International Journal of Molecular Sciences Article Urinary Neuropilin-1: A Predictive Biomarker for Renal Outcome in Lupus Nephritis Maria Teresa Torres-Salido 1,† , Mireia Sanchis 2,† , Cristina Solé 2, *,† , Teresa Moliné 3 , Marta Vidal 3 , Xavier Vidal 4 , Anna Solà 5,6 , Georgina Hotter 5,6 , Josep Ordi-Ros 2 and Josefina Cortés-Hernández 2 1 Hospital Quironsalud del Vallés, Internal Medicine Department, 08202 Sabadell, Spain; belovedmaite@hotmail.com 2 Hospital Universitari Vall d’Hebron, Vall d’Hebron Research Institute (VHIR), Rheumatology research group, Lupus Unit, 08035 Barcelona, Spain; msanchis@vhebron.net (M.S.); jordi@vhebron.net (J.O.-R.); fina.cortes@vhir.org (J.C.-H.) 3 Hospital Universitari Vall d’Hebron, Department of Renal Pathology, 08035 Barcelona, Spain; teresa.moline@vhir.org (T.M.); mvidal@tauli.cat (M.V.) 4 Clinical Pharmacology Service, Department of Pharmacology, Therapeutics and Toxicology, Fundació Institut Català de Farmacologia, Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, 08035 Barcelona, Spain; xvg@icf.uab.es 5 Department of Experimental Pathology, IIBB-CSIC-IDIBAPS, 08036 Barcelona, Spain; anna.sola@iibb.csic.es (A.S.); georgina.hotter@iibb.csic.es (G.H.) 6 CIBER-BBN, Networking Centre on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), 08036 Barcelona, Spain * Correspondence: cristina.sole@vhir.org; Tel.: +34-934894047 † These authors contributed equally to this work.  Received: 31 July 2019; Accepted: 10 September 2019; Published: 17 September 2019  Abstract: At present, Lupus Nephritis (LN) is still awaiting a biomarker to better monitor disease activity, guide clinical treatment, and predict a patient’s long-term outcome. In the last decade, novel biomarkers have been identified to monitor the disease, but none have been incorporated into clinical practice. The transmembrane receptor neuropilin-1 (NRP-1) is highly expressed by mesangial cells and its genetic deletion results in proteinuric disease and glomerulosclerosis. NRP-1 is increased in kidney biopsies of LN. In this work we were interested in determining whether urinary NRP-1 levels could be a biomarker of clinical response in LN. Our results show that patients with active LN have increased levels of urinary NRP-1. When patients were divided according to clinical response, responders displayed higher urinary and tissue NRP-1 levels at the time of renal biopsy. Areas under the receiver operating characteristic curve, comparing baseline creatinine, proteinuria, urinary NRP-1, and VEGFA protein levels, showed NRP-1 to be an independent predictor for clinical response. In addition, in vitro studies suggest that NRP-1could promote renal recovery through endothelial proliferation and migration, mesangial migration and local T cell cytotoxicity. Based on these results, NRP-1 may be used as an early prognostic biomarker in LN. Keywords: neuropilin-1; lupus nephritis; urinary biomarker; clinical responder; renal biopsy 1. Introduction Systemic lupus erythematosus (SLE) is a chronic inflammatory autoimmune disease with a broad spectrum of manifestations and organ involvement [1,2]. Lupus nephritis (LN) affects up to 50% of patients with SLE and is a major cause of morbidity, despite modern therapeutic approaches [2,3]. To date, renal biopsy is still the gold standard for diagnosing and classifying the degree of renal Int. J. Mol. Sci. 2019, 20, 4601; doi:10.3390/ijms20184601 www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2019, 20, 4601 2 of 19 inflammation and scarring, but its invasiveness makes it unsuitable for serial monitoring. Conventional clinical parameters are not sensitive or specific enough for detecting ongoing disease activity, early relapse, disease progression, or response to therapy [2–4]. In recent years there has been increasing interest in developing novel biomarkers; however, few of them have been rigorously validated in large scale longitudinal studies, none have been standardized for daily clinical practice, and mainly they had been assessed for their potential as “diagnostic biomarkers”. Neuropilin-1 (NRP-1) was originally identified as co-receptor for class 3 semaphorins, a family of molecules involved in axon repulsion [5]. Besides its critical role during embryogenesis, NRP-1 has important functions in adult tissues, being involved in axonal guidance, vascular endothelial sprouting, regeneration organ repair and immunosuppression. Evidence suggests that its role as immune-regulator would be in mediating interactions between activated dendritic cells and resting T cells [6–13], and promoting regulatory T cell activity [11]. Although originally detected in neurons, NRP-1 is also expressed in non-neural cells including epithelial and endothelial cells, where it also acts as a receptor for several members of the vascular endothelial growth factor (VEGF) family, enhancing signaling and promoting angiogenesis [14–16]. Other ligands include hepatocyte growth factor, platelet-derived growth factor BB, transforming growth factor-β1 (TGF-β1), and fibroblast growth factor2 (FGF2) [17,18]. In addition, it has been found that NRP-1 is present on cultured human mesangial cells and with the presence of VEGF play an important role in mesangial cell pathophysiology [19]. Little is known about the involvement of NRP-1 in SLE, and its role in lupus nephritis. Decreased NRP-1 and SEMA3A expression on serum B cells from patients with SLE has been described [20,21]. Vasdaz et al. in a study including 12 patients with LN showed an increased renal expression of NRP-1 in deposits found only in the damaged glomerular areas correlated with proteinuria and chronicity index (endothelial damage) [22]. So far, there are no studies evaluating NRP-1 as a biomarker of LN. Our aim was to evaluate expression levels of NRP-1 at the time of the renal biopsy in patients with LN and determine their predictive value for nephritis therapy response. 2. Results 2.1. Patients A total of seventy patients with active LN were included in the cross-sectional study. Patients’ demographic characteristics and laboratory measurements are summarized in Table 1. Mean (SD) age at inclusion was 41 (±10) years. There was a female (80%) and biopsy-proven type IV glomerulonephritis (GMN) (76%) predominance. For 41 (58.6%) of patients, it was the first renal episode. The mean (SD) of renal activity and chronicity indices were 7.5 (3.6) and 2 (1.9), respectively. Patients with active nephritis were treated with standard therapy (see material and methods) and were followed for a median of 6 years (range 1.5 to 8.5 years). 2.2. Urinary Expression of NRP-1 in Lupus Nephritis Urinary NRP-1 mRNA levels in patients with active LN were significantly increased when compared with other groups: SLE patients with active disease without renal involvement (30.70 ± 111.8 vs. 1.03 ± 0.94 relative expression; p = 0.01), other glomerular diseases (3.35 ± 3.65 relative expression; p = 0.03), and healthy controls (1.03 ± 0.95 relative expression; p = 0.02) (Figure 1A). Among patients with active LN, there were no differences in NRP-1 levels according to histological type or the degree of disease activity. 2.3. Protein Levels of NRP-1 in Patients with Lupus Nephritis In line with mRNA expression levels, patients with active LN had significantly higher urinary NRP-1 levels, as measured by ELISA, than lupus patients with active non-renal disease (1807 ± 2180 ng/mg Cr versus 95.26 ± 160.3 ng/mg Cr, p < 0.0001), patients with other glomerular Int. J. Mol. Sci. 2019, 20, 4601 3 of 19 diseases (1807 ± 2180 ng/mg Cr versus 13.11 ± 17.77 ng/mg Cr, p < 0.0001) and healthy controls (1807 ± 2180 ng/mg Cr versus 59.14 ± 26.39 ng/mg Cr, p < 0.0001) (Figure 1B). Levels of uNRP-1 (area under curve = 0.956) showed a sensitivity of 85.71% and specificity of 90.24% to discriminate active nephritis from active non-renal lupus disease (cut-off >293.55, Figure S1). Correlation analysis of uNRP-1 levels with other clinical and laboratory parameters only showed a correlation with C4 levels (r = −0.182, p = 0.045, Figure 1C). Higher urine levels of NRP-1 did not correlate with type IV glomerulonephritis or the degree of proteinuria, biopsy activity index, or urinary sediment. However, an inverse correlation with nephritic flare was found (r = −0.246, p = 0.043, Figure 1C). Measurement of serum NRP-1 levels did not show differences between groups (Figure S1). Table 1. Clinical and histological variables at the time of the renal biopsy. Active Other Active Lupus Healthy Characteristics Non-Renal Glomerular p Value a Nephritis (n = 70) Controls (n = 25) SLE (n = 25) Diseases (n = 25) Demographic 0.4857 (0.787) Age, yrs 41 ± 10 34 ± 6 35 ± 5 30 ± 4 [0.885] Gender 0.112 (0.723) 56/14 21/4 16/9 16/9 (Female/male) [0.112] Race/ethnicity, n (%) 65 (93) 22 (88) 23 (92) 22 (88) 0.966 (0.966) White Hispanic 4 (6) 2 (8) 1 (4) 2 (8) [0.500] Other 1 (1) 1 (4) 1 (4) 1 (4) Laboratory parameters Serum creatinine, 0.035 (0.006) 1.1 ± 0.5 0.8 ± 0.1 1.9 ± 0.8 0.8 ± 0.3 mg/dL [0.001] 0.091 (0.001) eGFR (mL/min) 82 ± 30 104 ± 16 48 ± 36 95 ± 22 [0.006] 0.076 (0.152) Urea (mg/dL) 54 ± 29 34 ± 14 81 ± 48 28 ± 11 [0.012] Anti-dsDNA Abs, 287 ± 68 39 ± 29 n.a. n.a. (0.087) IU/mL Serum C3, mg/dL 78 ± 31 94 ± 20 n.a. n.a. (0.101) Serum C4, mg/dL 12.8 ± 9.2 13.4 ± 10 n.a. n.a. (0.090) Proteinuria, g/24 h 3.3 ± 3.0 0.2± 0.1 9,1 ± 4,8 n.a. (0.010) [0.001] Leukocytes (cel/µL) 95 ± 114 n.a. n.a. n.a. Erythrocytes 133 ± 131 n.a. n.a. n.a. (cel/µL) Disease index (SLEDAI-2K) Total score 16 ± 2 8±2 n.a. n.a. (0.006) Renal score 12 ± 1 0 n.a. n.a. Extra-Renal score 4±2 8±2 n.a. n.a. (0.001) Renal Flare, n (%) Proteinuric 59 (84) n.a. n.a. n.a. Nephritic 11 (16) n.a. n.a. n.a. First flare 41 (59) n.a. n.a. n.a. Relapsing flare 29 (41) n.a. n.a. n.a. Renal Biopsy, n (%) Class III 9 (13) n.a. n.a. n.a. Class IV 53 (76) n.a. n.a. n.a. Class V 8 (11) n.a. n.a. n.a. Activity Index 7.5 ± 3.6 n.a. n.a. n.a. Chronicity Index 2.0 ± 1.9 n.a. n.a. n.a. Values are expressed as mean ± standard deviation (SD). BUN, blood urea nitrogen; eGFR, estimated glomerular filtration rate; anti-dsDNA, anti-double-stranded DNA (reference range <15 UI/mL); n.a., not applicable. a p-value refers to the comparison of the active lupus nephritis (LN) with healthy controls, the values in bracket referred to the comparison with active non-renal SLE and the values in square bracket referred to the comparison with the cohort of other glomerular-diseases: Mann-Whitney U Test or Pearson χ2 test. Int. J. Mol. Sci. 2019, 20, 4601 4 of 19 Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 5 of 20 Figure 1. Urinary NRP-1 relative expression levels (a) and concentrations (b) in active LN patients compared with active SLE patients without renal disease, with other glomerular diseases and healthy controls. Urinary biomarker expression levels (c) and concentrations (d) were measured according to clinical response to therapy (responders vs non-responders). Biomarker concentrations were standardised to urinary creatinine and expressed as median values. Horizontal line means median value for each group. One-way ANOVA followed by Bonferroni test (a,b) and Student’s t-test (d) were used to to compare biomarker concentrations between groups. * p < 0.05; *** p < 0.0001. Int. J. Mol. Sci. 2019, 20, 4601 5 of 19 2.4. Baseline Levels of NRP-1 Predict Clinical Response Of the 70 included patients, 38 (54%) achieved complete response within a median of 18.5 months (range: 2 to 65). Table 2 shows the baseline characteristics between responders and non-responders. Non-responders had significantly higher levels of serum creatinine, more nephritic flares and relapsing disease when compared with responders (p = 0.02, p < 0.0001, and p = 0.02, respectively). Measurement of NRP-1 at inclusion showed responders to have higher urinary mRNA levels of NRP-1 than non-responders (102 ± 210 vs. 8 ± 18 relative expression, p = 0.002) (Figure 1C). Differences were more significant at a protein level (2532 ± 2439 ng/mg Cr vs. 569 ± 851 ng/ mg Cr, p < 0.0001) (Figure 1D). Table 2. Baseline characteristics of patients according to clinical response to immunosuppressive therapy. Responders Non-Responders Characteristics Active LN Cohort (n = 38) Active LN Cohort (n = 32) p Value Demographic Age (years) 42 ± 12 39 ± 8 0.517 Gender (Female/male) 33/5 27/5 Race/ethnicity, n (%) White 35 (92) 30 (94) 0.811 Hispanic 2 (5) 2 (6) Other 1 (3) 0 Laboratory parameters Serum creatinine, mg/dL 1.0 ± 0.4 1.3 ± 0.6 0.025 eGFR (mL/min) 88 ± 26 75 ± 33 0.167 Urea (mg/dL) 48 ± 27 61 ± 30 0.054 Anti-dsDNA Abs, IU/mL 344 ± 84 220 ± 68 0.781 Serum C3, mg/dL 77 ± 32 79 ± 29 0.878 Serum C4, mg/dL 12.0 ± 9.6 13.7 ± 8.8 0.248 Proteinuria, g/24 h 3.0 ± 3.2 3.4 ± 2.7 0.563 Leukocytes (cel/µL) 95 ± 114 101 ± 190 0.495 Erythrocytes (cel/µL) 133 ± 131 187 ± 397 0.158 Disease index (SLEDAI-2K) Total score 14 ± 3 15 ± 2 0.145 Renal score 10 ± 2 9±3 0.112 Extra-Renal score 5±3 4±2 0.184 Renal Flare, n (%) Proteinuric 38 (100) 14 (44) <0.0001 Nephritic 0 18 (56) <0.0001 First flare 27 (71) 14 (44) 0.021 Relapsing flare 11 (29) 18 (56) 0.021 Renal Biopsy, n (%) Class III 4 (11%) 3 (9%) 0.714 Class IV 29 (76%) 26 (82%) 0.618 Class V 5 (13%) 3 (9%) 0.441 Activity Index 7.4± 3.2 7.6 ± 4.0 0.864 Chronicity Index 1.7 ± 2.1 2.2 ± 1.8 0.203 Values are expressed by means ± standard deviation (SD). eGFR, estimated glomerular filtration rate; anti-dsDNA, anti-double-stranded DNA (reference range <15 UI/mL). p-value refers to the comparison of the Responders with Non-Responders in combined cohorts by Mann-Whitney U Test or Pearson χ2 test. Next, we performed receiver operating characteristic analyses to determine the best cutoff that had the maximal sensitivity and specificity to predict clinical response. A urinary NRP-1 cutoff level of 1143 ng/mg Cr at baseline could predict clinical response with a sensitivity of 87.10%, specificity of 71.79% and a negative and positive predictive value of 87.50% and 71.05%, respectively (Figure 2A). Patients with higher uNRP1 baseline levels had a significantly increased probability to achieve CR (p < 0.0001, by log-rank test) (Figure 2B). Int. J. Mol. Sci. 2019, 20, 4601 6 of 19 Int. J. Mol. Sci. 2019, 20, x FOR PEER REVIEW 8 of 20 Figure 2. Urinary Levels of NRP-1 and vascular endothelial growth factor (VEGFA) in active LN. Figure (a) 2. Urinary The receiver Levels ofcharacteristic operating NRP-1 and vascular (ROC) endothelial growth curve of urinary factorlevels NRP-1 (VEGFA) in active at the time ofLN. (a) renal The receiver biopsy generatedoperating from thecharacteristic (ROC) optimal binary curveregression logistic of urinarymodel NRP-1when levels at the data fromtime of cohorts both renal biopsy were generatedtofrom combined the optimal discriminate binary between logistic regression responders model when and non-responders. AUC = area data from boththe under cohorts were ROC curve. combined to discriminate between responders and non-responders. AUC = area (b) Kaplan-Meier survival curve for clinical response following treatment among patients with active under the ROC curve. LN (b)time at the Kaplan-Meier survival of renal biopsy. Longcurve rank for test clinical was used response following for analysis. treatment p-value among ≤ 0.05 were patients considered with active(c) significant. LN at the time of renal biopsy. Creatinine-normalized Long of urine levels rank test was VEGFA used for cohorts in combined analysis.ofp-value ≤ 0.05 responders = 38) (n were considered and significant. non-responders (c) *** (= 32); p < 0.0001. (d) Correlation Creatinine-normalized urine levels ofurinary plots of VEGFANRP-1in combined and VEGFA cohorts of levels atresponders the time of(nrenal = 38)biopsy. and non-responders (= 32); ***purine Creatinine-normalized < 0.0001. levels(d) of Correlation VEGFA in LN plots in of urinary relation to NRP-1 NRP-1 and VEGFA levels levelsofatrenal at the time the time of renal biopsy biopsy. with in patients Creatinine-normalized urine levels active LN. (e) Receiver operatingof VEGFA in LN in characteristics relation curves to NRP-1 relating levels at the the specificity andtime of renal profiles sensitivity biopsy inof patients baseline with active urinary LN. VEGFA, NRP-1, (e) Receiver operating creatinine and characteristics protein levels. curves relating the specificity and sensitivity profiles of baseline urinary NRP-1, VEGFA, creatinine and protein levels. 2.5. VEGFA, VEGFR1, VEGFR2, and SEMA3A in Patients with Lupus Nephritis and Correlation with NRP-1 Levels 2.7. Serial Monitoring of uNRP-1 Levels to Predict Response As A there new is a functional prospective relationship cohort (n = 39)between (cohortNRP-1 3) (22 and the VEGFand responders and17thenon-responders) semaphorine family, was we measured the urinary mRNA and protein levels of VEGFA, VEGFR1, established. Serial measurements of urine NRP-1 and VEGFA levels were performed VEGFR2, and semaphorine3A three-monthly (SEMA3A). from baselineUrinary up to gene twelveexpression levels3). months (Table did not differ During between follow-up, patients NRP-1 with levels active LN remained when markedly compared with control groups, nor between responders and non-responders. increased in the responder group (median levels 1112 ng/mg Cr, p = 0.003), when compared with However, urinary VEGFA levels, measured non-responders (medianby ELISA, levels were 149.1 significantly ng/mg, increased Figure 3B). VEGFA inlevels patients with the during active firstLN compared 6 months of with active SLE patients without renal disease and healthy controls (p = 0.01 and p < 0.0001, follow-up were significantly increased when compared to non-responders (levels 303 vs. 88 pg/mg, p respectively) Int. J. Mol. Sci. 2019, 20, 4601 7 of 19 (Figure S2A). In contrast, urinary SEMA3A levels were significantly decreased in patients with active LN when compared to the same control groups (p = 0.002 and p = 0.007, respectively) (Figure S2B). There were no differences in urinary VEGFR1 and VEGFR2 levels (Figure S2C,D). When responders were compared with non-responders, mirroring NRP-1 levels, responders had significantly higher levels of urinary VEGFA compared with non-responders (166 ± 9 vs. 87 ± 7 ng/mg Cr, p < 0.0001) (Figure 2C). No differences in urinary VEGF receptors and SEMA3A levels were found between responders and non-responders (Figure S3). There was a direct correlation between urinary VEGFA and NRP-1 protein levels (r = 0.466, p < 0.0001, Figure 2D). However, VEGFA levels (12.34 ng/mg) showed an inferior profile to predict response with a sensitivity and specificity of 71% and 75%, respectively (Figure S4). ROC analysis comparing NRP-1 with baseline urinary VEGFA levels and other clinical factors such as creatinine and proteinuria levels as predictors of response continued to show uNRP-1 levels to be an independent predictive factor of response (p = 0.003) (Figure 2E). 2.6. Immunohistochemistry Localization of NRP-1, VEGFA and SEMA3A within Renal Biopsies NRP-1 and VEGFA stained with a significantly higher intensity in the active LN group when compared to the control group (Figure 3A). NRP-1 expression was mostly observed in the glomeruli and along the tubuli. In the glomeruli, it was mostly expressed in the endothelial cell membrane and in mesangial cells. Globally, NRP-1 expression was three times higher in responders than in non-responders. There was a clear difference in the glomeruli staining, with responders having much higher expression of NRP-1 (p < 0.0005). This difference was not observed in the tubuli (Figure 3A). Renal NRP-1 protein levels correlated with urinary levels (p = 0.002, r = 0.834). VEGFA was highly expressed in the glomeruli and tubular epithelial cells, but staining intensity did not differ between responders and non-responders. Finally, semaphorine 3A staining was increased in patients with active LN when compared to controls and expressed strongly in the tubuli of non-responders (Figure 3A). 2.7. Serial Monitoring of uNRP-1 Levels to Predict Response A new prospective cohort (n = 39) (cohort 3) (22 responders and 17 non-responders) was established. Serial measurements of urine NRP-1 and VEGFA levels were performed three-monthly from baseline up to twelve months (Table 3). During follow-up, NRP-1 levels remained markedly increased in the responder group (median levels 1112 ng/mg Cr, p = 0.003), when compared with non-responders (median levels 149.1 ng/mg, Figure 3B). VEGFA levels during the first 6 months of follow-up were significantly increased when compared to non-responders (levels 303 vs. 88 pg/mg, p = 0.05), but afterwards, levels remained similar in both study groups (around 100–80 pg/mg, Figure 3C). Int. J.Int. Mol.J. Mol. Sci. 2019, Sci. 2019, 20, 20, 4601PEER REVIEW x FOR 8 of 19 10 of 20 Figure 3. High levels of NRP-1 protein were confirmed in Responders vs Non-Responders. Figure 3. High levels of NRP-1 protein were confirmed in Responders vs Non-Responders. (a) (a) Immunohistochemistry for NRP-1 and VEGFA in kidney biopsy (×400). Average scores were Immunohistochemistry for NRP-1 and VEGFA in kidney biopsy (×400). Average scores were obtained for the evaluation of Vall Hebron pathologists group. (b) Changes in urinary protein levels obtained for the evaluation of Vall Hebron pathologists group. (b) Changes in urinary protein levels of NRP-1 and VEGFA. (c) over the 12-month period of treatment in patients with LN. Dots and bars of NRP-1 and VEGFA. show means and SEM(c) ofover thelevels protein 12-month period in urine of treatment samples in patients from baseline with though the LN.months twelve Dots and of bars show means and follow-up. * p 15% below the baseline value discontinuation of treatment due to side effects or renal relapse while on full treatment [36]. More information about renal flare [37] kidney biopsy evaluation [24,38] and, treatment [39] in Supporting Information. Urine and blood samples were collected from each patient 1 day before renal biopsy and processed immediately to be stored at −80 ◦ C. Patients with urinary tract infection, diabetes mellitus, pregnancy, malignancy, and non-lupus-related renal failure were not included. The control groups consisted of SLE patients with active disease (SLEDAI > 6) without renal involvement (n = 25), healthy volunteers (n = 25) and patients with other glomerular diseases (n = 25) (diabetic nephropathy (n = 12), IgA nephropathy (n = 4), idiopathic membranous nephropathy (n = 4), and focal segmental glomerulosclerosis (n = 5) were also included. The study was approved by the Vall d’Hebron Ethic Committee (Urinary Biomarkers LN, 22 April 2009) and written informed consent was obtained from all patients. More details about study design in Supporting Information. 4.2. mRNA Isolation, cDNA Synthesis and Real-Time PCR Urine samples were immediately centrifuged after collection at 3900× g for 30 min (4 ◦ C) and supernatant was stored at −80 ◦ C. Total RNA was isolated from the cell pellets using the RiboPure RNA Purification Kit (Ambion, Life Technology, Carlsbad, CA, USA) following the manufacturer’s instructions. Quantification of NRP-1, VEGFA, VEGFR1, VEGFR2 and SEMA3A mRNA by TaqMan Real-Time PCR was carried out as described by the manufacturer (ThermoFisher, Carlsbad, CA, USA). Int. J. Mol. Sci. 2019, 20, 4601 15 of 19 RNA was reverse-transcribed into cDNA using the High Capacity RNA-to-cDNA Kit and the quantitative RT-PCR reaction was performed in 96-well plates on the ABI PRISM 7000HT. The data was normalized based on the expression of the endogenous control GAPDH (more details in Supporting Information). 4.3. Enzyme-Linked Immunosorbent Assay (ELISA) Enzyme-linked immunosorbent assay (ELISA) was used to quantify urinary and serum levels of NRP-1 (Cloud-Cone Corp, Katy, TX, USA), VEGFA (RayBiotech, Norcross, GA, USA), VEGFRI (RayBiotech, Norcross, GA, USA), VEGFR2 (RayBiotech, Norcross, GA, USA), and SEMA3A (Cloud-Cone Corp, Katy, TX, USA) following the manufacturer’s instructions. Triplicate for all samples were done. Urinary levels were normalized against the corresponding urine creatinine levels. 4.4. Renal Histology and Immunohistochemistry Paraffin sections were stained with haematoxylin and eosin, periodic acid-Schiff, trichrome, and silver for light microscopy. The specimens were scored for activity and chronicity [24]. All biopsies were examined by one pathologist that was not aware of the molecular study results. For immunohistochemistry, formalin-fixed paraffin-embedded tissue sections were deparaffinized and primary antibodies were incubated with slides overnight at 4 ◦ C (more information in Supporting Information). As controls, we used disease-free kidney sections from tissue margins of total or subtotal nephrectomies obtained from patients undergoing surgery for renal malignancies. 4.5. Cell Cultures Primary Human Renal Endothelial Cells (HRECs), Primary Human Renal Glomerular Mesangial cells (HRMCs) and Primary Human Renal Tubular Epithelial cells (RTECs) were purchased and cultured in the recommended media provided by the manufacturer (Innoprot, Derio, Bizkaia, Spain). Isolated primary T cells were cultured in RPMI medium supplemented with 10% fetal bovine serum (FBS) and 5% penicillin/streptomycin (more details in Supporting Information). Cells were grown at 37 ◦ C in a humidified 5% CO2 atmosphere. Cell passes were performed using TrypLETM Express (ThermoFisher, Carlsbad, CA, USA). 4.6. NRP-1 Expression Levels in Primary Cells Primary human cells (HRECs, HRMCs, RTECs and T cells) were platted onto 24-wells (1 × 104 cells/mL). After 24 h, stimulation with IL-1 (10 ng/mL) or VEGF (50 ng/mL) cytokine was performed during 24 h. PBS were added as control in non-stimulation conditions. After that, RNA extraction was performed to analyze NRP-1 expression levels by real-time PCR. 4.7. NRP-1 Inhibiton and Stimulation Conditions Primary human cells were cultured in their appropriate medium and at passage 2 were plated onto 24-well or 96-well Cell+ culture plates (Sarstedt, Nümbrecht, Germany). After 24 h, primary cells were confluence between 70–80% and they were transfected with gRNA NRP-1 or their negative-control using LipofectamineTM CRISPRMAXTM Reagent Cas9 Nuclease Transfection Protocol (Invitrogen, Carlsbad, CA, USA) following the manufacturer’s instructions. After inhibition of NRP-1, renal cells were stimulated with different conditions during 24 h: 50 ng/mL of VEGF (Gibco®Thermofisher Scientific, Carlsbad, CA, USA), 50 ng/mL PDGFB (ThermoFisher, Carlsbad, CA, USA) or Non-stimulation as negative control. After that, wound healing assay, proliferation assay, apoptosis assay, immunofluorescence assay, or RNA extraction were performed. Int. J. Mol. Sci. 2019, 20, 4601 16 of 19 4.8. Wound Healing Assay To perform wound healing assays, we used a scratch assay in primary cultured cells inhibiting the NRP-1 gene and following stimulatory conditions. To calculate migration, we used the analysis of bright field microscopic images by determining the distance between wound edges over time compared to the control (more details in Supporting Information). 4.9. Proliferation Assay After 24 h of stimulation, proliferation assays were performed using CyQUANT® NF Cell Proliferation Assay Kit (ThermoFisher, Carlsbad, CA, USA) following the manufacturer’s instructions. The diluted CyQUANT® NF dye reagent was added to every well and the fluorescence was measured using a fluorescence microplate reader with excitation at 485 nm and emission detection at 530 nm. 4.10. Migration Assay Migration assay was conducted using Boyden chambers with 8-µm-pore polycarbonate membranes. The chambers were placed in culture wells in medium supplemented with PDGFB stimulation or non-stimulation. Cells that migrated across the chamber membrane within 6 h were stained with DAPI and quantified using immunofluorescence microscopy. At least, three independent experiments were performed, and results of representative experiments were shown. 4.11. Apoptosis Assay Apoptosis assay were carried out using Dead Cell Apoptosis Kith with APC annexin V and SYTOX® Green Flow Cytometry (ThermoFisher, Carlsbad, CA, USA) following the manufacturer’s instructions. Cells were stained using two fluorophores: Annexin V conjugated to allophycocyanin (APC) to detect apoptotic cell and SYTOX Green dye to stain dead cells. After incubation during 15 min at 37 ◦ C, stained cells were analyzed by flow cytometry (BD LSRFortessa™, Haryana, India). 4.12. Immunofluorescence Assay For immunofluorescence, cells were incubated with PFA 4% during 20 min. After washing with PBS, they were incubated with 0.1% triton during 10 min. Blocking using PBS 5% BSA was performed during 1 h at room temperature and primary antibody Rabbit pAb to VEGFR2 and NRP-1 Mouse monoclonal IgG (1:200, Santa Cruz Biotechnology, Dallas, TX, USA) were incubated overnight at 4 ◦ C. Secondary antibodies were incubated during 2.5 h at room temperature (more details in Supporting Information). 4.13. Statistical Analysis Raw threshold cycle (Ct) values were imported from ABI7000 SDS software and relative expression levels for each mRNA were calculated using the comparative Ct method. Continuous variables were compared using Student’s t-test or one-way ANOVA followed by Tukey’s multiple comparison test when appropriate. Categorical data were compared by the Chi-square test. Spearman’s rank-order correlation was used to analyze the correlation between two parameters. Time-to-event analyses were performed with Kaplan-Meier method and log-rank test. The diagnostic performance of biomarkers was evaluated by calculating their sensitivity and specificity using ROC curves. Cutoff values were determined according to Youden’s index. A p value <0.05 was considered statistically significant. Statistical analyses were performed by GraphPad Prism version 6 (GraphPad Software, La Jolla, CA, USA) and SAS version 9.3 (SAS Institute Inc., Cary, NC, USA). Supplementary Materials: Supplementary materials can be found at http://www.mdpi.com/1422-0067/20/18/ 4601/s1. Author Contributions: Conceptualization, A.S., G.H., M.T.T.-S., J.O.-R. and J.C.-H.; methodology, M.T.T.-S., C.S. and M.S.; validation, C.S., T.M. and M.S.; formal analysis, C.S., M.T.T.-S., M.S., J.O.-R. and J.C.-H.; investigation, Int. J. Mol. Sci. 2019, 20, 4601 17 of 19 C.S., M.T.T.-S., M.S., M.V., J.O.-R. and J.C.-H.; resources, J.O.-R. and J.C.-H.; data curation, X.V., M.T.T.-S., M.S., C.S., J.O.-R. and J.C.-H.; writing—original draft preparation, C.S. and M.S.; writing—review and editing, M.T.T.-S., J.O.-R. and J.C.-H.; visualization, M.T.T.-S., M.S., C.S., T.M., M.V., X.V., A.S., G.H., J.O.-R. and J.C.-H.; supervision, G.H., J.O.-R. and J.C.-H.; project administration, J.O.-R. and J.C.-H.; funding acquisition, J.O.-R. and J.C.-H. Funding: This work was supported by grants from the Spain Government (Instituto de Salud Carlos III). This research also received donations from Catalan Lupus Foundation and A.Bosch Foundation. The funders of this study were not involved in study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication. Acknowledgments: The authors acknowledge the sources of funding and the patients and all lupus patients for take part in the study. Conflicts of Interest: The authors declare no conflict of interest. References 1. Rahman, A.; Isenberg, D.A. Systemic lupus erythematosus. N. Engl. J. Med. 2008, 358, 929–939. [CrossRef] 2. Parodis, I.; Zickert, A.; Sundelin, B.; Axelsson, M.; Gerhardsson, J.; Svenungsson, E.; Malmström, V.; Gunnarsson, I. Evaluation of B lymphocyte stimulator and a proliferation inducing ligand as candidate biomarkers in lupus nephritis based on clinical and histopathological outcome following induction therapy. Lupus Sci. Med. 2015, 2, e000061. [CrossRef] [PubMed] 3. Cervera, R.; Khamashta, M.A.; Font, J.; Sebastiani, G.D.; Gil, A.; Lavilla, P.; Mejía, J.C.; Aydintug, A.O.; Chwalinska-Sadowsa, H.; de Ramón, E.; et al. Morbidity and mortality in systemic lupus erythematosus during a 10-year period: A comparison of early and late manifestations in a cohort of 1000 patients. Medicine 2003, 82, 299–308. [CrossRef] [PubMed] 4. Baker, K.P.; Edwards, B.M.; Main, S.H.; Choi, G.H.; Wager, R.E.; Halpern, W.G.; Lappin, P.B.; Riccobene, T.; Abramina, D.; Sekut, L.; et al. Generation and characterization of LymphoStat-B, a human monoclonal antibody that antagonizes the bioactivities of B lymphocyte stimulator. Arthritis Rheumatol. 2003, 48, 3253–3265. [CrossRef] 5. Kolodkin, A.L.; Lavengood, D.V.; Rowe, E.G.; Tai, Y.T.; Giger, R.J.; Ginty, D.D. Neuropilin is a semaphorin III receptor. Cell 1997, 90, 753–762. [CrossRef] 6. Schramek, H.; Sarközi, R.; Lauterberg, C.; Kronbichler, A.; Pirklbauer, M.; Albrecht, R.; Noppert, S.J.; Perco, P.; Rudnicki, M.; Strutz, F.M.; et al. Neuropilin-1 and neuropilin-2 are differentially expressed in human proteinuric nephropathies and cytokine-stimulated proximal tubular cells. Lab. Investig. 2009, 89, 1304–1316. [CrossRef] [PubMed] 7. Hu, C.; Jiang, X. The effect of anti-angiogenic drugs on regulatory T cells in the tumor microenvironment. Biomed. Pharmacother. 2017, 88, 134–137. [CrossRef] [PubMed] 8. Tordjman, R.; Lepelletier, Y.; Lemarchandel, V.; Cambot, M.; Gaulard, P.; Hermine, O.; Roméo, P.H. A neuronal receptor, neuropilin-1, is essential for the initiation of the primary immune response. Nat. Immunol. 2002, 3, 477–482. [CrossRef] [PubMed] 9. Perälä, N.; Sariola, H.; Immonen, T. More than nervous: The emerging roles of plexins. Differentiation 2012, 83, 77–91. [CrossRef] [PubMed] 10. Glinka, Y.; Prud’homme, G.J. Neuropilin-1 is a receptor for transforming growth factor-1, activates its latent form, and promotes regulatory T cell activity. J. Leukoc. Biol. 2008, 84, 302–310. [CrossRef] [PubMed] 11. Bruder, D.; Probst-Kepper, M.; Westendorf, A.M.; Geffers, R.; Beissert, S.; Loser, K.; von Boehmer, H.; Buer, J.; Hansen, W. Neuropilin-1: A surface marker of regulatory T cells. Eur. J. Immunol. 2004, 34, 623–630. [CrossRef] [PubMed] 12. Sarris, M.; Andersen, K.G.; Randow, F.; Mayr, L.; Betz, A.G. Neuropilin-1 expression on regulatory T cells enhances their interactions with dendritic cells during antigen recognition. Immunity 2008, 28, 402–413. [CrossRef] [PubMed] 13. Mizui, M.; Kikutani, H. Neuropilin-1: The glue between regulatory T cells and dendritic cells? Immunity 2008, 28, 302–303. [CrossRef] [PubMed] 14. Staton, C.A.; Kumar, I.; Reed, N.W.; Brown, N.J. Neuropilins in physiological and pathological angiogenesis. J. Pathol. 2007, 212, 237–248. [CrossRef] [PubMed] 15. Fuh, G.; Garcia, K.C.; de Vos, A.M. The interaction of neuropilin-1 with vascular endothelial growth factor and its receptor Flt-1. J. Biol. Chem. 2000, 275, 26690–26695. [CrossRef] Int. J. Mol. Sci. 2019, 20, 4601 18 of 19 16. Gagnon, M.L.; Bielenberg, D.R.; Grechtman, Z.; Miao, H.Q.; Takashima, S.; Soker, S.; Kagsbrun, M. Identification of a natural soluble neuropilin-1 that binds vascular endothelial growth factor: In vivo expression and antitumor activity. Proc. Natl. Acad. Sci. USA 2000, 97, 2573–2578. [CrossRef] 17. Karihaloo, A.; Karumanchi, S.A.; Cantley, W.L.; Venkatesha, S.; Cantley, L.G.; Kale, S. Vascular endothelial growth factor induces branching morphogenesis/tubulogenesis in renal epithelial cells in a neuropilin-dependent fashion. Mol. Cell. Biol. 2005, 25, 7441–7448. [CrossRef] 18. Villegas, G.; Tufro, A. Ontogeny of semaphorins 3A and 3F and their receptors neuropilins 1 and 2 in the kidney. Mech. Dev. 2002, 119, S149–S153. [CrossRef] 19. Thomas, S.; Vanuystel, J.; Gruden, G.; Rodríguez, V.; Burt, D.; Gnudi, L.; Hartley, B.; Viberti, G. Vascular endothelial growth factor receptors in human mesangium in vitro and in glomerular diseases. J. Am. Soc. Nephrol. 2000, 11, 1236–1243. 20. Vadasz, Z.; Haj, T.; Halasz, K.; Rosner, I.; Slobodin, G.; Attias, D.; Kessel, A.; Kessler, O.; Neufeld, G.; Toubi, E. Semaphorin 3A is a marker for disease activity and a potential immunoregulator in systemic lupus erythematosus. Arthritis Res. Ther. 2012, 14, R146. [CrossRef] 21. Vadasz, Z.; Haj, T.; Balber, A.; Peri, R.; Rosner, I.; Slobodin, G.; Kessel, A.; Toubi, E. A regulatory role for CD72 expression on B cells in systemic lupus erythematosus. Semin. Arthritis Rheum. 2014, 43, 767–771. [CrossRef] [PubMed] 22. Vadasz, Z.; Ben-Izhak, O.; Bejar, J.; Sabo, E.; Kessel, A.; Storch, S.; Toubi, E. The involvement of immune semaphorins and neuropilin-1 in lupus nephritis. Lupus 2011, 20, 1466–1473. [CrossRef] [PubMed] 23. Chen, Y.E.; Korbet, S.M.; Katz, R.S.; Schwartz, M.M.; Lewis, E.J.; Collaboratie Study Group. Value of a Complete or Partial Remission in Severe Lupus Nephritis. Clin. J. Am. Soc. Nephrol. 2008, 3, 46–53. [CrossRef] [PubMed] 24. Austin, H.A., 3rd; Muenz, L.R.; Joyce, K.M.; Antonovych, T.A.; Kullick, M.E.; Klippel, J.H.; Decker, J.L.; Balow, J.E. Prognostic factors in lupus nephritis. Contribution of renal histologic data. Am. J. Med. 1983, 75, 382–391. [CrossRef] 25. Ayodele, O.E.; Okpechi, I.G.; Swanepoel, C.R. Predictors of poor renal outcome in patients with biopsy-proven lupus nephritis. Nephrology 2010, 15, 482–490. [CrossRef] [PubMed] 26. Avihingsanon, Y.; Benjachat, T.; Tassanarong, A.; Sodsai, P.; Kittikovit, V.; Hirankarn, N. Decreased renal expression of vascular endothelial growth factor in lupus nephritis is associated with worse prognosis. Kidney Int. 2009, 75, 1340–1348. [CrossRef] [PubMed] 27. Hankenson, K.D.; Dishowitz, M.; Gray, C.; Schenker, M. Angiogenesis in bone regeneration. Injury 2011, 42, 556–561. [CrossRef] [PubMed] 28. Daniel, C.; Lüdke, A.; Wagner, A.; Todorov, V.T.; Hohenstein, B.; Hugo, C. Transgelin is a marker of repopulating mesangial cells after injury and promotes their proliferation and migration. Lab. Invest. 2012, 92, 812–826. [CrossRef] 29. Bartlett, C.S.; Scott, R.P.; Carota, I.A.; Wnuk, M.L.; Kanwar, Y.S.; Miner, J.H.; Quaggin, S.E. Glomerular mesangial cell recruitment and function require the co-receptor neuropilin-1. Am. J. Physiol. Ren. Physiol. 2017, 313, F1232–F1242. [CrossRef] 30. Gavalas, N.G.; Tsjatas, M.; Tsitsilonis, O.; Politi, E.; Ioannou, K.; Ziogas, A.C.; Rodolakis, A.; Vlahos, G.; Thomakos, N.; Haidopoulos, D.; et al. VEGF directly suppresses activation of T cells from ascites secondary to ovarian cancer via VEGF receptor type 2. Br. J. Cancer 2012, 107, 1869–1875. [CrossRef] 31. Ziogas, A.C.; Gavalas, N.G.; Tsiatas, M.; Tsitsilonis, O.; Politi, E.; Terpos, E.; Rodolakis, A.; Vlahos, G.; Thomakos, N.; Haidopoulos, D.; et al. VEGF directly suppresses activation of T cells from ovarian cancer patients and healthy individuals via VEGF receptor Type 2. Int. J. Cancer 2012, 130, 857–864. [CrossRef] [PubMed] 32. Couzi, L.; Merville, P.; Deminière, C.; Moreau, J.F.; Combe, C.; Pellegrin, J.L.; Viallard, J.F.; Blanco, P. Predominance of CD8+ T lymphocytes among periglomerular infiltrating cells and link to the prognosis of class III and class IV lupus nephritis. Arthritis Rheum. 2007, 56, 2362–2370. [CrossRef] [PubMed] 33. Roy, S.; Bag, A.K.; Singh, R.K.; Talmadge, J.E.; Batra, S.K.; Datta, K. Multifaceted Role of Neuropilins in the Immune System: Potential Targets for Immunotherapy. Front. Immunol. 2017, 10, 1228. [CrossRef] [PubMed] 34. Hochberg, M.C. Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum. 1997, 40, 1725. [CrossRef] Int. J. Mol. Sci. 2019, 20, 4601 19 of 19 35. Gladman, D.D.; Ibanez, D.; Urowitz, M.B. Systemic lupus erythematosus disease activity index 2000. J. Rheumatol. 2002, 29, 288–291. [PubMed] 36. Renal Disease Subcommittee of the American College of Rheumatology Ad Hoc Committee on Systemic Lupus Erythematosus Response Criteria. The American College of Rheumatology response criteria for proliferative and membranous renal disease in systemic lupus erythematosus clinical trials. Arthritis Rheum. 2006, 54, 421–432. [CrossRef] [PubMed] 37. Betsias, G.K.; Tektonidou, M.; Amoura, Z.; Aringer, M.; Bajema, I.; Berden, J.H.; Boletis, J.; Cervera, R.; Dörner, T.; Doria, A.; et al. Joint European League Against Rheumatism and Europena Renal association-European Dialysis and transplant Association (EULAR/ERA-EDTA) recommendations for the management of adult and paediatric lupus nephritis. Ann. Rheum. Dis. 2012, 71, 1771–1782. [CrossRef] [PubMed] 38. Weening, J.J.; D’Agati, V.D.; Schwartz, M.M.; Seshan, S.V.; Alpers, C.E.; Appel, G.B.; Balow, J.E.; Brujin, J.A.; Cook, T.; Ferrario, F.; et al. The classification of glomerulonephritis in systemic lupus erythematosus revisited. J. Am. Soc. Nephrol. 2004, 15, 241–250. [CrossRef] [PubMed] 39. Cortés-Hernández, J.; Torres-Salido, M.T.; Medrano, A.S.; Tarrés, M.V.; Ordi-Ros, J. Long-term outcomes–mycophenolate mofetil treatment for lupus nephritis with addition of tacrolimus for resistant cases. Nephrol. Dial. Transplant. 2010, 25, 3939–3948. [CrossRef] © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).