Sequence-specific targeting of VEGFA genomic DNA to inhibit tumor growth

Abstract

Vascular Endothelial Growth Factor A (VEGFA) is a critical regulatory gene involved in cellular proliferation, neovascularisation, and tumorigenic progression in solid tumors. Upregulation of VEGFA transcription is initiated upon the binding of Hypoxic Inducible Factor-1 (HIF-1α and HIF-1β) heterodimer to the Hypoxic Responsive Element (HRE) on the VEGFA gene within the hypoxic tumor microenvironment. Consequently, disruptions of the HIF-1 heterodimer interactions and the HRE cognate on the VEGFA gene should prevent its transcription in tumors. Herein, we demonstrated sequence-specific targeting of VEGFA genomic DNA using next-generation gamma-modified Peptide Nucleic Acid (γPNA) to prevent HIF-1 interaction and silence VEGFA expression in a series of solid cancer cell lines and in vivo studies. The efficacy of γPNA1 targeting genomic VEGFA in multiple solid tumor cell lines was confirmed through gene expression analysis, Western blot analysis, and cell viability-based functional studies. Preclinical testing in xenograft mouse models of triple-negative breast cancer (TNBC) demonstrated that targeting VEGFA genomic DNA resulted in a notable decrease in tumor growth and an increase in survival rates in mice. In this study, we established a therapeutic approach for precisely targeting VEGFA genomic DNA to suppress its transcription and control tumor progression.

Introduction

Vascular endothelial growth factor A (VEGFA) is upregulated in several solid tumors, promoting tumor progression^1,2. In the hypoxic tumor microenvironment (TME), transcription factors like Hypoxic Inducible Factor-1 (HIF-1α and HIF-1β)^2,3, form heterodimers and bind to the Hypoxic Responsive Element (HRE) within the enhancer region of VEGFA and recruit transcriptional co-activators^4–6. The resulting interaction causes VEGFA overexpression, leading to aggressive tumor growth⁶. VEGFA is a well-established pro-angiogenic gene that also signals for tumor cell proliferation and survival through an autocrine loop, independently of angiogenesis^7–9. Hence, VEGFA has been a compelling target for treating various malignancies.

FDA-approved anti-VEGFA monoclonal antibodies, Bevacizumab and Ramucirumab, target either the VEGFA protein or its receptor, VEGFR2.^10–12 Small molecules, Sunitinib and Sorafenib, act as multi-targeted kinase inhibitors that target VEGFR2 receptors have been tested as an anti-cancer agent.¹⁰ However, challenges such as monotherapy failure, distant metastasis, VEGFA self-renewal upon withdrawal, and toxicity from non-specific targeting persist for the strategies mentioned above.¹³ Recently, the targeting of messenger RNA (mRNA) with small interfering RNA (siRNA) and antisense oligonucleotides (ASO) has shown clinical success across various diseases.¹⁴ Despite the success, RNA-targeted drugs have shown limited progress in modulating VEGFA expression for cancer therapy.¹⁵ Therefore, direct targeting at the core of VEGFA genomic DNA and blocking transcription factor binding to regulate its expression offers a rational therapeutic strategy. Previously, pyrrole-imidazole-based polyamides, designed to recognize nine base pairs, including GC, CG, and AT/TA stretches in the DNA minor groove, have been utilized to target the 6-nucleotide length HRE sequence of VEGFA DNA.^16,17 However, targeting a shorter sequence reduces the in vivo efficacy of polyamides and increases the risk of potential off-target effects owing to non-specific interactions. Therefore, the development of modalities capable of precisely targeting the VEGFA genomic DNA sequence and inhibit transcription holds potential therapeutic interest in oncology.

Peptide nucleic acids (PNAs) have gained attention for targeting genomic DNA and RNA for gene regulation. Structurally, PNAs consist of a neutral N- (2-aminoethyl glycine) backbone that confers resistance to enzymatic degradation.^18–20 PNAs can target the complementary DNA and RNA strand via Watson-Crick base pairing.²¹ In particular, prior studies have demonstrated that PNA: DNA heteroduplexes are thermally more stable than DNA: DNA duplexes.²¹ Although conventional PNAs have demonstrated promising results in targeting single-stranded DNA, yet targeting of genomic duplex DNA persists as a challenge owing to the thermodynamic stability of duplex genomic DNA strands.²² To overcome this chllange, next-generation gamma PNAs (γPNAs) have been developed offering effective targeting of genomic DNA than conventional PNAs. γPNAs possess a chiral backbone that preorganizes their structure into a right-handed helix, conferring stronger binding affinity and superior invasion of duplex genomic DNA compared to conventional PNAs.²³ γPNAs have been employed in targeting DNA²⁴, mRNAs²⁵, and non-coding RNAs²⁶, gene editing²⁷, and barcoding applications.²⁸ Based on the chemical functional group present in the γPNA backbone, it has been established that serine-γPNAs have superior properties compared to other classes of γPNAs.^29,30 However, limited studies demonstrated the preclinical efficacy of γPNAs in targeting genomic DNA in oncogenes and suppressing tumor growth in vivo.²⁴ Further, to mediate transfer across the nuclear membrane, a nuclear localization signal (NLS) was conjugated with γPNAs.³¹ Previously, triplex-forming serine-γPNA conjugated with a nuclear NLS has been used to target genomic DNA and inhibit c-Myc transcription in multiple preclinical lymphoma mouse models.²⁴ Similarly, BGA002 (PNA-NLS), developed by Biogenera SpA targeting the MYCN oncogene, has demonstrated efficacy in neuroblastoma and has advanced into a phase 1 clinical trial.^31,32

Here, we have established that γPNAs effectively target VEGFA genomic DNA to control tumor progression in a series of solid cancer cell line-based in vitro studies and a triple-negative breast cancer (TNBC) xenograft mouse model. Overall, we preclinically validated sequence-specific VEGFA genomic targeting platform using γPNAs, demonstrating its robust efficacy for cancer therapy.

Results

Design of γPNAs targeting VEGFA genomic DNA

The VEGFA gene is located on chromosome 6 (6p21.1), consists of eight exons, with its promoter region situated within exon 1, lacking a TATA box sequence.^7,33 Several transcriptional factor binding sites are present in the enhancer region upstream of exon 1. The transcriptional regulatory element, HRE cognate, is within the enhancer region of the VEGFA gene, spanning positions -947 to -942 coding (5’-TACGTG-3’).^16,17,34 The HRE cognate becomes functional in a hypoxic microenvironment, leading to VEGFA overexpression (Fig. 1A). Prior studies establish that targeting a short stretch of HRE cognate downregulates VEGFA transcription.^17,35

Fig. 1. Design of transcription inhibition by γPNA oligomers to target the VEGFA gene.

A Schematic representation of γPNA1-mediated downregulation of VEGFA transcription. γPNA1 blocks the interaction of the HIF-1 heterodimer complex at the regulatory element, HRE, within the VEGFA gene by forming stable γPNA1: DNA complex, thereby downregulating its expression (created with BioRender.com). B Diagram of the HRE cognate and the target site of γPNA1 on the human VEGFA gene (Gene ID: 7422). C Chemical structures of the PNA monomers used in the synthesis of γPNA sequences. D Sequences of γPNAs are designed to target the specified site. Green represents γPNA monomers, and black represents regular PNA monomers. VKRKKKP represents the nuclear localization signal peptide sequence. OOO indicates a 3,6,9-Trioxaundecanoic acid linker. γPNA3-T is conjugated with 3’ carboxy tetramethylrhodamine (TAMRA) dye.

Here, we designed and synthesized a series of γPNA-based constructs complementary to the selected HRE cognate site of the VEGFA genomic DNA (Fig. 1B–D). To achieve specificity, we have targeted the 20-nucleotide stretch of VEGFA genomic DNA using perfectly matched γPNAs (Fig. 1D, γPNA1). The serine-γPNA monomers were alternated with regular monomers to promote helical pre-organization in the sequence. A scrambled sequence, Scr-γPNA2 (Fig. 1D), was synthesized as a control. γPNA3-T (Fig. 1D) contains the same sequence as γPNA1, conjugated to 5-carboxytertramethylrhodamine (TAMRA) fluorophore for imaging studies. γPNAs and the scramble control were synthesized using Boc chemistry-based solid-phase synthesis. A NLS sequence, PKKKRKV, was conjugated to the 3’ end (C-terminus) of all the γPNAs for enhanced nuclear uptake. For purification of the synthesized γPNAs, Reverse-Phase High Performace Liquid Chromatography (RP-HPLC) was performed (Figure S1).

Cellular uptake and nuclear localization of γPNA in tumor cells

We assessed the cellular uptake and nuclear localization of the γPNA1 in vitro in solid cancer cell lines where VEGFA plays a key role in proliferation.^16,36,37 We incubated A549 (adenocarcinoma), MDA-MB-231 (TNBC), and HeLa (cervical cancer) with γPNA3-T to evaluate internalization using flow cytometry analysis. Based on prior studies, γPNA3-T was evaluated at concentrations of 2 μM and 4 μM.²⁴ To assess the impact of prolonged exposure on intracellular accumulation, cells were treated for 72 h. We observed a dose-dependent increase in the uptake of the γPNA3-T across all the tested tumor cell lines (Fig. 2A). The median fluorescence intensity (MFI) confirms the optimal cellular uptake at a 4 μM concentration of γPNA3-T across all tested cell lines (Fig. 2B). Therefore, a 4 μM concentration was selected for subsequent functional studies. Next, evidences from the confocal microscopy images confirmed significant nuclear accumulation of γPNA3-T in HeLa, MDA-MB-231, and A549 cells (Fig. 2C). Additionally, the 3-dimensional orthogonal plot confirms the presence of γPNA3-T (red puncta) across the XY and XZ planes in all the tested cell lines, validating nuclear uptake (Fig. 2D). A z-stack video of treated-A549 cells also demonstrated the accumulation of γPNA3-T inside the nucleus (Video S1).

Fig. 2. Internalization of γPNA3-T in tumor cells.

A Flow cytometry histograms of HeLa, MDA-MB-231, and A549 cells after 72 h of treatment with varying concentrations of γPNA3-T to assess cellular uptake. Results are shown in mean ± SEM (n = 3). B Median fluorescence intensity of PBS, and γPNA3-T with indicated concentrations quantifies the cellular uptake of γPNA3-T. Results are shown in mean ± SEM (n = 3). A one-way ANOVA was used for statistical analysis followed by Bonferroni’s test for multiple comparisons. C Confocal microscopy images of live HeLa, MDA-MB-231, and A549 cells after 72 h with γPNA3-T treatment (4 μM). 60× magnification view of the cells displaying γPNA3-T distribution in the nucleus. Scale bar: 5 μm. Blue indicates DAPI, and red indicates γPNA3-T. D 3D orthogonal view with XY and XZ planes from a sliced section to confirm γPNA3-T accumulation inside the nucleus (blue).

Invasion of γPNA1 at the target site of VEGFA genomic DNA

We evaluated target-specific genomic DNA invasion using a PCR based amplicon assay in HeLa, MDA-MB-231, and A549 cells. After treating cells with γPNA1 and Scr-γPNA2 for 72 h, genomic DNA was isolated and amplified using primers specific to the VEGFA locus. γPNA1 binding to the VEGFA genomic DNA sterically hinders the formation of PCR products (amplicons). As expected, the Scr-γPNA2-treated cells showed an amplicon, while no amplicon was observed with γPNA1-treated cells (Fig. 3A). These results confirm that γPNA1 binds sequence selectively to the VEGFA genomic DNA target site. Time-course studies in HeLa, MDA-MB-231, and A549 cells were conducted to elucidate the binding kinetics of γPNA1 to the genomic DNA target site. Detectable amplicons (∼70%, ∼50% and ∼25%) appeared at day 5 after treatment with γPNA1 in HeLa, MDA-MB-231, and A549 cells, respectively (Fig. 3B–D). The variability in the amplified dsDNA across cell lines could be attributed to the cell origin, proliferation rate, and its intrinsic characteristics. Next, we investigated whether strand invasion by γPNA1 at the VEGFA locus induced double-strand breaks (DSBs) or related genotoxicity. We performed a γH2AX foci assay as a measure of DSB. γH2AX foci are detected in the nucleus by immunofluorescence and represent a chromatin modification that occurs upon DSB due to DNA damage. Cells treated with Bleomycin (BLM) were used as a positive control for inducing DSBs. We did not observe any γH2AX foci in the γPNA1-treated HeLa, MDA-MB-231, and A549 cells in the immunofluorescence images (Figs. 3E, S2A, S2B), confirming the absence of DNA double-strand breaks. Next, changes in the γH2AX protein levels were also determined by Western blot analysis in MDA-MB-231 cells. As anticipated, γPNA1-treated cells did not show any alterations in γH2AX protein levels (Fig. 3F). We confirmed that the DNA duplex invasion by γPNA1 did not induce DSB or genotoxic effects, consistent with prior results.^24,38

Fig. 3. Binding of γPNA1 at the target site of VEGFA genomic DNA.

A Polymerase chain reaction (PCR) based amplicon assay confirming binding of γPNA1 to the VEGFA target site in HeLa, MDA-MB-231, and A549 cells after 72 h of treatment. Genomic DNA was extracted from control (PBS), γPNA1 (4 μM), and Scr-γPNA2 (4 μM) treated cells. Primers complementary to the flanking regions of the target site were used to amplify the region. Samples were separated on 3% agarose gel stained with ethidium bromide. B–D 3% agarose gel showing a time-dependent amplicon formation in HeLa, MDA-MB-231, and A549 cells treated with 4 μM of γPNA1 and Scr-γPNA2, monitored over a 5-day incubation period to assess the kinetics of amplicon generation (left). Quantification of PCR amplicons are presented as mean ± SEM (n=3; right). E Representative immunofluorescence images of γPNA1 (4 μM, 72 h), Scr-γPNA2 (4 μM, 72 h), PBS, and Bleomycin (BLM; 150 μM, 24 h) treated MDA-MB-231 cells after staining with γH2AX antibody. Blue indicates the nucleus, and red indicates γH2AX foci. The graph represents the γH2AX foci counted per field of view from different treatment groups. One-way ANOVA was used to determine the statistically significant difference between groups. Scale bar: 5 μm. F Western blot representing the levels of γH2AX protein in PBS, γPNA1, and Scr-γPNA2 (4 μM, 72 hours) treated MDA-MB-231 cells (left). Quantification of γH2AX protein levels with respect to Scr-γPNA2 is presented as mean ± SEM (n = 3; right).

Anti-transcriptional activity of γPNAs in VEGFA silencing

We evaluated the efficacy of γPNA constructs in HeLa, MDA-MB-231, and A549 cell lines. To simulate the hypoxic TME, cells were incubated with Deferoxamine (DFO) for 16-18 hours, following previously reported protocol.^16,35 DFO is known to stabilize HIF-1α and enhance the activity of the HIF-1-induced genes, including VEGFA.^35,39 Previous studies have demonstrated that DFO incubation increases VEGFA transcription while maintaining cell viability.^35,40 We initially measured VEGFA mRNA levels of DFO-incubated HeLa, MDA-MB-231, and A549 cells using gene expression analysis. VEGFA mRNA levels increased by ∼ 6- fold, following DFO incubation as compared to PBS (Figure S3A). DFO incubation further upregulated VEGFA downstream targets, such as Protein kinase B (PKB/ AKT1) and Signal transducer and activator of transcription 3 (STAT3). VEGFA promotes increased phosphorylation of AKT1, highlighting its key role in regulating cell growth, apoptosis, survival, and differentiation through the Phosphatidylinositol 3-kinase (PI3K)/ AKT1 or PKB pathway.¹⁰ VEGFA drives the recruitment of the JAK2/STAT3 pathway, leading to STAT3 induction and the formation of an autocrine loop that drives self-renewal.⁴¹ DFO incubation upregulated AKT1 and STAT3 levels by ∼1.5- fold across all tested cell lines (Figure S3B). Western blot analysis confirmed a ∼4- fold increase in VEGFA protein levels and ∼1.2-fold upregulation in AKT1 and STAT3 proteins across the tested cells (Figure S3C, S3D). Cell viability assays with Cell Titer Glo 2.0 established that DFO incubation did not adversely affect the cell viability as compared to the control (Figure S3E), consistent with the literature.⁴⁰ To confirm that DFO does not induce any DSBs, γH2AX foci assay was performed. DFO-treated HeLa, MDA-MB-231 and A549 cells did not show any γH2AX foci, indicating the absence of DSBs (Figure S3F). Hence, in subsequent experiments, the tumor cells were incubated with DFO to simulate hypoxic conditions.

To evaluate the effectiveness of targeting VEGFA genomic DNA and its impact on the tumorigenesis signaling pathway under hypoxia, gene expression analysis was conducted. Initially, to determine the optimal incubation period for γPNA1 for achieving maximum transcriptional inhibition, we conducted a time-dependent gene expression study across all cell lines. We observed maximum statistically significant downregulation of VEGFA in HeLa (~80%), MDA-MB-231 (~45%), and A549 (~50%) after 72-hour γPNA1 treatment followed by DFO incubation (Figure S4 and Fig. 4A). The downstream targets were also assessed after treatment with γPNA1 following DFO incubation. We observed ∼20% downregulation of AKT1, and STAT3 levels in γPNA1-treated HeLa, MDA-MB-231 and A549 cells compared to Scr-γPNA2 control (Fig. 4A). As expected, Scr-γPNA2 showed no effect on the expression of VEGFA and its downstream targets across the tested cell lines. The variability in VEGFA expression knockdown across different cell lines may arise from the inherent characteristics of tumor cells and post-transcriptional modifications of VEGFA. Next, we evaluated VEGFA expression change following varying doses of γPNA1 in MDA-MB-231 and A549 cells. The half maximal effective concentration (EC₅₀) for transcriptional inhibition was found to be ∼2 µM for MDA-MB-231 and ∼4 µM for A549 cells (Figures S5A, B). The difference in EC₅₀ across the cell lines could be attributed to various factors, including cell doubling time and turnover, or differences in intrinsic VEGFA expression levels. To note, we did not observe a decrease in the levels of VEGFA expression beyond ∼60%, even at a higher dose (8 μM). This could be attributed to the activation of other signaling pathways, endosomal entrapment of γPNA, or post-transcriptional modifications.

Fig. 4. Transcription inhibitory activity of γPNA1 in tumor cells.

A Relative fold change in the mRNA levels of VEGFA, AKT1, and STAT3 compared to Scr-γPNA2 (control) in HeLa, MDA-MB-231, and A549 cells after treatment with γPNA1 (4 µM) for 72 h, followed by DFO incubation (300 μM/ 50,000 cells) for 16–18 h. The results in each graph are represented as mean ± SEM (n = 3). A one-way ANOVA was used for statistical analysis, followed by Bonferroni’s test for multiple comparisons. B Western blot analysis representing changes in VEGFA protein levels in HeLa, MDA-MB-231, and A549 cells after treatment with γPNA1 and Scr-γPNA2 (4 µM) for 72 hours (top). Quantification of VEGFA proteins in γPNA1- and Scr-γPNA2-treated cells (bottom). The results in each graph are represented as mean ± SEM (n = 3). An unpaired two-sample t-test was used for statistical analysis. C Representative Western blots and quantification of STAT3 and AKT1 proteins in HeLa, MDA-MB-231, and A549 cells after treatment with γPNA1 and Scr-γPNA2 (4 µM) for 72 h. The results are expressed as mean ± SEM (n = 3). A one-way ANOVA was used for statistical analysis, followed by Bonferroni’s test for multiple comparisons.

Next, we performed Western blot analysis to evaluate changes in VEGFA protein expression after treating with γPNA1 following DFO incubation. We noted a ∼50% reduction in VEGFA protein levels in HeLa, MDA-MB-231, and A549 cells compared to Scr-γPNA2 (Fig. 4B). We observed approximately a ∼30% knockdown of AKT1 and STAT-3 proteins in these cells relative to the Scr-γPNA2 control (Fig. 4C). Additionally, as a positive control standard FDA-approved anti-cancer drug, Sunitinib was used. Sunitinib is a small molecule oral multi-targeted tyrosine kinase inhibitor that targets Vascular Endothelial Growth Factor Receptors (VEGFRs) and platelet-derived growth factor receptors (PDGFRs), and other receptors.⁴² Sunitinib prevents autocrine/paracrine uptake of VEGFA by blocking VEGFR2 receptors, thereby inhibiting its signaling in tumorigenesis and angiogenesis.⁴³ We observed a ∼75% downregulation of VEGFA protein levels compared to PBS following 6 μM Sunitinib treatment post DFO incubation across tested tumor cells (Figure S5C).

To confirm hypoxia-dependent VEGFA knockdown, we incubated MDA-MB-231 cells with an alternative HIF-1 stabilizer CoCl₂, after treating with γPNA1 and Scr-γPNA2. We observed ∼50% reduced VEGFA protein levels after treatment with γPNA1 followed by CoCl₂ treatment (Figure S6A). γPNA1-mediated VEGFA protein knockdown was consistent under both DFO- and CoCl₂- induced hypoxic conditions (Fig. 4B). Hence, our overall results confirmed that VEGFA downregulation by γPNA1 is hypoxia-mediated.

We have further evaluated whether restoration of VEGFA exogenously could rescue the impact of the γPNA1 treatment across the DFO-incubated tumor cells. We observed only ~10% VEGFA protein downregulation after VEGFA rescue (Figure S6C). The restoration of VEGFA protein suggested phenotypical rescue of the γPNA1 treatment, which was primarily mediated through VEGFA suppression. The plausible reason for VEGFA rescue could be attributed to the autocrine uptake of VEGFA through VEGFR2 receptors in tumor cells.^44,45

Effects on cell viability, proliferation, and migration after VEGFA downregulation

VEGFA knockdown affects the viability and proliferation of tumor cells. We assessed dose-dependent cell viability of HeLa, MDA-MB-231, and A549 cells using the Cell Titer Glo 2.0 assay after treatment with γPNA1 and Scr-γPNA2 post DFO incubation as compared to PBS control. We observed a dose-dependent decrease in tumor cell viability. A 4μM γPNA1 treatment reduced the cell viability by ∼60% across treated cell lines (Fig. 5A). As anticipated, Scr-γPNA2 did not exhibit any comparable reduction in cell viability across the batteries of tumor cells (Fig. 5A). Next, we assessed the cell viability on batteries of tumor cells after Sunitinib treatment as a positive control. We noted a ∼50% decrease in tumor cell viability compared to PBS after DFO incubation. (Figure S5D). We also evaluated the cell viability of MDA-MB-231 cells after treatment with γPNA1 and Scr-γPNA2 followed by CoCl₂ incubation. We observed a similar pattern in decreased cell viability following γPNA1 and CoCl₂ treatment to that of DFO treatment (Figure S6B). Additionally, we evaluated the γPNA1-treated tumor cell viability after VEGFA restoration. The VEGFA rescue increased the tumor cell viability by ~40% when compared to prior γPNA1 treatment (Figs. S6D, 5A).

Fig. 5. Cell viability, proliferative, apoptotic, and migratory activity following γPNA1 treatment.

A Percentage viability of HeLa, MDA-MB-231, and A549 cells after treatment with PBS, γPNA1 and Scr-γPNA2 at increasing doses (1, 2, and 4 µM) for 72 h after 16-18 h of DFO incubation. Each graph is represented as mean ± SEM (n = 3). A non-liner fit model has been applied followed by two-way ANOVA for statistical analysis and Bonferroni’s test for multiple comparison between same dose of different groups (PBS, Scr-γPNA2 vs. γPNA1). B Colony formation efficiency of HeLa, MDA-MB-231, and A549 cells after 72 hours of treatment with γPNA1 and Scr-γPNA2 (4 µM) and post 16–18 h of DFO incubation. The crystal violet stain indicates the number of colonies. The graph shows the mean ± SEM of the colony survival fraction (n = 3), with statistical significance determined by an unpaired two-sample t-test. C Fold change in early apoptotic tumor cells after 72 h of treatment with γPNA1 and Scr-γPNA2 (4 µM) for 72 hours in HeLa, MDA-MB-231, and A549 cells following 16–18 h of DFO incubation. Each graph is represented as mean ± SEM (n = 3), with statistical significance determined by an unpaired two-sample t-test. D Representative images of HUVECs monolayers 0- and 6-hours post-scratch, showing the effects of γPNA1 and Scr-γPNA2 on healing. Magnification 4×. The effect of γPNA1 on the scratch closure marked by the yellow lines. The scratch width was measured at four evenly spaced points along the entire scratch (left). The graph represents the quantification of scratch width (right). Each graph is represented as mean ± SEM (n = 7), with statistical significance determined by an unpaired two-sample t-test.

A clonogenic assay was used to determine the effects on cell proliferation after treatment with γPNA1 compared to a Scr-γPNA2. Colony survival decreased to ∼40%, ∼70%, and ∼60% in γPNA1-treated HeLa, MDA-MB-231, and A549 cells, respectively, relative to the Scr-γPNA2 control (Fig. 5B). Additionally, an annexin V apoptosis assay was performed to measure the early apoptotic cell population following treatment with γPNA1. We observed an increase in apoptosis of approximately ∼1.5- fold in γPNA1-treared HeLa, MDA-MB-231, and A549 cells, compared to the Scr- γPNA2 control (Fig. 5C). These findings suggest that γPNA1-mediated VEGFA downregulation in tumor cells leads to decreased cell proliferation and increased apoptosis.

Next, we evaluated the effects of γPNA1 on cell migration in HeLa, MDA-MB-231, and A549 cells by performing a scratch test. After 24 h, γPNA1-treated cells exhibited a scratch width of approximately ∼200 μm, compared to ∼100 μm in Scr-γPNA2-treated cells (Figure S7). Further, we assessed the effects of γPNA1 on cell migration in human umbilical vein endothelial cells (HUVECs). The endothelial cell migration is initiated by paracrine VEGFA signaling during tumorigenesis, resulting in abnormal vasculature and angiogenesis.⁴⁶ After 6 h, γPNA1-treated cells exhibited a scratch width of approximately ∼270 μm. In contrast, the Scr-γPNA2-treated cells showed a scratch width of ∼140 μm (Fig. 5D). These results collectively demonstrate that γPNA1 impaired tumor cell migration as well as reduced endothelial cell sprouting for angiogenesis.

In vivo anti-transcription efficacy of γPNA1 in MDA-MB-231 CDX mouse model

Following a comprehensive evaluation in cell culture-based assays, γPNA1 demonstrated the most pronounced phenotypic effects in the MDA-MB-231 cell line. MDA-MB-231 (TNBC) cell line is associated with VEGFA upregulation, poor prognosis, and limited treatment options.^37,47 Therefore, we evaluated the efficacy of γPNA1 in vivo using a subcutaneous MDA-MB-231 cell-derived xenograft (CDX) mouse model. A survival study was conducted to evaluate the preclinical efficacy of γPNA1 in this model. When the xenograft tumors reached approximately 100–150 mm^³, we administered three 5 mg/kg doses of the γPNA1 and Scr-γPNA2 systemically over a period of 7 days. Based on our prior observations in MDA-MB-231 xenografts, the dose and the survival endpoint of 1200 mm^³ tumor volume were considered.²⁴ From the tumor growth curve, we observed that between days 10–15, the γPNA1-treated group exhibited approximately ∼50% less tumor growth than the Scr-γPNA2-treated group (Fig. 6A). Based on this significant reduction in tumor growth, no further dosing was administered. Mice treated with γPNA1 showed a median survival of 29 days, compared to 21 days in the Scr-γPNA2-treated group (Fig. 6B).

Fig. 6. In vivo efficacy in an MDA-MB-231 cell-derived xenograft mouse model.

A The workflow outlines the in vivo study plan to evaluate the efficacy of γPNA1 in the MDA-MB-231 CDX mouse model (created with BioRender.com) (top). Tumor growth curve for MDA-MB-231 CDX mice treated with γPNA1 and Scr-γPNA2. Results are shown as mean ± SEM (n = 7). Two-way ANOVA was used to identify statistically significant differences between groups (bottom). B Survival graphs showed mice treated with 5 mg/kg doses of γPNA1 and Scr-γPNA2. The survival endpoint was a tumor volume of 1200 mm³ plotted against the number of days (n = 7 mice per treatment group). The Log-rank Mantel-Cox test was used to assess the statistical significance of survival rates. C Relative fold change in the VEGFA mRNA levels in γPNA1-treated mice relative to Scr-γPNA2 (control) post-survival study. D Relative fold change in the mRNA levels of AKT1, MAPK3, STAT3, and HIF-1α of γPNA1-treated mice compared to Scr-γPNA2 (control) after the survival study. E Western blot showing VEGFA protein expression (left) after treatment in the post-survival study. The graph on the right depicts the quantification of VEGFA protein fold change after treatment with γPNA1 relative to Scr-γPNA2 (control). F Representative immunohistochemistry images of Ki-67 in MDA-MB-231 CDX post-survival. Scale bar: 50 µm (top). The box plot shows Ki-67 quantification from tumor sections of the indicated groups. G Representative of TUNEL images in MDA-MB-231 CDX post-survival (top). Green indicates TUNEL; blue indicates DAPI. Scale bar: 50 µm. The graph (bottom) represents the quantification from tumor sections of the indicated groups. H Representative immunohistochemistry images of HIF-1α in MDA-MB-231 CDX post-survival (top). The graph shows HIF-1α quantification from tumor sections of the indicated groups (bottom). I Representative immunohistochemistry images of CD31 in MDA-MB-231 CDX post-survival (top). The graph shows CD31 quantification from tumor sections of the indicated groups (bottom). G–I Magnification 20×. Five images per tumor sections were quantified for γPNA1 and Scr-γPNA2 (n = 3). An unpaired two-sample t-test was used for statistical analysis.

We evaluated the efficacy of γPNA1 by measuring its ability to knockdown VEGFA and its downstream targets using gene expression analysis after the survival study. We observed a ∼23% decrease in VEGFA mRNA levels in the γPNA1-treated group compared to the Scr-γPNA2-treated group after the survival study (Fig. 6C). Furthermore, we also observed the downregulation of VEGFA-mediated downstream targets (AKT1, MAPK3, and STAT3) and upstream target (HIF-1α) involved in tumorigenesis (Fig. 6D). Western blot analysis showed a reduction of ~40% VEGFA protein levels in γPNA1-treated groups compared to Scr-γPNA2-treated groups after the survival study (Fig. 6E).

Immunohistochemical (IHC) analyses of Ki67, a proliferation marker, were performed after the survival study. We observed a ~ 70% decrease in staining in the γPNA1-treated group compared to the Scr-γPNA2-treated group (Fig. 6F). Evidence of tumor cell apoptosis was obtained by Terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining of tumor sections. TUNEL is a method for the detection of apoptotic DNA fragmentation.⁴⁸ An increase in TUNEL-positive cells was detected in the γPNA1-treated group (Fig. 6G), suggesting that tumor cell apoptosis might have induced by VEGFA suppression. In the Scr-γPNA2-treated group, TUNEL-positive cells were low. Through histological analysis of the tumor sections using hematoxylin and eosin (H& E) staining, a reduction of tumor cells is detected in γPNA1-treated groups compared to the Scr-γPNA2 (Figure S8A). These findings collectively indicate that γPNA1 treatment significantly arrests tumor growth, cell proliferation and induces apoptosis in the MDA-MB-231 CDX model, contributing to its anti-tumor activity. Next, the intra-tumoral hypoxia has been characterized by IHC staining of the treated tumor sections with HIF-1α following the survival study. We observed ~50% increase in the level of HIF-1α with the γPNA1-treated tumor sections as compared to Scr-γPNA2 (Fig. 6H). Increased in HIF-1α levels could contribute to initiation of an evasive activation of HIF-1α as compensatory negative feedback.^49,50 CD31 staining has been utilized to evaluate the intratumoral microvessel density of the tumor sections and to determine the extent of angiogenesis. We observed ~50% lower CD31 staining in the γPNA1-treated tumor sections than in the control group (Fig. 6I), suggesting in vivo tumor neovascularization impairment. Therefore, the evidence from the studies implies that γPNA1 also exerts anti-angiogenic efficacy through VEGFA transcriptional silencing.

To assess the safety of synthesized γPNA constructs, we evaluated complete blood counts (CBCs) and organ weights in the treatment groups. Throughout the survival study, we also monitored the weight of the mice in the treatment groups. As expected, there were no fluctuations in their weight (Figure S8B). Likewise, CBC parameters and organ weight analysis showed no signs of toxicity (Figure S8C, S8D). Overall, these results confirmed the safety of administering γPNA1 in vivo for targeting VEGFA genomic DNA.

Discussion

VEGFA is a clinically relevant target that has garnered significant attention due to its active role in signaling tumor progression.² VEGFA stimulates tumor cell proliferation and migration through autocrine signaling and promotes angiogenesis in endothelial cells through paracrine signaling.⁹ Consequently, increased VEGFA levels in aggressive hypoxic TME are linked to tumor burden. Over the past two decades, many attempts have been made to inhibit VEGFA, including the use of anti-VEGFA monoclonal antibodies, VEGFR2 receptor antagonists, VEGFA sequestrants, or multi-targeted kinase inhibitors.^10,13 Efforts have also been made to target VEGFA mRNA to downregulate its expression in tumor cell lines and animal models.⁵¹ In particular, ALN-VSP02, a lipid nanoparticle formulation containing two distinct siRNAs (siVEGF and siKSP), was evaluated in Phase 1 clinical trials (NCT01158079) for the treatment of solid tumors.^51,52 Veglin, a phosphorothioate ASO targeting VEGFA mRNA combined with Pemetrexed and Cisplatin, was developed for treating malignant mesothelioma and initiated a Phase 1 clinical trial (NCT00668499).⁵³ However, both ALN-VSP02 and Veglin were discontinued after the Phase 1 clinical trial. A key limitation of the aforementioned strategies is the sustained VEGFA replenishment, promoting cancer stemcell survival and self-renewal within the TME.^41,54 Therefore, our approach of directly targeting VEGFA at the genomic DNA level by blocking the transcription factors’ binding could be an efficient therapeutic strategy for transcription repression.

In general, targeting genomic DNA presents challenges due to its organization within chromatin⁵⁵ and its inherent thermodynamic stability as a double helix.²² The thermodynamic stability results from the Watson-Crick base pairing and stacking interactions between the nucleobases.²² Further, the interactions between DNA and histones restrict its availability. However, the genomic DNA undergoes conformation fluctuations called “DNA breathing”, which increase the accessibility of the nucleobases in the duplex.⁵⁶ The γPNA possesses ample binding affinity to target the genomic DNA via strand invasion and form the stable DNA-γPNA-DNA complex (also called invasion complex or D-loop) even in the presence of a homologous strand.

Another important consideration in genomic DNA targeting is the selection of the target site. In this study, the target site is selected based on prior work that utilized short polyamides for targeting the HRE cognate to inhibit VEGFA transcription.^17,35 However, polyamides lack specificity and may inadvertently modulate other HIF-regulated genes, such as Erythropoietin (Epo), glucose transporter 1 (GLUT1), pyruvate dehydrogenase kinase 1 (PDK1), and insulin-like growth factor 2 (IGF-2).^3,16

The γPNA’s chemistry can further influence duplex DNA targeting and strand invasion. In two parallel studies, a comparison was made between including diethylene glycol side chain (miniPEG γPNA) and serine-γPNA.^29,30 Serine-γPNA demonstrated superior strand invasion²⁴, gene editing efficiency³⁰, and anti-miR activity²⁹ due to its unidirectional helical conformation than that of miniPEG γPNA. Hence, we would anticipate that the utilization of alternate serine-γPNA monomers in the PNA sequences would show better transcription inhibition efficiency. Notably, triplex-forming serine γPNAs have exhibited significant transcriptional inhibition of the c-myc oncogene across multiple preclinical mouse models.²⁴ However, tc-γPNAs can only target homopurine-rich stretches in the duplex DNA. Therefore, we have demonstrated the potential of a single-stranded γPNA against VEGFA genomic DNA with a mixed sequence site to achieve transcriptional silencing. Moreover, the single-stranded γPNAs offer flexibility to target diverse DNA sequences across various oncogenes, such as KRAS, BCL-2, SOX2, NF-κB, STAT3 and other mutated genes dysregulated in cancer.⁵⁷

Cellular uptake studies showed significant uptake of TAMRA-conjugated γPNA in tumor cell lines. Gene expression and Western blot analyses confirmed the chemically (DFO and CoCl₂) induced hypoxic conditions in the tumor cells. Various functional and phenotypic assays indicated the effectiveness of targeting the VEGFA genomic DNA locus to inhibit transcription. However, the absence of statistically significant changes in the downstream targets of VEGFA may result from the convergence of other oncogenic signaling cascades and the involvement of multiple genes. Additionally, VEGFA rescue reinforces our hypothesis that γPNA1 primarily acts through VEGFA suppression. In vivo studies on the TNBC xenograft mouse model revealed that γPNA-mediated VEGFA genomic DNA targeting strategy reduced tumor growth and significantly improved the survival of the mice. Our previous work has already demonstrated passive accumulation of γPNA-NLS in tumors for up to 24 h after systemic administration targeting the c-Myc oncogene in vivo.²⁴ The tumor accumulation of γPNA-NLS may be attributed to enhanced permeability and retention (EPR) effect. Nevertheless, despite improved survival, the gap between the final γPNA1 dosing to euthanizing and evaluation of VEGFA mRNA and protein levels might have attributed to the lack of its statistically significant knockdown. Further, VEGFA transcription inhibition in vivo triggered an evasive activation of HIF-1α as compensatory negative feedback mediated by disrupted microvasculature and oxygen supply.^49,50 Consequently, such activation causes the accumulation of HIF-1α protein due to its impaired proteasomal degradation under hypoxia.⁵⁸ Surprisingly, HIF-1α transcript levels in γPNA1-treated tumor were lower than the Scr-γPNA2, which may be attributed to its mRNA instability, degradation, post-transcriptional modifications and non-uniform hypoxic microenvironment across tumor tissues.^17,59,60 Furthermore, the reduction in endothelial cell migration, a critical initiating step in the angiogenic cascade,⁶¹ mechanistically supports the in vivo tumor neovascularization impairment. Collectively, these preclinical findings support the potential of γPNAs in targeting VEGFA at the DNA level, thereby suppressing its transcriptional activity and attenuating cancer progression.

We have conducted a proof-of-concept study of the VEGFA genomic DNA-targeting strategy using γPNAs. Possible limitations include the lack of absolute quantification of γPNA distribution within the nucleus and cytoplasm. The small in vivo sample size could be another limitation when considering long-term treatments and disease resistance or recurrence. Furthermore, a short-term study in vivo design could have significantly reflected the VEGFA knockdown levels and its downstreams significantly. Diverse preclinical mouse models such as patient-derived xenograft and transgenic mouse models, which reflect tumor heterogeneity, could enhance clinical relevance. Identification of additional potential target sites leveraging advanced bioinformatic analysis within the VEGFA genomic locus could be a valuable investigation. In addition, genome sequencing and spatial transcriptome analysis can help navigate the effects on potential downstream targets and off-targets. Although γPNA-mediated VEGFA DNA targeting demonstrated significant efficacy in solid tumor cell lines, studies in anti-VEGFA drug-resistant cell lines are necessary to thoroughly evaluate its effectiveness. Furthermore, systemic delivery using nanoparticles, receptor-targeted ligands, or pH-low insertion peptide (pHLIP)-based technologies could be studied for active targeting in acidic TME. γPNAs could also be combined with other therapies, including histone deacetylase inhibitors (HDACi), anti-VEGFA monoclonal antibodies, chemotherapy, radiotherapy, and drugs targeting key signaling pathways such as HIF-1α, AKT-1, and STAT-3, serving as adjuvant therapies to potentiate drug responsiveness in cancer patients. Finally, the VEGFA genomic DNA targeting approach could be investigated for diverse VEGFA-driven diseases, including cancer, diabetic retinopathy, and age-related macular degeneration.⁶² Overall, this research provides a robust preclinical foundation for developing sequence-specific DNA-targeting agents for transcription inhibition of various genes across multiple disorders.

Methods

Synthesis of γPNA oligomers

γPNAs were synthesized using Boc and Fmoc chemistry on 4-methylbenzhydrylamine (MBHA) resin following previously established solid-phase synthesis protocols.⁶³ Regular PNA-Boc and serine-γPNA-Boc monomers used for γPNA1 and Scr-γPNA2 synthesis were purchased from ASM Research Chemicals GmbH. The γPNAs were synthesized from the C to N terminus (3’ to 5’) direction. Boc-11-Amino-3,6,9-Trioxaundecanoic acid (OOO, Biosynth Cat. # BXX-5523-PI) was used as a linker, and the classical nuclear localization signal (NLS, PKKKRKV) was conjugated on the C terminus utilizing Boc-protected amino acids. Carboxytetramethylrhodamine (TAMRA) dye was conjugated to the C terminus of γPNA3-T for visualization. γPNAs were cleaved from the resin using a cleavage cocktail comprising trifluoracetic acid: trifluoromethane sulfonic acid: m-cresol: thioanisole at a ratio of 4:2:1:1 (v/v). The γPNAs were collected, precipitated using diethyl ether, washed, and vacuum dried. For purification of the crude γPNAs, reverse-phase high-performance liquid chromatography (RP-HPLC) was used, and 0.1% trifluoroacetic acid (TFA) in water and 0.1% TFA in acetonitrile as mobile phases. The absorbance of the purified γPNAs was measured at 260 nm using UV-Vis spectrometry to determine their concentration.

Cellular uptake

The solid tumor cell lines used in the study are HeLa (Cat#: CCL-2; RRID:CVCL_0030), MDA-MB-231 (Cat#: HTB-26; RRID:CVCL_0062), and A549 (Cat#: CCL-185; RRID:CVCL_0023), which were obtained from the American Type Culture Collection (ATCC, USA). These cell lines overexpress VEGFA, which promotes their growth and proliferation.^16,36,37 Additionally, the MDA-MB-231 (TNBC) cell line was selected for xenograft mouse models because of its aggressive growth and poor clinical prognosis.^37,47 Prior to use, rigorous testing was performed to confirm that the cell lines were free of mycoplasma or other contamination, using the MycoAlert mycoplasma detection kit (Cat#: LT07-318, Lonza). For the experiments, the cells were subcultured for 12 generations. Eagle’s minimum essential medium (EMEM), Leibovitz’s L-15 Medium, trypsin-EDTA, penicillin-streptomycin, and fetal bovine serum (FBS) were purchased from ATCC. Cellular uptake was evaluated using flow cytometry. HeLa, MDA-MB-231, and A549 cells (50,000 cells/ well) were seeded in a 24-well plate (37°C, 5% CO₂). The cells were treated with two different γPNA3-T concentrations (2 and 4 μM). After 72 h, the cells were collected, washed, and suspended in PBS. The analysis was performed using an LSR Fortessa X-20 Cell analyzer (BD Biosciences), and the data were analyzed using FlowJo 10.8.1. software.

HeLa, MDA-MB-231, and A549 cells (50,000 cells/ well) were seeded in 8-chamber slides. The cells were treated with γPNA3-T at a 4 μM concentration. After 72 hours, the cells were washed twice with PBS to remove non-internalized γPNA-T. The nucleus of the cells was stained using Hoechst dye. The cells were visualized under a confocal microscope (Nikon AXR Confocal, USA). Step sizes of 3–5 μm were used to record the z-stacks, and ImageJ 1.52a software was used to project images with maximum intensity.

PCR amplicon assay

HeLa, MDA-MB-231, and A549 cells (50,000 cells/ well) were treated with PBS, γPNA1, and Scr-γPNA2 at 4 μM for 24, 48, 72, and 120 h with γPNA1 and Scr-γPNA2 to determine a time-dependent amplicon formation. Wizard SV genomic DNA purification kit (Promega, USA, #Cat A2360) was used to extract the genomic DNA from the treated cells. The genomic DNA concentration was measured using Nanodrop (Thermo Fisher USA). The target region in the VEGFA gene comprising the binding site for γPNA1 was amplified using the following primers purchased from Keck Oligonucleotide Synthesis facility:

Forward: 5’ GTTTGTGGAGCTGAGAACGG 3’

Reverse: 5’ AGGAACAAGGGCCTCTGTC 3’

200 ng of the extracted genomic DNA from treated tumor cell lines was amplified using 0.2 μM of forward and reverse primers and 25 μL of 2x PCR mix (Sigma, Cat #P2317) in a 50 μL volume. Afterwards, using a thermal cycler, the target region was amplified using 94 °C (2 min), 94 °C (30 s), 60 °C (45 s), 68°C (1 min), 68 °C (1 min) (40 cycles). The amplified product was further purified using the QIAquick PCR purification kit (Qiagen, USA). The purified PCR amplicon product (144 bp) was separated using a 3% agarose gel (Thermofisher Scientific cat# J32802-22) containing ethidium bromide for 30 min. The bands were visualized on a ChemiDoc imager (Bio-Rad, USA), and the quantification was performed using ImageJ 1.52a software.

γH2AX foci assay

HeLa, MDA-MB-231 and A549 cells were seeded at 50,000 cells/well on a glass coverslip in a 24-well plate. Cells were treated with PBS, DFO (300 μM), γPNA1 (4 μM), Scr-γPNA2 (4 μM), and bleomycin (150 μM; Sigma-Aldrich #cat B7216) for 24 h. Cells were then washed and fixed with 4% paraformaldehyde (PFA; Thermofisher Scientific cat# 28908) for 10 min at room temperature. The cells were then permeabilized with 0.1% TritonX (Thermofisher Scientific cat# HFH10) in PBS. After fixing the cells, the cells were blocked for 30 minutes using a blocking reagent (UltraCruz^® cat# sc-516214) in PBS, followed by incubation with anti-γH2AX antibody conjugated with phycoerythrin (PE; BioLegend; #613412) for 2 h at 37 °C. After washing with PBS, the coverslip containing the cells was mounted by adding the mounting medium containing DAPI antifade agent (ThermoFisher; P36962) for counterstaining of the nucleus. The immunofluorescence images were taken using a Keyence BZ-X800 fluorescence microscope (USA), and the analysis was performed using ImageJ 1.52a software.

Gene expression assay by RT-PCR

The mRNA levels were quantified in HeLa, MDA-MB-231, and A549 cells using real-time PCR (RT-PCR). 50,000 cells were seeded in a 24-well plate and treated with 4 μM γPNA1 and Scr-γPNA2 for 72 h, followed by 16–18 h of incubation with 300 μM Deferxamine (DFO; Sigma cat #D9533) or 100 μM cobalt chloride hexahydrate (CoCl₂; Thermo Scientific Chemicals cat #AAA1634618). Afterwards, the total RNA from the cell pellet was extracted using the RNeasy Mini Kit (Qiagen), and the concentration was measured using Nanodrop. cDNA was synthesized using a high-capacity cDNA reverse transcription kit (Applied Biosystem, USA) in a thermal cycler (Bio-Rad) following the manufacturer’s recommended cycling conditions. Taqman gene expression assay for VEGFA (Hs00900055), AKT1 (Hs00178289), STAT3 (Hs00374280), and GAPDH (Hs02786624) was used to amplify the mRNAs using the specified cycling conditions in the QuantStudio 5 real-time PCR detection system (Thermo Fisher Scientific, USA). GAPDH was used as the housekeeping gene, and fold change in mRNA expression was obtained by normalizing against the Scr-γPNA2 or PBS. The 2 ^−ΔΔC_t method was utilized to estimate the fold change of the target genes.

Western blot

The protein levels were quantified in HeLa, MDA-MB-231, and A549 cells using western blot analysis. 50,000 cells were seeded in a 24-well plate and treated with 4 μM γPNA1 and Scr-γPNA2 for 72 h, followed by 16–18 h incubation with 300 μM DFO. To confirm hypoxia-dependent knockdown of VEGFA, we further treated 50,000/ well MDA-MB-231 cells with 4 μM γPNA1 and Scr-γPNA2 for 72 h, followed by 24 h of incubation with 100 μM CoCl₂. Next, as a positive control, HeLa, MDA-MB-231, and A549 cells were treated with 6 μM Sunitinib (MedChemExpress cat #HY-10255A) for 48 hours, followed by DFO incubation. The Sunitinib dosing regimen was chosen based on its IC₅₀ value.^64–66 For the VEGFA rescue experiment, MDA-MB-231 and A549 cells were first treated with γPNA1 or Scr-γPNA2, followed by DFO incubation. 50 ng/mL exogenous VEGFA protein (MedChemExpress cat # HY-P7110A) was introduced following the manufacturer’s protocol throughout the treatment.⁶⁷ Total protein was extracted from cell pellets using 1x RIPA buffer (CST, #9806) containing protease inhibitor (ThermoFisher # 78437). The total protein concentration was estimated by absorbance-based Lowry protein assay using (Bio-Rad, USA). An equal amount of protein (35–50 μg) was loaded on SDS PAGE gel (4%–20% MP TGX stain-free gels, Bio-Rad) and separated at 200 volts for 33 min. The protein was then transferred to a PVDF membrane and blocked using 5% milk in 1X Tris-buffered saline containing 0.1% Tween 20 for 1 h. VEGFA (CST, #50661S, 1:250 dilution), STAT3 (CST, #12640 T, 1:1000 dilution), AKT1 (75692S, 1:1000 dilution), and γH2AX (CST, #9718S, 1:250 dilution) proteins were probed using rabbit monoclonal primary antibody in 5% milk in Tris-buffered saline containing 0.1% Tween 20 at 4 °C overnight. Cyclophilin B (CST, #43603S), vinculin (CST, #13901S), and β-actin (CST, #4970S) were probed as endogenous controls. The bands were detected using anti-rabbit IgG HRP-linked secondary antibody (CST, #7074) (1:2000 dilution, 5% milk in Tris-buffered saline containing 0.1% Tween 20) and HRP substrate (Millipore Sigma, USA). The blots were imaged using the ChemiDoc Imaging System (Bio-Rad, USA), and band intensities were quantified using ImageJ 1.52a software.

Cell viability assay

HeLa, MDA-MB-231, and A549 cells were seeded in 96-well plates at a density of 10,000 cells/well. The cells were treated with different concentrations of γPNA1 and Scr-γPNA2 (1, 2, and 4 μM) for 72 hours, followed by DFO (18 h) or CoCl₂ (24 hours) incubation. As a positive control, cells were treated with Sunitinib (6 μM, 48 h). For the VEGFA rescue experiment, 50 ng/mL exogenous VEGFA protein was introduced following the manufacturer’s protocol throughout the γPNA and DFO treatment. Cell viability was measured using a luminescence-based CellTiter Glo 2.0 assay (Promega, #G8461) according to the manufacturer’s instructions. Luminescence from viable cells was measured on an Infinite 200 PRO microplate reader (TECAN).

Cell proliferation assay

Cell proliferation assay in HeLa, MDA-MB-231, and A549 cells was conducted using a clonogenic assay. Cells treated with γPNA1 and Scr-γPNA2 (4 μM) for 72 h were trypsinized, and cell count was measured using a cell counter (TC20™ Automated Cell Counter, Bio-Rad, USA). About 100 cells from each sample were passaged to 6-well plates and allowed to expand until there were more than 50 cells per colony in the untreated sample when viewed under an inverted microscope (Laxco™ LMI-3000, Laxco Inc., USA). Colonies were washed with PBS and fixed using 2 mL of fixation solution (4% PFA in PBS) for 10 min. Fixation solution was aspirated, and cells were incubated in 1 mL of 0.5% (w/v) crystal violet solution for 2 h. Crystal violet was then removed by immersing wells in water, and plates were air-dried overnight. The number of colonies was counted for each sample and imaged. The survival fraction (SF) was then calculated using the following formula and plotted.

$$\mathit{Plating}\mathit{efficiency}\left(\mathit{PE}\right)=\frac{\mathit{no}.\mathit{of}\mathit{colonies}\mathit{formed}}{\mathit{no}.\mathit{of}\mathit{cells}\mathit{seeded}}X100$$ 1

$$\mathit{Survival}\mathit{fraction}\left(\mathit{SF}\right)=\frac{\mathit{no}.\mathit{of}\mathit{colonies}\mathit{formed}\mathit{after}\mathit{treatment}}{\mathit{no}.\mathit{of}\mathit{cells}\mathit{seeded}X\mathit{PE}}X100$$ 2

Apoptosis assay

Apoptosis was evaluated using the fluorescein isothiocyanate (FITC) annexin V apoptosis detection kit (BD Biosciences cat # 560931). HeLa, MDA-MB-231, and A549 cells were seeded in a 12-well plate at 100,000 cells/well. The cells were treated with 4 μM of γPNA1 and Scr-γPNA2 for 72 h. The cells were then washed with cold PBS and suspended in annexin V binding buffer. The cells were then counted and stained with phycoerythrin (PE) annexin dye and 7-amino-actinomycin (7AAD) as per the manufacturer’s instructions. After 15 h incubation in the dark, 400 μL of annexin V binding buffer was supplemented. Cells were acquired using the LSR Fortessa X-20 Cell analyzer, and data were processed using FlowJo 10.8.1. software.

Cell migration assay

Cell migration was assessed using the HeLa, MDA-MB-231, A549 and HUVEC cells. Human umbilical vein endothelial cells (HUVECs, Cat#: C-12203) and endothelial cell growth medium (C-22211) were procured from PromoCell (Heidelberg, Germany). The cells were treated with 4 µM of γPNA1 and Scr-γPNA2, and the scratches were marked using a 100–200 µL pipette tip. The plates were imaged at 0 and 24 h after scratch in HeLa, MDA-MB-231, and A549 treated cells, and images were captured using a Keyence BZ-X800 fluorescence microscope (USA). The plates were imaged at 0 and 6 h after scratch in HUVEC-treated cells, and images were captured using the Rebel microscope (Echo, California, USA). The scratch width at four evenly spaced points along the scratch was measured in each biological replicate.

Study approval

All the live animal experiments were performed at the University of Connecticut, Storrs campus, in accordance with relevant guidelines and regulations and approved by the Institutional Animal Care and Use Committee (IACUC). The authorization number for approved IACUC protocol is A24-037.

In vivo studies in xenograft mouse models

Male NSG mice (n = 14) (NOD.Cg-Prkdc<scid> Il2rg<tm1Wjl>/SzJ, strain 005557) of age 7 weeks, weighing 20–23 g, were procured from The Jackson Laboratory. 4 mice were kept in each cage and acclamatised for 2 weeks before injecting tumor cells. 2 × 10⁶ MDA-MB-231 cells suspended in L-15 medium were injected subcutaneously in the right flank of NSG mice after anesthesia, by administering isoflurane (0–5% titrated to effect) using a nose cone. A small bump developed in mice after 3 weeks. A Vernier caliper was used to measure the tumor volume, length (l), breadth (b), and height (h). Tumor volume was calculated using the formula for an ellipsoid (0.5236 × lbh). When the tumor volume reached 100–150 mm³, the mice were randomized using excel function = random() and blindly grouped (n = 7 per group). All the mice were included in the survival study without setting any inclusion and exclusion criteria.

Survival study

Mice bearing tumors about 100–150 mm³ were blindly divided into two groups and treated with either γPNA1 or Scr-γPNA2 (n = 7 per group). Scr-γPNA2 was used as a control group. A small sample size was selected because this study represents an initial evaluation of γPNAs for VEGFA transcription inhibition. None of the mice were excluded from the study during the survival analysis. Freeze-dried γPNAs were dissolved in endotoxin-free water and passed through filters. The dissolved γPNAs were administered at a 5 mg/kg dose on days 1, 4, and 7 systemically. The alteration in tumor volume and body weight was monitored and measured every day. When the tumor volume reached 1200 mm³, mice were euthanized using CO₂ in inhalation chamber, gas where flow rate will displace 30–70% of chamber volume per minute. Cardiac puncture was performed to collect the blood in 1.5 mL tubes containing 0.5 M EDTA. After euthanizing, organs, including the tumor, liver, kidney, spleen, heart, and lung, were collected and weighed. Tumor sections and all other organs were stored in 10% formalin. The complete blood count (CBC) analysis was performed on the collected blood samples using a Sysmex CBC analyzer (USA).

Tumor dissociation to extract RNA and protein

The tumor fragments collected from the survival study were processed to enrich the implanted human tumor cells. The tumor fragments were cut into small pieces under sterile conditions and enzymatically dissociated using dispase (Stemcell Technologies, #100–0396), collagenase (Worthington, #LS004194), and L-15 medium at 37 °C for 2 h. The dissociated tumor fragments were centrifuged, washed with PBS, and passed through a 70 μm filter. The resulting tumor cell suspension was centrifuged and incubated with 1–2 mL of trypsin at room temperature for 5 min. Cells were then diluted in L-15 medium and passed through a 40 μm filter. The collected cell suspension was further centrifuged and resuspended in 0.7 mL of red blood cell (RBC) lysis buffer (Invitrogen cat# 00-4333-57) at room temperature for 4 min. Cells were subsequently diluted in PBS and centrifuged again, and the final cell pellet was suspended in 0.5% BSA. Cell count was determined, and 2 × 10⁷ live cells were incubated with 20 μL of mouse cell depletion cocktail (Miltenyi Biotec, #130-104-694) at 4 °C in the dark for 15 min. Cell suspension was then diluted to 0.5 mL using 0.5% BSA and passed through the LS column (Miltenyi Biotec, #130-042-401). The collected flow-through cells were the enriched human tumor cells. Cells were centrifuged, and pellets were stored at −80 °C for further analyses. Three samples from each group were blindly selected without any bias for analysis such as gene expression and western blot analysis.

Histological processing, Immunohistochemistry, and TUNEL assay

For tumor sections, n = 3 mice from each group were selected blindly without any bias. Tumor tissue sections (6 sections, 5 μm) from each mice were prepared from paraffin-embedded blocks blindly. The sections were stained using Mayers hematoxylin (Sigma-Aldrich, # 51275) and eosin Y (Fisher Scientific, # E511-25), and the images were captured using Rebel microscope (Echo, California, USA). For immunohistochemistry, the slides were heated at 60 °C for 15 min in a hot air oven to perform dewaxing. Sequential dipping of tissue sections was performed to deparaffinize using xylene for 10 min, followed by hydration with 100-75% ethanol. Using the low pH antigen retrieval buffer (Thermo Fisher, #00-4956-58) in a steamer at 95 °C, antigen retrieval was conducted. The sections were washed with phosphate-buffered saline containing 0.05% Tween 20 (PBST). Subsequently, 2.5% normal horse or sheep serum was used for blocking for 30 min at room temperature. The primary antibodies for Ki-67 (1:200 dilutions; CST #9027S), HIF-1α (1:100, Invitrogen #14-9100-80), CD31(1:100, BD Pharmingen # 550274), staining were incubated at 4°C overnight. After washing with PBST, peroxidase blocking (3% H₂O₂) was performed for 10 min at room temperature. The sections were further incubated with the ImPRESS HRP–polymer horse anti-rabbit secondary antibody (Vector Laboratories; MP-7401) for 30 min at room temperature or biotin-conjugated secondary anti-mouse antibody (1:200; Rockland; 610-1602) for 2 h followed by streptavidin HRP (1:200) for 30 min at room temperature. Freshly prepared 3,3′-diaminobenzidine (DAB) (Vector Laboratories; SK4100) solution was supplemented to each section for 10–20 min After 10 min of hematoxylin counterstaining, the sections were mounted using DPX mounting media (Electron Microscopy Sciences, #13510).

TUNEL (Terminal deoxynucleotidyl transferase dUTP nick end labeling) (Click-iT TUNEL Alexa Fluor 488 imaging assay kit, ThermoFisher, #cat C10617) assay was performed to evaluate apoptotic cells in the tumor tissues following the manufacturer’s protocol. Briefly, tissue sections were de-paraffinized, followed by dehydration with ethanol. Dehydrated sections were fixed in 4% PFA, then permeabilized using DNase-free Protease K solution. The sections were then incubated with the TUNEL reaction mixture containing TdT. After the completion of the TUNEL reaction, sections were treated with the Click-iT reaction mixture. Subsequently, sections were counterstained with DAPI and mounted with DPX mounting media. A Keyence BZ-X800 microscope (USA) and Rebel microscope (Echo, California, USA) were used to image the slides, and ImageJ 1.52a software was used to measure the intensity. All data points (n = 3 separate mice per group, and n = 5 pictures were quantified per tumor segment) are plotted in the results.

Statistical analysis

GraphPad Prism 10 (version 10.6.1) was used for statistical analysis. The data were presented as mean ± SEM, and the number of replicates is included in the figure captions. Statistical significance between two groups was assessed using an unpaired two-tailed t-test. One-way ANOVA was performed to compare the means across three or more independent groups defined by a single factor. The Two-way ANOVA was performed to test statistically significant differences between two independent variables. For multiple comparisons, a post hoc statistical analysis (Bonferroni’s test) has been implemented comparing selected pairs of means and is mentioned in the figure legends. For in vivo studies, animals were randomly assigned to groups to minimize bias, and based on prior experience with animal models, the sample size was selected^24,26. Log-rank Mantel-Cox test was performed for the survival study to evaluate statistically significant differences between groups. The p values lesser than 0.05 have been considered statistically significant.

Author contributions

A.D.: Conceptualization, formal analysis, validation, investigation, methodology, writing-original draft, writing-review and editing. S.P.: Formal analysis, supervision, validation, investigation, writing-review and editing. P.D.: Formal analysis, supervision, validation, investigation, writing-review and editing. R.R.G: Formal analysis, supervision, validation, investigation, writing-review and editing. A.V.: Formal analysis, supervision, validation, investigation, writing-review and editing. R.B.: Conceptualization, formal analysis, supervision, funding acquisition, validation, investigation, methodology, writing-original draft, writing-review and editing.

Data availability

The datasets generated and/or analyzed during the current study are partly provided in the supplementary information. Other datasets are not publicly available due to institution/ethical restrictions but are available from the corresponding author on reasonable request.

Code availability

Not applicable in this study.

Competing interests

R.B. is a co-founder of Zeal Therapeutics for kidney targeting delivery. R.B., A.D., and S.P.P. are inventors on the provisional patent application No. 63/940,802, which covers the work present in the manuscript and the patent status is currently pending.

Supplementary information

The online version contains supplementary material available at https://doi.org/10.1038/s41698-026-01565-0.