Maintaining quiescence of stem cells is a potential way to decrease cell nutrition demand for restoring the organization. Herein, a biomimetic peptide to maintain quiescence of stem cells through C-X-C motif chemokine ligand 8 (CXCL8)-C-X-C motif chemokine receptor 1 (CXCR1) pathway against intervertebral disc degeneration (IVDD) is developed. First, it is confirmed that quiescence can be induced via inhibiting phosphatidylinositol 3-kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway in nucleus pulposus stem cells (NPSCs). Meanwhile, it is well known that CXCR1, a chemokine receptor, can be targeted by CXCL8, resulting in cell proliferation via activating PI3K/Akt/mTOR pathway. Second, a biomimetic peptide (OAFF) that can bind to CXCR1 and form fibrous networks on NPSCs, mimicking extracellular matrix formation is developed. The multivalent effect and long-term binding to CXCR1 on NPSCs of OAFF fibers offer forcefully competitive inhibition with natural CXCL8, which induces NPSCs quiescence and ultimately overcomes obstacle in intradiscal injection therapy. In rat caudal disc puncture model, OAFF nanofibers still maintain at 5 weeks after operation and inhibit degeneration process of intervertebral disc in terms of histopathology and imageology. In situ fibrillogenesis of biomimetic peptide on NPSCs provides promising stem cells for intradiscal injection therapy against IVDD.
Tan Cuiyu,Huang Shuqiang,Xu Liying,Zhang Tongtong,Yuan Xiaojun,Li Zhihong,Chen Miaoqi,Chen Cairong,Yan Qiuxia
Background Changes in the oxidative stress and lipid metabolism (OSLM) pathways play important roles in polycystic ovarian syndrome (PCOS) pathogenesis and development. Consequently, a systematic analysis of genes related to OSLM was conducted to identify molecular clusters and explore new biomarkers that are helpful for the diagnostic of PCOS. Methods Gene expression and clinical data from 22 PCOS women and 14 normal women were obtained from the GEO database (GSE34526, GSE95728, and GSE106724). Consensus clustering identified OSLM-related molecular clusters, and WGCNA revealed co-expression patterns. The immune microenvironment was quantitatively assessed utilizing the CIBERSORT algorithm. Multiple machine learning models and connectivity map analyses were subsequently applied to explore potential biomarkers for PCOS, and nomograms were employed to develop a predictive multigene model of PCOS. Finally, the OSLM status of PCOS and the hub genes expression profiles were preliminarily verified using TUNEL, qRT‒PCR, western blot, and IHC assays in a PCOS mouse model. Results 19 differential expression genes (DEGs) related to OSLM were identified. Based on 19 DEGs that were strongly influenced by OSLM, PCOS patients were stratified into two distinct clusters, designated Cluster 1 and Cluster 2. Distinct differences in the immune cell proportions existed in normal and two PCOS clusters. The random forest showed the best results, with the least cross-entropy and the utmost AUC (cross-entropy: 0.111 AUC: 0.960). Among the 19 OSLM-related genes, CXCR1, ACP5, CEACAM3, S1PR4, and TCF7 were identified by a Bayesian network and had a good fit with PCOS disease risk by the nomogram (AUC: 0.990 CI: 0.968–1.000). TUNEL assays revealed more severe DNA damage within the ovarian granule cells of PCOS mice than in those of normal mice ( P < 0.001). The RNA and protein expression levels of the five hub genes were significantly elevated in PCOS mice, which was consistent with the results of the bioinformatics analyses. Conclusion A novel predictive model was constructed for PCOS patients and five hub genes were identified as potential biomarkers to offer novel insights into clinical diagnostic strategies for PCOS.
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