Abstract Intervertebral disc degeneration (IVDD) is a prevalent and debilitating condition associated with low back pain (LBP). Despite its significant impact, effective diagnostic markers for early-stage IVDD remain elusive. Recent research has implicated ferroptosis, a newly recognized form of programmed cell death, in the pathogenesis of IVDD, particularly involving disturbances in iron homeostasis. Additionally, the CC Chemokine Ligand 3 (CCL3) has been linked to macrophage migration and the progression of IVDD, yet its precise diagnostic and prognostic utility remains uncertain. This study aims to elucidate the underlying mechanisms of ferroptosis and the involvement of CCL3 in IVDD, with the objective of establishing their diagnostic and prognostic significance. By uncovering these mechanisms, novel biomarkers and therapeutic targets for the diagnosis and prognosis of IVDD may be identified. Single-cell sequencing data were acquired from the TCGA database, and a range of bioinformatics methods were employed for comprehensive analysis. Furthermore, validation experiments were conducted using in vitro techniques, including the analysis of human tissue samples, co-culture assays with neutralizing antibodies, quantitative real-time polymerase chain reaction (qRT-PCR), and Western blotting. Our findings suggest that CCL3 holds promise as a diagnostic and may was prognostic biomarker for IVDD. Validation experiments demonstrated that CCL3 functions via the pAMPK/AMPK pathway, thereby modulating apoptosis and impacting the progression of IVDD. Our study underscores the diagnostic and prognostic potential of CCL3 in patients with IVDD. Further investigations are warranted to explore therapeutic strategies targeting CCL3, ultimately enhancing the management of IVDD. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-94989-w. Keywords: IVDD, CCL3, Diagnosis, Prognosis, Ferroptosis Subject terms: Cell biology, Computational biology and bioinformatics, Molecular biology, Biomarkers, Diseases, Molecular medicine Introduction Low back pain (LBP) represents a widespread concern among spine surgeons globally, presenting substantial economic and lifestyle burdens on affected individuals. Among the various causes, intervertebral disc degeneration (IVDD) stands out as the primary culprit, emerging as the most prevalent degenerative ailment in this domain^[38]1. Given its pervasive impact, ongoing endeavors are concentrated on enhancing preventive measures, early detection protocols, and management approaches. The timely identification and intervention of underlying etiologies, coupled with supportive measures and, as warranted, intervertebral disc replacement therapy, are pivotal in ameliorating the prognosis of IVDD patients^[39]2. Nonetheless, the existing therapeutic armamentarium is limited, often yielding unsatisfactory outcomes^[40]3. Consequently, early diagnosis and intervention assume paramount importance. Regrettably, effective diagnostic markers are scarce in the early phases of IVDD, accentuating these challenges^[41]4. Despite notable advancements in comprehending IVDD’s pathophysiological and molecular underpinnings, the quest for dependable markers for grading, subclassification, and prognostication persists as a daunting task. Further exploration into biomarkers for IVDD and the identification of more efficacious therapeutic modalities are warranted^[42]5. In recent years, a novel type of cellular demise known as ferroptosis has emerged and garnered considerable attention in the context of IVDD^[43]6. Ferroptosis distinguishes itself from other modes of cell death by its unique morphological and biochemical characteristics. Notably, dysregulation of iron metabolism is closely linked to the onset and advancement of IVDD^[44]7. Iron, a vital micronutrient, when its equilibrium is disrupted, precipitates oxidative stress and inflammatory responses, ultimately culminating in cellular injury and demise. Numerous lines of evidence indicate that ferroptosis may influence the pathological mechanisms underlying IVDD through various pathways^[45]8. For instance, there may be a reduction in the activity or inhibition of the antioxidant enzyme glutathione peroxidase 4 (GPX4) during IVDD, consequently facilitating ferroptosis^[46]9. Moreover, the expression and functionality of iron-related proteins like transferrin and iron transporters can modulate the occurrence of ferroptosis in IVDD. Ferroptosis also interacts with other forms of cell death, contributing to disease progression. Elucidating the mechanistic role of genes associated with ferroptosis may offer promising avenues for the development of therapeutic interventions. CCL3, also known as macrophage inflammatory protein-1 alpha (MIP-1α), is a chemokine pivotal in orchestrating immune responses and inflammation. In the realm of intervertebral disc degeneration (IVDD) research, the involvement of macrophages has been well-established, with extensive investigations focusing on the CCL chemokine family^[47]10. Recent studies have highlighted TNF-α and IL-1β-induced upregulation of CCL3 expression in nucleus pulposus (NP) cells, fostering macrophage migration, a pivotal event in IVDD pathogenesis^[48]11. Resistin modulates CCL4 expression via Toll-like receptor-4 (TLR-4) and the p38-MAPK/NF-κB signaling pathway, while TGF-β1 suppresses CCL3/4 expression through the ERK signaling cascade^[49]11. Nevertheless, dedicated exploration of CCL3 remains scarce, and the diagnostic and prognostic significance of CCL3 in IVDD remains elusive. Elucidating the precise role of CCL3 in IVDD onset and progression holds promise for unraveling the underlying mechanisms and facilitating the development of targeted therapeutic strategies. A comprehensive exploration into the involvement of CCL3 in IVDD can shed light on its correlation with the condition and potentially unveil new biomarkers and therapeutic targets for diagnosing and prognosing IVDD. Hence, delineating the diagnostic and prognostic relevance of CCL3 in IVDD holds pivotal significance for guiding clinical management and devising more efficacious treatment modalities. Results Transcriptional analysis of transcriptome data We conducted an examination of transcriptomic bulk data retrieved from the GEO database, comparing samples from disease and control cohorts. Subsequently, utilizing ssGSEA enrichment analysis, we investigated the enrichment patterns of genes associated with iron-induced cell death in both groups. The heatmap depicted in Fig. [50]1A illustrates the distinct expression profiles of these genes between the disease and control cohorts. Furthermore, we scrutinized the distribution of infiltrating immune cells in these groups. As depicted in the bar graph presented in Fig. [51]1B, the disease cohort exhibited a heightened prevalence of immune cell types such as naïve B cells and Macrophages M0. Additionally, we performed pathway enrichment analysis on the differentially expressed genes associated with iron-induced cell death between the disease and control cohorts. Our findings, as depicted in Fig. [52]1C,D, revealed significant enrichment of pathways related to cellular response to chemical stress, cellular response to oxidative stress, and outer membrane pathways. Fig. 1. [53]Fig. 1 [54]Open in a new tab The characteristics of ferroptosis-related genes (FRGs) in Intervertebral Disc Degeneration (IVDD). (A) FRGs differential expression heat map; (B) Histogram of the expression levels of 22 immunocyte in control and IVDD cases; (C,D) GO function analysis of FRGs. Dimensionality reduction analysis of single-cell samples In Supplementary Fig. 1A, we selected eight samples from the [55]GSE165722 dataset for our analysis. The even distribution of cells across these samples suggests the absence of significant batch effects, rendering them suitable for subsequent analyses. UMAP, or Uniform Manifold Approximation and Projection, is a non-linear dimensionality reduction technique that leverages manifold learning and projection methodologies to reduce dimensionality. It calculates distances between points in high-dimensional space, projects them onto a lower-dimensional space, and computes distances between points in the lower-dimensional space. Subsequently, it employs stochastic gradient descent to minimize disparities between these distances, as illustrated in Supplementary Fig. 1B. Clustering and selection of single-cell samples Following log normalization and dimensionality reduction, we grouped all cells into 15 clusters, as depicted in Fig. [56]2A. Leveraging the genetic characteristics of each cluster, we annotated distinct cell types utilizing the singleR package, as illustrated in Fig. [57]2B. A total of eight cell types were discerned, comprising Neutrophils, Chondrocytes, Myelocytes, T cells, Pro-Myelocytes, Monocytes, HSC CD34+, and Erythroblasts. Subsequently, the differentiation of each cell group was delineated based on differentially expressed iron death-related marker genes, with representative marker genes for each group showcased in Fig. [58]2C. These genes encompass CCL3, CXCL3, CCL3L3, HLA-DRA, EREG, CXCL2, CCL4L2, HLA-DRB1, and SPP1. Fig. 2. [59]Fig. 2 [60]Open in a new tab Single cell cluster analysis. (A) The UMAP plot showed that all the cells in 15 clusters. (B) The UMAP indicates that IVDD samples can be annotated as 8 cell types in the TME (different colors represent different cell types) (C) Typical marker genes for each cell group. The expression profiles of cell type-specific marker genes for the eight cell types are presented in a bubble plot (Fig. [61]3A). Here, the bubble size reflects the percentage of cells expressing the specific gene within a given cluster, while the color denotes the average expression level of the gene in the specified cluster relative to the average expression level across all other cell clusters. Additionally, the histogram illustrates the distribution of each cluster within the eight identified clusters (Fig. [62]3B). Fig. 3. [63]Fig. 3 [64]Open in a new tab The identification of cells clusters according to scRNA data of Intervertebral Disc Degeneration (IVDD) patients. (A) Bubble diagram of the top5 marker gene expression of subgroups. (B) Calculating cell numbers as well as neighboring tissue. (C) Heatmap of the top5 marker gene expression of subgroups. (D) Volcano plot of the top5 marker gene expression of subgroups. Furthermore, we conducted a comprehensive examination of the expression patterns of the top five differentially expressed iron death-related genes across the eight cell types using heatmaps and volcano plots (Fig. [65]3C,D). Notably, Monocytes exhibited elevated expression levels of marker genes such as CCL3, CCL3L3, CXCL3, CD47, and HLA-DRA. Analysis of iron death gene expression in single-cell samples Subsequently, we evaluated the expression levels of iron death-related genes in individual samples. Remarkably, we observed notable variances in the expression levels of these genes across the four pathological grades of IVDD, demonstrating statistical significance (Supplementary Fig. 2A,B). Moreover, we conducted a comprehensive examination of the expression levels of iron death-related genes within the eight cell clusters. Violin plots unveiled statistically significant disparities in the expression levels of iron death-related genes across various cell types (Supplementary Fig. 2C,D). Analysis of the CCL3 gene We conducted a gene analysis focusing on CCL3, the most significantly differentially expressed gene associated with iron-induced cell death. The percentage of CCL3 gene expression in each cell was determined based on its characteristics. Employing the median value, we stratified the cells into high and low expression groups, delineating the high-expression CCL3 group and the low-expression CCL3 group (Fig. [66]4A). Subsequently, histograms were utilized to assess the distribution of the high and low CCL3 groups across the four sample groups (Fig. [67]4B). Notably, a higher proportion of patients exhibited low expression of the CCL3 gene in stages 1–2, whereas a greater proportion of patients demonstrated high expression of the CCL3 gene in stages 3–4. This observation aligns with prior research, suggesting that CCL3 may serve as a risk factor for IVDD and facilitate its progression. Additionally, KEGG and GO enrichment analyses^[68]12–[69]14 were conducted on the high and low CCL3 groups, revealing the CCL3 gene’s predominant association with the AMPK pathway and structural constituent of ribosome (Fig. [70]4C, D). Furthermore, we evaluated the expression levels of CCL3 in the eight cell clusters, with the results indicating that CCL3 is predominantly expressed in monocytes (Fig. [71]4E). Fig. 4. [72]Fig. 4 [73]Open in a new tab Single gene analysis of CC Chemokine Ligand 3 (CCL3). (A) AUCell score and grouping of CCL3 expression activity in each cell. (B) The proportion of subpopulation in each sample and the number of cells calculated. (C) KEGG analysis of CCL3. (D) GO analysis of CCL3. (E) Expression level of CCL3 gene in 8 cell clusters. Based on the scoring of CCL3 expression levels, we validated the expression levels of various marker genes in the two groups. The findings suggested that CCL3, CCL3L3, CCL4, CCL4L2, and TNF exhibited high expression in the high-expression group, while HBB, LTF, LYZ, MPO, and S100A9 demonstrated low expression in the low-expression group (Fig. [74]5). Fig. 5. [75]Fig. 5 [76]Open in a new tab Analysis of maker gene expression. (A) Expression levels of 10 maker genes in 2 groups. Ligand-receptor interaction analysis We conducted an analysis of differential pathways concerning cell interactions between the high and low expression groups (Fig. [77]6A). Moreover, variations in interactions among the eight cell clusters were observed between the two groups. The network diagram depicting intercellular interactions unveiled the ligand-receptor relationships across different cell clusters. The findings highlighted neutrophils and monocytes as exhibiting the highest proportion and quantity of interactions among the eight cell clusters (Fig. [78]6B,C). Additionally, Fig. [79]6D showcased that the ligand-receptor protein VEGF predominated in interactions within the high CCL3 expression group, while membrane proteins ADGRE5, CD45, LAMININ, RESISTIN, IGF, PERIOSTIN, JAM, PECAM1, and PDGF dominated interactions in the low-scoring group. Furthermore, an analysis of ligand-receptor pairs involved in cell interactions revealed that identical cell interactions did not entirely overlap between the high and low scoring groups (Fig. [80]6E). This underscores the heterogeneity of diseased cells and lays a theoretical foundation for future research on novel therapeutic agents. Fig. 6. [81]Fig. 6 [82]Open in a new tab Ligand-receptor interaction analysis. (A,B) Receptor and ligand proteins pathway distance analysis between 2 groups. (C) 8 types of cell cluster interaction network diagram, the thickness of the line represents the level of proportion. (D) The histogram shows the expression of receptor and ligand proteins in 2 groups, with red representing the high expression group and blue representing the low expression group. (E) The bubble diagram shows the correspondence between the two groups of receptor proteins and ligand proteins. Analysis of immunological relevance We utilized a heatmap to assess the correlation between differentially expressed genes associated with iron-induced cell death and 12 distinct immune cell types. Employing the CIBERSORT method, we analyzed the immune cell composition within IVDD samples and its association with the iron-induced cell death-related genes. Figure [83]7 depicts that EGR1, GABARAPL1, IL6, and MAPK14 exhibited positive correlations with immune cells, while TNFAIP3 and TXN displayed negative correlations with immune cells. Fig. 7. [84]Fig. 7 [85]Open in a new tab Immunocorrelation analysis. (A) The heat map shows the association of the Maker gene with 12 types of immune cells. Macrophage-derived CCL3 promotes apoptosis of IVDD cells Figure [86]8A illustrates a significant upregulation of CCL3 protein levels in intervertebral disc degeneration (IVDD) tissues compared to non-degenerative control (NC) tissues (p < 0.001), indicating heightened CCL3 expression in IVDD. Relative quantification analysis depicted in Fig. [87]8B further confirms the increased expression of CCL3 in IVDD tissues relative to NC tissues. At the mRNA level, Fig. [88]8C demonstrates a significant upregulation of CCL3 mRNA in IVDD tissues compared to NC tissues (p < 0.001) Fig. [89]8D reveals elevated CCL3 levels are determined by comparison with internal reference. Additionally, Fig. [90]8E shows an ELISA assay confirming the elevated concentration of CCL3 in the culture medium of IVDD cells, Mø1, and Mø5. Co-culture of IVDD cells with NC, Mø1, and Mø5 leads to increased CCL3 expression in IVDD cells (p < 0.01), suggesting a potential interaction resulting in CCL3 upregulation (Fig. [91]8F). Co-culture of IVDD cells with Mø1, Mø5, and NTAB-CCL3 induces a higher apoptotic rate compared to co-culture with NC (p < 0.05), indicating a potential pro-apoptotic effect (Fig. [92]8G). Fig. 8. [93]Fig. 8 [94]Open in a new tab Macrophage-derived CCL3 promotes apoptosis of IVDD cells. (A) The protein level of CCL3 in NC tissues and paired IVDD tissues (n = 8) was detected by western blot; (B) Relative quantification of CCL3 expression in A; (C) The mRNA level of CCL3 in NC tissues and paired IVDD tissues (n = 20) was detected by qRT-PCR; (D) mRNA levels of target gene and reference gene respectively; (E) The concentration of CCL3 in IVDD cells, Mø1, and Mø5 cultured medium was verified by ELISA assay; (F) The expression of CCL3 in IVDD cells was detected by western blot (lower panel) when co-cultured with NC, Mø1, and Mø5 and Relative quantification (upper panel); (G) Apoptotic rate of IVDD cells was detected by apoptosis kit when co-cultured with NC, Mø1, Mø5, and NTAB-CCL3; Macrophage-derived CCL3 promotes apoptosis of IVDD cells in a PH-dependent manner via AMPK pathway Quantitative analysis in Fig. [95]9C shows the increased apoptotic rate in IVDD cells when co-cultured with Mø1, Mø5, and NTAB-CCL3 (Fig. [96]9A). Western blot analysis in Fig. [97]9C reveals alterations in apoptosis-related proteins in IVDD cells when co-cultured with Mø1, Mø5, and NTAB-CCL3, suggesting potential molecular mechanisms involved in the observed increase in apoptosis. Figure [98]9D shows the Quantitative analysis in Fig. [99]8G. The expression of CCL3 and BCL-2 in IVDD cells varies under different pH conditions (7.0, 6.8, 6.6, and 6.4) when co-cultured with NC, Mø1, and Mø5, indicating pH-dependent regulation of these molecules in the context of IVDD and cell co-culture. Figure [100]9B demonstrates the pH-dependent changes in the expression of CCL3 and BCL-2 in IVDD cells when co-cultured with NC, Mø1, and Mø5. Quantitative analysis in Fig. [101]8E showcases pH-dependent changes in the expression of CCL3 and BCL-2 in IVDD cells when co-cultured with NC, Mø1, and Mø5, further supporting the notion of pH as a modulator of these molecules in the context of IVDD and cell co-culture. Co-culture of IVDD cells with Mø1 and Mø5 activates the AMPK pathway, as indicated by western blot analysis (Fig. [102]8F), suggesting potential involvement of this pathway in cellular interactions associated with IVDD. Quantitative analysis in Fig. [103]8G confirms increased protein levels associated with the AMPK pathway in IVDD cells co-cultured with Mø1 and Mø5, providing additional evidence for pathway activation in the context of IVDD and cell co-culture. Fig. 9. [104]Fig. 9 [105]Open in a new tab Macrophage-derived CCL3 promotes apoptosis of IVDD cells in a PH-dependent manner via AMPK pathway. (A) Relative quantification of apoptotic rate in C; (B) The expression of CCL3 and BCL-2 in IVDD cells was detected by western blot when co-cultured with NC, Mø1, and Mø5 in different PH condition (7.0, 6.8, 6.6, and 6.4); (C) Apoptosis-related protein of IVDD cells was detected by western blot when co-cultured with NC, Mø1, Mø5, and NTAB-CCL3; (D) Relative quantification of apoptosis in Fig. [106]8G; (E) Relative quantification of CCL3 and BCL-2 expression in Fig. 9B; (F) The activation of AMPK pathway was detected by western blot when IVDD cells co-cultured with NC, Mø1, Mø5; (G) Relative quantification of proteins in AMPK pathway in Fig. 9F. IVDD, intervertebral disc disease; IHC, Immunohistochemistry; Mø, macrophages; NTAB, Neutralizing antibody. *p < 0.05, **p < 0.01, ***p < 0.001. Discussion IVDD represents a global health concern with a rising incidence rate^[107]15, imposing substantial challenges on patient well-being and healthcare systems worldwide. Timely identification and intervention are imperative in managing IVDD, enabling optimal treatment outcomes and prognosis. Treatment strategies for IVDD vary depending on disease severity and individual patient requirements^[108]16. Traditional approaches encompass conservative measures such as rest, physical therapy, and pharmacotherapy, with surgical intervention reserved for severe cases. However, these interventions often yield limited efficacy. Consequently, recent medical efforts have prioritized advancing our understanding of IVDD pathophysiology, early diagnostic modalities, and efficacious treatment modalities^[109]17. Notably, the exploration of diagnostic and prognostic biomarkers has garnered increasing attention^[110]18,[111]19. This study undertook a comprehensive analysis integrating transcriptome data and single-cell samples to elucidate the involvement of iron death-related genes in IVDD. Our findings offer valuable insights into the molecular mechanisms and cellular interactions underpinning IVDD progression. Transcriptome analysis of bulk data from both disease and control cohorts unveiled a repertoire of differentially expressed genes associated with iron-mediated cell death. Subsequent single-sample gene set enrichment analysis (ssGSEA) underscored the enrichment of these genes in pathways pivotal to cellular responses to chemical and oxidative stress, alongside outer membrane pathways. These findings hint at the potential role of iron-induced cell demise in driving intervertebral disc degeneration (IVDD) pathogenesis by perturbing cellular stress responses and membrane integrity^[112]20,[113]21. Additionally, immune cell infiltration analysis unveiled an augmented presence of naïve B cells and M0 macrophages within the disease cohort, indicative of immune system involvement in IVDD^[114]22. Given the pivotal roles of immune cells in orchestrating inflammation and tissue remodeling^[115]23. the observed dysregulation of immune cell populations in IVDD may perpetuate a chronic inflammatory milieu within the intervertebral disc^[116]24. Furthermore, dimensionality reduction analysis of single-cell samples facilitated the delineation of discrete cell clusters and the annotation of distinct cell types based on their genetic signatures and marker genes^[117]25. We identified eight distinct cell types, including neutrophils, chondrocytes, myelocytes, T cells, pro-myelocytes, monocytes, HSC CD34+, and erythroblasts. The expression profiles of cell type-specific marker genes strongly validated the identified cell clusters and provided insights into their functional characteristics. The presence of erythroblasts and other blood cell precursors, including RBC and WBC, may be attributed to both the degenerative nature of the intervertebral disc and potential blood contamination during tissue retrieval, given the surgical procedures involved. Furthermore, ligand binding studies linking these cells to VEGF suggest a possible functional relevance. Additionally, examination of iron death-related gene expression in single-cell samples revealed significant differences in expression levels across various pathological grades of intervertebral disc degeneration (IVDD). These findings suggest a potential link between dysregulated iron death-related genes and the progression and severity of IVDD^[118]26. Moreover, the differential expression of iron death-related genes across diverse cell types underscores the heterogeneous cellular involvement in IVDD pathogenesis^[119]7. Notably, CCL3 emerged as the most significantly differentially expressed gene linked to iron-induced cell demise. Patients exhibiting elevated CCL3 expression were predominantly associated with stages 3–4 of IVDD, indicative of CCL3’s potential role as a risk factor for disease progression. The enrichment analysis underscored the association of CCL3 with the AMPK pathway and the structural constituent of the ribosome, implicating its involvement in cellular energy regulation and protein synthesis processes^[120]27,[121]28. Examination of ligand-receptor interactions provided valuable insights into intercellular communication dynamics and highlighted the extensive interactions between different cell clusters. Notably, Neutrophils and monocytes emerged as pivotal contributors, demonstrating the highest proportion and quantity of interactions, thus indicating their indispensable roles in mediating cellular crosstalk within the disc microenvironment^[122]29. Furthermore, the differential patterns of ligand-receptor interactions observed between the high and low expression groups underscore the heterogeneous nature of diseased cells and suggest potential avenues for therapeutic intervention in future investigations. Lastly, the immunological relevance analysis unveiled correlations between differentially expressed iron death-related genes and immune cell populations. Positive correlations were noted for genes such as EGR1, GABARAPL1, IL6, and MAPK14, indicating their potential involvement in immune responses and inflammation^[123]30–[124]32. Conversely, negative correlations were observed for genes like TNFAIP3 and TXN, suggesting potential regulatory roles in tempering immune activation^[125]33,[126]34. In subsequent in vitro investigations, we sought to validate the correlation between heightened CCL3 expression in human tissue and the presence of IVDD pathology. Prior evidence has established CCL3 as a chemokine prominently expressed on the surface of macrophages, a finding corroborated by our single-cell analysis^[127]35. Consistent with these observations, our analysis of macrophage samples extracted from in vitro experiments further supported this characterization^[128]36 Given the pivotal role of cellular apoptosis in IVDD progression, we conducted co-culture experiments involving macrophages and IVDD cells to emulate their interaction within an in vivo milieu. Subsequent assessment of indicators associated with cellular apoptosis revealed that dampening CCL3 expression appeared to mitigate cellular apoptosis, thereby potentially ameliorating the course of IVDD progression. These findings underscore the significance of CCL3 in the pathological mechanisms underlying IVDD. Moreover, our pathway enrichment analysis unveiled that CCL3 exerts an impact on cellular metabolism, thereby influencing the cellular apoptosis process through the activation of the AMPK pathway^[129]28. This discovery offers novel insights into the intricate molecular mechanisms governing IVDD pathology and holds promise for the development of precision-targeted therapeutic interventions aimed at modulating CCL3-mediated pathways. Our study underscores the critical significance of comprehending and addressing IVDD disease. Our findings elucidate the correlation between macrophage-secreted CCL3 and the progression of IVDD, proposing that interventions targeting CCL3 and its associated signaling pathways could hold promise as therapeutic avenues for IVDD^[130]10,[131]37. Building upon our research, there are several avenues for future investigations to explore and leverage these discoveries for precise targeted therapies. Further experimental inquiries can validate the direct influence of CCL3 on the pathological cascades of IVDD and delineate the molecular mechanisms by which CCL3 modulates cellular apoptosis^[132]38. Mechanistically, investigations can elucidate how CCL3 impacts cellular apoptosis via the AMPK pathway and delve into the underlying molecular pathways involved. Developing targeted therapeutic strategies against CCL3 and its associated pathways, establishing drug screening models targeting CCL3 and its signaling pathways, and identifying potential inhibitors or activators can facilitate tailored therapeutic interventions. Presently, clinical translation research in IVDD is burgeoning^[133]39, necessitating the application of these findings to preclinical and clinical trials to evaluate the feasibility of CCL3 as a therapeutic target for IVDD and ascertain the efficacy and safety of drug treatment strategies targeting CCL3 and its related pathways. By advancing these research trajectories, we can enhance our understanding of the molecular underpinnings of IVDD and lay the groundwork for the development of efficacious personalized targeted therapeutic approaches. These endeavors will contribute to enhancing the quality of life for IVDD patients and provide novel directions and insights for research in the realm of degenerative spinal disorders. In this study, we investigated the role of CCL3 in the pathogenesis of intervertebral disc degeneration (IVDD) and its potential as a therapeutic target. Our results indicate that CCL3 expression is closely associated with the progression of IVDD, particularly through its involvement in the regulation of ferroptosis-related genes. However, it is important to emphasize that these findings are preliminary and primarily based on in vitro models. The therapeutic implications of CCL3 require further validation, especially through in vivo studies, to confirm its role in the degeneration process and assess its potential as a therapeutic target for IVDD. The findings of this study suggest that CCL3 may play a significant role in promoting the inflammatory microenvironment in degenerated discs, which could, in turn, influence the activation of ferroptosis and contribute to tissue damage. The upregulation of CCL3 was found to correlate with the expression of genes related to iron-mediated cell death, indicating a potential mechanism by which inflammation accelerates IVDD progression. However, it is important to note that these observations need to be confirmed in vivo to establish a clear cause-and-effect relationship and to explore the therapeutic benefits of targeting CCL3 in a more controlled biological context. In addition to the preliminary nature of our findings, several factors should be considered when interpreting the role of CCL3 in IVDD. For example, while this study suggests that CCL3 expression is elevated in degenerated tissues, the specific role of CCL3 in the disease progression could be modulated by a variety of factors, such as the patient’s sex, age, and other clinical characteristics. Previous studies have shown that inflammatory responses and immune cell activity, including the expression of chemokines like CCL3, can vary between males and females due to hormonal differences. Furthermore, age-related changes in immune function and tissue resilience may also influence the inflammatory response in IVDD. Unfortunately, our current study did not specifically assess the impact of these variables, but we acknowledge that they could significantly alter the expression and functional role of CCL3 in the degenerative process. To better understand the clinical implications of CCL3 in IVDD, future studies should consider analyzing the effects of sex and age on its expression and function. This would provide a more comprehensive understanding of how these factors may influence the inflammatory microenvironment and the progression of IVDD. In addition, the potential therapeutic targeting of CCL3 should be explored in animal models that more closely mimic human conditions, considering both sex and age-related factors. In vivo validation will also allow for the assessment of potential therapeutic interventions aimed at modulating CCL3 levels, either through direct inhibition or modulation of its downstream signaling pathways. Moreover, we recommend that future studies include a broader range of clinical samples with varied demographic characteristics to explore how individual patient differences, including sex and age, may impact the role of CCL3 in IVDD. Such studies could also examine the potential for CCL3 as a biomarker for disease progression, with a focus on how CCL3 levels correlate with different stages of IVDD and the effectiveness of CCL3-targeted therapies. In conclusion, while our study provides valuable insights into the potential role of CCL3 in IVDD, it is clear that further in vivo research is needed to validate these findings and fully understand the therapeutic implications. Considering the impact of demographic factors such as sex and age will be crucial in future studies to ensure that the therapeutic potential of CCL3 is fully realized. We are optimistic that further investigation into CCL3 will provide novel insights into the pathogenesis of IVDD and open new avenues for targeted therapeutic strategies. In summary, our investigation offers thorough insights into the transcriptomic profile, cellular constitution, and molecular interplays linked to iron death-related genes in IVDD. These observations advance our comprehension of IVDD pathogenesis and offer potential guidance for forthcoming research endeavors focused on targeted therapeutics and interventions for this debilitating ailment. Conclusions Increased expression of the CCL3 gene correlates significantly with prognosis and enhanced apoptosis. CCL3 likely impacts immune cell infiltration, particularly macrophages, thereby contributing to the progression of IVDD. These results highlight CCL3 as a promising diagnostic and may was a prognostic biomarker with novel functional implications, rendering it a potential target for the diagnosis and treatment of IVDD patients. Materials and methods Transcriptome data acquisition and processing IVDD transcriptomic data, including RNA expression profiles, gene mutations, and corresponding clinical information, were obtained from the TCGA database (n = 1095). The dataset was then divided into a training group and a validation group in a 7:3 ratio. The training group was utilized for model construction, while the validation group was employed to assess the stability and accuracy of the model. Additionally, the [134]GSE20685 GEO expression profiles were downloaded and utilized as an external independent validation cohort. All data were initially provided in TPM format and subsequently transformed to log2 for further analysis. To account for batch effects between the TCGA dataset and [135]GSE20685, adjustments were performed using the “sva” package. Acquisition and processing of scRNA-seq data We retrieved the single-cell dataset [136]GSE161529 of IVDD from the GEO database. The dataset consists of ten samples in total. Quality control was performed on the scRNA-seq data using the “seurat” and “singleR” R packages^[137]40. To ensure the quality of the scRNA-seq data, we applied strict criteria for cell retention. Cells were kept if they had less than 10% mitochondrial genes, more than 200 genes overall, and gene expression levels ranging from 200 to 7000, expressed in at least three cells. This rigorous selection process aimed to preserve high-quality scRNA-seq data. A total of 50,917 eligible cells were selected for further exploration. The remaining cells underwent scaling and normalization using a linear regression model with the “Log-normalization” technique^[138]41. This step aimed to minimize technical variations and ensure comparability across cells. After data normalization, we identified the top 3000 hypervariable genes using the “FindVariableFeatures” function^[139]42. These genes are likely to contribute significantly to the observed biological differences within the dataset. Considering that the data were obtained from multiple samples, we utilized the “FindIntegrationAnchors” function of the canonical correlation analysis (CCA) method to address any batch effects that could potentially impact downstream analysis. Subsequently, we integrated and scaled the data adequately using the “IntegrateData” and “ScaleData” functions, respectively. Principal component analysis (PCA) dimensionality reduction was employed to identify anchor points. Additionally, we employed the t-distributed stochastic neighbor embedding (t-SNE) approach to visualize the top 20 principal components (PCs) and identify meaningful clusters within the IVDD dataset. To assess cell cycle heterogeneity within the identified clusters, we evaluated cell cycle markers embedded in the “seurat” package^[140]43. By employing these analytical techniques, we can gain a comprehensive understanding of the cellular heterogeneity, molecular characteristics, and potential biological pathways underlying IVDD. This integrated approach contributes valuable insights into disease pathogenesis and may guide future clinical interventions. The acquisition of genes related to ferroptosis We retrieved ferroptosis-related genes from the GeneCards database, focusing on genes with relevance scores greater than 1.0. A total of 110 SRGs were selected for subsequent investigation in our study. The selection process ensured that we included genes with high relevance and potential significance in the context of ferroptosis biology. AUCell analysis To identify the key genes influencing ferroptosis activity, we leveraged scRNA-seq data analysis. The “AUCell R” package was employed to evaluate the active status of gene sets specific to ferroptosis in each cell lineage. By calculating the area under the curve (AUC) value for selected SRGs, we estimated the percentage of highly expressed gene sets within individual cells. Cells with higher AUC values indicated greater expression of the ferroptosis-related genes. To determine the cells actively involved in ferroptosis gene sets, we utilized the “AUCell explore Thresholds” function. Based on the median AUC score, the cells were categorized into high and low-ferroptosis-AUC groups. Visualization of these groups was performed using the “ggplot2 R” tool. This approach allowed us to discern distinct cell populations exhibiting either high or low levels of ferroptosis activity. Single sample gene set enrichment analysis (ssGSEA) We employed ssGSEA analysis to calculate the SM scores for each patient in the TCGA-IVDD cohort. This method enabled us to quantify the enrichment of ferroptosis-related gene sets within individual samples accurately. By evaluating the activity of these gene sets, we aimed to gain insights into the role of ferroptosis metabolism in the context of TCGA-IVDD patients. Weighted co-expression network analysis (WGCNA) The R package “WGCNA” was utilized to implement weighted gene co-expression network analysis (WGCNA) in this study. WGCNA is a systems biology technique that constructs gene co-expression networks in TCGA-IVDD data. By assessing the interconnectivity of gene sets and their relationship with the phenotype, WGCNA enables the identification of highly correlated gene sets and the discovery of potential biomarkers or therapeutic targets. In our research, WGCNA was employed to identify gene modules associated with ferroptosis scores in IVDD and to elucidate the underlying genes involved in these modules. Development ferroptosis -associated risk signature Initially, a univariate Cox analysis was conducted to identify ferroptosis-related genes with prognostic value. Subsequently, a prognostic model was constructed using Lasso regression to further refine the selection of prognostic SRGs. Each breast cancer (BC) patient was assigned a risk score based on this algorithm. Using the median value as a threshold, patients in the TCGA-IVDD cohort were categorized into high- and low-risk groups. We then examined the differences in prognosis between these two groups and assessed the accuracy of the model. Evaluation of the prognostic model’s independence and validity We developed a nomogram incorporating the risk score, age, gender, pathological stage, and other clinical parameters as independent prognostic factors to calculate the probabilities of overall survival (OS) at 1, 3, and 5 years. Survival curves were generated using the Kaplan-Meier method, and log-rank tests were performed to determine statistical significance (24). Calibration and receiver operating characteristic (ROC) curves were used to evaluate the accuracy of the nomogram. Decision curve analysis (DCA) was employed to assess the net benefit of the nomogram compared to clinical features alone. Stratified analysis was conducted to evaluate the prognostic significance of the risk score and clinical features based on age, gender, clinical stage, and pathological T stage. Cell culture and tissue collection The tissue samples used in this study were provided by The First Affiliated Hospital of Anhui Medical University and stored at -80 °C. Eight paired tissue samples, consisting of degenerative intervertebral disc (IVD) tissue (D) and normal IVD tissue (N), were collected from patients diagnosed with intervertebral disc degeneration (IVDD) who underwent spinal surgery between February 2022 and December 2022. All samples were paired based on the clinical diagnosis of IVDD, with degenerative tissues being sourced from the affected discs and normal tissues from unaffected areas. The pairing was conducted by reviewing the patient’s preoperative imaging and surgical findings, with the degenerative samples being selected from the most severely affected regions, while the normal samples were obtained from adjacent, non-degenerate areas. The study was approved by the Institutional Ethical Board of The First Affiliated Hospital of Anhui Medical University (Approval No. 2010-SR-091), and informed consent was obtained from all participants and/or their legal guardians. All procedures were conducted in strict adherence to the Declaration of Helsinki. The degeneration grade of the intervertebral discs was determined using the Pfirrmann grading system, which classifies disc degeneration into five grades (I-V), based on MRI imaging and morphological features. A detailed summary of the age, degeneration grade, and characteristics of the procured IVDs is provided in Table [141]1. Table 1. Summary of age, degeneration grade, and characteristics of procured intervertebral discs (IVDs) from 8 patients. Patient no. Age (years) Degeneration grade IVD characteristics 1 42 Grade 2 Mild dehydration, slight fissures 2 59 Grade 3 Moderate dehydration, annular tear 3 36 Grade 1 Moderate degeneration, intact annulus 4 65 Grade 4 Severe dehydration, multiple radial tears 5 48 Grade 2 Mild dehydration, slight fissures 6 53 Grade 3 Moderate dehydration, annular tears 7 61 Grade 4 Severe dehydration, disc bulge 8 45 Grade 2 Mild dehydration, intact annulus [142]Open in a new tab For tissue preparation, the nucleus pulposus (NP) and annulus fibrosus (AF) were separated from each other in the degenerated IVDs by first identifying the boundaries between the two regions using anatomical landmarks. The NP tissue was isolated from the central region of the disc, while the AF tissue was isolated from the peripheral fibrous ring. Both tissues were carefully washed three times with sterile phosphate-buffered saline (PBS, Sigma), minced into approximately 0.5 × 0.5 × 0.5 mm³ fragments using sterile ophthalmic scissors, and digested with 2 mg/ml of type II collagenase (Sigma-Aldrich, USA) at 37 °C for 6 h. Following digestion, the tissue was centrifuged at 1500×g for 5 min, and the pellet was collected and cultured in DMEM/F12 medium (HyClone, USA) containing 10% fetal bovine serum (FBS) for 24 h to remove non-adherent cells. The cells were passaged weekly using 0.25% trypsin-EDTA (Biosharp). The cells from the second passage (P2) were used for further in vitro experiments. Acid-conditioned medium was prepared as previously described, and a neutralizing antibody against CCL3 (NTAB-CCL3), purchased from R&D Systems (Minneapolis, MN, 270-LD-050/CF), was used in subsequent experiments. The culture medium was replaced with acid-conditioned medium or serum-free DMEM/F12 for 12 h prior to treatment with NTAB-CCL3 (0–6 µg/ml), according to the manufacturer’s recommendations. Acid-conditioned media were used to simulate the acidic microenvironment found in degenerated intervertebral discs, where metabolic and inflammatory processes lead to a lower pH. This condition better mimics the physiological state of degenerated IVDs and allows for more relevant investigation of cellular responses under these conditions. Establishment of an in vitro intervertebral disc degeneration acid-induced model The isolated IVDD cells were suspended in an appropriate cell culture medium, and the pH of the medium was adjusted to desired levels (pH 7.0, 6.8, 6.6, and 6.4) using specific acid-buffering solutions. The pH-adjusted IVDD cell suspension was then transferred to culture dishes or plates containing the corresponding pH-adjusted medium. The cells were incubated at 37 °C in a 5% CO[2] atmosphere for a specified duration. Following incubation, CCL3 expression was analyzed by Western blot to validate the association between the process of IVDD and CCL3. Reverse transcription-quantitative PCR RNA was isolated using the TRIzol reagent (Invitrogen, Carlsbad, California). Using the HiScript RT Mix (Vazyme, Nanjing, China), total RNA (500 ng) was reverse transcribed into cDNA. Quantitative real-time PCR (qRT-PCR) was performed using the SYBR Green Kit (Vazyme, Nanjing, China). β-ACTIN was used as the internal control for normalization. All primers were designed by Tsingke Biotech (Beijing, China), and detailed primer sequences are provided in Supplementary Table [143]S1. For CT analysis, the threshold cycle (Ct) value for each target gene was determined by analyzing the amplification curves, and relative expression levels were calculated using the ΔΔCt method. Briefly, the Ct value represents the cycle number at which the fluorescence signal exceeds a defined threshold, indicating the amount of target gene expression. The ΔCt value was obtained by subtracting the Ct value of the internal control (β-ACTIN) from the Ct value of the target gene. The relative expression of the target gene was calculated using the formula ΔΔCt, comparing the expression in the experimental group to the control group. Isolation of macrophages Specimens were obtained from intervertebral disc (IVD) tissues of patients with degenerative disc disease. The IVD tissues were processed to isolate individual cells using mechanical cutting and enzymatic digestion methods. Specifically, the nucleus pulposus (NP) and annulus fibrosus (AF) regions were carefully separated, and the tissue was mechanically minced into smaller pieces. The tissue fragments were then digested with collagenase type II (Sigma-Aldrich) in a controlled environment to release the individual cells. To isolate macrophages from the mixed cell population, density gradient centrifugation was performed. This process exploits the differential sedimentation rates of cells based on their density. CD11b microbeads (CAT: 130-093-634, Miltenyi, Germany) were used to magnetically sort macrophages from other cell types. Following isolation, the macrophages were cultured in appropriate growth media supplemented with essential nutrients and growth factors to support their proliferation and functionality. The medium used included DMEM/F12 (HyClone, USA) with 10% FBS, and selective adhesion techniques were applied to further purify the macrophage population, ensuring the removal of contaminants and other unwanted cell types. This resulted in a high-purity sample of macrophages for subsequent experimentation. Co-culture of macrophages and IVDD cells Following the isolation of both cell types, the isolated macrophages and IVDD cells were cultured together in suitable growth media to create a co-culture system. The growth media for this co-culture contained appropriate nutrients and growth factors to support the proliferation and functionality of both cell types involved. The media composition was optimized to maintain the viability and physiological characteristics of both macrophages and IVDD cells. During the co-culture, selective adhesion or alternative separation methods were implemented to further purify and separate the macrophage population from any contaminants or unwanted cell types. This step aimed to ensure a high-purity macrophage sample in the co-culture system. Then, the NTAB-CCL3 was performed in this system. And the expression of CCL3 in IVDD cells was dected by Western blot. Detection of apoptosis To assess apoptosis after co-culture of macrophages and IVDD Cells, an Annexin V assay and Western blot were performed. The Annexin V assay is a commonly used method to detect apoptotic cells based on the externalization of phosphatidylserine (PS) residues on the cell membrane. PS is normally located on the inner leaflet of the plasma membrane but becomes exposed on the outer leaflet during the early stages of apoptosis. After co-culture of macrophages and IVDD Cells, the cells were harvested and washed with phosphate-buffered saline (PBS). The cells were then resuspended in binding buffer provided with the Annexin V staining kit. Annexin V conjugated with a fluorescent marker: FITC (fluorescein isothiocyanate), was added to the cell suspension and incubated for a specific period according to the manufacturer’s instructions. Following the incubation period, cells were analyzed using flow cytometry. Annexin V binds specifically to exposed PS residues on apoptotic cells, resulting in a fluorescent signal. The intensity of the fluorescence is proportional to the extent of apoptosis in the cell population. In addition to Annexin V, a viability dye, such as propidium iodide (PI), can also be used to distinguish between apoptotic and necrotic cells. The Bcl-2 expression was analysed by Western blot. Cell counting Kit-8 Co-culture of macrophages and IVDD Cells were cultured in appropriate growth media to ensure their optimal proliferation and functionality. The media contained suitable nutrients and growth factors specific to the co-culture cell line being used. The cells were maintained in a controlled incubator at the recommended temperature, and CO2 levels (37 °C, 5% CO2). For the CCK8 assay, the co-culture cells were seeded into 96-well plates at a predetermined density to achieve optimal cell confluency. After allowing the cells to adhere and grow for a specified period, the rhCCL3 treatments were applied. Following the treatment period, the media was carefully aspirated from each well, and the cells were washed with an appropriate buffer or saline solution to remove any residual compounds or debris that may interfere with the assay results. A CCK8 reagent (Beyotime, Shanghai, China, C0048M) was then added to each well, according to the manufacturer’s instructions. The plates were then incubated for 1 h to allow the formazan formation. After the incubation, the absorbance of the colored solution was measured using a plate reader at a specific wavelength determined by the CCK8 assay protocol. The absorbance values were directly proportional to the number of viable cells present in each well. To account for any background noise or non-specific signals, control wells containing only media and CCK8 reagent were included. These wells provided a baseline measurement for comparison and allowed for the determination of relative cell viability. Methodology for ELISA analysis of CCL3 in cell culture supernatants and co-culture supernatants For the detection of CCL3 in cell culture supernatants and co-culture supernatants, an ELISA kit (Human CCL3/MIP-1α ELISA Kit, Catalog # ab100689, Abcam, Cambridge, UK) was used according to the manufacturer’s protocol. Briefly, supernatants from IVDD and co-culture systems were collected and clarified by centrifugation at 1,000 × g for 10 min. The ELISA assay was performed by adding 100 µL of the sample or standards to the precoated 96-well plate. After incubation at 37 °C for 1 h, wells were washed, and 100 µL of biotinylated antibody was added. After further incubation and washing, streptavidin-HRP was added, followed by a substrate solution. The reaction was stopped with the provided stop solution, and the absorbance was measured at 450 nm using a microplate reader (Model, Thermo Fisher Scientific, Waltham, MA, USA). CCL3 concentrations were determined from the standard curve generated with known concentrations of recombinant CCL3. All reagents were purchased from Abcam (Cambridge, UK). This methodology ensures accurate and reliable quantification of CCL3 in both cell culture and co-culture supernatants, providing insight into the inflammatory response within these experimental models. Statistical analysis GraphPad Prism (version 8.0) software was used to analyze the experimental data. Data from three independent experiments are presented as the mean ± standard deviation (SD). Comparisons between groups were performed using Student’s t-test (*P < 0.05, **P < 0.01, ***P < 0.001). Normality of the data was assessed using the Shapiro-Wilk test prior to performing the t-test. Statistical significance was considered at P < 0.05. Limitations While this study provides valuable insights into the potential role of CCL3 in intervertebral disc degeneration (IVDD) and its association with ferroptosis, several limitations should be acknowledged. Firstly, the findings presented here are preliminary, particularly regarding the therapeutic implications of CCL3. While our in vitro data suggest a potential therapeutic role, further validation through in vivo studies is required to assess the efficacy and safety of CCL3-targeted therapies. The lack of animal model validation at this stage limits the ability to draw definitive conclusions about the clinical relevance of CCL3 as a therapeutic target. Secondly, our study did not specifically examine the influence of sex and age on CCL3 expression or its role in IVDD. It is well established that biological sex and age can affect immune responses and disease progression. Therefore, these factors may contribute to variability in CCL3 expression and its association with ferroptosis and IVDD. Future studies should consider including a more diverse sample population with respect to sex and age to explore the potential impact of these variables on the observed outcomes. Additionally, while we focused on the expression of CCL3 in relation to IVDD and ferroptosis, other confounding factors that could influence the disease progression, such as genetic predispositions, lifestyle factors, and comorbid conditions, were not systematically addressed in this study. These factors could play a significant role in the pathophysiology of IVDD and should be considered in future research. Finally, the study’s design was limited to in vitro experiments, which, while valuable for understanding the molecular mechanisms, do not fully recapitulate the complexity of the in vivo environment. Thus, additional studies incorporating more physiological models, including animal studies and clinical samples, are needed to confirm the relevance of our findings to human IVDD. In conclusion, while our study provides important insights, it is crucial to recognize its limitations, and further research addressing these aspects is necessary to fully understand the role of CCL3 in IVDD and its potential as a therapeutic target. Electronic supplementary material Below is the link to the electronic supplementary material. [144]Supplementary Material 1^ (2.1MB, docx) Acknowledgements