Abstract
Circular single-stranded DNA (cssDNA), an emerging nucleic acid vector, exhibits significant clinical potential for treating genetic disorders, enabling gene editing, and advancing oncotherapy. Its unique attributes, including high stability, structural simplicity, conformational flexibility, and low molecular mass, establish it as a promising gene therapy tool. Our study reveals that cssDNA demonstrates superior expression efficiency over conventional plasmids across diverse tumor cell lines. Notably, cssDNA expression is enhanced under certain tumor microenvironment (TME) conditions (glucose deficiency, glutamine deficiency and hypoxia) compared to normal condition. Mechanistically, these TME conditions induce significant cell cycle perturbations, particularly pronounced G1 arrest. Intriguingly, transfected cssDNA expression peaks during the late G2/M phase, immediately preceding entry into the G1 phase. We further identify S-phase kinase-associated protein 2 (SKP2) as a critical regulator of cssDNA expression under TME conditions. SKP2 inhibition directly or indirectly notably enhances the expression levels of cssDNA. These findings confirm cssDNA’s advantages as a gene expression vector and how specific TME conditions modulate its expression via cell cycle and SKP2-dependent mechanisms in vitro. This work provides a scientific foundation for cssDNA-based cancer therapy and opens new avenues for future clinical translation.
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Introduction
Circular DNA, characterized by its covalently closed topology, represents a distinct structural departure from linear DNA and has garnered considerable interest as a versatile platform for non-viral gene delivery. Beyond its role in genetic information transmission1,2,3,4, circular DNA serves as a key non-viral vector for gene cloning and expression5,6,7,8. Current circular DNA vectors comprise two categories: plasmid-based double-stranded DNA (dsDNA) and circular single-stranded DNA (cssDNA)9. CssDNA exhibits distinctive properties as a non-viral vector, including high nuclease stability, synthetic accessibility, conformational flexibility, and low molecular mass, accelerating its adoption in transgene expression and therapeutic genome editing. In structural DNA nanotechnology, cssDNA (such as M13 bacteriophage genomic deoxyribonucleic acid and other synthetically engineered single-stranded DNA) enables programmable nanostructures10,11,12,13 for applications ranging from molecular computation14,15,16,17, to nanomedicine18,19,20,21,22,23,24. Critically, due to its unique functional mechanisms, cssDNA has emerged as a promising non-viral vector for regulating protein expression through multiple mechanisms: (I) Functioning as expression vectors to amplify therapeutic genes, thereby compensating for genetic deficiencies or enhancing gene functionality7; (II) Serving as gene editing donor template for precise gene correction with high efficiency and minimal cytotoxicity25,26,27,28; (III) Acting as miRNA sponges to silence or interfere with disease-associated gene expression29,30; (IV) Targeting oncogenes for cancer therapy6,30,31. Unlike plasmids, cssDNA produced via the pScaf phagemid system lacks bacterial propagation sequences (e.g., antibiotic resistance genes and replication origins)32, eliminating risks of horizontal gene transfer and innate immune activation—key advantages for clinical translation. These characteristics position cssDNA at the forefront of non-viral precision therapeutics, combining targeted delivery with minimal off-target effects.
Cancer, characterized by dysregulated cellular proliferation, remains a major focus in medical research33. Beyond malignant cells themselves, the tumor microenvironment (TME) plays an increasingly recognized role in tumor progression. The TME—comprising the peritumoral stromal cells, extracellular matrix, vasculature, immune cells and various cytokines—is now acknowledged as a critical determinant in the genesis and progression of cancer34,35. The dynamics within the TME, including immune modulation, angiogenesis, extracellular matrix remodeling, and cytokine interactions, profoundly influence tumor growth, metastatic dissemination, and therapeutic resistance36,37. The TME exhibits characteristic features such as nutrient deprivation, acidosis, hypoxia, oxidative stress, altered glutathione metabolism, and dysregulated enzyme expression38,39,40. Thorough investigation of these microenvironmental parameters and their therapeutic implications is essential. Understanding their mechanistic roles enables the development of more effective cancer management strategies, providing innovative approaches for the treatment and prevention of cancer.
In this study, we performed comparative analysis of the expression of various forms of circular DNA in some mammalian cells, revealing that cssDNA exhibits superior expression efficiency. Subsequently, we investigated the influence of specific TME conditions on cssDNA expression and underlying mechanisms in vitro, focusing on glucose deficiency, glutamine deficiency, and hypoxia. Mechanistically, our findings demonstrate that these TME conditions modulate the cell cycle via S-phase kinase-associated protein 2 (SKP2) signaling pathway thereby consequently enhancing cssDNA expression. This work not only underscores the potential of cssDNA as a potent gene therapy vector, but also elucidates how the tested TME conditions affect cssDNA expression and its underlying mechanisms, highlighting the sensitivity of cssDNA to the nuanced and dynamic within the TME conditions. This academic refinement aims to articulate the significance of our findings within the broader context of cancer biology and gene therapy, emphasizing the need for a deeper understanding of the TME’s role in modulating gene expression vectors and its implications for developing novel therapeutic strategies.
Results
cssDNA(+) exhibits superior expression compared to other circle DNAs in mammalian cell lines
To assess the differential expression performance of various circular DNA forms, we engineered two distinct plasmids, pScaf-Luciferase(+)7 (Fig. 1A, left) and pScaf-Luciferase(-) (Fig. 1B, left). Employing the pScaf phagemid method32, we derived css-Luciferase(+) and css-Luciferase(-), two forms of circular single-stranded DNA (cssDNA). Css-Luciferase(+) presented the expression cassette encoding the luciferase sense strand from 5’ to 3’ (Fig. 1A, right), in contrast, css-Luciferase(-) contained the complementary sequence of the expression cassette encoding luciferase antisense strand in the direction of 3’ to 5’ (Fig. 1B, right). These cssDNAs contain only the promoter and coding sequences necessary for gene expression, omitting bacterial backbone sequences typically required for plasmid production, such as antibiotic resistance genes and replication origins32. To evaluate the impact of redundant sequences on cssDNA expression, we constructed another cssDNA, cssUC18-Luciferase(+) (Fig. 1C, right), which shares sequence identity and length with its corresponding plasmid, pUC18-Luciferase(+) (Fig. 1C, left)41. Unlike css-Luciferase(+), it retains the bacterial backbone sequences from the plasmid32,41. These diverse circular DNA forms were characterized using agarose gel electrophoresis (Fig. 1D).
Characterization and expression of different types of circular DNA. (A) Design schematic of pScaf-Luciferase(+) and css-Luciferase(+). (B) Design schematic of pScaf-Luciferase(-) and css-Luciferase(-). (C) Design schematic of pUC18-Luciferase(+) and cssUC18-Luciferase(+). (D) The 1% agarose gel analysis of pScaf-Luciferase(+) (pScaf-Luci(+)), pScaf-Luciferase(-) (pScaf-Luci(-)), css-Luciferase(+) (css-Luci (+)), css-Luciferase(-) (css-Luci(-)) and cssUC18-Luciferase(+) (cssUC18-Luci(+)). (E) Gene expression of equal molar mass of pScaf-Luciferase(+), pScaf-Luciferase(-), css-Luciferase(+), css-Luciferase(-) and cssUC18-Luciferase(+) in different cell lines. All luciferase activity were respectively normalized to the value of cells transfected with pScaf-Luciferase(+). (F) Design schematic of pScaf-EGFP(+) and css-EGFP(+). (G) Design schematic of pScaf-EGFP(-) and css-EGFP(-). (H) The 1% agarose gel analysis of pScaf-EGFP(+), css-EGFP(+), pScaf-EGFP(-) and css-EGFP(-). (I) The percentage of EGFP + cells in total MCF7 cells transfected with equal molar mass of pScaf-EGFP(+), css-EGFP(+), pScaf-EGFP(-) or css-EGFP(-) after 12, 24–48 h using Lipo2000 by flow cytometry. Data are shown as mean ± SD for n = 3 biologically independent experiments. Statistical comparisons were performed using one-way ANOVA followed by Tukey’s post hoc test. Asterisks indicate statistically significant differences. (*p < 0.05, ** p < 0.01, *** p < 0.001, ns: not significant).
We used Lipofectamine™ 2000 transfection reagent (Lipo2000) to transfect the tested cells with equal molar mass of pScaf-Luciferase(+), pScaf-Luciferase(-), css-Luciferase(+), css-Luciferase(-) and cssUC18-Luciferase(+), respectively, and the luciferase activity was measured after 24 h of culturing. As shown in Fig. 1E, in MCF7 cells, the luciferase activity of css-Luciferase(+) was 13.82-fold (p < 0.01) higher than that of pScaf-Luciferase(+). By contrast, pScaf-Luciferase(-), css-Luciferase(-) and cssUC18-Luciferase(+) showed 0.56-fold (ns), 4.22-fold (p < 0.01) and 9.68-fold (p < 0.01) activities relative to pScaf-Luciferase(+), respectively. A similar trend was observed across all other cell lines tested, with css-Luciferase(+) exhibiting the highest luciferase activity compared to other circular DNA forms.
To determine whether cssDNA(+) confers a similar advantage in expressing other proteins, we constructed pScaf-EGFP(+) (Fig. 1F, left), pScaf-EGFP(-) (Fig. 1G, left), css-EGFP(+) (Fig. 1F, right), and css-EGFP(-) (Fig. 1G, right). css-EGFP(+) contained the enhanced green fluorescent protein (EGFP) expression cassette in the sense orientation, whereas css-EGFP(-) harbored the antisense sequence. These cssDNAs were characterized and compared with their respective plasmids by agarose gel electrophoresis (Fig. 1H). We selected MCF7 cells, which showed the highest expression of css-Luciferase(+), and transfected them with pScaf-EGFP(+), pScaf-EGFP(-), css-EGFP(+), and css-EGFP(-), respectively. The percentage of EGFP + cells was evaluated at 12, 24, and 48 h post-transfection by flow cytometry to assess the proportion of cells exhibiting fluorescence. As shown in Fig. 1I, the percentage of EGFP + cells for pScaf-EGFP(+), pScaf-EGFP(-), css-EGFP(+), and css-EGFP(-) was 8.59%, 13.77%, 16.27%, and 16.7% at 12 h; 23.40%, 24.80%, 35.37%, and 30.83% at 24 h; and 18.80%, 20.87%, 29.80%, and 27.57% at 48 h, respectively. Css-EGFP(+) consistently yielded the highest proportion of EGFP + cells at all time points.
These results suggest that cssDNA(+) may confer superior protein expression capabilities compared to other circular DNAs.
TME conditions promote cssDNA(+) expression
Previous studies demonstrated the therapeutic potential of cssDNA in tumors6,30,31. However, the tumor growth and progression are accompanied by a series of abnormal microenvironmental features, such as hypoxia, glucose deficiency, glutamine deficiency, low pH, oxidative stress, elevated glutathione concentration and overexpression of specific enzymes38. Among these, glucose deficiency, glutamine deficiency and hypoxia are the key features of the TME. Therefore, we mimicked these distinct TME conditions in vitro—specifically glucose deficiency ((-)Glu), glutamine deficiency ((-)Gln) and hypoxia—to investigate their effects on cssDNA(+) in the context of tumor therapy.
After 4 h of css-EGFP(+) delivery to HCCLM3 cells, the cells were cultured under normal, glucose-deficient, glutamine-deficient, or hypoxic conditions, respectively. After 24 h of treatment under different conditions, EGFP expression was assessed by fluorescence microscopy (Fig. 2A) and quantified by flow cytometry (Fig. 2B–D). We found that the expression of css-EGFP(+) in cells cultured under glucose deficiency, glutamine deficiency, or hypoxia was slightly higher compared to those under normal condition (Fig. 2A). The percentage of EGFP + cells increased from 3.57% under normal condition to 5.18% (p < 0.01) under glucose deficiency, 4.17% (p < 0.01) under glutamine deficiency, and 5.35% (p < 0.001) under hypoxia (Fig. 2C). Correspondingly, the mean fluorescence intensity per cell increased by 1.60-fold (p < 0.001), 1.21-fold (p < 0.05), and 1.32-fold (p < 0.05) under glucose deficiency, glutamine deficiency, and hypoxia, respectively (Fig. 2D). These results indicate a modest yet statistically significant enhancement in both the proportion of EGFP + cells and fluorescence intensity under TME conditions. Consistently, css-EGFP(+) expression was elevated at both the mRNA (Fig. 2E) and protein levels (Fig. 2F). Overall, glucose-deficient, glutamine-deficient, and hypoxic conditions promoted css-EGFP(+) expression relative to normal condition.
The effects of different TME conditions on the expression of css-EGFP(+). 4 h after transfection with css-EGFP(+) by Lipo2000, HCCLM3 cells were cultured for 24 h under normal, glucose-deficient ((-)Glu), glutamine-deficient ((-)Gln), or hypoxic conditions, respectively, cells were collected and total protein or RNA extracted. (A) Representative microscopy images were assessed by light microscopy and fluorescence microscopy. Scale bar: 500 μm. (B) Diagrammatic dot-plots for assessing EGFP expression in HCCLM3 cells by flow cytometry. (C and D) The percentage of EGFP + cells and mean fluorescence intensity per cell in HCCLM3 cells cultured under different conditions. All fluorescence intensities were normalized to the value of HCCLM3 cells transfected with css-EGFP(+) and cultured under normal condition. (E) qPCR analysis showing the mRNA expression of css-EGFP(+). (F) Total cellular proteins were collected and subjected to Western blot with the antibodies against EGFP and β-actin. FACS plots are representative of one of n = 3 biologically independent experiments. Western blot images are representative of one of n = 3 biologically independent experiments. Data are shown as mean ± SD for n = 3 biologically independent experiments. Statistical comparisons were performed using one-way ANOVA followed by Tukey’s post hoc test. Asterisks indicate statistically significant differences. (*p < 0.05, ** p < 0.01, *** p < 0.001).
The enhancing effect of TME conditions on cssDNA(+) expression has potentially broad applicability
To investigate whether TME conditions also contribute to the expression of css-EGFP(+) across diverse tumor cell lines, Huh7, HCT116, SW480, and BT474 cells were transfected with css-EGFP(+), and both cells and total RNA were collected 24 h later under normal, glucose-deficient, glutamine-deficient, or hypoxic conditions. The percentage of EGFP + cells and mean fluorescence intensity per cell were quantified by flow cytometry. FACS (fluorescence-activated cell sorting) analysis revealed that all four cell lines exhibited increased css-EGFP(+) expression under TME conditions relative to normal culture, with the magnitude of enhancement varying among cell lines (Fig. 3A, B). Specifically, SW480 cells exhibited the largest increases in both the percentage of EGFP + cells and mean fluorescence intensity per cell under glutamine deficiency, whereas Huh7 cells displayed more modest enhancement. At the transcriptional level, glucose deficiency, glutamine deficiency, and hypoxia significantly upregulated css-EGFP(+) mRNA in all tested lines, with the strongest induction observed in SW480 cells (Fig. 3C). These findings align with observations in HCCLM3 cells, indicating that these three TME conditions may enhance css-EGFP(+) expression across multiple tumor types, although the extent of responsiveness is cell line-dependent.
The enhancing effect of TME conditions on cssDNA(+) expression has potentially broad applicability. (A–C) 4 h after transfection with css-EGFP(+), various mammalian cells (Huh7, HCT116, SW480, BT474 cell lines, respectively) were cultured for 24 h under normal, glucose-deficient, glutamine-deficient, or hypoxic conditions, respectively, cells were collected and total RNA extracted. (A,B) The percentage of EGFP + cells and mean fluorescence intensity per cell of css-EGFP(+). All fluorescence intensities were normalized to the value of the corresponding mammalian cell transfected with css-EGFP(+) and cultured under normal condition. (C) qPCR analysis showing the mRNA expression of css-EGFP(+). (D) Design schematic of pScaf-EF1α-EGFP(+) and css-EF1α-EGFP(+). (E) Design schematic of pScaf-EF1α-mIL12(+) and css-EF1α-mIL12(+). (F) The 1% agarose gel analysis of pScaf-EF1α-EGFP(+) and css-EF1α-EGFP(+). (G) The 1% agarose gel analysis of pScaf-EF1α-mIL12(+) and css-EF1α-mIL12(+). (H-K) 4 h after transfection with css-EF1α-EGFP(+) or css-EF1α-mIL12(+), HCCLM3 cells were cultured for 24 h under normal, glucose-deficient, glutamine-deficient, or hypoxic conditions, respectively, cells were collected and total RNA extracted. (H and I) The percentage of EGFP + cells and mean fluorescence intensity per cell of css-EF1α-EGFP(+). All fluorescence intensities were normalized to the value of HCCLM3 cells transfected with css-EF1α-EGFP(+) and cultured under normal conditions. (J and K) qPCR analysis showing the mRNA expression of css-EF1α-EGFP(+) or css-EF1α-mIL12(+). Data are shown as mean ± SD for n = 3 biologically independent experiments. Statistical comparisons were performed using one-way ANOVA followed by Tukey’s post hoc test. Asterisks indicate statistically significant differences. (*p < 0.05, ** p < 0.01, *** p < 0.001).
Studies have shown that different promoters can differentially affect gene expression42,43,44,45,46,47,48,49. To investigate whether TME-enhanced cssDNA(+) expression is promoter-dependent, we constructed a new plasmid, pScaf-EF1α-EGFP(+), in which the CMV promoter was replaced with the EF-1α promoter (Fig. 3D, left) and generated the corresponding cssDNA, css-EF1α-EGFP(+) (Fig. 3D, right). Css-EF1α-EGFP(+) and its corresponding plasmid were characterized by gel electrophoresis (Fig. 3F). We then transfected css-EF1α-EGFP(+) into HCCLM3 cells and evaluated its expression under normal, glucose-deficient, glutamine-deficient, and hypoxic conditions. Consistent with the results obtained using the CMV promoter, the TME conditions significantly increased the percentage of EGFP + cells (Fig. 3H), the mean fluorescence intensity per cell (Fig. 3I), and mRNA expression (Fig. 3J) of css-EF1α-EGFP(+). Although these findings suggests that the TME-enhanced expression may be promoter-independent, it is important to noted that both CMV and EF-1α promoters are strong viral promoters. Therefore, further studies using a broader range of promoter classes, such as tissue-specific or inducible promoters, are required to determine the generalizability of this effect across diverse promoters.
To evaluate whether cssDNA(+) exhibits a comparable effect when expressing other proteins, we constructed a new cssDNA, css-EF1α-mIL12(+) (Fig. 3E, right). We characterized it and its corresponding plasmid (Fig. 3E, left) by agarose gel electrophoresis (Fig. 3G). We then assessed the impact of glucose deficiency, glutamine deficiency, and hypoxia on css-EF1α-mIL12(+) expression in HCCLM3 cells. Consistent with previous observations, these TME conditions significantly enhanced the expression of css-EF1α-mIL12(+) at the mRNA level (Fig. 3K).
In summary, the TME conditions can promote the expression of cssDNA(+). This effect was observed across multiple cell types, promoters, and target proteins under the tested conditions, suggesting a potentially broad—but not yet universally proven—applicability.
TME conditions affect cssDNA(+) expression by modulating the cell cycle
To further explore the molecular mechanism by which TME conditions influence cssDNA(+) expression, we analyzed relevant RNA sequencing datasets (transcriptome profiling) of liver cancer and colon cancer from the GEO database. We identified the related pathways of differentially expressed genes (DEGs) by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The outcome of this enrichment analysis revealed that glucose deficiency, glutamine deficiency, and hypoxia treatments all lead to significant enrichment in cell cycle-related pathways (Fig. 4A, B).
TME conditions affect cssDNA(+) expression by modulating the cell cycle. (A,B) The top ten KEGG pathways of DEGs in liver cancer cells (A) or colon cancer cells (B) cultured under conditions of glucose deficiency (left), glutamine deficiency (center), or hypoxia (right). (C) HCCLM3 cells were treated for 24 h under normal, glucose-deficient, glutamine-deficient, or hypoxic conditions, cells were collected and stained with PI for flow cytometry to analysis cell cycle distribution. (D) HCCLM3 cells were treated as follows: mock; mimosine (200 µM) for 24 h (G1 phase); thymidine (TDR, 2.5 mM) for 17 h, then released for 10 h, followed by TDR again for 17 h, then released for 3 h (S phase); TDR for 17 h, then released for 10 h, followed by nocodazole (50 ng/mL) for 17 h (G2/M phase). The cells were harvested and stained with PI for flow cytometry to analyze cell cycle distribution. (E–H) HCCLM3 cells in different cell cycle phases were transfected with css-EGFP(+) and cultured under normal condition for 12 h, cells were collected and total protein or RNA extracted. (E and F) The percentage of EGFP + cells and mean fluorescence intensity per cell of css-EGFP(+). All fluorescence intensities were normalized to the value of the mock group. (G) qPCR analysis showing the mRNA expression of css-EGFP(+). (H) Total cellular proteins were collected and subjected to Western blot with the antibodies against EGFP and β-actin. FACS plots are representative of one of n = 3 biologically independent experiments. Western blot images are representative of one of n = 3 biologically independent experiments. Data are shown as mean ± SD for n = 3 biologically independent experiments. Statistical comparisons were performed using one-way ANOVA followed by Tukey’s post hoc test. Asterisks indicate statistically significant differences. (*p < 0.05, ** p < 0.01, *** p < 0.001).
To investigate how the TME conditions influence the expression of cssDNA(+) through the cell cycle, HCCLM3 cells were treated under different TME conditions for 24 h, and collected for analysis. Cells treated with different conditions were analyzed by propidium iodide (PI) staining followed by flow cytometry for cell cycle analysis. FACS analysis showed a marked increase in the proportion of cells in G1 phase under TME conditions. Specifically, G1-phase cells accounted for 48.6% under normal conditions, increasing to 60.2% under glucose deficiency, 60.0% under glutamine deficiency, and 81.1% under hypoxia (Fig. 4C), indicating substantial G1-phase arrest.
The above results indicated that glucose deficiency, glutamine deficiency and hypoxia significantly enhance cssDNA(+) expression, and induce G1-phase arrest, suggesting that cells in G1 may be more permissive for cssDNA(+) expression. To verify this hypothesis, HCCLM3 cells were synchronized into G1, S, and G2/M phases and verified by flow cytometry (Fig. 4D). Subsequently, cells at distinct cell cycle phases were released from arrest and cultured under normal condition while immediately transfected with css-EGFP(+), and the expression of EGFP was measured 12 h later. FACS results showed that G1 phase cells (immediately entering S phase) showed the lowest percentage of EGFP + cells and mean fluorescence intensity per cell, G2/M phase cells (immediately entering G1 phase) exhibited the highest percentage of EGFP+ cells and mean fluorescence intensity per cell, and S phase cells (immediately entering G2/M phase and subsequently G1 phase) displayed intermediate percentage of EGFP + cells and mean fluorescence intensity per cell (Fig. 4E, F). Additionally, EGFP expression was assessed at mRNA (Fig. 4G) and protein levels (Fig. 4H) across different cell cycle phases, and the trends were consistent with the FACS results. These results suggest that cssDNA(+) expression is most enhanced in cells transitioning from G2/M to G1.
SKP2 negatively modulates the expression of cssDNA(+)
To identify genes in the cell cycle signaling pathway commonly altered in both liver and colon cancers under glucose deficiency, glutamine deficiency, and hypoxia, we analyzed the DEGs within the cell cycle signaling pathway across three distinct TME conditions of liver cancer or colon cancer (Fig. 5A). A subset of genes exhibiting significant expression alterations in both cancer types was identified, including SKP2, BUB1B, ESPL1, CCNA2, MCM4, TTK and CDC25A (Fig. 5B), all of which were downregulated. SKP2 encodes an F-box protein component of the SCF (SKP1-Cullin-F-box) E3 ubiquitin ligase complex that promotes the G1/S phase transition by mediating ubiquitin-dependent degradation of phosphorylated cell cycle inhibitors such as p2750. BUB1B (BUB1 mitotic checkpoint serine/threonine kinase B) encodes a spindle assembly checkpoint kinase ensuring accurate chromosome segregation51. ESPL1 (extra spindle pole bodies like 1) encodes separase, a cysteine protease mediating sister chromatid separation52. CCNA2 (cyclin A2) activates CDK2 to drive the G1/S transition and DNA replication during S phase, and also interacts with CDK1 to facilitate G2/M progression53. MCM4 (minichromosome maintenance complex component 4) is part of the MCM2-7 helicase complex essential for DNA replication54. TTK (also known as MPS1) encodes a dual-specificity kinase and core spindle assembly checkpoint (SAC) component required to prevent premature anaphase onset, thereby safeguarding chromosomal stability55,56. CDC25A encodes a dual-specificity phosphatase that activates cyclin-dependent kinases (CDKs) by dephosphorylation, thus driving both G1/S and G2/M cell cycle transitions57. Recent studies have documented that SKP2 emerges as a potential therapeutic target in oncology58,59,60. Therefore, we elected to pursue further investigation of the SKP2 gene.
SKP2 negatively modulates the expression of cssDNA(+). (A) Venn diagram of overlapping genes within the cell cycle signaling pathway in liver cancer cells (left) or colon cancer cells (right) under the conditions of glucose deficiency, glutamine deficiency, and hypoxia. (B)Venn diagram of overlapping genes in liver cancer cells and colon cancer cells obtained from A. (C and D) Various mammalian cells (HCCLM3, Huh7, HCT116, SW480, BT474 cell lines, respectively) were cultured under normal, glucose-deficient, glutamine-deficient or hypoxic conditions for 24 h, cells were collected and total protein or RNA extracted. (C) qPCR analysis showing the mRNA expression of SKP2. (D) Total cellular proteins were collected and subjected to Western blot with the antibodies against SKP2 and β-actin. (E) qPCR analysis showing the mRNA expression of SKP2 in HCCLM3 cells treated with 5–50 µM of Skp2 inhibitor C1 for 12 h. (F) Western blot analysis of the expression of SKP2 and β-actin in HCCLM3 cells treated with 5–50 µM of Skp2 inhibitor C1 for 12 h. (G-I) HCCLM3 cells were co-treated with Skp2 inhibitor C1 (10µM) and css-EGFP(+) for 24 h, cells were collected and total protein or RNA extracted. (G and H) qPCR analysis showing the mRNA expression of SKP2 and EGFP. (I) Total cellular proteins were collected and subjected to Western blot with the antibodies against SKP2, EGFP, and β-actin. (J-L) HCCLM3 cells were pre-incubated with Skp2 inhibitor C1 (10µM) for 12 h, then transfected with or without css-EGFP(+) for 24 h, cells were collected and total protein or RNA extracted. (J and K) qPCR analysis showing the mRNA expression of SKP2 and EGFP. (L) Total cellular proteins were collected and subjected to Western blot with the antibodies against SKP2, EGFP, and β-actin. (M) Western blot analysis of relative EGFP protein expression, corresponding to lanes 3–4 in panels I and L. (N,O) HCCLM3 cells were pre-transfected with SKP2 siRNA or Control siRNA for 24 h, then transfected with css-EGFP(+) for 24 h, cells were collected and total protein or RNA extracted. (N) qPCR analysis showing the mRNA expression of EGFP. (O) Total cellular proteins were collected and subjected to Western blot with the antibodies against SKP2, EGFP, and β-actin. Western blot images are representative of one of n = 3 biologically independent experiments. Data are shown as mean ± SD for n = 3 biologically independent experiments. Statistical comparisons were performed using one-way ANOVA followed by Tukey’s post hoc test and unpaired two-tailed Student’s t-test. Asterisks indicate statistically significant differences. (*p < 0.05, ** p < 0.01, *** p < 0.001).
We further examined the influence of TME conditions on SKP2 expression. Glucose deficiency, glutamine deficiency, and hypoxia significantly reduced SKP2 expression at both mRNA (Fig. 5C) and protein levels (Fig. 5D), corroborating the transcriptomic data. To delve into the regulatory role of SKP2 on cssDNA(+) expression, we employed a specific SKP2 inhibitor, designated as Skp2 inhibitor C1. The objective was to assess the impact of SKP2 inhibition on cssDNA(+) expression. Initially, HCCLM3 cells were exposed to varying concentrations (5–50 µM) of Skp2 inhibitor C1 for a duration of 12 h to evaluate its effect on SKP2 gene expression. The results demonstrated a marked suppression of both SKP2 transcription (Fig. 5E) and protein expression (Fig. 5F) at concentrations above 10 µM of the Skp2 inhibitor C1. Subsequently, to further ascertain the influence of SKP2 inhibition on css-EGFP(+) expression, HCCLM3 cells were subjected to two distinct treatment protocols involving Skp2 inhibitor C1: concurrent treatment with css-EGFP(+) transfection or pretreatment prior to css-EGFP(+) transfection. When cells were co-treated with Skp2 inhibitor C1 and css-EGFP(+), significant repression of SKP2 transcription (Fig. 5G) and protein expression (Fig. 5I) was observed. Concurrently, transcription of css-EGFP(+) was markedly enhanced in the presence of Skp2 inhibitor C1 (Fig. 5H), and the protein level of EGFP was also higher than those in the untreated control group (Fig. 5I). Furthermore, when cells were pre-incubated with Skp2 inhibitor C1 for 12 h prior to css-EGFP(+) transfection, Skp2 inhibitor C1 maintained its efficacy in significantly suppressing SKP2 transcription (Fig. 5J) and protein expression (Fig. 5L). Similarly, pretreatment with Skp2 inhibitor C1 resulted in a pronounced enhancement in css-EGFP(+) transcription (Fig. 5K) and translation (Fig. 5L). Notably, pretreatment yielded a more pronounced increase in EGFP protein (Fig. 5I, L). To better visualize these differences, we quantified the relative EGFP protein levels from lanes 3 and 4 in Fig. 5I and 5L (Fig. 5M). The results demonstrate that both co-treatment and pretreatment with the Skp2 inhibitor C1 significantly enhanced EGFP expression. Moreover, pretreatment led to a more substantial increase, which was statistically significant (p < 0.001). This effect may be attributed to more complete depletion of SKP2 protein prior to transfection, achieved through pre-incubation with the Skp2 inhibitor C1. To rule out off-target effects of Skp2 inhibitor C1, SKP2 siRNA was used to knockdown SKP2 expression. Consistent with inhibitor results, SKP2 knockdown significantly increased css-EGFP(+) transcription and translation (Fig. 5N, O).
In conclusion, applying Skp2 inhibitor C1 and SKP2 siRNA both yielded a significant upregulation of css-EGFP(+) expression at both transcription and translation levels. These observations collectively imply the pivotal role for SKP2 inhibition in promoting cssDNA(+) expression in TME conditions, highlighting the potential therapeutic significance of targeting SKP2 to modulate cssDNA(+)-mediated pathways.
Discussion
Conventional plasmid vectors are covalently closed double-stranded DNA molecule derived from natural plasmids, typically existing as tightly supercoiled topoisomers61. These vectors contain essential prokaryotic sequences required for plasmid amplification in bacterial hosts (such as origin of replication and antibiotic resistance gene) and a eukaryotic expression cassette61,62. Research based on plasmids indicates plasmid elements like replication origins and prokaryotic markers have been shown to be required only for bacterial propagation. When introduced into mammalian systems, these elements reduce vector stability, trigger innate immune responses, and silence transgene expression61,63,64,65, highlighting the importance of minimalist circular DNA vectors. CssDNA derived from the M13 bacteriophage lacks bacterial elements and has been shown to serve as an efficient gene expression vector32. Our previous studies indicate that both sense and antisense cssDNA are capable of expressing target proteins7. By constructing plasmids and cssDNAs expressing luciferase or EGFP in both sense and antisense orientations, as well as cssUC18-Luciferase(+) matched in length and sequence to the plasmids, we observed that cssDNA exhibits higher expression than conventional plasmids, with cssDNA(+) demonstrating the highest expression. Therefore, we conclude that cssDNA demonstrates superior expression after transfection into cells, and removing unnecessary sequences, such as prokaryotic elements, may further enhance the expression of cssDNA. Moreover, determining whether elimination of bacterial backbone sequences can improve cssDNA-mediated expression, and understanding the mechanisms involved, represents an important area for future investigation.
Numerous drugs demonstrate antitumor potential at the cellular level, yet their efficacy in vivo often differs from in vitro outcomes, likely due to the complex TME. Understanding TME-drug interactions is therefore critical for therapeutic development. Recent studies have confirmed that cssDNA-based DNA origami structures deliver functional genes in mammalian systems66,67,68, and that cssDNA can achieve therapeutic effects in murine breast cancer models via local intratumoral administration69. However, the impact of TME conditions on cssDNA expression remains largely unexplored. To address this, we established three physiologically relevant TME conditions (glucose deficiency, glutamine deficiency and hypoxia) in vitro. Our results showed that these TME conditions can enhance the expression of cssDNA(+), which is consistent across multiple tumor cells tested, potentially independent of promoter or transgene sequence. While this effect appears generalizable, its broader applicability requires to be further verified through more different conditions. Mechanistically, TME conditions appear to enhance cssDNA(+) expression by modulating cell-cycle dynamics, including G1 phase arrest and the G2/M to G1 transition. Additional factors, such as stress-induced chromatin remodeling or altered translational efficiency, may also contribute to the regulation of cssDNA(+) expression. Notably, inhibition of SKP2, a key component of the cell cycle signaling pathway, plays a role in enhancing cssDNA(+) expression under glucose-deficient, glutamine-deficient, and hypoxic conditions (Fig. 6). Although the precise mechanisms—whether via cell cycle control, transcriptional activation, or post-transcriptional regulation—remain to be fully elucidated, these findings provide valuable mechanistic insight and may guide future therapeutic applications of cssDNA(+) in tumors.
Schematic diagram of TME-mediated cssDNA expression enhancement. TME conditions (glucose deficiency, glutamine deficiency, and hypoxia) suppress SKP2 expression, inducing G1-phase cell cycle arrest and thereby upregulation of cssDNA expression.
SKP2, an F-box protein component of the SCF (SKP1-Cullin-F-box) E3 ubiquitin ligase complex58,60, is a well- recognized oncogene frequently overexpressed in various cancers70. It regulates many key processes of cellular biology such DNA replication, cell cycle and migration71,72,73. Although SKP2’s direct transcriptional or translational control of exogenous genes remains incompletely characterized, its role in ubiquitin-mediated degradation of p21/p27 well documented74,75. This degradation accelerates G1-S progression and promotes proliferation76, thereby potentially altering the cellular milieu for transgene expression. The highly proliferative state of cancer cells may further enhance exogenous protein expression by increasing metabolic activity, altering chromatin accessibility, and elevating nuclear import efficiency. In our study, SKP2 downregulation under TME conditions suggests a compensatory mechanism that favors cell-cycle arrest and may facilitate recombinant protein production. Specifically, under TME conditions, the observed G1-phase arrest and SKP2 downregulation are consistent with stabilization of p21 and p27 proteins, in line with SKP2’s established role in targeting these cell-cycle inhibitors for proteasomal degradation. This provides a plausible mechanism underlying the observed arrest phenotype. Future studies directly measuring the half-lives of p21 and p27 under these TME conditions would be valuable to confirm their post-translational stabilization. Furthermore, in psoriasis, SKP2-mediated degradation of PTEN leads to activation of the PI3K/Akt pathway, which subsequently modulates mTOR-dependent translation77 and may further influence exogenous protein synthesis. However, this hypothesis has not yet been validated through direct mechanistic experiments and requires further investigation. Thus, although the precise mechanisms underlying TME-enhanced cssDNA(+) expression remain unclear, SKP2 likely modulates cssDNA expression through these multiple signaling cascades. Further studies are required to delineate the specific contributions of transcriptional regulation, translational control, and additional mechanisms such as epigenetic modifications or innate immune pathways.
It is also important to note that the impacts of glucose deficiency, glutamine deficiency and hypoxia on SPK2-related upstream pathways remain unaddressed in our work. The Akt/mTOR signaling pathway and the transcription factor c-Myc are well-established upstream regulators that positively modulate SKP2 expression78,79,80. And these stress conditions such as glucose deficiency, glutamine deficiency, and hypoxia are known to modulate the activity of both Akt/mTOR and c-Myc81,82. These pathways may therefore act as upstream mediators through which metabolic and hypoxic stresses regulate SKP2 expression. Nevertheless, this proposed mechanism remains speculative and requires further experimental validation to confirm causality.
Collectively, we have demonstrated that cssDNA(+) exhibits higher expression compared to other circular DNA, and further evaluated its performance under the specific TME conditions tested. Although the precise cellular and molecular mechanisms through which TME conditions influence cssDNA(+) expression remain to be elucidated, the inhibition of SKP2 appears to be a key contributing factor underlying the enhancing effect of TME conditions on cssDNA(+) expression. These findings hold significant clinical implications, highlighting the potential of cssDNA(+) as a novel tool in cancer therapy. Furthermore, combining SKP2 inhibition with cssDNA(+) delivery may further enhance its therapeutic efficacy against tumors.
Materials and methods
Plasmid construction
The plasmids pScaf-Luciferase(+), pScaf-EGFP(+), pScaf-EGFP(-) and pScaf-EF1α-mIL12(+) were described previously7,69. pScaf-Luciferase(+), pScaf-EGFP(+), pScaf-EF1α-mIL12(+) and pUC18 (cat. no. 50004 in addgene) are used as backbone vectors or as templates to generate insertion fragments. All recombinant plasmids were constructed using a homology-based cloning strategy. Specifically, linearized vector and insert fragments were obtained by PCR amplification using specific primers. The insert fragment was then recombined into the linearized vector using the ClonExpress II One Step Cloning Kit (Vazyme, China) to generate each target plasmid. All constructed plasmids were verified by sequencing (Tsingke Biotechnology Co., Ltd). The sequences of all oligonucleotide primers used for PCR amplification are listed in Table 1.
CssDNA extraction and production
CssDNA was generated through the pScaf phagemid method as described previously8,32,83. Briefly, we co-transfected XL1-Blue competent cells with the recombinant pScaf plasmid and a helper plasmid (pSB4423). Then the monoclonal cells selected on the bacterial culture plate containing ampicillin and chloramphenicol were grown for 18–20 h in 800mL 2×YT media (1% tryptone, 0.5% yeast extract, 1% NaCl) supplemented with 100 µg/mL ampicillin, 10 µg/mL chloramphenicol (30 °C, 220 rpm). Next, the cultures were centrifuged at 10,000 g for 30 min at 4℃, and the supernatant was harvested and filtered through 0.45µM cellulose acetate. The phage in the clarified supernatant was precipitated by adding 6% w/v PEG8000 and 3% w/v NaCl and shaking for 2 h at room temperature. The phage pellet was collected by centrifugation at 15,000 g for 45 min at 4℃ and resuspended in 5mL TE buffer (10mM Tris-HCl pH8.0, 1mM ethylenediaminetetraacetic acid (EDTA)). Finally, the phage-containing resuspension solution was processed using an EndoFree® Plasmid Maxi Kit (QIAGEN, Germany) to purify cssDNA.
Agarose gel electrophoresis
The 1.0% agarose gels were prepared by 1×TAE buffer and stained by 0.01% v/v Ultra Gelred (Vazyme, China). Then the cssDNAs and plasmids were run for 35 min at a voltage of 120 V in a TAE buffer. Finally, the target gel bands were imaged using Amersham ImageQuant 800.
Cell culture
HCCLM3, Huh7 and BT474 cell lines were kindly provided by Pengfei Zhang (Hangzhou Institute of Medicine, Chinese Academy of Sciences, China). HCT116 and SW480 cell lines were kindly provided by Lianxin Liu’s research team (the first affiliated hospital of USTC, China). MCF7 (CL-0149) and DC2.4 (CL-0545) cell lines were obtained from Procell Life Science & Technology Co., Ltd (Wuhan, China). HCCLM3, Huh7, HCT116, SW480 and MCF7 cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM) (Gibco, USA), while DC2.4 and BT474 cells were cultured in Roswell Park Memorial Institute (RPMI) 1640 medium (Gibco, USA). All cell lines were cultured in a medium supplemented with 10% fetal bovine serum (FBS) (Gibco, USA) and 1% penicillin/streptomycin (Gibco, USA) at 37℃ in a humidified atmosphere of 5% CO2. More information about the cells is listed in Table 2.
Cells were cultured under defined conditions to mimic TME conditions (glucose deficiency, glutamine deficiency and hypoxia). For glucose-deficient or glutamine- deficient conditions, cells were maintained in DMEM medium lacking glucose or glutamine (Gibco, USA), respectively. For hypoxic condition, cells were incubated in a controlled atmosphere containing 1% O2, 5% CO2, and 94% N2. Unless otherwise stated, all other culture conditions were identical to standard culture condition.
DNA and siRNA transfection by Lipo2000
Cells were seeded in 96, 24 or 6-well plates at a density of 10,000 cells/well, 70,000 cells/well or 350,000 cells/well and incubated at 37 °C in 5% CO2 for 24 h, when the cell density reached ~ 70 − 80%, DNA (0.1 pmol for 96-well plate, 0.5 pmol for 24-well plate or 2.5 pmol for 6-well plate) or siRNA (GENEWIZ, China) (125 pmpl for 6-well plate ) were transfected into the cells by a Lipofectamine™ 2000 transfection reagent (Lipo2000; Invitrogen) (0.5 µL for 96-well plate, 2 µL for 24-well plate or 10 µL for 6-well plate) following its commercial protocols. Before transfection, the medium was replaced with fresh complete medium, and after transfection for 4 h, the complete medium was replaced to the corresponding medium (complete, glucose-deficient, glutamine-deficient medium) for culture.
For DNA transfection, cells transfected with Lipo2000 alone served as the negative control; for siRNA transfection, cells transfected with Control siRNA by Lipo2000 were used as the negative control. The siRNA sequences targeting SKP2 were as follows (5′–3′):
Control siRNA:
Sense: UUCUCCGAACGUGUCACGUTT.
antisense: ACGUGACACGUUCGGAGAATT.
SKP2 siRNA:
Sense: GCCUAAGCUAAAUCGAGAGAATT.
antisense: UUCUCUCGAUUUAGCUUAGGCTT.
Luciferase luminescence assays
Cells transfected with DNAs were cultured for 24 h in a 96-well plate. Subsequently, cells in each well were washed twice with phosphate-buffered saline (PBS) buffer and incubated with 200 µL of d-luciferin potassium salt (0.15 mg/mL in PBS buffer) for 5 min at room temperature. Luminescence was measured using a Spark multimode microplate reader (Tecan) with an integration time of 1000 ms. Data were exported to GraphPad Prism v.9.0 for analysis.
Fluorescence microscopy assay
The culture dish was placed horizontally on the microscope stage, and cellular morphology was first examined and recorded under a 10× objective using transmitted light. Subsequently, without altering the field of view, the appropriate fluorescence filter set for EGFP (excitation ~ 488 nm, emission ~ 510 nm) was selected, and fluorescence images of the same region were acquired to document EGFP expression.
Flow cytometry assays
Cells transfected with DNAs were cultured for 12, 24–48 h, then the cells were digested with trypsin and washed twice with phosphate-buffered saline (PBS) buffer. Next, the cells were resuspended in 200µL PBS buffer and were analyzed by flow cytometry assays. The analysis was carried out using a flow cytometer (CytoFLEX LX-3-301, Beckman Coulter), and the fluorometry data were processed using FlowJo V10 software.
RNA extraction and Real-Time PCR
Total cellular RNA from the cells was extracted using RNAiso Plus (Trizol) (Takara Bio, China) according to the manufacturer’s instructions. Total RNA was subjected to ABScript Neo RT Master Mix (ABclonal, China) to generate complementary DNA (cDNA), and cDNA was then used as a template for real-time PCR, which was performed with 2× Universal SYBR Green Fast qPCR Mix (ABclonal, China). The level of β-actin mRNA was used as an endogenous reference to normalize the quantities of target mRNAs. The sequences of oligonucleotide primers used in qPCR were included in Table 3.
Western blot
Cells were cultured and treated as indicated. Before harvest, cells were washed twice with PBS buffer. Total cell lysates were prepared with RIPA lysis buffer (Beyotime, China) containing 1% protease inhibitor cocktail (Roche) and 1% phosphatase inhibitor mixture (Roche). The protein concentrations were quantified by a BCA protein assay kit (Beyotime, China). Protein samples were mixed with protein loading buffer and followed by denaturation at 95 °C for 10 min. Then, equal amount of proteins (10–20 µg/lane) was separated on 10% SDS-PAGE gels. After being transferred to nitrocellulose (NC) membranes, nonspecific sites were blocked with 5% non-fat milk in Tris-buffered saline containing 0.1% Tween 20 (TBST) for 1 h prior to incubating with primary antibodies at 4℃ overnight. The membranes were washed with TBST and further incubated with horseradish peroxidase-conjugated second antibody. Finally, blots were exposed with the Amersham ImageQuant 800 Imaging System for a proper exposure period.
The western blots were carried out with primary antibodies against GFP (cat. no. 2956, Cell Signaling Technologies, dilution 1:1,000), β-actin (cat. no. 3700, Cell Signaling Technologies, dilution 1:1,000) and SKP2 (cat. no. 2652, Cell Signaling Technologies, dilution 1:1,000). The horseradish peroxidase (HRP)-labelled anti-rabbit (cat. no. AS014; ABclonal, dilution 1:10000) and anti-mouse (cat. no. AS003; ABclonal, dilution 1:10000) secondary antibodies were applied.
Retrieval and analysis of RNA-seq data
By searching the keywords “(glucose starvation) or (glutamine deprivation) or (hypoxia)” in the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/), five datasets (GSE140867, GSE13548, GSE123062, GSE116087, and GSE41666) were chosen for subsequent analysis. Differentially expressed genes (DEGs) were calculated in five datasets by HOME for Researchers (https://www.aclbi.com/static/index.html#/geo). Functional annotation of the DEGs was performed via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis using DAVID Bioinformatics Resources 6.8 (https://david.ncifcrf.gov/home.jsp)84, with pathways exhibiting an enrichment score ≥ 2 and an adjusted p-value < 0.05 considered statistically significant.
Cell cycle analysis
Cells were cultured and treated as indicated, and then the cells were harvested. Approximately 2,000,000 cells were harvested into a 15 mL centrifuge tube and washed twice with ice-cold PBS. The cells were then fixed in 70% ethanol at 4 °C overnight. After fixation, the samples were centrifuged at 160 g for 5 min at 4 °C and washed twice with PBS. The resulting cell pellets were resuspended in RNase A solution (final concentration, 100 µg/mL) and incubated at 37 °C for 30 min. Subsequently, the cells were centrifuged at 360 g for 5 min, the supernatant was removed, and the pellets were stained with propidium iodide (PI; final concentration, 50 µg/mL) for 15 min at room temperature in the dark. Red fluorescence was measured by flow cytometry (CytoFLEX LX-3-301, Beckman Coulter) with excitation at 488 nm, and the data were processed using FlowJo V10 software.
Cell cycle synchronization
HCCLM3 cells were synchronized at specific phases of the cell cycle using chemical inhibitors. For G1-phase arrest, cells were treated with mimosine (200 µM) for 24 h. To synchronize cells in S phase, cells were exposed to 2.5 mM thymidine (TDR) for 17 h, released into fresh medium for 10 h, and subsequently treated with TDR again for 17 h, followed by release for 3 h. For G2/M-phase arrest, cells were treated with TDR for 17 h, released for 10 h, and then incubated with nocodazole (50 ng/mL) for 17 h.
Statistical analysis
The data are presented as mean ± standard deviation (SD) of three biologically independent experiments. Data analysis was performed using GraphPad Prism v.9.0 software. Statistical significance was assessed by One-way analysis of variance (ANOVA) with Tukey’s post hoc corrections and unpaired two-tailed Student’s t-test. p < 0.05 was considered statistically significant, and *p < 0.05, **p < 0.01, ***p < 0.001.
Data availability
The datasets analysed during the current study are available in the Gene Expression Omnibus (GEO) database (https://www.ncbi.nlm.nih.gov/geo/) under the following accession numbers: GSE140867, GSE13548, GSE123062, GSE116087, and GSE41666. The original contributions presented in the study are included in the article.
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Acknowledgements
The authors are grateful for the financial support from: the National Key Research and Development Program of China (Grant No. 2021YFF1200200), the National Natural Science Foundation of China (No. 22161132008), the Leading Health Talents in Zhejiang Province (WS2022LJ01) and the Natural Science Foundation of Zhejiang Province (No. YXD23B0301), the Hangzhou Joint Fund of the Zhejiang Provincial Natural Science Foundation of China (No. LHZY24H300002), and the Science and Technology Development Program of Hangzhou (No. 202204B04). We also acknowledge facility supported by Hangzhou Institute of Medicine, Chinese Academy of Sciences.
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J.S., P.Z. and D.S developed the concepts. D.S. was responsible for all experiments, results and discussions, and for drafting and revising the manuscript. P.Z. and J.W. provided guidance on experimental planning. D.S., J.W. and K.Z. carried out data analysis and discussion. J.W. and Y.C. contributed to the writing of the manuscript. J.S. and P.Z. supervised the project and edited the manuscript.
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Shao, D., Wang, J., Zou, K. et al. The tumor microenvironment enhances the expression of cssDNA by modulating cell cycle signaling pathways via SKP2. Sci Rep 15, 38760 (2025). https://doi.org/10.1038/s41598-025-22477-2
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DOI: https://doi.org/10.1038/s41598-025-22477-2
