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RNA 腺苷修饰相关亚型的串扰、预后模型的建立及卵巢癌的免疫浸润特征。

Crosstalk of RNA Adenosine Modification-Related Subtypes, Establishment of a Prognostic Model, and Immune Infiltration Characteristics in Ovarian Cancer.

机构信息

Department of Obstetrics and Gynecology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, China.

Department of Laboratory Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.

出版信息

Front Immunol. 2022 Jun 28;13:932876. doi: 10.3389/fimmu.2022.932876. eCollection 2022.

DOI:10.3389/fimmu.2022.932876
PMID:35837397
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9274011/
Abstract

BACKGROUND

Four RNA adenosine modifications, including m6A, m1A, alternative polyadenylation, and adenosine-to-inosine RNA editing, have been identified as potentially valuable in influencing colorectal carcinogenesis, immune infiltration, and response to drug therapy. However, the regulatory mechanisms and clinical significance of these four RNA modifications in ovarian cancer (OC) remain unknown.

METHODS

We comprehensively described the transcriptional and genetic modifications of 26 RNA modification "writers" in OC and assessed the expression patterns. We identified two RNA modification subtypes using an unsupervised clustering approach. Subsequently, using differentially expressed genes (DEGs) in both subtypes, we calculated RNA modification "writer" scores (RMW scores) to characterize the RNA modifications of single OC patients. RMW score-related gene expression was investigated by qRT-PCR. We explored the correlation between RMW score and clinical features, immune infiltration, and drug sensitivity. We drew a nomogram to more intuitively and accurately describe the application value of the RMW score.

RESULTS

We found that molecular alterations in "writers" are strongly related to prognostic and immune-infiltrating features in OC patients. We identified two different clusters of RNA modifications. According to the immune infiltration characteristics in the two RNA modification isoforms, cluster A and cluster B can correspond to "hot" and "cold" tumors, respectively. With the median RMW score, we classified the patients into high- and low-score subgroups. A low RMW score was associated with good patient prognosis and lower immune infiltration. In addition, a low RMW score equated with a higher cancer stem cell index and a lower tumor mutation burden, which to some extent affected the sensitivity of patients to therapeutic drugs. Seven RMW score-related gene expressions were investigated by qRT-PCR in three OC cell lines. Compared to previously known models, our established RMW score has higher accuracy in predicting patient survival.

CONCLUSION

A comprehensive analysis of four RNA modification patterns in OC reveals their potential value in OC prognosis, immune microenvironment, and drug sensitivity. These results could deepen our knowledge of RNA modification and yield fresh insights for new personalized therapeutic strategies.

摘要

背景

四种 RNA 腺苷修饰,包括 m6A、m1A、可变多聚腺苷酸化和腺苷到次黄嘌呤 RNA 编辑,已被确定为可能影响结直肠癌发生、免疫浸润和对药物治疗反应的有价值的因素。然而,这些四种 RNA 修饰在卵巢癌(OC)中的调控机制和临床意义尚不清楚。

方法

我们全面描述了 OC 中 26 种 RNA 修饰“书写器”的转录和遗传修饰,并评估了它们的表达模式。我们使用无监督聚类方法识别了两种 RNA 修饰亚型。随后,使用两种亚型中的差异表达基因(DEGs),我们计算了 RNA 修饰“书写器”评分(RMW 评分)来描述单个 OC 患者的 RNA 修饰。通过 qRT-PCR 研究 RMW 评分相关基因的表达。我们探讨了 RMW 评分与临床特征、免疫浸润和药物敏感性之间的相关性。我们绘制了一个诺莫图,以更直观和准确地描述 RMW 评分的应用价值。

结果

我们发现“书写器”中的分子改变与 OC 患者的预后和免疫浸润特征密切相关。我们鉴定了两种不同的 RNA 修饰亚型。根据两种 RNA 修饰异构体中的免疫浸润特征,簇 A 和簇 B 可分别对应于“热”和“冷”肿瘤。根据中位数 RMW 评分,我们将患者分为高评分和低评分亚组。低 RMW 评分与患者预后良好和免疫浸润程度低相关。此外,低 RMW 评分与更高的癌症干细胞指数和更低的肿瘤突变负担相关,这在一定程度上影响了患者对治疗药物的敏感性。我们在三个 OC 细胞系中通过 qRT-PCR 研究了 7 个 RMW 评分相关基因的表达。与之前已知的模型相比,我们建立的 RMW 评分在预测患者生存方面具有更高的准确性。

结论

OC 中四种 RNA 修饰模式的综合分析揭示了它们在 OC 预后、免疫微环境和药物敏感性方面的潜在价值。这些结果可以加深我们对 RNA 修饰的认识,并为新的个性化治疗策略提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/65933c0cc32f/fimmu-13-932876-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/65fba9b98733/fimmu-13-932876-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/33a8481019bc/fimmu-13-932876-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/59151ed1ebc2/fimmu-13-932876-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/78455cabd896/fimmu-13-932876-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/1c34262a6926/fimmu-13-932876-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/571ad515db49/fimmu-13-932876-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/697d7ee7d8b3/fimmu-13-932876-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/20560c02d893/fimmu-13-932876-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/65933c0cc32f/fimmu-13-932876-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/65fba9b98733/fimmu-13-932876-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/33a8481019bc/fimmu-13-932876-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/59151ed1ebc2/fimmu-13-932876-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/78455cabd896/fimmu-13-932876-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/1c34262a6926/fimmu-13-932876-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/571ad515db49/fimmu-13-932876-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/697d7ee7d8b3/fimmu-13-932876-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/20560c02d893/fimmu-13-932876-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/03d6/9274011/65933c0cc32f/fimmu-13-932876-g009.jpg

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