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使用单细胞RNA测序和机器学习鉴定EGFR调节的椎间盘退变的潜在靶点

Identification of Potential Targets for EGFR-Regulated Nucleus Pulposus Degeneration Using Single-Cell RNA Sequencing and Machine Learning.

作者信息

Peng Xiaoyao, Wang Yi, Chen Yangyang, Hu Yuxiang, Wu Fashuai, Zhang Lu, Xu Weihua, Wei Yulong

机构信息

Department of Orthopaedics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.

Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, People's Republic of China.

出版信息

J Inflamm Res. 2025 Sep 2;18:12059-12075. doi: 10.2147/JIR.S530776. eCollection 2025.

DOI:10.2147/JIR.S530776
PMID:40927356
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12415117/
Abstract

INTRODUCTION

While nucleus pulposus cell (NPC) degeneration is a primary driver of intervertebral disc degeneration (IVDD), the cellular heterogeneity and molecular interactions underlying NPC degeneration remain poorly characterized. Previous studies have shown that EGFR signaling plays a significant role in NPC differentiation and collagen matrix production. Consequently, this study aims to identify the critical downstream regulatory molecule of EGFR in the process of NPC degeneration.

METHODS

We conducted subpopulation identification and functional analysis on scRNA-seq results in the GSE165722 dataset. Through pseudotime analysis, we identified genes with significant changes. Furthermore, we performed single-gene GSEA based on EGFR expression levels and conducted WGCNA to identify hub genes. Then, a combination of three machine learning algorithms (Lasso, XGBoost, and Random Forest), ROC curve, and validation in clinical specimens was employed to identify potential downstream regulatory molecule of EGFR associated with NPC degeneration. Finally, the regulatory effect of EGFR on potential downstream molecules was validated through both in vitro and in vivo experiments.

RESULTS

NPC from six severe IVDD samples were classified into six subpopulations, among which Fib-NPC was identified by functional and pseudotime analyses as a late-stage degenerative subpopulation linked to IVDD, with upregulated EGFR expression observed during degeneration. Five hub genes were identified through the intersection of pseudotime analysis, single-gene GSEA, and WGCNA. By integrating the results from three machine learning and validating through ROC curve and IHC, JAK1 was further identified as a downstream regulatory target of EGFR. Then, we found that JAK1 expression was elevated in NPC under oxidative stress, but remained unchanged following Gefitinib pretreatment. We further developed an IVDD model using mice with NP-specific inactivation of EGFR, which demonstrated that EGFR inactivation attenuated the upregulation of JAK1 in the degenerated NP region.

CONCLUSION

This study reveals a significant degenerative process in NPC and indicates that EGFR may contribute to this degeneration by regulating JAK1, thereby identifying a potential therapeutic target for delaying IVDD.

摘要

引言

虽然髓核细胞(NPC)退变是椎间盘退变(IVDD)的主要驱动因素,但NPC退变背后的细胞异质性和分子相互作用仍未得到充分表征。先前的研究表明,表皮生长因子受体(EGFR)信号通路在NPC分化和胶原基质产生中起重要作用。因此,本研究旨在确定EGFR在NPC退变过程中的关键下游调节分子。

方法

我们对GSE165722数据集中的单细胞RNA测序(scRNA-seq)结果进行了亚群鉴定和功能分析。通过伪时间分析,我们确定了有显著变化的基因。此外,我们基于EGFR表达水平进行了单基因基因集富集分析(GSEA),并进行了加权基因共表达网络分析(WGCNA)以确定枢纽基因。然后,结合三种机器学习算法(套索回归、XGBoost和随机森林)、ROC曲线以及临床标本验证,以确定与NPC退变相关的EGFR潜在下游调节分子。最后,通过体外和体内实验验证了EGFR对潜在下游分子的调节作用。

结果

来自六个严重IVDD样本的NPC被分为六个亚群,其中通过功能和伪时间分析确定Fib-NPC为与IVDD相关的晚期退变亚群,退变过程中EGFR表达上调。通过伪时间分析、单基因GSEA和WGCNA的交集确定了五个枢纽基因。通过整合三种机器学习的结果并经ROC曲线和免疫组化验证,进一步确定JAK1为EGFR的下游调节靶点。然后,我们发现氧化应激下NPC中JAK1表达升高,但吉非替尼预处理后保持不变。我们进一步构建了NP特异性EGFR失活的小鼠IVDD模型,结果表明EGFR失活减弱了退变NP区域中JAK1的上调。

结论

本研究揭示了NPC中的一个重要退变过程,并表明EGFR可能通过调节JAK1促进这种退变,从而确定了一个延缓IVDD的潜在治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/a12142fe1dfb/JIR-18-12059-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/66f16735a13a/JIR-18-12059-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/c382336728cf/JIR-18-12059-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/a7051dfc9529/JIR-18-12059-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/64e409382361/JIR-18-12059-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/4154f1eaac73/JIR-18-12059-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/a12142fe1dfb/JIR-18-12059-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/66f16735a13a/JIR-18-12059-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/c382336728cf/JIR-18-12059-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/a7051dfc9529/JIR-18-12059-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/64e409382361/JIR-18-12059-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/4154f1eaac73/JIR-18-12059-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc91/12415117/a12142fe1dfb/JIR-18-12059-g0006.jpg

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