Liu Yong, Chen Xueyan, Chen Jingwen, Song Chao, Wei Zhangchao, Liu Zongchao, Liu Fei
Department of Orthopedics, The Affiliated Hospital of Traditional Chinese Medicine Southwest Medical University Luzhou China.
Department of Anesthesiology, The Affiliated Traditional Chinese Medicine Hospital Southwest Medical University Luzhou China.
JOR Spine. 2025 Mar 24;8(1):e70060. doi: 10.1002/jsp2.70060. eCollection 2025 Mar.
Intervertebral disc degeneration (IDD) is a human aging disease related mainly to inflammation, cellular senescence, RNA/DNA methylation, and ECM. The mitogen-activated protein kinase (MAPK) signaling pathway is engaged in multiple biological functions by phosphorylating specific serine and threonine residues on target proteins through phosphorylation cascade effects, but the role and specific mechanisms of the MAPK signaling pathway in IDD are still unclear.
We identified 20 MAPK-related differential genes by differential analysis of the GSE124272 and GSE150408 datasets from the GEO database. To explore the biological functions of these differential genes in humans, we performed GO and KEGG analyses. Additionally, we applied PPI networks, LASSO analysis, the RF algorithm, and the SVM-RFE algorithm to identify core MAPK-related genes. Finally, we conducted further validation using clinical samples.
We ultimately identified and validated four pivotal MAPK-related genes, namely, KRAS, JUN, RAP1B, and TNF, using clinical samples, and constructed the ROC curves to evaluate the predictive accuracy of the hub genes. A nomogram model was subsequently developed based on these four hub MAPK genes to predict the prevalence of IDD. Based on these four hub genes, we classified IDD patients into two MAP clusters by applying the consensus clustering method and identified 1916 DEGs by analyzing the differences between the two clusters. Further analysis using the same approach allowed us to identify two gene clusters based on these DEGs. We used a PCA algorithm to determine the MAPK score for each sample and discovered that MAPK cluster A and gene cluster A had higher scores, suggesting greater sensitivity to MAPK signaling pathway-associated agents in the subtype. We displayed the differing expression levels of four hub MAPK-related genes across the two clusters and their relationship with immune cell infiltration to highlight the distinctions between clusters A and B.
In summary, four hub MAPK signaling pathway-related genes, KRAS, JUN, RAP1B, and TNF, could be applied to the diagnosis and subtype classification of IDD and benefit the prevention and treatment of IDD.
椎间盘退变（IDD）是一种与炎症、细胞衰老、RNA/DNA甲基化和细胞外基质（ECM）主要相关的人类衰老疾病。丝裂原活化蛋白激酶（MAPK）信号通路通过磷酸化级联效应使靶蛋白上的特定丝氨酸和苏氨酸残基磷酸化，从而参与多种生物学功能，但MAPK信号通路在IDD中的作用和具体机制仍不清楚。
我们通过对来自基因表达综合数据库（GEO）的GSE124272和GSE150408数据集进行差异分析，鉴定出20个与MAPK相关的差异基因。为了探究这些差异基因在人类中的生物学功能，我们进行了基因本体（GO）和京都基因与基因组百科全书（KEGG）分析。此外，我们应用蛋白质-蛋白质相互作用（PPI）网络、套索（LASSO）分析、随机森林（RF）算法和支持向量机-递归特征消除（SVM-RFE）算法来鉴定核心MAPK相关基因。最后，我们使用临床样本进行进一步验证。
我们最终使用临床样本鉴定并验证了四个关键的MAPK相关基因，即KRAS、JUN、RAP1B和TNF，并构建了ROC曲线以评估枢纽基因的预测准确性。随后基于这四个枢纽MAPK基因开发了一个列线图模型来预测IDD的患病率。基于这四个枢纽基因，我们应用一致性聚类方法将IDD患者分为两个MAP簇，并通过分析两个簇之间的差异鉴定出1916个差异表达基因（DEG）。使用相同方法的进一步分析使我们能够基于这些DEG鉴定出两个基因簇。我们使用主成分分析（PCA）算法确定每个样本的MAPK评分，发现MAPK簇A和基因簇A的评分较高，表明该亚型对MAPK信号通路相关药物更敏感。我们展示了两个簇中四个枢纽MAPK相关基因的不同表达水平及其与免疫细胞浸润的关系，以突出A簇和B簇之间的差异。
总之，四个枢纽MAPK信号通路相关基因KRAS、JUN、RAP1B和TNF可应用于IDD的诊断和亚型分类，并有助于IDD的预防和治疗。
