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整合单细胞转录组学与机器学习以定义肺腺癌中的ac4C基因特征

Integrating Single-Cell Transcriptomics and Machine Learning to Define an ac4C Gene Signature in Lung Adenocarcinoma.

作者信息

Wang Yuan, Su Wei, Zhou Guangyao, Wang Yijie, Wu Chunnuan, Zhang Pengpeng, Zhang Lianmin

机构信息

Key Laboratory of Cancer Prevention and Therapy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin, China.

Department of Lung Cancer, Tianjin Lung Cancer Center, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.

出版信息

Thorac Cancer. 2025 Aug;16(15):e70140. doi: 10.1111/1759-7714.70140.

DOI:10.1111/1759-7714.70140
PMID:40767620
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12326626/
Abstract

INTRODUCTION

Lung adenocarcinoma, the most common subtype of non-small cell lung cancer, faces challenges such as drug resistance and tumor heterogeneity. N4-acetylcytidine (ac4C) is an important RNA modification involved in cancer progression, but its role in lung adenocarcinoma remains unclear.

METHODS

This study analyzed transcriptomic and single-cell RNA sequencing data from public databases to investigate the expression and clinical significance of ac4C-related genes in lung adenocarcinoma. Ten machine learning algorithms were applied to develop and validate an ac4C-related gene signature (ARGSig) for prognosis prediction across multiple independent cohorts.

RESULTS

Cells with high ac4C activity showed increased intercellular communication and activation of tumor-associated pathways. The ARGSig model effectively stratified patients by survival outcomes and predicted sensitivity to immune checkpoint inhibitors and chemotherapy agents.

CONCLUSION

ac4C modification and its related genes play a critical role in lung adenocarcinoma development. The ARGSig model provides a promising molecular tool for prognosis evaluation and personalized treatment guidance in lung adenocarcinoma patients.

摘要

引言

肺腺癌是非小细胞肺癌最常见的亚型，面临着耐药性和肿瘤异质性等挑战。N4-乙酰胞苷（ac4C）是一种参与癌症进展的重要RNA修饰，但其在肺腺癌中的作用仍不清楚。

方法

本研究分析了来自公共数据库的转录组和单细胞RNA测序数据，以研究ac4C相关基因在肺腺癌中的表达及临床意义。应用十种机器学习算法开发并验证了一种用于多个独立队列预后预测的ac4C相关基因特征（ARGSig）。

结果

具有高ac4C活性的细胞显示细胞间通讯增加和肿瘤相关通路的激活。ARGSig模型有效地根据生存结果对患者进行分层，并预测对免疫检查点抑制剂和化疗药物的敏感性。

结论

ac4C修饰及其相关基因在肺腺癌发展中起关键作用。ARGSig模型为肺腺癌患者的预后评估和个性化治疗指导提供了一种有前景的分子工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/0ca2fbfbfc7d/TCA-16-e70140-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/f423cdef5634/TCA-16-e70140-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/76fc7762daa6/TCA-16-e70140-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/1e32594a3bdb/TCA-16-e70140-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/55db32585dd7/TCA-16-e70140-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/f4d5588f1589/TCA-16-e70140-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/f50b690addf9/TCA-16-e70140-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/0ca2fbfbfc7d/TCA-16-e70140-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/f423cdef5634/TCA-16-e70140-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/76fc7762daa6/TCA-16-e70140-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/1e32594a3bdb/TCA-16-e70140-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/55db32585dd7/TCA-16-e70140-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/f4d5588f1589/TCA-16-e70140-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/f50b690addf9/TCA-16-e70140-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/893e/12326626/0ca2fbfbfc7d/TCA-16-e70140-g002.jpg

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本文引用的文献

1
The role and mechanism of NAT10-mediated ac4C modification in tumor development and progression.NAT10介导的ac4C修饰在肿瘤发生发展中的作用及机制。
MedComm (2020). 2024 Dec 4;5(12):e70026. doi: 10.1002/mco2.70026. eCollection 2024 Dec.
2
Ac4C modification of lncRNA SIMALR promotes nasopharyngeal carcinoma progression through activating eEF1A2 to facilitate ITGB4/ITGA6 translation.Ac4C 修饰的长链非编码 RNA SIMALR 通过激活 eEF1A2 促进鼻咽癌的进展，从而促进 ITGB4/ITGA6 的翻译。
Oncogene. 2024 Sep;43(38):2868-2884. doi: 10.1038/s41388-024-03133-x. Epub 2024 Aug 18.
3
NAT10 inhibition promotes ac4C-dependent ferroptosis to counteract sorafenib resistance in nasopharyngeal carcinoma.
NAT10 抑制促进 ac4C 依赖性铁死亡以抵抗鼻咽癌索拉非尼耐药。
Cancer Sci. 2024 Oct;115(10):3256-3272. doi: 10.1111/cas.16249. Epub 2024 Jul 22.
4
NAT10 Promotes Prostate Cancer Growth and Metastasis by Acetylating mRNAs of HMGA1 and KRT8.NAT10 通过乙酰化 HMGA1 和 KRT8 的 mRNAs 促进前列腺癌的生长和转移。
Adv Sci (Weinh). 2024 Aug;11(32):e2310131. doi: 10.1002/advs.202310131. Epub 2024 Jun 23.
5
NAT10-mediated upregulation of GAS5 facilitates immune cell infiltration in non-small cell lung cancer via the MYBBP1A-p53/IRF1/type I interferon signaling axis.NAT10介导的GAS5上调通过MYBBP1A-p53/IRF1/I型干扰素信号轴促进非小细胞肺癌中的免疫细胞浸润。
Cell Death Discov. 2024 May 18;10(1):240. doi: 10.1038/s41420-024-01997-2.
6
Exosomal NAT10 from esophageal squamous cell carcinoma cells modulates macrophage lipid metabolism and polarization through ac4C modification of FASN.食管鳞状细胞癌细胞来源的外泌体NAT10通过对脂肪酸合酶进行N4-乙酰胞嘧啶修饰来调节巨噬细胞脂质代谢和极化。
Transl Oncol. 2024 Jul;45:101934. doi: 10.1016/j.tranon.2024.101934. Epub 2024 Apr 30.
7
Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy.机器学习揭示了肺腺癌预后和治疗中的多种细胞死亡模式。
NPJ Precis Oncol. 2024 Feb 26;8(1):49. doi: 10.1038/s41698-024-00538-5.
8
NAT10/ac4C/FOXP1 Promotes Malignant Progression and Facilitates Immunosuppression by Reprogramming Glycolytic Metabolism in Cervical Cancer.NAT10/ac4C/FOXP1 通过重编程宫颈癌中的糖酵解代谢促进恶性进展并促进免疫抑制。
Adv Sci (Weinh). 2023 Nov;10(32):e2302705. doi: 10.1002/advs.202302705. Epub 2023 Oct 11.
9
NAT10-mediated ac4C tRNA modification promotes EGFR mRNA translation and gefitinib resistance in cancer.NAT10 介导的 ac4C tRNA 修饰促进癌症中 EGFR mRNA 的翻译和吉非替尼耐药性。
Cell Rep. 2023 Jul 25;42(7):112810. doi: 10.1016/j.celrep.2023.112810. Epub 2023 Jul 18.
10
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Adv Sci (Weinh). 2023 Aug;10(23):e2300898. doi: 10.1002/advs.202300898. Epub 2023 Jun 16.