:T sites.

GANSamples-ac4C: Enhancing ac4C site prediction via generative adversarial networks and transfer learning.

RNA modification, N4-acetylcytidine (ac4C), is enzymatically catalyzed by N-acetyltransferase 10 (NAT10) and plays an essential role across tRNA, rRNA, and mRNA. It influences various cellular functions, including mRNA stability and rRNA biosynthesis. Wet-lab detection of ac4C modification sites is highly resource-intensive and costly. Therefore, various machine learning and deep learning techniques have been employed for computational detection of ac4C modification sites. The known ac4C modification sites are limited for training an accurate and stable prediction model. This study introduces GANSamples-ac4C, a novel framework that synergizes transfer learning and generative adversarial network (GAN) to generate synthetic RNA sequences to train a better ac4C modification site prediction model. Comparative analysis reveals that GANSamples-ac4C outperforms existing state-of-the-art methods in identifying ac4C sites. Moreover, our result underscores the potential of synthetic data in mitigating the issue of data scarcity for biological sequence prediction tasks. Another major advantage of GANSamples-ac4C is its interpretable decision logic. Multi-faceted interpretability analyses detect key regions in the ac4C sequences influencing the discriminating decision between positive and negative samples, a pronounced enrichment of G in this region, and ac4C-associated motifs. These findings may offer novel insights for ac4C research. The GANSamples-ac4C framework and its source code are publicly accessible at http://www.healthinformaticslab.org/supp/.

ac4C: a fragile modification with stabilizing functions in RNA metabolism.

In recent years, concerted efforts to map and understand epitranscriptomic modifications in mRNA have unveiled new complexities in the regulation of gene expression. These studies cumulatively point to diverse functions in mRNA metabolism, spanning pre-mRNA processing, mRNA degradation, and translation. However, this emerging landscape is not without its intricacies and sources of discrepancies. Disparities in detection methodologies, divergent interpretations of functional outcomes, and the complex nature of biological systems across different cell types pose significant challenges. With a focus of N4-acetylcytidine (ac4C), this review endeavors to unravel conflicting narratives by examining the technological, biological, and methodological factors that have contributed to discrepancies and thwarted research progress. Our goal is to mitigate detection inconsistencies and establish a unified model to elucidate the contribution of ac4C to mRNA metabolism and cellular equilibrium.

NAT10-mediated ac4C-modified ANKZF1 promotes tumor progression and lymphangiogenesis in clear-cell renal cell carcinoma by attenuating YWHAE-driven cytoplasmic retention of YAP1.

BACKGROUND: Lymphatic metastasis is one of the most common metastatic routes and indicates a poor prognosis in clear-cell renal cell carcinoma (ccRCC). N-acetyltransferase 10 (NAT10) is known to catalyze N4-acetylcytidine (ac4C) modification of mRNA and participate in many cellular processes. However, its role in the lymphangiogenic process of ccRCC has not been reported. This study aimed to elucidate the role of NAT10 in ccRCC lymphangiogenesis, providing valuable insights into potential therapeutic targets for intervention. METHODS: ac4C modification and NAT10 expression levels in ccRCC were assessed using public databases and clinical samples. Functional investigations involved manipulating NAT10 expression in cellular and mouse models to study its role in ccRCC. Mechanistic insights were gained through a combination of RNA sequencing, mass spectrometry, co-immunoprecipitation, RNA immunoprecipitation, immunofluorescence, and site-specific mutation analyses. RESULTS: We found that ac4C modification and NAT10 expression levels increased in ccRCC. NAT10 promoted tumor progression and lymphangiogenesis of ccRCC by enhancing the nuclear import of Yes1-associated transcriptional regulator (YAP1). Subsequently, we identified ankyrin repeat and zinc finger peptidyl tRNA hydrolase 1 (ANKZF1) as the functional target of NAT10, and its upregulation in ccRCC was caused by NAT10-mediated ac4C modification. Mechanistic analyses demonstrated that ANKZF1 interacted with tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein epsilon (YWHAE) to competitively inhibit cytoplasmic retention of YAP1, leading to transcriptional activation of pro-lymphangiogenic factors. CONCLUSIONS: These results suggested a pro-cancer role of NAT10-mediated acetylation in ccRCC and identified the NAT10/ANKZF1/YAP1 axis as an under-reported pathway involving tumor progression and lymphangiogenesis in ccRCC.

CircMAST1 inhibits cervical cancer progression by hindering the N4-acetylcytidine modification of YAP mRNA.

BACKGROUND: Cervical cancer (CCa) is the fourth most common cancer among females, with high incidence and mortality rates. Circular RNAs (circRNAs) are key regulators of various biological processes in cancer. However, the biological role of circRNAs in cervical cancer (CCa) remains largely unknown. This study aimed to elucidate the role of circMAST1 in CCa. METHODS: CircRNAs related to CCa progression were identified via a circRNA microarray. The relationship between circMAST1 levels and clinicopathological features of CCa was evaluated using the clinical specimens and data of 131 patients with CCa. In vivo and in vitro experiments, including xenograft animal models, cell proliferation assay, transwell assay, RNA pull-down assay, whole-transcriptome sequencing, RIP assay, and RNA-FISH, were performed to investigate the effects of circMAST1 on the malignant behavior of CCa. RESULTS: CircMAST1 was significantly downregulated in CCa tissues, and low expression of CircMAST1 was correlated with a poor prognosis. Moreover, our results demonstrated that circMAST1 inhibited tumor growth and lymph node metastasis of CCa. Mechanistically, circMAST1 competitively sequestered N-acetyltransferase 10 (NAT10) and hindered Yes-associated protein (YAP) mRNA ac4C modification to promote its degradation and inhibit tumor progression in CCa. CONCLUSIONS: CircMAST1 plays a major suppressive role in the tumor growth and metastasis of CCa. In particular, circMAST1 can serve as a potential biomarker and novel target for CCa.

Peptidylprolyl isomerase D circular RNA sensitizes breast cancer to trastuzumab through remodeling HER2 N4-acetylcytidine modification.

Human epidermal growth factor receptor 2 (HER2) overexpression and activation are crucial for trastuzumab resistance in HER2-positive breast cancer; however, the potential regulatory mechanism of HER2 is still largely undetermined. In this study, a novel circular RNA derived from peptidylprolyl isomerase D (PPID) is identified as a negative regulator of trastuzumab resistance. Circ-PPID is highly stable and significantly downregulated in trastuzumab-resistant cells and tissues. Restoration of circ-PPID markedly enhances HER2-positive breast cell sensitivity to trastuzumab in vitro and in vivo. Circ-PPID directly binds to N-acetyltransferase 10 (NAT10) in the nucleus and blocks the interaction between NAT10 and HER2 mRNA, reducing N4-acetylcytidine (ac4C) modification on HER2 exon 25, leading to HER2 mRNA decay. Intriguingly, the subcellular localization of circ-PPID differs between trastuzumab-sensitive and -resistant cells. Circ-PPID in trastuzumab-resistant cells is located more in the cytoplasm, mainly due to the upregulation of Exportin 4 (XPO4), which results in the loss of spatial conditions for circ-PPID to bind to nuclear NAT10. Taken together, our data suggest that circ-PPID is a previously unappreciated ac4C-dependent HER2 epigenetic regulator, providing a promising therapeutic direction for overcoming trastuzumab resistance in clinical setting.

N4-acetylcytidine modifies primary microRNAs for processing in cancer cells.

N4 acetylcytidine (ac4C) modification mainly occurs on tRNA, rRNA, and mRNA, playing an important role in the expression of genetic information. However, it is still unclear whether microRNAs have undergone ac4C modification and their potential physiological and pathological functions. In this study, we identified that NAT10/THUMPD1 acetylates primary microRNAs (pri-miRNAs) with ac4C modification. Knockdown of NAT10 suppresses and augments the expression levels of mature miRNAs and pri-miRNAs, respectively. Molecular mechanism studies found that pri-miRNA ac4C promotes the processing of pri-miRNA into precursor miRNA (pre-miRNA) by enhancing the interaction of pri-miRNA and DGCR8, thereby increasing the biogenesis of mature miRNA. Knockdown of NAT10 attenuates the oncogenic characters of lung cancer cells by regulating miRNA production in cancers. Moreover, NAT10 is highly expressed in various clinical cancers and negatively correlated with poor prognosis. Thus, our results reveal that NAT10 plays a crucial role in cancer initiation and progression by modulating pri-miRNA ac4C to affect miRNA production, which would provide an attractive therapeutic strategy for cancers.

N-acetyltransferase 10 regulates alphavirus replication via N4-acetylcytidine (ac4C) modification of the lymphocyte antigen six family member E (LY6E) mRNA.

Epitranscriptomic RNA modifications can regulate the stability of mRNA and affect cellular and viral RNA functions. The N4-acetylcytidine (ac4C) modification in the RNA viral genome was recently found to promote viral replication; however, the mechanism by which RNA acetylation in the host mRNA regulates viral replication remains unclear. To help elucidate this mechanism, the roles of N-acetyltransferase 10 (NAT10) and ac4C during the infection and replication processes of the alphavirus, Sindbis virus (SINV), were investigated. Cellular NAT10 was upregulated, and ac4C modifications were promoted after alphavirus infection, while the loss of NAT10 or inhibition of its N-acetyltransferase activity reduced alphavirus replication. The NAT10 enhanced alphavirus replication as it helped to maintain the stability of lymphocyte antigen six family member E mRNA, which is a multifunctional interferon-stimulated gene that promotes alphavirus replication. The ac4C modification was thus found to have a non-conventional role in the virus life cycle through regulating host mRNA stability instead of viral mRNA, and its inhibition could be a potential target in the development of new alphavirus antivirals.IMPORTANCEThe role of N4-acetylcytidine (ac4C) modification in host mRNA and virus replication is not yet fully understood. In this study, the role of ac4C in the regulation of Sindbis virus (SINV), a prototype alphavirus infection, was investigated. SINV infection results in increased levels of N-acetyltransferase 10 (NAT10) and increases the ac4C modification level of cellular RNA. The NAT10 was found to positively regulate SINV infection in an N-acetyltransferase activity-dependent manner. Mechanistically, the NAT10 modifies lymphocyte antigen six family member E (LY6E) mRNA-the ac4C modification site within the 3'-untranslated region (UTR) of LY6E mRNA, which is essential for its translation and stability. The findings of this study demonstrate that NAT10 regulated mRNA stability and translation efficiency not only through the 5'-UTR or coding sequence but also via the 3'-UTR region. The ac4C modification of host mRNA stability instead of viral mRNA impacting the viral life cycle was thus identified, indicating that the inhibition of ac4C could be a potential target when developing alphavirus antivirals.

Recent advances in the potential role of RNA N4-acetylcytidine in cancer progression.

N4-acetylcytidine (ac4C) is a highly conserved chemical modification widely found in eukaryotic and prokaryotic RNA, such as tRNA, rRNA, and mRNA. This modification is significantly associated with various human diseases, especially cancer, and its formation depends on the catalytic activity of N-acetyltransferase 10 (NAT10), the only known protein that produces ac4C. This review discusses the detection techniques and regulatory mechanisms of ac4C and summarizes ac4C correlation with tumor occurrence, development, prognosis, and drug therapy. It also comments on a new biomarker for early tumor diagnosis and prognosis prediction and a new target for tumor therapy. Video Abstract.

MetaAc4C: A multi-module deep learning framework for accurate prediction of N4-acetylcytidine sites based on pre-trained bidirectional encoder representation and generative adversarial networks.

MOTIVATION: N4-acetylcytidine (ac4C) is a highly conserved RNA modification that plays a crucial role in various biological processes. Accurately identifying ac4C sites is of paramount importance for gaining a deeper understanding of their regulatory mechanisms. Nevertheless, the existing experimental techniques for ac4C site identification are characterized by limitations in terms of cost-effectiveness, while the performance of current computational methods in accurately identifying ac4C sites requires further enhancement. RESULTS: In this paper, we present MetaAc4C, an advanced deep learning model that leverages pre-trained bidirectional encoder representations from transformers (BERT). The model is based on a bi-directional long short-term memory network (BLSTM) architecture, incorporating attention mechanism and residual connection. To address the issue of data imbalance, we adapt generative adversarial networks to generate synthetic feature samples. On the independent test set, MetaAc4C surpasses the current state-of-the-art ac4C prediction model, exhibiting improvements in terms of ACC, MCC, and AUROC by 2.36%, 4.76%, and 3.11%, respectively, on the unbalanced dataset. When evaluated on the balanced dataset, MetaAc4C achieves improvements in ACC, MCC, and AUROC by 2.6%, 5.11%, and 1.01%, respectively. Notably, our approach of utilizing WGAN-GP augmented training RNA samples demonstrates even superior performance compared to the SMOTE oversampling method.

Stacking-ac4C: an ensemble model using mixed features for identifying n4-acetylcytidine in mRNA.

N4-acetylcytidine (ac4C) is a modification of cytidine at the nitrogen-4 position, playing a significant role in the translation process of mRNA. However, the precise mechanism and details of how ac4C modifies translated mRNA remain unclear. Since identifying ac4C sites using conventional experimental methods is both labor-intensive and time-consuming, there is an urgent need for a method that can promptly recognize ac4C sites. In this paper, we propose a comprehensive ensemble learning model, the Stacking-based heterogeneous integrated ac4C model, engineered explicitly to identify ac4C sites. This innovative model integrates three distinct feature extraction methodologies: Kmer, electron-ion interaction pseudo-potential values (PseEIIP), and pseudo-K-tuple nucleotide composition (PseKNC). The model also incorporates the robust Cluster Centroids algorithm to enhance its performance in dealing with imbalanced data and alleviate underfitting issues. Our independent testing experiments indicate that our proposed model improves the Mcc by 15.61% and the ROC by 5.97% compared to existing models. To test our model's adaptability, we also utilized a balanced dataset assembled by the authors of iRNA-ac4C. Our model showed an increase in Sn of 4.1%, an increase in Acc of nearly 1%, and ROC improvement of 0.35% on this balanced dataset. The code for our model is freely accessible at https://github.com/louliliang/ST-ac4C.git, allowing users to quickly build their model without dealing with complicated mathematical equations.

Profile analysis of N4-acetylcytidine (ac4C) on mRNA of human lung adenocarcinoma and paired adjacent non-tumor tissues.

BACKGROUND: RNA modification, a major component of post-transcriptional modification, plays an essential role in tumor initiation and progression. N4-acetylcytidine (ac4C) present in different species as a highly conserved RNA modification. ac4C on mRNA increases the stability of mRNA and the efficiency of protein translation. However, the mRNA profiling of ac4C in lung adenocarcinoma (LUAD) is unknown. METHODS: NAT10 expression was tested using immunohistochemistry in tissue microarray (TMA). The ac4C peaks on mRNA were identified through acetylated RNA immunoprecipitation sequencing in both human LUAD tissues and adjacent non-tumor tissues, and differences of acetylation and mRNA between the two groups were analyzed. Furthermore, the function of AC4C-specific acetylated transcripts was analyzed bioinformatically. And a ac-RIP-PCR was used to verify the ac4C acetylation sites of TFAP2A. RESULTS: The expression of acetylated key enzyme NAT10 was obviously increased in LUAD group. Then we found noticeable differences in ac4C mRNA modification between LUAD and adjacent non-tumor tissues. In addition, bioinformatics analysis showed that the distinctive distribution pattern of mRNA ac4C in LUAD affects a variety of cellular functions, such as protein sumoylation and transmembrane transporter activity. Importantly, we verified the ac4C level of TFAP2A was up-regulated in LUAD. CONCLUSIONS: Our study revealed that the degree of ac4C in mRNA in LUAD was significantly higher than in adjacent tissues and was concentrated mainly in the coding sequences with a implications in a wide range of cellular functions. The ac4C may become a new molecular marker and treatment target for lung cancer.