Efficient Downregulation of Flt-1 Mediated by Splice Switching ASO in Murine Endothelial Cells

Abstract

Impaired angiogenesis is a common feature of several pathological conditions, including neuromuscular disorders. Such vascular defects not only contribute to disease progression but also may compromise the efficacy of systemically delivered therapies such as antisense oligonucleotides (ASOs) and adeno-associated virus vectors. Enhancing muscle vascularization is therefore an attractive strategy to improve both therapeutic delivery and tissue regeneration. Vascular endothelial growth factor A (VEGF-A) is the principal driver of angiogenesis, but its bioavailability is negatively regulated by VEGFR1/Flt-1, a high-affinity decoy receptor. Here, we investigated a splice-switching ASO (SSO) approach to downregulate Flt-1 expression in murine endothelial cells. We designed ASOs to induce skipping of an out-of-frame exon in the Flt1 transcript, triggering nonsense-mediated decay and reducing protein expression. Screening in C166 endothelial cells identified a lead SSO that efficiently skipped exon 5, resulting in robust Flt-1 downregulation, similar to levels achieved with a control siRNA. Functionally, Flt-1 knockdown enhanced endothelial cell proliferation, survival, and migration upon VEGF-A stimulation. These results provide proof-of-concept for targeting Flt-1 via exon skipping to promote angiogenesis, with potential applications in degenerative or ischemic contexts where vascularization is impaired.

Keywords

antisense oligonucleotides splice switching exon skipping siRNA angiogenesis Flt-1

Introduction

Angiogenesis, the formation of new blood vessels from preexisting vasculature, is a tightly regulated biological process essential for tissue growth, regeneration, and repair. Vascular endothelial growth factor A (VEGF-A) is the master regulator of angiogenesis and primarily signals through its receptor VEGFR2 (Flk-1) to promote endothelial cell proliferation, migration, and survival.¹ In skeletal muscle, angiogenesis plays a crucial role in maintaining metabolic homeostasis, ensuring adequate oxygen and nutrient delivery, and supporting muscle plasticity during adaptation to exercise or response to injury.² It is also critical during muscle regeneration following trauma or degeneration, as endothelial cells interact with satellite cells and infiltrating immune cells to orchestrate tissue repair.^3,4 Impaired angiogenesis is a pathological hallmark of numerous conditions, including ischemic vascular diseases, diabetes, and neuromuscular disorders.^5–7 Among these, Duchenne muscular dystrophy (DMD) has emerged as a disease in which vascular abnormalities are increasingly recognized as key contributors to disease pathogenesis. Indeed, DMD muscles exhibit multiple vascular defects, including altered VEGF-A signaling, reduced capillary density, and vessel rarefaction, even at early stages of the disease progression.^7–9 In recent years, several therapeutic strategies have been developed to address the genetic defect underlying DMD, including exon skipping using antisense oligonucleotides (ASOs) and gene replacement strategies using adeno-associated virus (AAV) vectors.^10–16 However, these approaches rely on systemic administration, which requires efficient biodistribution and vascular delivery, which are potentially compromised in dystrophic muscles. Addressing vascular dysfunction may therefore enhance the efficacy of current therapeutic approaches to reach meaningful clinical benefits.

Therapeutic strategies aimed at promoting angiogenesis by using VEGF-A have shown beneficial effects across several preclinical models where VEGF-A promotes endothelial proliferation, increases capillary density, improves perfusion, and supports tissue regeneration. However, such strategies often rely on exogenous and sustain growth factor overexpression, which does not mimic physiological signaling and poses concerns for clinical translation, including control of expression levels and long-term safety.^17,18

A potential strategy to circumvent these limitations is to modulate the endogenous VEGF-A signaling pathway by targeting one of its negative regulators, which would enhance VEGF-A bioavailability without perturbing its endogenous expression. The activity of VEGF-A is modulated by VEGFR1 (Flt-1), a high-affinity decoy receptor that limits VEGF-A availability for VEGFR2 binding.¹⁹ Flt-1 exists in both membrane-bound and soluble forms, the latter being produced by alternative splicing and known to sequester circulating VEGF-A (Fig. 1A).²² Previous studies have shown that heterozygous deletion of Flt1 in mdx mice leads to improved muscle perfusion, reduced fibrosis, and enhanced function.²³ Additionally, administration of anti-Flt-1 antibodies or inhibitory peptides similarly promoted vascularization and regeneration in dystrophic muscle.²⁴ These results suggest that Flt-1 is a promising target for modulating VEGF-A signaling in a more physiological manner.

FIG. 1.

Screening and selection of the most potent ASO targeting Flt-1. (A) Schematic representation of Flt1 and Flk1 signaling following VEGF binding. (B) Schematic representation of Flt1 exons 5 and 7, and the position of the designed ASO. For exon 5, two ASOs targeting putative exonic splicing enhancers (ESE) and one targeting the donor splice site were designed. For exon 7, one ASO targets an ESE and one targets the donor splice site. (C) PCR analysis amplifying exons 4 to 8 from C166 cells transfected with each ASO, allowing visualization of exon 5 or exon 7 on the same gel. The lower arrow indicates the 510 bp product, whereas the upper arrow indicates the 673 bp product. (D) Quantification of exon 5 skipping by qPCR. (E) PCR analysis showing exon 5 skipping after transfection with ASO Ex5 (+121 +140) alone or in combination with other ASOs. The lower arrow indicates the 510 bp product, whereas the upper arrow indicates the 673 bp product. (F) qPCR quantification of exon 5 skipping for the same combinations. (G) PCR analysis showing exon 5 skipping in a dose-response experiment with 2′OMe Flt1 ASO (10–100 nM). The lower arrow indicates the 510 bp product, whereas the upper arrow indicates the 673 bp product. (H) qPCR quantification of the dose-response experiment. (I) qPCR quantification of exon 5 skipping in a kinetic study (24–96 h). (*P < 0.05; ****P < 0.0001 compared to 2′OMe CTRL treated cells, analyzed by one-way ANOVA). Note that additional bands between the nonskipped and skipped products are visible in some PCR analyses. This is due to heteroduplex formation and has been described previously.^20,21 Results are expressed as means ± SEM, n = 3 replicates per condition.

In this study, we aimed to downregulate Flt-1 using ASOs as a strategy to promote angiogenesis. ASOs can modulate gene expression in many ways, and downregulation is typically achieved using gapmer ASOs recruiting RNase H1.²⁵ However, splice switching ASOs (also called SSOs) can also be used to create a frameshift in an mRNA, leading to mRNA degradation and protein inhibition.²⁶ In this case, ASOs are designed to skip an out-of-frame exon, which disrupts the open reading frame and leads to reduced expression of the target through nonsense-mediated decay.²⁷ We thus screened several ASOs targeting two out-of-frame exons from Flt-1 in mouse endothelial C166 cells. The lead skipping-ASO was evaluated for effects on endothelial cells proliferation, viability and migration, and benchmarked against a validated siRNA targeting sFlt1 developed for preeclampsia.²⁸ These results provide the proof-of-concept for future therapeutic applications in ischemic and dystrophic settings.

Materials and Methods

Cell culture

Mouse endothelial C166 cells were obtained from the American Type Culture Collection (ATCC, Manassas, VA, USA) and cultured in high-glucose Dulbecco’s modified Eagle Medium (DMEM; 4.5 g/L glucose, Gibco, Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS; Gibco, Thermo Fisher Scientific, Waltham, MA, USA) and 1% penicillin-streptomycin (Gibco, Thermo Fisher Scientific, Waltham, MA, USA). Cells were maintained at 37°C in a humidified incubator with 5% CO₂. Regular passaging was performed to maintain optimal cell density and viability.

In-silico antisense oligonucleotides design

ASOs were designed using the ExoSplice system, an in-silico platform developed to evaluate all potential antisense sequences targeting a selected exon and its adjacent intronic regions. ExoSplice performs a comprehensive analysis of the targeted genomic region by integrating multiple parameters, including prediction of exonic splicing enhancers (ESEs) with an associated scoring system reflecting sequence strength, identification of potential transcriptome-wide off-targets and associated mismatch profiles, and prediction of local RNA secondary structures that may limit ASO accessibility and binding.

These features are combined to generate a global score for each candidate ASO, which was used to prioritize sequences predicted to efficiently interfere with splicing while minimizing off-target interactions.

Transfection of antisense oligonucleotides and siRNAs

C166 cells were seeded in 6-well plates and transfected at 60%–70% confluency using Lipofectamine RNAiMAX transfection reagent (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) according to the manufacturer’s instructions. Transfections were performed using chemically modified 20-mer ASOs, synthesized by Eurogentec (Liège, Belgium). All ASOs were fully modified with 2′-O-methyl (2′OMe) RNA on a phosphorothioate backbone, and all sequences have been provided in Supplementary Table S1. As a control, we used an ASO (CAUUGUUUUUUGUCUU) that has been previously published.²⁹

In parallel, scramble and sFlt1-targeting siRNAs were transfected as positive controls compared to ASOs; siRNAs were modified as previously described^28,30,31 with the following sequences: sFlt-1 siRNA sense strand: (mC)#(mG)#(mG)(fA)(mU)(fC)(mU)(fC)(mC)(fA)(mA)(mA)(mU)(fU)#(mU)#(mA)(dT)(dT)-DCAv1 and antisense strand: VP(mU)#(fA)#(mA)(fA)(fU)(fU)(mU)(fG)(mG)(fA)(mG)(fA)(mU)(fC)#(mC)#(fG)#(mA)#(mG)#(mA)#(mxU)#(fxU), where VP = 5′vinyl phosphonate, m = 2′OMe, f = 2′Fluoro, x = extended nucleic acid modified RNA (exNA) and # = phosphorothioate links.^28,30,31 When applicable, transfected cells were serum-deprived overnight in DMEM without FBS and subsequently stimulated with 10 ng/mL recombinant mouse VEGF-A164 (Novus Biologicals, Bio-Techne, Centennial, CO, USA; Cat# 18630841) for 24 h prior to sample collection or functional assays.

RNA extraction, reverse transcription, PCR, and qPCR

Total RNA was extracted using TRIzol Reagent (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA) following the manufacturer’s protocol. RNA concentration and purity were assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Reverse transcription was performed using the LunaScript RT SuperMix Kit (New England Biolabs, Ipswich, MA, USA). Endpoint PCR was conducted with GoTaq DNA Polymerase (Promega, Madison, WI, USA), and products were resolved by electrophoresis on 2% agarose gels stained with ethidium bromide. Densitometric analysis was performed using Image Lab software (Bio-Rad, Hercules, CA, USA) to quantify exon skipping.

Quantitative PCR (qPCR) was carried out with iTaq Universal Probes Supermix (Bio-Rad, Hercules, CA, USA) using the CFX384 real-time PCR system (Bio-Rad). Cycling conditions were as follows: 95°C for 10 s and 60°C for 30 s, repeated for 50 cycles. Exon skipping efficiency was calculated as the ratio between the skipped transcript (exon 4–6) to the sum of skipped and unskipped transcripts (exon 4–5 + exon 4–6). For siRNA conditions, Flt1 mRNA expression was quantified using primers targeting the exon 4–5 junction and normalized to GAPDH. Primer and probe sequences are listed in Supplementary Table S2. All primers were synthesized, validated, and their efficiency confirmed by standard curves from serially diluted known-concentration cDNA or synthetic DNA (GBlocks; Integrated DNA Technologies, Coralville, IA, USA). Reactions were performed in triplicate with no-template controls.

Western blot analysis

Cell lysates were prepared in RIPA buffer (Thermo Fisher Scientific, Waltham, MA, USA; Cat# 89901) supplemented with 5% SDS and protease inhibitor cocktail (25×). Lysates were denatured at 100°C for 3 min and centrifuged at 12,000 g for 10 min at 10°C. Protein concentrations were determined using the BCA Protein Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA; Cat# 23225). Equal protein amounts (25 µg) were separated on 3%–8% Tris-acetate gradient gels (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA; Cat# EA03785BOX) and transferred to nitrocellulose membranes (Dutscher, Brumath, France; Cat# 10600002). Membranes were blocked with diluted blocking buffer (1:10; Thermo Fisher Scientific, Waltham, MA, USA; Cat# 37565) and probed overnight with primary antibodies: goat anti-Flt1 (R&D Systems, Bio-Techne, Minneapolis, MN, USA; Cat# AF471, 1:500) and mouse anti-vinculin (Sigma-Aldrich, St. Louis, MO, USA; 1:5000). Secondary antibodies, donkey anti-goat (Li-Cor Biosciences, Lincoln, NE, USA; Cat# D40416-15, 1:5000) and goat anti-mouse (Li-Cor Biosciences, Cat# 926-32210, 1:1000), were added for 1 h after a quick washing step. Fluorescent signals at 700 nm (Flt1) and 800 nm (vinculin) were detected with the Odyssey Imaging System, and bands were quantified using Image Studio Lite software (Li-Cor Biosciences, Lincoln, NE, USA).

The AF471 antibody is a polyclonal goat anti-mouse Flt-1 antibody raised against the extracellular domain of murine VEGFR1/Flt-1 and is therefore expected to recognize both membrane-bound and soluble Flt-1 isoforms. Accordingly, membrane-bound Flt-1 was detected at ∼180 kDa, whereas soluble FLT-1 migrated as a lower molecular-weight band (∼90–120 kDa).

Cell proliferation and viability by cell counting

C166 cells (1 × 10⁵ per well) were seeded in 6-well plates in complete DMEM (10% FBS and 1% penicillin-streptomycin). After transfection, serum deprivation, and VEGF-A stimulation, cells were washed with PBS, detached, and resuspended in culture medium. A 1:1 mixture of cell suspension and Trypan Blue (Invitrogen, Thermo Fisher Scientific, Waltham, MA, USA; Cat# T10282) was loaded onto a cell counting slide (Invitrogen, Cat# C10228), and live cells were quantified using an automated cell counter.

Cell viability by MTT assay

Cells (1 × 10⁵/well in 6-well plates) were treated as described above. Cell proliferation was assessed using the MTT Cell Proliferation Assay Kit (OZ Biosciences, Marseille, France; Cat# MT01000), following the manufacturer’s instructions. After incubation with MTT reagent, MTT Solubilization Solution (1:1 ratio) was added. Absorbance was measured at 570 nm and 650 nm, and the differential optical density was used to calculate cell proliferation.

Wound healing assay

After seeding and transfection as above, a linear scratch was created in confluent monolayers using a sterile pipette tip. Cells were washed with PBS to remove detached cells and placed in a live imaging chamber (cellVivo, PeCon GmbH, Erbach, Germany) integrated into an inverted microscope (IX83, Olympus, Tokyo, Japan) at 37°C with 5% CO₂. Images were acquired every 10 min over 24 h. Wound closure was quantified using Fiji (ImageJ, NIH, Bethesda, MD, USA) for each well by subtracting the wound area measured at 24 h from the initial wound area at T0, thereby normalizing migration to baseline wound size for each well.

Statistical analysis

All data were analyzed with the GraphPad Prism8 software (San Diego, California, USA) and expressed as means ± SEM. The “n” refers to the number of replicates per condition, i.e., the number of independent transfections. Group comparisons were performed using one- and two-way analysis of variance or t-test as indicated in figure legends. The Kruskal–Wallis test was used to compare groups that do not follow a normal distribution (assessed with the Shapiro-Wilk test). Significant levels were set at *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

RESULTS

Design and screening of ASOs targeting Flt-1

An initial in silico analysis of the Flt-1 pre-mRNA sequence was performed to identify out-of-frame exons whose skipping would disrupt the open reading frame and introduce a premature termination codon. Given the presence of multiple Flt-1 isoforms (both transmembrane [TM] and soluble), we focused on exons common to all isoforms in order to achieve broad downregulation. Exons 5 and 7 were selected as suitable targets. To guide ASO design, the ExoSplice tool from Genomnis (https://genomnis.com/exosplice) was used to annotate both canonical and auxiliary splicing elements, including donor and acceptor splice sites, branch points, ESEs, and silencers. A total of five ASOs were designed: three targeting exon 5 and two targeting exon 7 (Fig. 1B). For each exon, one ASO was directed against the donor splice site, a region commonly targeted in antisense strategies due to its essential role in exon recognition and inclusion.³² ASO candidates were prioritized based on the predictive scoring system provided by ExoSplice, with particular attention to those showing the highest potential for modulating splicing at or near the donor site. The remaining ASOs were designed to target ESE motifs within the exons. Disruption of these enhancer elements has been shown to interfere with exon recognition by the spliceosome, thereby promoting exon skipping.³³

To assess the efficacy of the designed ASOs, exon skipping levels were evaluated in the murine endothelial cell line C166. Cells were transfected with each ASO at a concentration of 100 nM and incubated for 48 h prior to RNA extraction. The expression of the Flt1 gene was then analyzed by PCR targeting the region spanning exons 4 to 8, to detect exon exclusion following ASO treatment. PCR products were resolved on a 2% agarose gel (Fig. 1C). The full-length (non-skipped) transcript was detected as a band of 673 base pairs (bp). For ASOs targeting exon 5, the expected skipped transcript was 510 bp in size, while for ASOs targeting exon 7, the skipped product was expected at 498 bp. Among the five ASOs tested, only ASO Ex5 (+121+140) induced a detectable exon-skipped band corresponding to exclusion of exon 5. No exon skipping was observed with the other ASOs. To confirm and quantify the efficiency of exon 5 skipping induced by ASO Ex5 (+121+140), RT-qPCR analysis was performed (Fig. 1D). This analysis confirmed that ASO Ex5 (+121+140) promotes exon 5 exclusion with an efficiency of approximately 70%. The accuracy of the newly generated exon 4–6 junction was further validated by Sanger sequencing of the corresponding RT-PCR product (Supplementary Fig. S1). These results identify this ASO as the most effective candidate for Flt1 mRNA downregulation via exon skipping.

To assess whether exon 5 skipping efficacy could be increased further, we evaluated combinations of ASOs targeting different regions of exon 5. The lead SSO, ASO Ex5 (+121+140), was tested in combination with either Ex5 (+9–11) or Ex5 (+37+50) and compared with its potency as a single molecule. For combination experiments, both ASOs were applied at 50 nM each (total 100 nM), matching the 100 nM concentration used for single-agent treatments. Following treatment, exon 5 skipping efficiency was assessed by RT-PCR (Fig. 1E) and RT-qPCR (Fig. 1F). Quantification of skipping indicated no increase or decrease in exon 5 skipping when ASO Ex5 (+121+140) was combined with an additional ASO. Skipping efficiency remained around 75% in all conditions, with no statistically significant differences between single and combined ASO treatments. These results indicate that combining ASOs does not improve exon 5 skipping efficiency. Therefore, ASO Ex5 (+121+140) alone was selected for subsequent experiments and will hereafter be referred to as 2′OMe Flt1.

A dose-response study was then performed to determine the optimal concentration for inducing exon 5 skipping and to confirm the specificity of the observed effect. C166 cells were transfected with increasing concentrations of 2′OMe Flt1 (10 to 100 nM). PCR analysis showed that exon skipping reached ∼10% at 25 nM and up to ∼50% at 100 nM (Fig. 1G). RT-qPCR quantification confirmed a dose-dependent effect, supporting a clear correlation between ASO concentration and exon skipping efficiency (Fig. 1H). Based on these results, 100 nM was selected as the working concentration for all subsequent experiments.

To further characterize the effect of ASO 2′OMe Flt1, a kinetic study was conducted to assess Flt1 downregulation at both RNA and protein levels. C166 cells were transfected with 2′OMe Flt1 and harvested at multiple time points post-transfection (24–96 h). RT-qPCR analysis revealed that exon 5 skipping peaked at 48 h (∼37%), then declined to 15% and 6% at 72 and 96 h, respectively (Fig. 1I). To evaluate the impact of exon skipping on protein expression, Flt1 levels were analyzed by western blot (Fig. 2A). A progressive decrease in the full-length TM Flt1 isoform levels was detected from 48 h, with a significant reduction of 60% at 72 h and 80% at 96 h (Fig. 2B). The expression of the soluble sFlt1 isoform was also significantly decreased from 24 h onwards, reaching 60% of knockdown at 96 h (Fig. 2C). These findings confirm that exon 5 skipping disrupts the Flt1 reading frame and induces significant reduction in protein expression of both the TM and soluble Flt1 isoforms.

FIG. 2.

Evaluation of Flt1 protein expression after ASO treatment. (A) Western blot illustration of transmembrane (TM) and soluble Flt-1 (sFlt1) expression over time following transfection with ASO CTL (CTL) and ASO Flt1 at 100 nM in C166 cells. The expected molecular weights are 180 kDa for transmembrane Flt1 and between 90 and 120 kDa for the soluble isoform. (B) Quantification of transmembrane (TM) Flt-1 protein and the soluble sFlt1(C) expression in C166 cells. Results are expressed as means ± SEM, n = 3 replicates per condition. (*P < 0.05; **P < 0.01; (***P < 0.001 and ****P < 0.0001 compared to CTL analyzed by one-way ANOVA).

Comparison with an siRNA approach

To enable a comparison between the effects of the splice switching ASO 2′OMe Flt1 and a previously validated siRNA, we used the siRNA that was previously developed for the treatment of preeclampsia.²⁸ This siRNA was specifically designed to target the soluble isoform of Flt1 (Flt1-i13 short and Flt1-i13 long) (Fig. 3A). To quantify the expression of the different isoforms of Flt1 following treatment, multiple primer pairs were employed. Total Flt1 expression was measured using primers targeting the junction between exons 4 and 5 (Fig. 3B), and a significant reduction in Flt1 mRNA levels was observed, approximately 30% at 0.5 nM and up to 50% at 2.5 nM. A second primer pair targeting the TM (full length) isoform revealed no significant difference in expression between control and siRNA-treated conditions (Fig. 3C). In contrast, primers specific to the exon 13-i13 junction confirmed the specificity of the siRNA, showing a marked and selective decrease in soluble Flt1 mRNA (Fig. 3D). These dose-response data supported the selection of 2.5 nM as the optimal concentration for subsequent experiments.

FIG. 3.

Evaluation of siRNA targeting sFlt-1. (A) Schematic representation of alternative splicing and differential polyadenylation of the Flt1 gene. Usage of an alternative polyadenylation site within intron 13 generates the soluble isoform sFlt1-i13, which contains exons 1–13 followed by an intron 13–derived sequence. In contrast, selection of the distal polyadenylation site results in the production of the full-length Flt1 transcript encoding the membrane-bound VEGFR1. (B) Quantification of total Flt1 mRNA in a dose-response experiment (**P < 0.01; ****P < 0.0001; one-way ANOVA). (C) Quantification of transmembrane Flt1 mRNA in a dose-response experiment. (D) Quantification of soluble Flt1 mRNA in a dose-response experiment (*P < 0.05; **P < 0.01 compared to siRNA Scramble-treated cells, analyzed one-way ANOVA). (E) qPCR quantification of total Flt1 mRNA in a kinetic study (24–96 h) (**P < 0.01 compared to siRNA Scramble-treated cells, analyzed one-way ANOVA). (F) Quantification of transmembrane (TM) Flt1 protein expression in C166 cells by WB in the kinetic study (no statistical difference compared to siRNA Scramble-treated cells at any time point, analyzed one-way ANOVA). (G) Quantification of soluble sFlt1 protein expression in C166 cells by WB in the kinetic study (*P < 0.01 compared to siRNA Scramble-treated cells, analyzed one-way ANOVA). Results are expressed as means ± SEM, n = 3–6 replicates per condition.

Following dose determination, we assessed the kinetics of siRNA efficacy to identify the optimal time point for maximum target knockdown. Compared to the siRNA scramble, a significant decrease in Flt1 mRNA (approximately 40%) was observed 48 h post-transfection (Fig. 3E). At the protein level, the siRNA was found to specifically downregulate the soluble isoform of Flt1 (sFlt1) at 48 h while not significantly impacting the TM isoform (Fig. 3F–G and Supplementary Fig. S2). The 48-h time point was therefore selected as the optimal window for downstream analyses.

Functional impact of Flt1 downregulation on VEGF-induced cell signaling

To evaluate the functional consequences of Flt1 downregulation in C166 cells, VEGF-A stimulation was used to activate the downstream signaling cascade. First, a dose-response experiment was performed to determine the optimal VEGF concentration capable of promoting cell proliferation. C166 cells were cultured in complete medium with increasing concentrations of VEGF (5–100 ng/mL). Cell counts were assessed at 8 and 24 h using the Trypan Blue exclusion method. No effect was observed at 8 h, while a proliferative response was detected at 24 h (Fig. 4A). The optimal VEGF concentration was determined to be 10 ng/mL and was used in subsequent experiments. To confirm activation of the VEGF-induced signaling cascade, the expression of downstream target genes was analyzed by RT-qPCR. The selected genes, Aurkb and Ccnd1 (involved in mitosis) and Vasp (implicated in cell migration), were significantly upregulated following VEGF-A stimulation, confirming effective activation of the signaling pathway (Fig. 4B).

FIG. 4.

Functional effects of Flt1 downregulation following VEGF stimulation. (A) Quantification of C166 cell numbers after VEGFA164 stimulation (5–100 ng) at 8 h and 24 h. (B) qPCR quantification of VEGF signaling pathway target genes after control 2′OMe transfection with or without VEGF stimulation (*P < 0.05; two-way ANOVA). (C) Endothelial cell proliferation after control or Flt1 2′OMe transfection (**P < 0.01; t-test). (D) Endothelial cell proliferation after scramble or Flt1 siRNA transfection (*P < 0.05; t-test). (E) Cell viability after control or Flt1 2′OMe transfection (**P < 0.01; t-test). (F) Cell viability after scramble or Flt1 siRNA transfection. ( ^# P = 0.06; t-test). Results are expressed as means ± SEM, n = 3 replicates per condition.

With this optimized protocol and validated VEGF-A responsiveness, the functional impact of Flt1 downregulation was then assessed. C166 cells were transfected with 2′OMe Flt1, 2′OMe CTRL, siRNA targeting Flt1, or a scramble siRNA. Following transfection and serum starvation, cells were stimulated with VEGF, and proliferation was measured using the Trypan Blue exclusion method. Fold change in cell number was calculated relative to the respective control condition. Flt1 downregulation via 2′OMe Flt1 significantly increased cell proliferation by almost 50% compared to the 2′OMe CTRL condition (Fig. 4C). A similar increase was observed upon siRNA-mediated knockdown of Flt1 compared to the scramble siRNA control (Fig. 4D). These results indicate that Flt1 downregulation enhances VEGF-mediated proliferation in C166 cells. Beyond its use for assessing proliferation, the Trypan Blue exclusion method also provides insights into cell viability by measuring the ratio of live to total cells. As shown in Figure 4E, treatment with 2′OMe Flt1 significantly increased cell viability by approximately 15% compared to the control. This suggests that Flt1 downregulation may enhance cell survival in response to VEGF-A stimulation. This was also observed following siRNA Flt1 treatment but to a lesser extent (Fig. 4F) (P = 0.06), likely due to the already high baseline viability in control conditions, which averaged around 95%. Metabolic activity was also assessed by MTT assay and showed significant improvement in both cases (Supplementary Fig. S3). In addition to proliferation and viability assessments, cell migration was evaluated using a wound healing assay. C166 cells were cultured in 6-well plates in complete medium and transfected with either ASO 2′OMe Flt1, 2′OMe CTRL, siRNA Flt1 or siRNA scramble. Following VEGF-A stimulation, a scratch was performed across each well using a sterile pipette tip (Fig. 5A). The plates were then placed under a microscope equipped with a 37°C incubated chamber, and images were taken at regular intervals up to 24 h. The extent of wound closure was quantified by measuring the area covered by migrating cells over time. It should be noted that scratch assays reflect a combination of cell migration and proliferation, and therefore the observed wound closure may result from contributions of both processes. As shown in Figure 5B, cells treated with 2′OMe Flt1 exhibited a 13% increase in covered area compared to ASO 2′OMe CTRL, suggesting enhanced migratory capacity. This observation was further supported by the use of siRNA targeting Flt1, which led to an 18% increase in wound closure compared to the scrambled siRNA control (Fig. 5C).

FIG. 5.

Impact of Flt1 downregulation on cell migration following VEGF stimulation. (A) Representative images of scratch assays at T0 and T24 h following control, 2′OMe Flt1, or siRNA Flt1 transfection after VEGF stimulation (×10 objective). (B) Quantification of scratch closure (covered area) after 24 h of VEGF stimulation in 2′OMe-transfected cells. (C) Quantification of scratch closure after 24 h of VEGF stimulation in siRNA-transfected cells. Results are expressed as means ± SEM, n = 3–4 replicates per condition. (P > 0.05; t-test).

Taken together, these results indicate that ASO- and siRNA-mediated Flt1 downregulation efficiently promotes endothelial cell proliferation, survival, and migration in this model.

Discussion

Impaired angiogenesis is a common pathological feature shared by a wide range of diseases, such as ischemic vascular diseases, neuromuscular disorders, aging, diabetes, and chronic non-healing wounds.^5,34,35 In these contexts, the inability to properly form or remodel blood vessels contributes significantly to tissue degeneration and therapeutic inefficacy. Despite extensive research over the past decades, clinical success in targeting angiogenesis remains limited, largely due to the complexity of the underlying molecular mechanisms and their finely tuned regulation.³⁶

Numerous preclinical studies have explored the administration of angiogenic factors, particularly VEGF-A, as a therapeutic avenue to restore vascular function. While these approaches often yield promising results in animal models and have even reached clinical trials, their therapeutic impact has remained limited due to safety concerns, difficulties in dose control, the short half-life of recombinant proteins, and the risk of generating aberrant or non-functional blood vessels.^37,38 To address these limitations, alternative strategies have been developed, including vasodilators or cell-based therapies.^37,39 Among the emerging targets, modulating endogenous angiogenic regulators has gathered increasing interest. One such target is Flt1 (VEGFR-1), a decoy receptor that negatively regulates VEGF availability by sequestering it away from its pro-angiogenic receptor VEGFR-2.⁴⁰ Blocking Flt1 with monoclonal antibodies has been shown to effectively promote angiogenesis in the mdx mouse model of DMD, leading to increased vascular density and improved muscle perfusion.⁴¹ This strategy may also be of interest for other diseases characterized by impaired angiogenesis, in which Flt1 has been shown to be upregulated, such as type 2 diabetes mellitus and preeclampsia, suggesting a broader therapeutic potential.^42,43

In this study, we sought to develop and characterize a new antisense-based strategy targeting Flt1 in endothelial cells, aiming to enhance angiogenic potential by promoting exon skipping and transcript downregulation. Not all SSOs screened in this study resulted in efficient exon skipping or target downregulation. This variability in SSO efficacy depends on multiple factors, including accessibility of the targeted splice sites, local RNA secondary structure, or binding competition with spliceosomal components, which may explain why the donor splice site underperformed. Nevertheless, we identified a lead SSO capable of inducing efficient skipping of exon 5 in the Flt1 transcript, leading to a robust and transient decrease in Flt1 protein expression. This molecular effect translated into clear functional outcomes: Flt1 knockdown significantly increased proliferation, survival, and migration of endothelial cells upon VEGF-A stimulation, three key processes in angiogenesis. These findings support the concept that endogenous pathway modulation can achieve pro-angiogenic benefit while potentially preserving physiological signaling dynamics.

The use of SSOs to downregulate Flt1 offers several advantages over other existing approaches such as antibodies or peptides. First, these oligonucleotide-based strategies act directly at the mRNA level, reducing protein production at the source, which results in longer-lasting effects compared to transient receptor blockade. Second, they offer high specificity, as they are designed to hybridize with unique RNA sequences, making them more precise than protein-targeting molecules, which often rely on recognition of conformational epitopes. Additionally, oligonucleotide therapies generally display low immunogenicity and are more easily controllable than viral gene therapies, especially those using AAVs, which may lead to persistent expression and immune responses. SSO-based modulation can be reversible, dose-dependent, and, if needed, discontinued to restore baseline expression. This is particularly relevant in the context of Flt-1 inhibition, as prolonged or permanent suppression may not be desirable given its role in constraining excessive VEGF-A signaling and maintaining vascular quiescence once new vessels have formed. Defining the optimal magnitude and duration of Flt-1 inhibition will therefore require dedicated in vivo studies, ideally combining vascular readouts with functional measures of tissue perfusion. In this regard, the 2′OMe-PS chemistry used here is well suited for in vitro proof-of-concept studies but is unlikely to be optimal for durable endothelial targeting in vivo. Future translational efforts will require optimization of both oligonucleotide chemistry and delivery strategies to achieve efficient Flt-1 modulation in muscle endothelial cells. Furthermore, owing to sequence divergence between murine and human Flt-1 transcripts, the lead SSO identified in this study is not directly transferable to the human gene and would require sequence re-optimization and validation in a human-specific splicing context for translational application.

Altogether, our results support the therapeutic potential of Flt-1 downregulation by SSO as a novel strategy to boost angiogenesis. This approach, by targeting an endogenous repressor of VEGF-A signaling, may offer a safer and more controllable alternative to direct VEGF administration or gene therapy-based strategies. Future studies are now warranted to evaluate the in vivo angiogenic potential of this approach, particularly its capacity to induce neovascularization and improve muscle perfusion.

Authors’ Contributions

Conceptualization and methodology, M.B., H.H.F., and A.G. Investigation, M.B., O.LC., and V.O. Writing—review and editing, M.B., H.H.F., and A.G. Funding acquisition, A.G. Supervision A.G. and A.K.

Footnotes

Availability of Data and Materials

The primary data for this study are available from the authors upon request.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

This work was supported by the Institut National de la santé et la recherche médicale (INSERM), the Association Monegasque contre les myopathies (AMM), the Paris Ile-de-France Region and the Fondation UVSQ. M. Blitek is the recipient of a MESRI thesis fellowship.

Supplemental Material

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