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. 2025 Sep 11;63(1):1–13. doi: 10.1159/000548353

Immunosuppression Drugs Exhibit Differential Effects on Endothelial Cell Function

Aly Elezaby a,b, Ryan Dexheimer a, David Wu a,c, Sze Yu Chan a,b, Ines Ross Tacco a,b,d, Ian Y Chen a,b,d, Nazish Sayed a,c, Karim Sallam a,b,✉
PMCID: PMC12772628  NIHMSID: NIHMS2113454  PMID: 40934129

Abstract

Introduction

Immunosuppressive medications are widely used to treat patients with neoplasms, autoimmune conditions, and solid organ transplants. Prior studies indicate that immunosuppression drugs can cause adverse vascular remodeling. Given the systemic effects of the drugs, elucidating cell-type-specific drug effects has been challenging.

Methods

We utilized induced pluripotent stem cell-derived endothelial cells to investigate the role of widely used immunosuppression drugs on endothelial cell function.

Results

We found that among immunosuppression agents, sirolimus reduced basic endothelial cell functions including cell migration, proliferation, acetylated LDL uptake, mitochondrial respiration, and angiogenic properties, while tacrolimus only reduced nitric oxide release.

Conclusions

This model allows for investigation of differential effect of immunosuppression drugs on endothelial function that can elucidate the mechanisms contributing to clinically observed adverse vascular profiles.

Keywords: Immunosuppression, Vascular remodeling, Endothelial cell function, Transplant

Introduction

Immunosuppressant agents, including mTOR (mammalian target of rapamycin) inhibitors and calcineurin inhibitors, are essential in preventing organ rejection following transplantation [1]. However, their use is associated with potential side effects, many of which impact the vascular system with long-term complications [2]. While calcineurin inhibitors are associated with an increased risk of hypertension, mTOR inhibitors, such as sirolimus, are associated with a lower incidence of hypertension [3]. However, mTOR inhibitors have been linked to the development of capillary leak, leading to peripheral edema and lymphedema [4]. Furthermore, while mTOR inhibitor use increases serum lipids [5], they paradoxically are associated with a lower risk of atherosclerosis [6].

In heart transplantation, immunosuppressants have variable effects on the attenuation of cardiac allograft vasculopathy (CAV), a condition marked by pathologic vascular remodeling and fibrosis and a major driver of graft dysfunction and mortality [7]. Calcineurin inhibitors are largely associated with an increased risk of CAV, while mTOR inhibitors attenuate this risk [8]. Even though immunosuppressants are known to cause endothelial injury, inflammation, and dysregulation of vascular smooth muscle cell proliferation, the precise mechanisms by which immunosuppressants contribute to transplant vasculopathy are not yet fully understood [9]. Thus, elucidating the impacted cellular subtypes and the cell-specific changes that drive abnormal vascular phenotype can help highlight therapeutic targets to attenuate pathologic vascular remodeling and minimizing cardiovascular complications in transplant recipients.

Our aim here was to investigate the direct role of immunosuppressive agents on the endothelium. Human-induced pluripotent stem cell-derived endothelial cells (iPSC-ECs) were used to investigate the effects of calcineurin inhibitors (tacrolimus) and mTOR inhibitors (sirolimus) on critical components of vascular remodeling.

Methods

EC Differentiation

iPSCs used in this study were provided by the Stanford Cardiovascular Institute Biobank from three healthy donors. We cultured these iPSCs in StemMACS™ iPS-Brew media until cells reached 85% confluence. Differentiation was started with RPMI-B27 minus insulin media (Life Technologies) with 6 μm CHIR99021 (GSK3 inhibitor) for 2 days to drive cells down the mesodermal lineage, as previously described [10]. From days 2–4, cells were cultured in RPMI-B27 minus insulin media with 2 μM CHIR99021 media. From days 4–12, cells were cultured in EGM™-2 Endothelial Cell Growth Medium-2 (Lonza CC-3162) supplemented with 50 ng/mL vascular endothelial growth factor (PeproTech), 10 μM SB 431542 (Tocris), and 20 ng/mL fibroblast growth factor 2 (PeproTech) where media are changed on days 4, 6, 8, and 10. On day 12, cells were dissociated with TrypLE for 6–8 min and non-endothelial cells (ECs) were separated through MAC sorting with CD144 MicroBeads (Miltenyi Biotec). Purified ECs (passage 0) were seeded onto 10 cm dishes coated with 0.2% gelatin and cultured in EGM2 medium with 10 μM SB 431542. To passage iPSC-ECs, cells were dissociated with TrypLE for 5 min and transferred to plates coated with 0.2% gelatin and cultured in EGM2 media without supplements for downstream experiments (passage 1). The iPSC-ECs used in this study were cultured until passage 2.

Drug Treatment

For each of the experiments, iPSC-ECs from three healthy donors were treated with vehicle (control), tacrolimus (1 μM), or sirolimus (50 nm) for 5 days. Drug dosing was repeated with media change every 24 h. Drug treatment dose and duration were based on the Cmax dose of tacrolimus and sirolimus with higher adjustment to account for daily dosing and shorter duration of exposure in our model compared to chronic treatment clinically. The doses utilized did not affect cell viability.

Fluorescence-Activated Cell Sorting Analysis of iPSC-ECs

iPSC-ECs were harvested by trypsinization and resuspended in cold fluorescence-activated cell sorting buffer made of 2% fetal bovine serum and 2 mm ethylenediaminetetraacetic acid. Cell aliquots were either unstained or stained with either BV421-conjugated mouse anti-human CD144 antibody (5 μL/100 μL staining volume; BioLegend) or BV421-conjugated mouse anti-IgG1, κ (isotype control; 5 μL/100 μL staining volume; Bio Legend) for 30 min in the dark. Afterward, cells were washed with fluorescence-activated cell sorting buffer and added propidium iodide (Invitrogen) prior to analysis with the CytoFLEX LX flow cytometer (Beckman Coulter). During flow analysis, sequential gating strategies were implemented to gate out cell debris, doublets, and propidium iodide-labeled dead cells. Positivity gating was based on unstained cells, whereas isotype control was used to rule out nonspecific binding. All flow data analyses were performed using the CytExpert 2.4.0.28 software (Beckman Coulter). One representative cell line was tested.

Scratch-Wound Assay

The scratch-wound assay was adapted from a previously established protocol [11]. ECs were cultured on a 12-well plate until 95–100% confluent and treated for 5 days with vehicle (control), tacrolimus (1 μM), or sirolimus (50 nm). A single line, approximately 500 μM wide, was scratched in each well. After washing, fresh complete EGM2™ was added to the cells and wells underwent serial brightfield imaging of the scratch at 10× magnification on the Keyence BZ-X800 at 0 h and at 24 h (after incubation at 37°C, 5% CO2, and 20% O2). Images were analyzed manually using ImageJ to measure cell-free scratch area. The speed of cell migration was determined from the change in the width of the empty space from 0 h to 24 h divided by 24 h. For each well, the scratch closure percentage was calculated by dividing the change in empty space over the 24 h by the initial scratched area. These values were exported to GraphPad Prism 10 and a one-way ANOVA was performed to determine statistical significance. Three different cell lines were tested and each was tested in 4 technical replicates (4 individual wells) (N = 12 for each condition).

Low-Density Lipoprotein Fluorescence Assay

ECs were cultured in a 6-well plate and treated with vehicle (control), tacrolimus (1 μM), and sirolimus (50 nm) for 5 days. The cells were incubated at 37°C, 5% CO2, and 20% O2 for 5 min and then the cells were gently pipetted off the wells. The TrypLE-cell suspension mix was added at a 1:1 ratio to complete EGM2™ media in a 15 mL confocal tube. The cells were centrifuged for 5 min at 300 rpm. EGM2™ was used to resuspend the cells and the number of ECs was calculated using a Countess 3 automatic cell counter (Invitrogen). In 8-well chamber slides, coated with Matrigel™ (Fisher Scientific, CB-40230C), ECs were seeded at 6 × 103 cells in complete EGM2 media and incubated at 37°C, 5% CO2, and 20% O2 for 3 h and subsequently serum-starved overnight. Acetylated Low-Density Lipoprotein Alexa Fluor™ 594 conjugate (Thermo Fisher Scientific, L35353) was added directly to each well and incubated at 37°C for 4 h. After incubation, the cells were washed with PBS containing calcium and magnesium (Thermo Fisher Scientific, 14040133). A cover slip was placed on the slide and immediately imaged. Fluorescent imaging was performed at ×20 using a Texas Red filter on the Keyence BZ-X800. Corrected total cell fluorescence was performed via ImageJ. For each image, intracellular fluorescence was measured, corrected for cell area and background fluorescence. These values were analyzed via one-way ANOVA on GraphPad Prism 10. All 3 cell lines were tested; for each condition, 9 wells (technical replicates) were used, each well harboring 91–181 cells.

Cell Viability Assay

ECs were cultured on a 96-well plate (Costar, 3603) until 95–100% confluent and treated with vehicle (control), tacrolimus (1 μM), and sirolimus (50 nm) at 37°C, 5% CO2, and 20% O2. After treatment, the cells were incubated with NucBlueTM Live Cell Stain ReadyProbesTM reagent (Thermo, R37605) for 30 min, followed by a cell count completed with BioTek Cytation5. Statistical analysis was performed with one-way ANOVA in GraphPad Prism 10. Three cell lines were used with each condition being tested in 3 wells (technical replicates) resulting in n = 9 in each condition.

Angiogenesis (Tube Formation Assay)

The angiogenesis assay was adapted from a previously established protocol [12]. iPSC-ECs were treated with vehicle (control), tacrolimus (1 μM), and sirolimus (50 nm) on a 6-well plate for 5 days and seeded at 5 × 104 cells in complete EGM2™ media (Lonza Bioscience, CC-3156 and CC-4176) on Basement Membrane Matrix (Fisher Scientific, CB-40234A)-coated 24-well plates. Cells were incubated at 37°C, 5% CO2, and 20% O2 for 8 h and underwent brightfield imaging at ×10 magnification on a Keyence BZ-X800. Images were analyzed using a well-established angiogenesis analyzer plug-in on ImageJ to quantify branch and semgent quantitiy and length parameters [13]. On ImageJ, the raw image files were converted to RGB color and then analyzed using the “HUVEC Phase Contrast” option under the “Network Analysis Menu.” The results were exported from ImageJ and analyzed using one-way ANOVA on GraphPad Prism 10. Each well was plated into 3 replicates per cell line (n = 27–30 data points from 9 wells per condition) (3 cell lines with 3 replicates per cell line).

Nitric Oxide Assay

ECs were cultured at 95–100% confluency on a 6-well plate and treated for 4 h with vehicle (control), tacrolimus (1 μM), and sirolimus (50 nm). After washing, cells were incubated in Opti-MEM reduced serum medium (Thermo Fisher Scientific, 31985062) at 37°C, 5% CO2, and 20% O2 for 1 h. The nitric oxide assay was performed per Greiss Reagent Kit protocol for nitrite determination (Thermo Fisher Scientific, G7921). Cells were treated with angiotensin-II (MedChemExpress, HY-13948) at 200 nm for 48 h with media change every 24 h. Experimental samples were measured in triplicates and standard curve was measured in duplicates. In a clear 96-well plate, 150 μL of the experimental samples (in triplicates) and standard solutions (in duplicates) were added along with 20 μL of prepared Greiss Reagent, incubated at room temperature for 30 min, and absorbance measured using a Cytation5 (BioTek) to determine nitric oxide concentrations based on standard curve. These values were exported to GraphPad Prism 10 and analyzed by one-way ANOVA to determine statistical significance between treatment groups (n = 21–30 wells per condition from 3 cell lines). For angiotensin-II treatment, media were collected from one well per cell line and separated into 3 technical replicates for NO concentration detection, n = 9.

eNOS Expression by qRT-PCR

At passage 1, iPSC-ECs from the various treatment groups (control, sirolimus, tacrolimus) were collected with TRIzol®. Total RNA was isolated by using the Direct-zol™ RNA Microprep Kit (Zymo Research, #R2062). The iScript™ cDNA Synthesis Kit (Bio-Rad, #1708891) was used to synthesize cDNA according to manufacturer instructions. The TaqMan™ Gene Expression Assay (Applied Biosystems™, #4444556) and primers were used to quantify the expression of GAPDH and NOS3 for each of the conditions. Three replicates of each line were used for each condition (n = 9 in each condition).

Seahorse XF Cell Mito Stress Test Assay and XF Real-Time ATP Rate Assay

The Seahorse Mitochondrial Stress Test and the XF Real-Time ATP Rate Assays were conducted per manufacturer’s protocol (Agilent Technologies). ECs were cultured on an XFe96 Seahorse microplate (Agilent Technologies, 102340-100) or XFe24 Seahorse microplate (Agilent Technologies, 100882-004) until 95–100% confluent and treated for 5 days prior to performing the Seahorse assay. On the day of the experiment, cells were incubated in Seahorse XF DMEM medium (Agilent Technologies, 103575-100) supplemented with 1 mm sodium pyruvate (Agilent Technologies, 103578-100), 10 mm glucose (Agilent Technologies, 103577-100), and 2 mml-glutamine (Agilent Technologies, 103579-100). Per ATP Rate Assay protocol, oxygen consumption rate (OCR) and extracellular acidification rate were measured in cells treated with 1.5 μM oligomycin (via Port A) followed by 0.5 μM antimycin A and 0.5 μM rotenone (via Port B) (Agilent Technologies, 103592-100). Glycolytic ATP production rate (pmol ATP/min) is measured as glycolytic proton efflux rate (pmol H+/min). Mitochondrial ATP production rate is calculated as OCRATP (pmol O2/min) × 2 (pmol O/pmol O2) × P/O (pmol ATP/pmol O). Per mitochondrial stress test protocol, OCR and extracellular acidification rate were measured in cells treated with 1.5 μM oligomycin (via Port A), 2 μM FCCP (via Port B), and 0.5 μM antimycin A and 0.5 μM rotenone (via Port C) (Agilent Technologies, 103010-100). At the end of the Seahorse experiment, cell count was completed using NucBlue™ Live ReadyProbes™ (Thermo Fisher Scientific, R37605) using a BioTek Cytation5 to normalize OCR values. Basal respiration is calculated as initial OCR with non-mitochondrial (after antimycin A + rotenone) OCR subtracted. Proton leak is calculated as post-oligomycin OCR with non-mitochondrial (after antimycin A + rotenone) OCR subtracted. Maximal respiration is calculated as post-FCCP OCR with non-mitochondrial (after antimycin A + rotenone) OCR subtracted. Spare respiration is calculated as maximal respiration (post-FCCP OCR) with basal respiration subtracted. Statistical analysis was performed with one-way ANOVA in GraphPad Prism 10 (for the mitochondrial stress test assay, n = 6–9 with 2–3 wells per cell line per condition and for the ATP rate assay, n = 5–6 with 1–2 wells per cell line per condition using all 3 cell lines).

Statistical Analysis

Values are presented as mean ± SD relative to the average value for the control group unless otherwise stated. In experiments with two groups, group differences were assessed by Student’s unpaired two-tailed t test. In experiments with more than two groups, one-way ANOVA with Tukey’s multiple comparison test was used. Statistical significance was established at p < 0.05 (GraphPad Prism).

Results

EC Purity

We examined the effects of immunosuppressant agents on ECs derived from iPSCs from three control subjects using established monolayer protocols [10]. To determine the purity of the iPSC-EC population, expression of the EC marker CD144 was measured by flow cytometry and found to be >91% (Fig. 1). iPSC-ECs were treated with tacrolimus and sirolimus, revealing changes in EC function with significant differences between the drug classes.

Fig. 1.

(A) FACS analysis showing gating strategies of sorting endothelial cells. Sorting is performed by first cells are identified by measuring forward scatter area and side scatter area, and then sorted by forward scatter area and side scatter height. Then viable cells are sorted by forward scatter area and propidium iodide uptake. Lastly CD144+ cells are identified by sorting for CD144 antibody. (B) For the first biological replicate there is FACS analysis graph demonstrating CD144 on the X-axis and count on the Y-axis, The first peak in red and green indicates unstained and isotype control peaks and then the second peak indicates cells that are anti-CD144 positive which amounts to 93.1%. (C) For the second biological replicate there is a FACS analysis graph demonstrating CD144 on the X-axis and count on the Y-axis. The first peak in red and green indicates unstained and isotype control peaks and then the second peak indicates cells that are anti-CD144 positive which amounts to 91.3%. (D) For the third biological replicate there is a FACS analysis graph demonstrating CD144 on the X-axis and count on the Y-axis. The first peak in red and green indicates unstained and isotype control peaks and then the second peak indicates cells that are anti-CD144 positive which amounts to 98.2%.

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FACS analysis of the purity of iPSC-ECs. a Gating strategies to isolate singlet viable CD144+ iPSC-ECs. Overlay histograms of unstained (red), isotype control-stained (green), and CD144 antibody-stained (blue) iPSC-ECs derived from 3 different individuals (b–d), with their corresponding purities (% positive for CD144 expression) indicated. n = 30,074–30,371 from 1 cell line.

Sirolimus-Treated ECs Exhibit Decreased Cell Migration and Scratch Closure

We conducted a scratch assay to examine the differential effects of tacrolimus and sirolimus on EC migration and wound healing (Fig. 2). The assay manually disrupts the endothelial monolayer by “scratch” and then assesses the size of the cell-free zone in the monolayer 24 h later. iPSC-ECs treated with sirolimus showed 68% decrease in cell migration compared to controls, whereas tacrolimus treatment did not differ from control with respect to cell migration. In addition, sirolimus resulted in a 72% decrease in scratch closure compared to the controls. Tacrolimus treatment, on the other hand, did not result in any significant change in scratch closure compared to the control group.

Fig. 2.

(A) Demonstrates a schematic cartoon of the assay. First a mechanical scratch is performed on a monolayer of endothelial cells creating a gap in the monolayer. After 24 hours that gap is closed by dividing endothelial cells. (B) Representative images of scratch gaps created in monolayer of endothelial cells and size of gaps 24 hours later in control, sirolimus-treated showing persistent large gap at 24 hours, or tacrolimus treated cells looking similar to control. (C) Bar graph with dot blots of indexed cell migration on the Y-axis with X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). The bar graph shows significant reduction in cell migration with sirolimus (red) compared to control (green) or tacrolimus (blue). Bar graph with dot plot with indexed scratch closure percentage on the Y-axis with X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). Sirolimus (red) treatment shows significant reduction in scratch closure compared to control (green) or tacrolimus (blue).

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Sirolimus-treated ECs exhibit decreased cell migration and scratch closure. a Schematic of scratch assay. b Representative images of scratch closure at times 0 and 24 h in vehicle-treated control cells, sirolimus-treated cells, and tacrolimus-treated cells. c Indexed rate of cell migration and scratch closure percentage in cells treated with sirolimus (Siro), tacrolimus (Tac), or vehicle (control). 4 technical replicates (4 individual wells) were used for each of the 3 cell lines. n = 12 for each condition. ***p < 0.001 using one-way ANOVA with Tukey correction for multiple comparisons.

Sirolimus-Treated ECs Have Decreased LDL Uptake

Prior studies have indicated that both calcineurin inhibitors and mTOR inhibitors are associated with dyslipidemia [3, 14, 15]. To determine the effect of immunosuppression agents on LDL uptake by iPSC-ECs, we examined LDL levels in ECs after treatment with sirolimus or tacrolimus (Fig. 3). Sirolimus resulted in a significant reduction in acetylated LDL uptake compared to control or tacrolimus treatment. Tacrolimus and control groups LDL uptake did not differ significantly. The reduction in LDL uptake may explain the lower risk of atherosclerosis associated with sirolimus despite the drug being associated with dyslipidemia [16].

Fig. 3.

(A) Demonstrates a schematic cartoon of the LDL assay in which endothelial cells are cultures with labeled LDL particles and the particles are taken up by the endothelial cells. The fluorescence signal is then measured using a high-resolution fluorescence microscope. (B) Representative images of LDL uptake in endothelial cells in control condition, treated with sirolimus showing reduced uptake, or treated with tacrolimus showing similar uptake to control condition. (C) Bar graph with dot plots with indexed fluorescence on the Y-axis and the X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). The graph demonstrates reduced fluorescence in cell treated with sirolimus (red) compared to control (green) or tacrolimus (blue).

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Sirolimus-treated ECs have decreased LDL uptake. a Schematic of acetylated LDL uptake assay in cells treated with sirolimus, tacrolimus, or vehicle control. b Representative image of fluorescent acetylated LDL uptake in iPSC-ECs treated with sirolimus, tacrolimus, or vehicle control. c Quantification of LDL fluorescence intensity in iPSC-ECs treated with sirolimus (Siro), tacrolimus (Tac), or vehicle (control). n = 91–181 cells from 9 chamber slides per condition (3 cell lines with 3 technical replicates per cell line). ***p < 0.001 using one-way ANOVA with Tukey correction for multiple comparisons.

Sirolimus-Treated iPSC-ECs Have Diminished Angiogenic Potential

mTOR inhibitors have been shown to inhibit pathological angiogenesis (in the context of malignancy) as well as physiological angiogenesis (occurring with wound healing and development) [17]. To examine the relative effects of sirolimus and tacrolimus on angiogenesis, we performed a tube formation assay. This in vitro assay surveys the natural tendency of ECs in culture to form tube networks, which is disrupted by endothelial dysfunction. We found that sirolimus-treated iPSC-ECs had limited branching capability, with a decrease in branch numbers, network length, and branch length relative to controls. Sirolimus also exhibited a higher number of isolated segments and isolated total segment length compared to control, consistent with poor tube formation. Conversely, cells treated with tacrolimus showed no difference in branch number, branch length, number of isolated segments, or isolated segment length branch length compared to controls (Fig. 4). Notably, there was no difference in cell viability after treatment with sirolimus or tacrolimus. These findings are indicative of reduced angiogenesis with sirolimus but not tacrolimus treatment.

Fig. 4.

(A) Demonstrates a schematic cartoon of endothelial cells before and after treatment with immunosuppression drugs. (B) Representative images demonstrating endothelial cell branching in control condition, after sirolimus treatment images show reduced endothelial branching and formed networks, and after tacrolimus treatment images show preserved endothelial branching and networks. (C) Three bar graphs showing indexed number of branches, total length, and total branch length on the Y-axis and the X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). Sirolimus (red) resulted in reduced number of branches, total length, and total branch length compared to control (green) or tacrolimus (blue). There are two bar graphs showing indexed number of isolated segments and total isolated segment length on the Y-axis and the X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). Sirolimus (red) treatment resulted in higher number of isolated segments and total isolated segment length compared to control (green) or tacrolimus (blue).

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Sirolimus-treated iPSC-ECs have diminished angiogenic potential. a Schematic of tube formation assay in iPSC-ECs treated with sirolimus, tacrolimus, or vehicle control for 5 days. b Representative brightfield microscopy images showing differences in branch formation in iPSC-ECs treated with sirolimus, tacrolimus, or vehicle control. c iPSC-ECs treated with sirolimus have a decrease in number of branches, number of segments, total length, branch length, and isolated segment length with unchanged cell viability. For angiogenesis experiments, n = 27–30 data points from 9 wells per condition (3 replicates from each of the 3 cell lines). For cell viability, n = 9 per condition with 3 replicates from each of the 3 cell lines. ***p < 0.001 using one-way ANOVA with Tukey correction for multiple comparisons.

Sirolimus and Tacrolimus Decrease Nitric Oxide Production

ECs produce and release nitric oxide to induce vasodilation. Additionally, nitric oxide produced in the vascular lumen prevents platelet aggregation and leukocyte adhesion, thereby decreasing atherogenesis [18]. The use of calcineurin inhibitors and mTOR inhibitors is associated with a differential effect on atherosclerosis [6, 19]. We sought to determine the relative effects of sirolimus and tacrolimus on nitric oxide release from ECs (Fig. 5). Both sirolimus and tacrolimus treatment reduced nitric oxide production. Sirolimus decreased nitric oxide release from iPSC-ECs by 47% and tacrolimus by 28% compared to controls. Treatment with angiotensin-II decreased nitric oxide release in control cells but did not affect cells treated with sirolimus or tacrolimus. This is consistent that both immunosuppression agents cause similar impairment in nitric oxide release to angiotensin II.

Fig. 5.

(A) Demonstrates a schematic showing endothelial cells treated with drugs and then measurement of nitric oxide using Greiss Reagent followed by measurement of light emission at 548 nm. (B) Bar graph with indexed nitric oxide release on the Y-axis and the X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). The bar graph shows that treatment with sirolimus (green) and tacrolimus (blue) reduced nitric oxide levels compared to control (green). A second bar graph shows nitric oxide level on the Y-axis and the X-axis having 6 discrete categories control (green), sirolimus (red), and tacrolimus (blue) with each condition measured at baseline and following angiotensin II co-treatment. Treating control cells (green) with angiotensin II caused a reduction in nitric oxide (striped, green), while treating sirolimus (red) or tacrolimus (blue) resulted in no significant change in nitric oxide levels (striped red and striped blue respectively). A bar graph showing enos mRNA gene expression on the Y-axis and the X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). In response to immunosuppression treatment there was no difference in eNOS mRNA expression between control (green), sirolimus (red), and tacrolimus (blue).

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Sirolimus and tacrolimus decrease nitric oxide production. a Schematic of nitric oxide production assay from iPSC-ECs treated with sirolimus, tacrolimus, or vehicle control. b iPSC-ECs treated with sirolimus (Siro) and tacrolimus (Tac) have a decrease in nitric oxide production relative to control. n = 21–30 wells per condition, with 7–10 replicates from each of the 3 cell lines. We did not observe changes in ENOS mRNA levels in any of the conditions. For Ang-II treatment and ENOS expression, n = 9 per condition with 3 replicates from each of the 3 cell lines. ***p < 0.001 using one-way ANOVA with Tukey correction for multiple comparisons. *p < 0.01. ns, not significant.

Sirolimus Treatment of iPSC-ECs Decreases Mitochondrial Respiration

EC function has been linked to mitochondrial energetics [20], and immunosuppressive agents can exert direct effects on mitochondria to impact metabolism and cellular energetics [21, 22]. We sought to determine the effect of tacrolimus and sirolimus treatment on mitochondrial respiration in ECs. Interestingly, we found that sirolimus treatment led to a decrease in mitochondrial respiration in ECs, suggesting that mitochondrial metabolic impairment may play a role in EC dysfunction caused by sirolimus treatment (Fig. 6a). Tacrolimus treatment of ECs trended toward a small decrease in mitochondrial respiration, but this was not statistically significant. Mitochondrial and glycolytic ATP production rates were unchanged by treatment with sirolimus or tacrolimus (Fig. 6b).

Fig. 6.

(A) Line graph showing basal levels of oxygen consumption rate over time with basal levels of all 3 conditions being similar; following addition of FCCP (carbonyl cyanide-p-trifluoromethoxyphenylhydrazone) there is a rise in rate of oxygen consumption but sirolimus group (red) appears lower than control (green) or tacrolimus (blue). Following addition of Rotenone + Antimycin A there is a drop in the rate of oxygen consumption to very low levels in all groups. Three bar graphs with oxygen consumption rate, proton leak, maximal respiration, and spare respiration on the Y-axis and the X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). The bar graphs show there is a reduction in oxygen consumption rate, proton leak, maximal respiration, and spare respiration with sirolimus (red) compared to control (green). Tacrolimus (blue) shows a trend to being reduced but not statistically significant. An additional three bar graphs with glycolytic ATP production, mitochondrial ATP production, and total ATP production on the Y-axis and the X-axis having 3 discrete categories control (green), sirolimus (red), and tacrolimus (blue). The bar graphs show no difference in glycolytic ATP production, mitochondrial ATP production, and total ATP production between control (green), sirolimus (red), and tacrolimus (blue).

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Sirolimus treatment of iPSC-ECs decreases mitochondrial respiration. a Sirolimus-treated iPSC-ECs had lower basal, maximal, proton leak, and spare oxygen consumption rate (OCR). n = 6–9 with 2–3 wells per cell line per condition. b iPSC-ECs had no difference in glycolytic ATP production, mitochondrial ATP production, or total ATP production. n = 4–6 with 1–2 wells per cell line per condition. Statistics using one-way ANOVA with Tukey correction for multiple comparisons.

Discussion

Immunosuppressant use is associated with vascular outcomes, with differential rates of hypertension, dyslipidemia, and atherosclerosis in patients treated with mTOR inhibitors and calcineurin inhibitors [3]. Given the systemic effects of the drugs and the multi-organ interactions implicated in vascular function, delineating cell-specific alterations is difficult in vivo. Here, we show that sirolimus and tacrolimus have direct effects on EC function. Specifically, sirolimus treatment led to a decrease in cell migration, proliferation, acetylated LDL uptake, and mitochondrial respiration, while both tacrolimus and sirolimus reduced nitric oxide release from iPSC-ECs. These effects may provide mechanistic insight into the vascular phenotype associated with mTOR inhibitor and calcineurin inhibitor use.

Hypertension is a well-described side effect of immunosuppressive medication use, particularly calcineurin inhibitors, and is associated with an increased risk of coronary artery disease, cerebrovascular events, renal dysfunction, and adverse cardiovascular remodeling [23]. Cyclosporine A and tacrolimus are associated with promoting direct vasoconstriction by increased tone of vascular smooth muscle and activation of the endothelin-1 receptor [24–26]. mTOR inhibitors, on the other hand, have been associated with a lower risk of hypertension compared to calcineurin inhibitors when used in solid organ transplant recipients [27]. Sirolimus is thought to prevent endothelial hyperplasia and dysfunction [28]. Here, we found that in iPSC-ECs, treatment with sirolimus and tacrolimus decreased nitric oxide production. The decrease in nitric oxide in response to tacrolimus is in line with other models of calcineurin inhibitor treatment and clinically observed hypertension. Our sirolimus result is also in line with clinical observations of endothelial vasomotor dysfunction in response to sirolimus exposure [29]. Our findings support both immunosuppression drugs reducing endothelial nitric oxide production in similar fashion to angiotensin II treatment.

Immunosuppressive medications are associated with dyslipidemia [14, 30]. Each drug class is associated with individual variations in affected lipid particles and more importantly in the conferred risk of atherosclerosis. Among calcineurin inhibitors, cyclosporine A is associated with a dose-dependent increase in total cholesterol and LDL cholesterol, a decrease in high-density lipoprotein (HDL) cholesterol, and an increase in serum triglycerides [31]. Tacrolimus use is associated with a milder dyslipidemia profile [32]. mTOR inhibitors, particularly sirolimus, are stronger inducers of hyperlipidemia than calcineurin inhibitors, associated clinically with an increase in serum LDL and triglyceride levels [33]. The mechanism remains unclear, although it may be due to a combination of reduced catabolism, an increase in the free fatty acid pool, increased hepatic production of triglycerides, and secretion of very low density lipoprotein [34, 35]. Interestingly, despite the increase in serum lipids, mTOR inhibitors are associated with an overall lower risk of atherosclerosis [6]. Here, we show that sirolimus treatment of ECs decreases LDL uptake, while tacrolimus treatment maintains ability to uptake LDL. In agreement with our findings, treatment of human umbilical vein endothelial cells with sirolimus was associated with a decrease in oxidized LDL uptake, marked by NF-kB inhibition and LOX-1 suppression [36]. This may in part explain the differential effect of mTOR inhibitors on dyslipidemia and atherosclerosis.

Immunosuppressive agents directly contribute to abnormal vascular remodeling that may drive cardiovascular adverse events, independent of hypertension or dyslipidemia [7]. In one study, treatment with calcineurin inhibitor and mTOR inhibitors had differential effect on ICAM-1 expression and extracellular matrix reactivity in microvascular ECs [37], whereas in another study, acute treatment with sirolimus or tacrolimus had no effect on proliferation in a human microvascular endothelial cell line (HMEC-1) [38]. Defining this risk and the contributing mechanisms for each drug is important in order to ensure appropriate follow-up and identify potential actionable targets to modify the risk profile. Calcineurin inhibitors have been associated with an increased risk of allograft vasculopathy, a notable complication of transplanted hearts, which represents a major driver of graft dysfunction and has significant implications for quality of life and longevity of heart transplant recipients [39]. In animals treated with tacrolimus, adverse remodeling features described include vascular stiffness, thickening, inflammation, and fibrosis [40, 41]. Proposed mechanisms include decreased fibrinolytic activity in vessel walls and possibly increased intracellular calcium in vascular smooth muscle cells [42–44]. Both sirolimus and everolimus have been associated with a more favorable vascular profile with clinical efficacy in reducing the rate of progression of CAV, which has led to widespread use in heart transplant recipients [45, 46]. mTOR inhibitors treatment has been shown to minimize intimal hyperplasia, vascular smooth muscle proliferation, and infiltration by inflammatory cells [9, 47, 48]. Experimentally, others have shown that in vascular smooth muscle cells and ECs isolated from human saphenous veins, treatment with sirolimus was associated with impaired proliferation and migration relative to tacrolimus treatment [49]. Here, we show that sirolimus treatment of iPSC-derived ECs decreases their proliferation, migration, and nitric oxide release. Concordant with our findings, a study in mouse aortas showed that treatment with sirolimus or tacrolimus exacerbated intracellular calcium leak in ECs and led to a decrease NO production [50]. While this may translate to an increased risk of capillary leak and lymphedema, this may confer a protective effect in terms of coronary pathology such as atherosclerosis and CAV.

Mitochondrial functions are critical to EC homeostasis, with effects on cellular metabolism, calcium signaling, and oxidative damage [51]. Sirolimus has been shown to deplete intracellular calcium stores with an associated impairment in mitochondrial respiration in pancreatic beta cells [52]. Sirolimus treatment of mouse fibroblasts was associated with downregulation of mitochondrial gene expression and impaired mitochondrial respiration [53]. In rat ECs, treatment with sirolimus was associated with EC dysfunction marked by mitochondrial oxidant production [54]. Mechanistically, sirolimus treatment led to dephosphorylation of mitochondrial metabolic proteins via inhibition of mTOR-raptor complex formation [55]. Experiments in isolated mitochondria showed that treatment with sirolimus or tacrolimus led to an increase in mitochondrial proton leak (state 4 respiration) [56]. Here, we show that sirolimus treatment of iPSC-ECs decreases basal and maximal mitochondrial respiration. Treatment with tacrolimus led to a trend toward decreased respiration, which was not statistically significant. This was not associated with a change in ATP production rates, although that may be due to increased variability in the assay.

We show distinct endothelial function profiles in response to tacrolimus or sirolimus treatment. Sirolimus exerted a broader effect on EC function, while tacrolimus primarily affected nitric oxide release. The knowledge of these endothelial-specific effects can be used to inform further studies on immunosuppression-associated vascular remodeling in multicellular or organ models.

Statement of Ethics

The iPSC lines used in this study were obtained from the Stanford Cardiovascular Institute Biobank (https://med.stanford.edu/scvibiobank.html). The recruitment and reprogramming of the iPSC lines was done with written informed consent with Stanford IRB Approval (Protocol 29904).

Conflict of Interest Statement

The authors have no conflicts of interest to declare.

Funding Sources

This work has been supported by National Institutes of Health K08 HL135343 (K.S.), American Heart Association and Enduring Hearts Grant # 924127/Sallam and Hollander/2023 (K.S.), and Stanford CVI Seed Grant.

Author Contributions

A.E. performed experiments, analyzed data, and wrote the manuscript. R.D. performed experiments, analyzed data, and assisted in manuscript writing and figures. D.W., S.C., and I.T. performed experiments and analyzed data. I.Y.C. and N.S. designed experiments, analyzed the data, and wrote the manuscript. K.S. conceptualized the project, designed experiments, analyzed data, and wrote the manuscript.

Funding Statement

This work has been supported by National Institutes of Health K08 HL135343 (K.S.), American Heart Association and Enduring Hearts Grant # 924127/Sallam and Hollander/2023 (K.S.), and Stanford CVI Seed Grant.

Data Availability Statement

The data generated and analyzed during the current study are available from the corresponding author on reasonable request. The data that support the findings are not publicly available because they make compromise privacy of original donor but are available from K.S. (sallam@stanford.edu).

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The data generated and analyzed during the current study are available from the corresponding author on reasonable request. The data that support the findings are not publicly available because they make compromise privacy of original donor but are available from K.S. (sallam@stanford.edu).

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