Radiotherapy (RT) is a cornerstone treatment for non-small cell lung cancer (NSCLC), yet tumor hypoxia and DNA repair mechanisms often contribute to resistance [
1]. Recent studies suggest that RT can reshape the tumor microenvironment (TME) and modulate immune responses, potentially enhancing its efficacy when combined with immunomodulatory strategies [
2,
3]. Secreted phosphoprotein 1 (SPP1), expressed by tumor-associated macrophages (TAMs), contributes to tumor progression and immune suppression, and its high expression correlates with poor prognosis in cancers [
4]. This study investigates how RT affects SPP1 expression in macrophages and explores the potential of targeting SPP1 to overcome RT resistance in lung cancer.
We first compared gene expression in lung tumors before and after RT, revealing an up-regulation of SPP1 following irradiation (Fig.
1A). Immune cell infiltration analysis indicated an increase in macrophage abundance after RT, with SPP1 expression positively correlating with macrophage infiltration (Fig.
1B and Fig. S1A to D). Immunofluorescence staining in a mouse model confirmed elevated levels of SPP1 and CD68 after RT (Fig.
1C). Functional enrichment analysis showed activation of extracellular matrix–receptor interaction and adhesion pathways following RT, linking SPP1 to RT resistance (Fig. S1E and F).
Single-cell RNA sequencing (RNA-seq) of lung cancer identified 9 distinct subpopulations, including macrophages, with varying distributions (Fig.
1D to G). SPP1 was highly expressed in macrophages, especially in tumor tissues (Fig.
1H). Macrophages were further categorized into 4 subpopulations: immune-related macrophages (IR_Macs), TCR-positive macrophages (TCR_Macs), lipid metabolism-associated macrophages (LM_Macs), and mitochondria-related macrophages (MT_Macs) (Fig.
1I). Notably, SPP1 was predominantly expressed in IR_Macs, which exhibited the highest M2 (anti-inflammatory) score, suggesting SPP1’s role in macrophage-mediated immunosuppression (Fig.
1J and K). Differential gene expression analysis showed that IL4I1 was more highly expressed in SPP1
+ IR macrophages, correlating with T cell immunosuppression (Fig.
1L). Enrichment analysis of the differentially expressed gene set also revealed that SPP1
+ IR macrophages were more active in several key pathways, including hypoxia, JAK-STAT, MAPK, PI3K, and TGF-β (Fig.
1M and N). Hypoxic tumor regions, enriched in SPP1
+ macrophages, foster an immunosuppressive and tissue-repairing microenvironment, which impairs RT efficacy [
5]. Additionally, the abundance of SPP1
+ IR macrophages correlated with worse prognosis in The Cancer Genome Atlas (TCGA) cohorts (Fig.
1O).
T cells are essential effectors of antitumor immunity. Therefore, we investigated the relationship between SPP1
+ IR macrophages and T cell subsets. We performed dimensionality reduction and clustering on NK/T cells, identifying 7 subpopulations: XCL1
+ NK cells, FCGR3A
+ NK cells, IL7R
+ CD4
+ naive T cells, CTLA4
+ regulatory T cells (Tregs), ZNF683
+ CD8
+ memory T cells, ISG
+ CD8
+ T cells, and GZMK
+ CD8
+ effector T cells (Fig. S2A to D). Cell-type correlation analysis revealed a negative correlation between SPP1
+ IR macrophages and T cell subsets, suggesting an immunosuppressive role (Fig. S2E). Communication analysis demonstrated strong interactions between SPP1
+ IR macrophages and T cells, particularly in tumor tissues, with the SPP1–CD44 axis showing the strongest interaction (Fig. S3A and B). SPP1
+ IR macrophages interacted with T cells via the macrophage migration inhibitory factor (MIF)–CD74–CD44/CXCR4 axis (Fig.
2A). The MIF signaling pathway, which is linked to poor prognosis and immune evasion, exhibited the second-highest interaction strength after the MHC pathway [
6] (Fig. S3C). This signal was predominantly secreted by SPP1
+ IR macrophages, with GZMK
+ CD8
+ T cells as the primary recipients (Fig.
2B).
MIF expression was significantly higher in SPP1
+ IR macrophages compared to SPP1
− IR macrophages (Fig.
2C and D). A strong positive correlation between SPP1 and MIF expression was observed at the single-cell level (Fig.
2E) and in bulk RNA-seq data from the TCGA cohorts (Fig.
2F). Patients with high expression of both SPP1
+ IR macrophage signature and MIF showed significantly worse overall survival, highlighting their cooperative role in promoting an immunosuppressive microenvironment (Fig.
2G).
Taken together, our findings suggest that combining RT with strategies targeting SPP1
+ macrophage-mediated immunosuppression may enhance CD8
+ T cell-mediated antitumor immunity. To validate the potential of combining RT with targeting SPP1
+ macrophages as a therapeutic strategy, we first generated the Lys
Cre-SPP1
fl/fl mouse model. The design strategy is illustrated in Fig. S4A, and the knockout efficiency is shown in Fig. S4B. The mice were divided into 4 groups: SPP1
fl/fl, Lys
Cre-SPP1
fl/fl, SPP1
fl/fl + RT, and Lys
Cre-SPP1
fl/fl + RT. The experimental workflow is shown in Fig. S4C. The results showed that both SPP1 knockout in macrophages and RT alone inhibited tumor growth, while the combination treatment exhibited a significantly stronger antitumor effect (Fig.
2H and I). Hematoxylin–eosin (HE) staining and PCNA immunohistochemistry further supported the enhanced antitumor efficacy of the combination therapy (Fig.
2J to L). We also examined the relationship among SPP1
+ macrophages, MIF, and CD8
+ T cells. Knockout of SPP1 in macrophages significantly reduced MIF expression and increased CD8 expression. This effect became more pronounced after RT (Fig.
2M to P). Based on these observations, we speculate that targeting SPP1 can significantly suppress the expression of MIF, thereby reducing immunosuppressive signals and subsequently activating the function of CD8
+ T cells. These findings suggest that targeting SPP1
+ macrophages combined with RT can enhance antitumor immune responses.
Our results indicate that targeting SPP1
+ macrophages represents a promising radiosensitizing strategy in NSCLC by reducing macrophage-mediated immunosuppression and enhancing CD8
+ T cell infiltration, thereby improving RT efficacy. Combining RT with SPP1-targeted interventions could overcome radioresistance and potentially improve clinical outcomes. Although our results provide valuable mechanistic insights, further exploration is needed for clinical translation. Nanoparticle systems, such as CANDI460, have shown success in targeting SPP1 to inhibit tumor growth [
7]. Macrophage targeting specificity is also crucial, and antibody–drug conjugates or engineered nanoparticles targeting TAMs may enhance specificity [
8,
9].
While our study provides valuable insights using mouse models and public datasets, these models may not fully replicate the complexity of the human TME. Future research should incorporate more clinically relevant models, such as patient-derived organoids or humanized mice, to better evaluate the efficacy and toxicity of SPP1-targeted therapies. Additionally, optimizing SPP1 inhibitors and delivery systems, such as nanoparticle-based platforms, and exploring combinations with immune checkpoint inhibitors or chemotherapy could enhance RT efficacy. Addressing other immune-suppressive mechanisms, like myeloid-derived suppressor cells (MDSCs), Tregs, or mregDC, may also improve therapeutic outcomes [
10]. In conclusion, targeting SPP1
+ macrophages shows promise for enhancing RT efficacy in NSCLC and overcoming radioresistance.
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