Abstract
Background
The clinical treatment of Osteosarcoma (OS) faces major barriers due to the risk of tumor recurrence. Immunotherapy utilizing immune checkpoint blockade (ICB) antibodies has exhibited promise in inducing tumor rejection and providing clinical benefits for patients among various tumor types. However, tumors often develop resistance to immune rejection. Given the limitations of current therapies, there is an urgent need to explore novel therapeutic strategies to enhance anti-tumor immunity and prevent recurrence. This study aims to investigate the potential of α2-adrenergic receptor (α2-AR) agonists, delivered via a thermo-sensitive hydrogel (PLGA-PEG-PLGA), as a therapeutic strategy to combat immune rejection and tumor recurrence in osteosarcoma.
Methods
In this study, we investigated the anti-tumor effects of α2-AR agonists using a thermo-sensitive PLGA-PEG-PLGA hydrogel as a drug delivery system. The hydrogel was loaded with the α2-AR agonist UK14,304 and evaluated for its efficacy and biosafety in vitro and in vivo. In vitro experiments included cell viability assays (CCK-8), scratch wound healing assays, and Transwell assays to assess the impact of UK14,304 on OS cell lines. For in vivo studies, a subcutaneous OS xenograft mouse model was established using BALB/c nude and immunocompetent BALB/c mice. Tumor recurrence and growth were monitored after surgical resection and treatment with the hydrogel-agonist formulation. Proteomic analysis of tumor immune microenvironment (TME), Metascape, STRING, Cytoscape, TCGA and GTEx databases were performed to elucidate the underlying mechanisms of the anti-tumor effects.
Results
We evaluated the anti-tumor effects of α2-AR agonists (specifically UK14,304) loaded into a thermo-sensitive PLGA-PEG-PLGA hydrogel both in vitro and in vivo. In vitro experiments using OS cell lines (K7M2, 143b, and Khos) showed that UK14,304 did not significantly affect cell viability, migration, or invasion, indicating minimal direct cytotoxicity. In vivo studies using immunocompetent BALB/c mice demonstrated a significant reduction in tumor recurrence and growth when treated with UK14,304-loaded hydrogels compared to controls, highlighting an immune-mediated anti-tumor effect. Proteomic analysis of TME revealed that the anti-tumor mechanism involves the activation of CD8+ T cells and TCR signaling pathways, with ITGAL identified as a central regulatory factor. Additionally, bioinformatics analysis suggested the involvement of LLPS in enhancing TCR signaling. Correlation analysis with TCGA and GTEx databases further indicated that the identified proteins (e.g., MSN, TOLLIP, ITGAL) are associated with improved clinical outcomes.
Conclusion
Overall, our results demonstrate that α2-AR agonists may serve as a potential drug for a prospective drug delivery system in the post-surgical management of OS.
Significance statement
This study highlights the therapeutic efficacy of α2-AR agonists in osteosarcoma treatment through a novel drug delivery system, suggesting their potential to enhance anti-tumor immune responses by modulating CD8+ T cell activity and TCR signaling, as supported by correlations with clinical outcomes in TCGA and GTEx databases.
The translational potential of this article
The findings of this study present a promising translational potential by demonstrating the efficacy of α2-AR agonists in enhancing anti-tumor immunity in OS, potentially paving the way for targeted immunotherapies in post-surgical management to combat tumor recurrence and resistance.
Keywords: Osteosarcoma (OS), Tumor recurrence, α2-AR agonists, Liquid-liquid phase separation (LLPS), Bioinformatics, Therapy
Graphical abstract
A schematic procedure of this study.
1. Introduction
Osteosarcoma (OS), a highly aggressive bone tumor predominantly affecting children and adolescents, remains challenging to treat due to the persistence of residual cancer cells post-surgical resection and the adverse effects of systemic chemotherapy [[1], [2], [3], [4], [5]]. While multimodal strategies combining surgery with chemotherapy have improved outcomes, the development of targeted therapies to eliminate residual cells is critical. Adrenergic antagonists, particularly β-adrenoceptor blockers like propranolol, have shown promise in attenuating cancer growth in melanoma and other cancers by modulating adrenergic receptor (AR) signaling [1,[6], [7], [8], [9], [10], [11], [12]]. However, the anti-tumor potential of α2-AR agonists remains largely unexplored [13].
PLGA-PEG-PLGA hydrogels, known for their biodegradability and capacity to deliver both hydrophilic and hydrophobic drugs, offer a promising platform for localized drug delivery [[14], [15], [16], [17], [18], [19]]. In this study, we developed a drug delivery system using PLGA-PEG-PLGA hydrogels loaded with the α2-AR agonist UK14,304. We evaluated its anti-tumor efficacy and biosafety in preclinical models, including BALB/c nude mice and K7M2 cell line-transplanted mice, alongside proteomic analysis of TME to elucidate underlying mechanisms. This drug-delivery platform can be co-formulated compatible with 3D-printed bone-defect fillers. Evaluating such combinations for simultaneous tumour control and bone regeneration will be the focus of future work [5,[14], [15], [16], [17], [18], [19]].
2. Materials and methods
2.1. Ethics statement
All animal experiments for this study were reviewed and approved by the Animal Care and Use Committee of Peking University People’s Hospital (Ethics Number: 2024PHE026). All the experiments were conducted in compliance with the ARRIVE guidelines and were carried out in accordance with the U.K. Animals (Scientific Procedures) Act, 1986 and associated guidelines, EU Directive 2010/63/EU for animal experiments, or the National Research Council's Guide for the Care and Use of Laboratory Animals. During all experimental procedures, the number of animals and their suffering were minimized.
2.2. Fabrication of PLGA(1500–2000)-PEG(1000–1500)-PLGA(1500–2000) and UK14,304 compound
The hydrogel protocol was prepared following previously described methods (references 44, 45). The PLGA(1500–2000)-PEG(1000–1500)-PLGA(1500–2000) copolymer was sourced from Xian Ruixi Bio-Technology Co., Ltd. (R-PL1002-3, Xian, China). The gel exhibited thermoresponsive behavior, transitioning to a sol state at 15–20 °C and forming a gel at 35 ± 2 °C. For preparation, 0.3 g of the polymer was mixed with 1.2–1.5 g of deionized water (1:4–5 ratio, w/w) and allowed to hydrate for 3 h. During this period, the polymer initially hardened and was subsequently crushed thoroughly using a glass rod to enhance the contact surface area between the polymer and water, facilitating dissolution. The final PLGA(1500–2000)-PEG(1000–1500)-PLGA(1500–2000) polymer solution appeared as a homogeneous yellowish-brown viscous liquid. The hydrogel was then loaded with UK14,304 (B3465, Apexbio, USA) at a concentration of 1 mg/L for further use.
2.3. Cell culture and lentiviral transduction
The OS cell lines (KHOS, 143b, and K7M2) were acquired from Department of Bone Tumor, Peking University People's Hospital, Beijing, China. These cell lines were cultured in Dulbecco's Modified Eagle's Medium/Nutrient Mixture F-12 (11320033, Thermo Fisher, USA) with 10 % fetal bovine serum (5669701, Thermo Fisher, USA) and 100 U/ml penicillin/streptomycin solution (15070063, Thermo Fisher, USA) at 37 °C in a humidified incubator with 5 % CO2. The OS cell lines were transduced with recombinant lentiviruses expressing luciferase (GeneChem, China).
2.4. Cell counting kit-8 (CCK-8) assay
Cell viability was assessed using the Cell Counting Kit-8 (CCK-8; CK04-500T, Dojindo, Japan). Cells were seeded in 96-well flat-bottom plates at 5 × 103 cells/ml (100 μl/well), with five replicates per group. To minimize evaporation, 200 μl of sterile PBS was added to peripheral wells. Following overnight incubation at 37 °C with 5 % CO2, 10 μl of CCK-8 solution was added to each well, and cells were incubated for 3 h. Absorbance at 450 nm was measured at 0, 24, 48, and 72 h.
2.5. Transwell assay
Cell migration and invasion assays were performed using Corning Matrigel Basement Membrane Matrix (356234, Corning, USA). For invasion assays, Matrigel was thawed, diluted, and applied to Transwell Permeable Supports (3422, Corning, USA), followed by 1 h incubation at 37 °C; this step was omitted for migration assays. Cells in logarithmic growth phase were trypsinized, resuspended in serum-free medium, and seeded into the upper chamber (100 μl/well). The control group was maintained in serum-free medium, while the experimental group was treated with conditioned medium containing UK14,304. The lower chamber was filled with 600 μl of 20 % serum medium. Each group included five replicates. After 24 h or 48 h incubation, chambers were washed with PBS, fixed in 70 % methanol, and stained with crystal violet. Migrated or invaded cells were imaged using an inverted fluorescence microscope, with random fields of view captured for analysis.
2.6. Scratch wound healing assay
Cells were seeded in 6-well plates at 3 × 104 cells/well and cultured to 80–90 % confluence, with three replicates per group. A sterile 10 μl pipette tip was used to create a scratch in the cell monolayer, and detached cells were gently removed with PBS. Cells were then cultured in normal or conditioned medium. Scratch closure was monitored at 0, 24, and 48 h, with images captured at 100 × magnification.
2.7. In vivo anti-tumor effect and biosafety
To evaluate the in vivo anti-tumor efficacy of UK14,304, we established an osteosarcoma mouse model using female BALB/c nude mice (5–6 weeks old; Beijing Vital River Company, China). Mice were housed under standard conditions with ad libitum access to food and water. All procedures were approved by the Ethics Committee of Peking University People's Hospital. K7M2-WT cells, labeled with RFP and exhibiting high proliferative activity, were subcutaneously injected into the right flank of mice (3 × 107 cells/ml, 200 μl/mouse). Tumor dimensions (length [D] and width [d]) were measured using a vernier caliper, and tumor volume (V) was calculated as V = (D × d2)/2. Experiments commenced when tumors reached 100 mm3.
Fifteen tumor-bearing mice were randomized into three groups: (1) surgery alone, (2) surgery + PLGA-PEG-PLGA gel, and (3) surgery + PLGA-PEG-PLGA gel + UK14,304. To mimic post-surgical residual microtumors, ∼99 % of the tumor mass was resected, leaving ∼1 % residual tumor. Mice were anesthetized with isoflurane (1–3 % maintenance, 5 % induction), and PLGA-PEG-PLGA gels ± UK14,304 were implanted at the surgical site.
Tumor volume and body weight were monitored every 4 days. Tumor recurrence was assessed using a small-animal 3D fluorescence imaging system (IVIS Lumina Series III, PerkinElmer, USA). Mice were intraperitoneally injected with D-luciferin (15 mg/ml in DPBS; 100 μl/100 g) and imaged 15 min post-injection. Regions of interest were quantified as average radiance using Living Image software. Mice were euthanized if tumors exceeded 1000 mm3 or if signs of poor health were observed. Relative tumor volumes were calculated as the ratio of current to initial (Day 0) tumor volume. After 4 weeks, serum, tumor tissues, surrounding tissues, and major organs were collected for histopathological analysis using H&E staining.
2.8. Proteomic sequencing analysis
LC-MS/MS (Liquid Chromatography Tandem Mass Spectrometry, LC-MS/MS)-based proteomics analysis were conducted to discover differentially expressed proteins (DEPs). Subsequently, the DEPs were evaluated under the software of Metascape, STRING, Cytoscape, and databases of GO (Gene Ontology, GO), KEGG (Kyoto Encyclopedia of Genes and Genomes, KEGG), Reactome, and Wiki pathway.
2.9. Statistical analysis
Statistical analysis was conducted using GraphPad Prism software version 8.0 (San Diego, CA, USA). Student's t-test was used for comparisons between two groups, and one-way ANOVA followed by Tukey's correction was employed for comparisons among multiple groups. Statistical significance was defined as p < 0.05.
3. Result
3.1. In vitro cell assessment of UK14,304 compound
We performed a scratch test and a transwell assay to elucidate the influence of UK14,304 on the migratory and invasive behaviors of the OS cell lines in vitro (Fig. 1A and B). CCK-8 assay was utilized to detect the OS cell lines proliferative capacity in vitro. Our findings demonstrated that the UK14,304 did not dramatically decrease the viability of the cell lines (K7M2, 143b, Khos) at 0h, 24h, and 48h (Fig. 1C). The outcomes indicated no significant attenuation in cell migration (as shown in Fig. 1B and D) or invasion (as depicted in Fig. 1A and E) following treatment with UK14,304, compared to the control group.
Fig. 1.
In vitro anti-tumour effect of the UK14,304 in osteosarcoma cell lines. (A) The transwell assay of migration for OS cell lines (K7M2, 143b, Khos) after incubation with UK14,304 at 24h and 48h (n = 5 independent samples). (B) The wound test of invasion for OS cell lines (K7M2, 143b, Khos) after incubation with UK14,304 at 0h, 24h and 48h (n = 5 independent samples). (C) CCK-8 assay for the viability of OS cell lines (K7M2, 143b, Khos) after incubation with UK14,304 at 24h and 48h (n = 7 independent samples). (D) The statistical chart of the invasion test. (E) The statistical graph of the migration experiment. Data are represented as mean ± standard error of mean (mean ± SEM). Student's t-test was used for (C), (D), (E), while one-way ANOVA with Tukey's post hoc test was used for (D). ns: not significant.
The above results indicated that α2-AR agonists (UK14,304) may not dramatically compromise the biological functions of the OS cell lines in vitro.
3.2. In vivo post-surgical tumor recurrence suppression of the UK14,304/PLGA-PEG-PLGA implant
Although UK14,304 showed no significant effects on OS cell viability, migration, or invasion in vitro, we explored its anti-tumor potential in vivo using a UK14,304/PLGA-PEG-PLGA formulation. Two OS mouse models were employed: immunodeficient BALB/c nude mice and immunocompetent BALB/c mice. Tumors were grown to 100 mm3, surgically resected to mimic clinical primary OS removal, and treated post-operatively to evaluate local recurrence and therapeutic efficacy.
Surprisingly, the UK14,304/PLGA-PEG-PLGA formulation showed no significant effect on tumor growth in the tumor formation model of BALB/c nude mice (Fig. 2A and B). However, in a BALB/c model with luciferase-expressing K7M2 cells, distinct therapeutic outcomes emerged. While rapid tumor progression was observed in both the surgery-only and surgery + PLGA-PEG-PLGA groups, mice treated with UK14,304/PLGA-PEG-PLGA exhibited markedly reduced bioluminescence signals (Fig. 2C, right panel), indicating suppressed residual tumor burden. These findings suggest that UK14,304/PLGA-PEG-PLGA may not directly inhibit tumor growth but effectively prevents post-surgical recurrence in immunocompetent models.
Fig. 2.
In vivo anti-tumour studies of the UK14,304 loaded into the PLGA-PEG-PLGA hydrogel in the models of BALB/c nude and mice. (A) Digital images at day 24 in BALB/c nude model (n = 5 animals per group). (B) Relative tumor volume in BALB/c nude (n = 5 animals per group). (C) IVIS images of tumor-bearing mice right before surgical removal of the solid tumors and after accepting different treatments for 4 and 24 days (n = 3 animals per group). (D) Digital images at day 24 in BALB/c model (n = 5 animals per group). (E) The relative tumor growth curves in different groups of tumor-bearing mice after various treatments (n = 5 animals per group). (F) Tumor weight of the resected tumors in different groups of tumor-bearing mice at day 24 (n = 5 animals per group). (G) The body weight of each group at day 24 (n = 5 animals per group). All p values were determined by one-way ANOVA with Tukey's post hoc test. ∗∗p < 0.01, ns: not significant.
As exhibited in Fig. 2, tumors in control groups exhibited rapid growth, while the UK14,304/PLGA-PEG-PLGA treatment group demonstrated significantly slower tumor progression (Fig. 2E). No significant differences in body weight were observed among groups (Fig. 2F), suggesting the treatment was well-tolerated. At the study endpoint, dissected tumors further corroborated these findings (Fig. 2D and G).
The anti-tumor effects were not mediated by direct engagement of α2-AR agonists with OS cells, as in vitro assays revealed no significant impact on OS cell growth, migration, or invasion.
3.3. In vivo biosafety of UK14,304/PLGA-PEG-PLGA implant
To assess the potential systemic toxicity and biocompatibility of UK14,304/PLGA-PEG-PLGA implant, a comprehensive in vivo assessment was conducted. The results for H&E pathology analysis, as depicted in Fig. 3A, disclosed no significant pathological alterations in the major organs, including the heart, lung, liver, spleen, and kidney, across the three groups. These results implied that the compound does not exert any significant detrimental effects on normal tissues. Furthermore, on the final day of the treatment regimen, the biochemical blood tests were conducted to further probe the biosafety of implant. Specifically, ALP (Alkaline Phosphatase, ALP) and ALT (Alanine Transaminase, ALT) levels were assayed as diagnostic indicators of liver function. BUN (Blood Urea Nitrogen, BUN) was used to assess the kidney function. ALB (Albumin, ALB) was determined as an indicator of the nutritional status. PCT (Procalcitonin, PCT) was conducted to evaluated the levels of systemic inflammatory response. As illustrated in Fig. 3B–F, there were no dramatic differences between the three groups. The above results indicated that UK14,304/PLGA-PEG-PLGA compound lacks any discernible systemic adverse effects or toxicity.
Fig. 3.
In vivo toxicity of UK14,304+PLGA-PEG-PLGA. (A) H&E staining of the major organ (n = 5 animals per group). (B–F) Blood biochemical indexes of tumor-bearing BALB/c mice in different treatment groups (n = 5 animals per group). All p values were determined by one-way ANOVA with Tukey's post hoc test. ns: not significant.
3.4. The anti-tumor mechanism of α2-AR agonists
Next, aiming to elucidate the mechanism of anti-tumor effect, we performed proteomic sequencing of the tumor and the TME (tumor microenvironment, TME) surrounding the tumor. A total of 930 differential proteins were identified, and the “limma” package was utilized for further analysis. |Log2FC| ≥ 0.58 and the p value ≤ 0.05 were applied as the screening criteria for DEPs. Ultimately, 131 DEPs were subjected to a comprehensive enrichment analysis utilizing the R package (version 3.6.3), along with software applications such as Metascape, STRING, Cytoscape, and databases including GO, KEGG, Reactome, and Wiki pathway.
Fig. 4A and B depicted that the majority of the DEPs were predominantly associated with the cytoplasm and the cell membrane. Specifically, Fig. 4B illustrated that 558,37.6 % of the DEPs were cytoplasmically localized, whereas 408,27.49 % were situated within the cytoplasm, which indicated that the anti-tumor mechanism of UK14,304 is primarily mediated through modulation of cytoplasmic and/or membrane-associated signaling pathways.
Fig. 4.
The enrichment analysis of DEPs according to the metascape software. (A, B) Subcellular localization of DEPs. (C) Bar graph of enriched terms across input gene lists, colored by p - values. (D) The top-level Gene Ontology biological processes can be viewed. (E) Summary of enrichment analysis in TRRUST.
Next, the DEPs enrichment analysis was performed under the Metascape software. As shown in Fig. 4C, “GO:0031012: extracellular matrix”, “GO:0003925: G protein sctivity”, and “GO:0050865:regulation of cell activation” were all significantly enriched on top terms, which indicated that these signaling pathways participate in the anti-tumor mechanism. Concurrently, our analysis highlighted the significant enrichment of “R-MMU-111447: Activation of BAD and its subsequent translocation to the mitochondria," implying a potential role for this pathway in the anti-tumor activity of UK14,304. The top-level Gene Ontology biological processes can be observed in Fig. 4D, and “GO:0002376: immune system process” ranked at the top, although such as “multicellular organismal process”, “biological regulation”, “response to stimulus”, “cellular process”, and “metabolic process” also played a very important role in the process of anti-tumor effect with the UK14,304. In addition, we found that SP1, IRF1, USF2, USF1, HDAC1 were the most important transcriptional regulatory factors (Fig. 4E).
Additionally, to thoroughly investigate the regulatory mechanisms of the DEPs, we performed GO, KEGG, Reactome, and Wiki pathway analysis. GO enrichment analysis exhibited that the DEPs were enriched in “T cell migration”, “regulation of lymphocyte activation”, “regulation of T cell activation”, and “positive regulation of T cell activation"(Fig. 5A). KEGG pathway analysis showed that the DEPs were enriched into the “Fc gamma R-mediated phagocytosis”, “Rap 1 signaling pathway”, which are also involved in the immune response (Fig. 5B). Meanwhile, Reactome analysis revealed that “Rap 1 signaling”, “MHC class Ⅱ antigen presentation”, and “adaptive immune system” were highly enriched (Fig. 5C). Wiki pathway displayed that “comprehensive IL 17A signaling” was related with the anti-tumor effect of α2-AR agonists(Fig. 5D). The enrichment of these signaling pathways indicated that the anti-tumor mechanism of α2-AR agonists is intricately linked to T cell activation and immune response pathways, encompassing both innate and adaptive immune system components.
Fig. 5.
Proteomic enrichment analysis of DEGs. (A) GO analysis. (B, C) KEGG analysis. (D) Reactome analysis. (E) Wiki pathway analysis.
Protein–protein interaction network and MCODE components were performed by the Metascape software. As exhibited in Fig. 6, MCODE_1 Description: anti binding, focal adhesion, and cell-substrate junction; MCODE_2 Description: Chk1/Chk2(Cds1) mediated inactivation of Cyclin B: Cdk1 complex, Activation of BAD and translocation to mitochondria, Activation of BH3-only proteins; MCODE_3 Description: high-density lipoprotein particle, lipoprotein particle, plasma lipoprotein particle; MCODE_4 Description: Membrane Trafficking, Vesicle-mediated transport; MCODE_5 Description: Salmonella infection - Mus musculus (house mouse), Membrane Trafficking, Vesicle-mediated transport. These clustered five MCODE indicated that the above biological signaling was related to the anti-tumor process.
Fig. 6.
Network of enriched terms. (A) Colored by cluster ID, where nodes that share the same cluster ID are typically close to each other. (B and C) Protein–protein interaction network and MCODE components identified in the gene lists.
CD8+ T cells act as pivotal regulators within numerous immune signaling pathways and are integral to the prognostication of the tumor microenvironment. Therefore, we pursued an in-depth investigation into the possible interplay between CD8+ T cells and the anti-tumor efficacy of α2-AR agonists. As shown in Fig. 7A, up-regulated protein MHC-Ⅰ mainly acted on the TCR for cytotoxic T cells, which is also called CD8+ T cells. MHC-Ⅱ mainly affected the TCR for Helper T cells (Th cell). Surprisingly, we found the ITGAL protein as the central modulatory element within the immune system, pivotal to the anti-tumor mechanism of UK14,304. Furthermore, the PPI network disclosed that the proteins of MSN, TOLLIP, and Rdh7 were notably enriched, highlighting their significance as core components of the immune response (Fig. 7B).
Fig. 7.
The enrichment analysis of DEGs. (A) The KEGG map of the enrichment of DEGs. (B) The PPI network of the enrichment of DEPs by STRING software and Cytoscape software.
In sum, analysis of the KEGG map revealed that the ITGAL protein is a crucial regulatory factor in the adaptive immune process, particularly for the CD8+ T cells. This finding suggested that ITGAL likely exerts an essential role in the anti-tumor mechanism mediated by α2-AR agonists.
3.5. UK14,304/PLGA-PEG-PLGA may undergoes LLPS in response to the TCR signaling pathway
In the field of immunology, LLPS has been identified in both the cell surface receptor pathways, including the TCR [20,21] and the BCR pathways [22,23], and the cytosolic signaling pathways, such as RIG-1 [24], cGAS-STING [25,26], and NF-κB pathway [27]. So, we predicted of the natural disordered regions for SP1, USF1, USF2, IRF1, TOLLIP, HDAC1, MSN, and ITGAL on the tutorial of PONDR® (Fig. 8 and Table 1) and PhaSePred (Fig. 9 and Table 2). As showed in Fig. 8 and Table 1, the average scores of VLXT and VL3 for SP1, USF1/2, TOLLIP, IRF1 ranked in the top. As exhibited in Fig. 9 and Table 2, SP1, HDAC1, and MSN ranked in the top. Additionally, radar maps refer to the bigger the number, the higher the ranking (SP1, USF1/2, IRF1, TOLLIP, HDAC1, MSN and ITGAL). IF (immunofluorescence, IF) image from the human protein atlas refer to intracellular form of the protein (SP1, USF1/2, IRF1, TOLLIP, HDAC1 and MSN), which suggested that the droplet-like morphology was more prone to phase separation.
Fig. 8.
Predictor of natural disordered regions for SP1, USF1, USF2, IRF1, TOLLIP, HDAC1, MSN, and ITGAL on the tutorial on PONDR®.
Table 1.
Predictor for phase-separating proteins of PONDR®.
| UniProt | Score (PS-Self/PS-Part) | Score (8-feature) | Rank (8-feature) | Score (10-feature) | Rank (10-feature) |
|---|---|---|---|---|---|
| P08047 | PS-Self score | 0.929 | 0.993 | 0.937 | 0.996 |
| PS-Part score | 0.792 | 0.954 | 0.883 | 0.965 | |
| P22415 | PS-Self score | 0.417 | 0.788 | 0.097 | 0.594 |
| PS-Part score | 0.413 | 0.643 | 0.220 | 0.596 | |
| Q15853 | PS-Self score | 0.422 | 0.790 | 0.122 | 0.653 |
| PS-Part score | 0.367 | 0.602 | 0.364 | 0.706 | |
| P10914 | PS-Self score | 0.165 | 0.601 | 0.132 | 0.670 |
| PS-Part score | 0.376 | 0.609 | 0.325 | 0.681 | |
| Q9H0E2 | PS-Self score | 0.067 | 0.292 | 0.313 | 0.786 |
| PS-Part score | 0.265 | 0.505 | 0.243 | 0.617 | |
| Q13547 | PS-Self score | 0.867 | 0.980 | 0.898 | 0.981 |
| PS-Part score | 0.762 | 0.937 | 0.894 | 0.971 | |
| P26038 | PS-Self score | 0.750 | 0.947 | 0.875 | 0.970 |
| PS-Part score | 0.623 | 0.835 | 0.876 | 0.961 | |
| P20701 | PS-Self score | 0.083 | 0.414 | 0.058 | 0.252 |
| PS-Part score | 0.381 | 0.614 | 0.102 | 0.438 |
Fig. 9.
Predictor for phase-separating proteins of PhaSePred. Ranks of the protein in the corresponding organism, the bigger the number, the higher the ranking (SP1, USF1/2, IRF1, TOLLIP, HDAC1, MSN and ITGAL). Immunofluorescence image from the human protein atlas (SP1, USF1/2, IRF1, TOLLIP, HDAC1 and MSN).
Table 2.
Predictor for phase-separating proteins of PhaSePred.
| Gene ID | Approved symbol | Approved name | NCBI Gene | UniProt | Score VLXT | Score VL3 |
|---|---|---|---|---|---|---|
| ENSG00000185591 | SP1 | Sp1 transcription factor | 6667 | P08047 | 0.7381 | 0.6186 |
| ENSG00000158773 | USF1 | upstream transcription factor 1 | 7391 | P22415 | 0.5678 | 0.6308 |
| ENSG00000105698 | USF2 | upstream transcription factor 2, c-fos interacting | 7392 | Q15853 | 0.5828 | 0.6334 |
| ENSG00000125347 | IRF1 | interferon regulatory factor 1 | 3659 | P10914 | 0.4954 | 0.5482 |
| ENSG00000078902 | TOLLIP | toll interacting protein | 54472 | Q9H0E2 | 0.5036 | 0.3537 |
| ENSG00000116478 | HDAC1 | histone deacetylase 1 | 3065 | Q13547 | 0.2565 | 0.3571 |
| ENSG00000147065 | MSN | moesin | 4478 | P26038 | 0.2702 | 0.2586 |
| ENSG00000005844 | ITGAL | integrin subunit alpha L | 3683 | P20701 | 0.3254 | 0.2861 |
In short, these potential candidates are of high relevance in the process of LLPS and further trigger the TCR signaling pathway.
3.6. Gene expression profiling interactive analysis and Kaplan–Meier survival analysis
Subsequently, the Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression Project (GTEx) databases were conducted to further evaluate the above mentioned significant genes. As shown in Fig. 10A and B, the genes: MSN, TOLLIP, ITGAL, SP1, IRF1, USF1, USF2, HDAC1 were all over-expressed. Kaplan–Meier survival analysis were performed by the R Version 3.3.2 “survival” package. Fig. 10C depicted that differential expressed genes: MSN, TOLLIP, ITGAL, IRF1, and HDAC1 had clinical relevance.
Fig. 10.
Analysis of DEGs under TCGA, GTEx databases. (A) Transcripts per million (TPM). (B) Boxplots of DEGs. (C) KM analysis of DEGs with overall survival.
4. Discussion
α2-ARs signal through the Gi pathway, inhibiting adenylate cyclase to reduce cAMP levels and PKA activity [13]. While their role in the sympathetic nervous system is well-established [13], extra-neuronal functions of α2-ARs remain poorly understood. Emerging evidence suggests anti-cancer properties of α2-AR agonists. Maccari et al. reported α2-AR stimulation inhibits melanoma growth in murine models [13], while Matarrese et al. demonstrated that agonists like clonidine suppress cancer cell proliferation. The crosstalk between β2-AR and α2-AR signaling pathways modulates B16F10 cell proliferation, offering potential therapeutic strategies for melanoma [28]. α2-AR agonists have shown anti-neoplastic effects in multiple cancer models [29].
Recent studies highlight complex interactions between the immune system and autonomic nervous system in cancer [[30], [31], [32], [33], [34]]. While β2-adrenergic signaling typically suppresses anti-tumor immunity [[35], [36], [37], [38]], our findings revealed an opposing role for α2-ARs in enhancing immune responses. Evidence suggests α-adrenergic signaling restricts MDSC (Myeloid-Derived Suppressor Cell, MDSC) growth, with chemical sympathectomy impairing anti-tumor immunity [34].
Our study demonstrated that α2-AR agonists lack direct tumor-promoting effects on OS cell lines or tumor volume in immunodeficient BALB/c nude mice, whereas they significantly modulated tumor progression in immunocompetent BALB/c mice. This tumor-suppressive effect was mediated via immune regulation rather than direct neoplastic targeting. Integrated proteomics and bioinformatics analyses (Metascape, Cytoscape, GO, KEGG, Reactome, WikiPathways) of TME datasets revealed pronounced enrichment of immune activation pathways, particularly CD8+ T cell recruitment and functional activation. Key regulators identified include transcription factors (SP1, IRF1, USF1/2, HDAC1), effector proteins (MSN, TOLLIP, RDH7), and the central hub protein ITGAL, which orchestrates CD8+ T cell activity and TCR signaling. Computational modeling (PONDR®, STRING, PPI) further predicted involvement of these candidates in LLPS within TCR complexes. Concurrently, autophagy and apoptosis pathways were markedly enriched, suggesting crosstalk between immunomodulation and tumor cell death mechanisms underpinning α2-AR agonist efficacy.
Notably, while α2-AR agonists exhibit established clinical liabilities (hypertension, hyperkalemia, organotoxicity) at high doses or with prolonged use, our findings highlight their therapeutic potential in OS through immune context-dependent tumor suppression. Further validation of these mechanisms is warranted to advance translational applications.
5. Conclusion
In conclusion, our findings regarding the anti-tumor role of α2-AR agonists represent only a preliminary insight into a much broader and complex mechanism. To elucidate the precise antineoplastic mechanisms, a robust and expansive scientific inquiry must be undertaken in future studies. Additionally, given the intricate interplay and cross-regulation among the immunity, apoptosis, and autophagy systems, it would be intriguing and compelling to explore the extra-neuronal biological function and mechanism, particularly for α2-AR. In conclusion, we discovered the potent therapeutic effectiveness of α2-AR agonists in OS mice model. We believe that this strategy has tremendous potential for clinical translation.
6. Limitations of the study
Our study acknowledges several technical limitations. Firstly, the mechanism by which α2-AR agonists exert their anti-tumor effects, particularly in relation to CD8+ T cell activation, remains unclear. It is uncertain whether this effect is direct or indirect, or whether it involves the stimulation of macrophages to recruit and activate CD8+ T cells within TME. Secondly, while our bioinformatics analysis identified several transcription factors and potential proteins, including those predicted to be involved in phase-separation, these findings require further experimental validation. Future research should focus on synthesizing antibodies that target specific epitopes and validating them through ELISA assays, flow cytometry, immunofluorescence analyses of tumor-infiltrating lympocytes, especially CD8+ T cells, as well as elucidating the precise mechanisms of action and verifying the identified proteins and transcription factors using direct experimental approaches.
Declaration of Generative AI in scientific writing
No generative artificial intelligence (AI) or AI-assisted technologies were used in the preparation of this manuscript.
Authors’ contributions
Conceptualization, YHP; methodology, ZW, YSZ, HJL; software, ZYW, BYW, LXC; formal analysis, YHP, CWC, ZJJ; investigation, ZW; ZJJ, SYL, LXC; writing – original draft preparation, YHP; writing – review and editing, ZW, HJL, BYW, SYL; visualization, LXC; supervision, WG and MX; funding acquisition, MX.
Funding
This work was supported by the National Key Research and Development Program of China (2023YFB4706305) and the National Defense Science and Technology Excellence Youth Science Fund Program (2022-JCJQ-ZQ-018).
Declaration of competing interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Acknowledgments
We would like to thank Editage (www.editage.cn) for English language editing.
Contributor Information
Wei Guo, Email: bonetumour_guo@bjmu.edu.cn.
Meng Xu, Email: profxum301@163.com.
Data availability
The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding authors.