cancers Article Loss of microRNA-135b Enhances Bone Metastasis in Prostate Cancer and Predicts Aggressiveness in Human Prostate Samples Mireia Olivan 1,2,3, *,† , Marta Garcia 3,4,† , Leticia Suárez 3 , Marc Guiu 5 , Laura Gros 3 , Olga Méndez 3 , Marina Rigau 6 , Jaume Reventós 6,7,8 , Miguel F. Segura 9 , Inés de Torres 3,10 , Jacques Planas 3,11 , Xavier de la Cruz 12,13 , Roger R. Gomis 5,7,12 , Juan Morote 3,11 , Ruth Rodríguez-Barrueco 1,2,‡ and Anna Santamaria 3, *,‡ 1 Translational Oncology Laboratory, Anatomy Unit, Department of Pathology and Experimental Therapy, School of Medicine, Universitat de Barcelona (UB), 08907 L’Hospitalet de Llobregat, Spain; rrodriguezb@ub.edu 2 Molecular Mechanisms and Experimental Therapy in Oncology-Oncobell Program, Bellvitge Biomedical Research Institute (IDIBELL), 08908 L’Hospitalet de Llobregat, Spain 3 Cell Cycle and Cancer Laboratory, Biomedical Research Group in Urology, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Spain; marta.garcial@sjd.es (M.G.); leticia.suarez@vhir.org (L.S.); laura.gros@mafrica.es (L.G.); olga.mendez@vhir.org (O.M.); itorres@vhebron.net (I.d.T.); jplanas@vhebron.net (J.P.); jmorote@vhebron.net (J.M.) 4 Developmental Tumor Biology Laboratory, Institut de Recerca Sant Joan de Déu, 08950 Esplugues de Llobregat, Spain  5 Cancer Science Programme, Institute for Research in Biomedicine (IRB-Barcelona), 08028 Barcelona, Spain;  marc.guiu@irbbarcelona.org (M.G.); roger.gomis@irbbarcelona.org (R.R.G.) 6 Bellvitge Biomedical Research Institute (IDIBELL), 08908 L’Hospitalet de Llobregat, Spain; Citation: Olivan, M.; Garcia, M.; Suárez, L.; Guiu, M.; Gros, L.; mrigau@idibell.cat (M.R.); jreventos@uic.es (J.R.) 7 Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), 28029 Madrid, Spain Méndez, O.; Rigau, M.; Reventós, J.; 8 Departament de Ciències Bàsiques, Universitat Internacional de Catalunya, 08017 Barcelona, Spain Segura, M.F.; de Torres, I.; et al. Loss 9 Group of Translational Research in Child and Adolescent Cancer, Vall d’Hebron Research Institute (VHIR), of microRNA-135b Enhances Bone Universitat Autònoma de Barcelona (UAB), 08035 Barcelona, Spain; miguel.segura@vhir.org Metastasis in Prostate Cancer and 10 Department of Pathology, University Hospital Vall d’Hebron, Universitat Autònoma de Barcelona (UAB), Predicts Aggressiveness in Human 08035 Barcelona, Spain Prostate Samples. Cancers 2021, 13, 11 Department of Urology, University Hospital Vall d’Hebron, Universitat Autònoma de Barcelona (UAB), 6202. https://doi.org/10.3390/ 08035 Barcelona, Spain 12 Institució Catalana de Recerca i Estudis Avançats (ICREA), 08010 Barcelona, Spain; xavier.delacruz@vhir.org cancers13246202 13 Group of Clinical and Translational Bioinformatics, Vall d’Hebron Research Institute (VHIR), Academic Editor: Lyndsay Rhodes Universitat Autònoma de Barcelona (UAB), 08035 Barcelona, Spain * Correspondence: mireiaolivan@ub.edu (M.O.); anna.santamaria@vhir.org (A.S.); Tel.: +34-934035890 (M.O.); +34-932746708 (A.S.) Received: 21 November 2021 † The authors contributed equally to this work. Accepted: 3 December 2021 ‡ The authors contributed equally to this work. Published: 9 December 2021 Simple Summary: Prostate cancer (PCa) is the most prevalent cancer in males worldwide, and it Publisher’s Note: MDPI stays neutral was the fifth leading cause of cancer mortality in this group in 2020. Near 70% of advanced-stage with regard to jurisdictional claims in PCa patients will undergo bone metastasis, suffering pathological complications that severely affect published maps and institutional affil- patients’ quality of life and probably progress in most cases to lethal PCa. Our main objective was to iations. unveil novel molecules associated with choosing the bone as a metastatic niche. For this purpose, we generated and characterized a cell line with increased tropism to bone. Its molecular analysis has led us to identify factors with a potential role in bone metastasis that could also be used as biomarkers of disease progression. These data help us to understand the mechanisms that increase Copyright: © 2021 by the authors. bone metastasis penetrance of PCa cells and could provide new therapeutic tools in the future for Licensee MDPI, Basel, Switzerland. patients with worse prognoses. This article is an open access article distributed under the terms and conditions of the Creative Commons Abstract: About 70% of advanced-stage prostate cancer (PCa) patients will experience bone metasta- Attribution (CC BY) license (https:// sis, which severely affects patients’ quality of life and progresses to lethal PCa in most cases. Hence, creativecommons.org/licenses/by/ understanding the molecular heterogeneity of PCa cell populations and the signaling pathways 4.0/). associated with bone tropism is crucial. For this purpose, we generated an animal model with high Cancers 2021, 13, 6202. https://doi.org/10.3390/cancers13246202 https://www.mdpi.com/journal/cancers Cancers 2021, 13, 6202 2 of 22 penetrance to metastasize to bone using an intracardiac percutaneous injection of PC3 cells to identify PCa metastasis-promoting factors. Using genomic high-throughput analysis we identified a miRNA signature involved in bone metastasis that also presents potential as a biomarker of PCa progression in human samples. In particular, the downregulation of miR-135b favored the incidence of bone metastases by significantly increasing PCa cells’ migratory capacity. Moreover, the PLAG1, JAKMIP2, PDGFA, and VTI1b target genes were identified as potential mediators of miR-135b’s role in the dissemination to bone. In this study, we provide a genomic signature involved in PCa bone growth, contributing to a better understanding of the mechanisms responsible for this process. In the future, our results could ultimately translate into promising new therapeutic targets for the treatment of lethal PCa. Keywords: miRNA-135b; prostate cancer; bone metastasis; miRNAs 1. Introduction Bone metastasis is a common complication of cancer and occurs in around 70% of patients with metastatic prostate cancer (PCa), PCa being the second-most commonly diagnosed cancer in men in the western world [1]. Generally, patients with advanced-stage PCa are treated with androgen deprivation therapy (ADT). Unfortunately, ADT is only tem- porarily effective in most cases; PCa gradually acquires resistance to androgen deprivation and eventually becomes castration-resistant PCa (CRPC), which is often associated with tumor dissemination [2]. This type of cancer is frequently multifocal, and it is associated with a higher grade, stage, and recurrence rate [3]. Such heterogeneity has an impact on PCa progression since individual cancer cells contained within the tumor may have distinct genomic profiles and, consequently, influence the efficacy of current and future therapies [3,4]. Bone metastasis results in devastating consequences for patients such as pain, hyper- calcemia, and spinal cord and nerve-compression syndromes; importantly, after metastasis, tumors become generally incurable [5]. Each metastatic microenvironment favors or op- poses colonization by disseminated tumor cells. Therefore, assuming that disseminated tumor cells that populate the bone marrow arise from primary tumors and could be found in early stages of the disease, understanding the distinct organ-specific mechanisms that enable metastatic growth is paramount. For this, clonal selection strategies based on preclinical models that faithfully reproduce some stages of bone metastasis have been developed [6,7]. These models provide us with useful tools to better understand the molecular basis underlying the orchestration of bone metastasis from initiation to develop- ment of distant dissemination and lead us to engineer solutions to improve outcomes for PCa patients. Small non-coding microRNAs (miRNAs) are master regulators of gene expression which have the capacity to regulate multiple genes simultaneously and, thus, to redirect biological pathways [8]. Due to their properties, miRNAs emerged as promising tools for diagnosis, prognosis determination, and management of cancer patients [9,10]. In recent years, numerous studies have identified that the dysregulation of miRNA expression in cancer cells can modulate multiple aspects of cancer progression [11–15], including the bone metastasis process [8,16,17]. To date, some miRNAs have already been identified as metastasis suppressors in PCa, including miR-33a [18], the miR-34 family [19], miR- 145 [20], miR-212 [21], and the miR-200 family [22]. On the other hand, a set of miRNAs has been identified as metastasis-promoting miRNAs such as miR-9 [23], miR-181a [24], miR-210-3 [25], and miR-454 [26]. Zhu et al. identified the miR-636 that is up-regulated in bone metastatic PCa tissue, and they found that this miRNA could promote migration and invasion by targeting MBNL2, TNS1, and STAB1 [17,27]. Of particular relevance to this study, miR-135b has been reported to be aberrantly expressed and to play different roles in the progression of a variety of cancers in a context-dependent manner. It has been shown Cancers 2021, 13, 6202 3 of 22 that miR-135b has an oncogenic role in non-small-cell lung cancer [28], gastric cancer [29], colon cancer [30], and pancreatic cancer [31], among other tumor types. Contrary to this, miR-135b has also been identified as a tumor-suppressor miRNA in breast cancer [32] and osteosarcoma [33]. Focusing on the PCa context, only a few studies have been conducted to rule out the function of miR-135b on androgen receptor (AR) regulation [34–36]. Inter- estingly, Wang et al. [37] found that the expression of miR-135b was associated with tumor metastasis suppression by targeting STAT6. In summary, despite the progress of miRNAs that have been incorporated as diagnostic and therapeutic targets in clinical trials for solid tumors [38,39], to date none of them are aimed at targeting PCa metastasis [40]. Therefore, it is important to shed light on which miRNAs regulate tumorigenesis and metastasis, and how those miRNAs do this, so that they can be included in the future management of patients with PCa metastasis. In this study, we report the establishment and characterization of a high-penetrant PCa bone-metastasizing cell line after several rounds of intracardiac injection in mice. In vivo selection gave rise to aggressive bone-seeking variants of PCa cells with an increased ability to grow in the bone. Using genomic high-throughput expression analysis and functional studies, we found evidence for a role of miR-135b downregulation in highly metastatic tumor cells suggesting that populations with low levels of miR-135b present in the primary tumors could potentiate the bone metastatic spread. Restoration of miR-135b in PCa cells decreased their migratory capacity. Furthermore, we found PLAG1, JAKMIP2, PDGFA, and VTI1b to be directly regulated by miR-135b and to be potential downstream effectors of miR-135b phenotypic effects. In summary, our data unveil a novel key regulator of bone metastatic PCa dissemination and enable future characterization of the dynamic changes in the bone metastatic niche, suggesting new therapeutic targets to be considered for the treatment of this lethal disease. 2. Materials and Methods 2.1. Cell Lines The human PCa cell line PC3 was obtained from the American Type Culture Collection (#CRL-1435, ATCC, Rockville, MD, USA). The PC3 bone-metastatic clone (PC3-BM) was isolated from bone metastases produced in nude mice after intracardiac injection of PC3 cells. Both parental PC3 (PC3-P) and clone-derivative cells carried the firefly luciferase gene coding region cloned upstream of the green fluorescent protein (GFP) gene as described be- fore [41]. PCa cells were cultured at 37 ◦ C in a humidified atmosphere (5% CO2 /95% air), in complete media RPMI-1640 (Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (FBS), 50 U/mL penicillin and streptomycin, 1X non-essential amino acids (MEM), 2 mM L-glutamine, 10 mM HEPES (all from Gibco), and 1 mM sodium pyruvate (PAA Laboratories, Manchester, UK). The osteoblast cell line (hFOB 1.19) was kindly provided by Dr. Javier Garcia Castro (Cellular Biotechnology Unit from the Instituto de Salud Carlos III) and cultured with 1:1 mixture of Ham’s F12 Medium Dulbecco’s Modified Eagle’s Medium, with 2.5 mM L -glutamine (without phenol red) supplemented with 1% G418 (Thermo Fisher Scientific, Waltham, MA, USA) and fetal bovine serum to a final concentration of 10%. 2.2. Animal Model Congenitally athymic male nude mice (Hsd.Athymic Nude-Foxn1nu ) were purchased from Harlan Laboratories (Italy) at 4 weeks of age and maintained under specific pathogen- free conditions. The animals were kept in a sterile environment in cages with beds of sterilized soft wood granulate and fed an irradiated rodent diet ad libitum with autoclaved tap water. All the procedures associated with experimentation and animal care were performed according to the guidelines of the Spanish Council for Animal Care and the protocols of the ethics committee for animal experimentation at our own institution. Five-week-old male mice were deeply anesthetized with ketamine (100 mg/kg of body weight) and xylazine (10 mg/kg of body weight) solution, and PC3 luciferase-transfected Cancers 2021, 13, 6202 4 of 22 cells (3 × 105 in 0.1 mL sterile PBS) were inoculated by intracardiac (i.c.) injection using a 25-gauge syringe. The presence of a rapid pulsatile flow of bright red arterial blood into the syringe was indicative of correct needle placement, as opposed to darker, burgundy- colored blood [42]. Mice were imaged for luciferase activity immediately after injection and continued to be monitored weekly using IVIS® imaging. Animals were sacrificed by cervical dislocation 6 weeks post-injection, or earlier if there were early signs of serious distress. As a quality control, photon flux for each mouse was measured by the number of highlighted pixels calculated by using a circular region of interest (ROI) in a ventral or dorsal position and normalized to the value obtained immediately after xenografting at the same area (day 0) of each mouse, so that all mice had an arbitrary starting bioluminescence signal of 1. Bioluminescence imaging (BLI) was assessed to monitor tumor burden and tumor cell localization. Tumor-induced bone destruction was analyzed by micro-CT imaging using a Skyscan 1076 desktop microtomograph with high resolution capture and 3D modelling (Skyscan, Kontich, Belgium). After the mice were sacrificed, tumor cells from bone metastases were localized by ex vivo BLI imaging and freshly harvested under sterile conditions using a flushing procedure. Bone marrow and tumor cells were rinsed with PBS and put in cell culture dishes with geneticin selection. Attached cells were expanded in vitro and selected by GFP fluorescence-activated cell sorting using the FacsAria (BD Bioscience, San Jose, CA, USA) and reinjected via i.c. injection into a second set of animals. This process, based on the in vivo selection of metastatic PC3 cells, was repeated three times (n = 5 mice/round). 2.3. Study Subjects This study was approved by the Clinical Research Ethics Committee from Vall Hebron University Hospital (PR(AG)96-2015). Written informed consent was obtained from all the study participants and samples were coded to ensure sample tracking and confidentiality of patient/donor identity. A total of 42 formalin-fixed and paraffin-embedded (FFPE) samples from radical prostatectomies (RP) were available from the archives of the Pathology Department of the Vall Hebron University Hospital (Barcelona, Spain) and kindly provided by Antonio López-Guerrero and Jose Rubio-Briones from Instituto Valenciano de Oncología (Valencia, Spain); the clinic–pathologic features of these patients are detailed in Table S1. FFPE samples from patients who underwent RP were divided into two study groups: (i) patients without biochemical recurrence (BCR) after ≥10 years of follow up (No-BCR) and (ii) patients who had BCR (1–5 years after RP). BCR is defined as the first post-operative PSA of >0.4 ng/mL, as confirmed by at least one subsequent increasing value (persistent PSA increase) after achieving undetectable PSA post-operatively. Plasma samples were obtained from 40 men with suspicion of PCa according to abnormal digital rectal examination (DRE) and/or serum PSA levels higher than 4 ng/mL, referred for a first prostate biopsy at the Urology Department of the Vall Hebron University Hospital (Barcelona, Spain). Patients with a diagnosis of PCa were divided into three groups: (i) localized PCa, (ii) locally advanced PCa, and (iii) metastatic PCa. Moreover, age-matched controls were selected. The clinic–pathologic features of these patients are detailed in Table S2. 2.3.1. Laser Capture Microdissection (LCM) A slide of each FFPE sample was stained with hematoxylin, and an experienced pathologist selected the area of the tumor that presented the most predominant pattern of Gleason Score. To ensure that the entire sample used for subsequent RNA extraction was only tumoral tissue, laser capture microdissection was performed. Areas with high density and purity of tumor cells (>80%) were marked for microdissection of adjacent sections to minimize contamination from surrounding healthy prostate tissue. Overlapping areas in up to six adjacent slides were microdissected using a Leica LMD 6000 microdissection system (Leica Microsistemas S.L.U, L’Hospitalet de Llobregat, Spain). Samples were obtained from 10 to 15 µm unstained histological sections under the guidance of a hematoxylin-stained Cancers 2021, 13, 6202 5 of 22 slide using an FSX100 System Olympus microscope (Olympus, Shinjuku City, Tokyo) and placed into sterile tubes for a subsequent RNA extraction. 2.3.2. Plasma Collection Blood samples were collected in EDTA-containing tubes at room temperature and processed for plasma isolation within 2 h. Blood samples were centrifuged at 4 ◦ C for 20 min at 1500× g. Plasma was then aliquoted and stored at −80 ◦ C within 24 h. 2.4. In Vitro Assays 2.4.1. Transient Transfection of miRNA Mimics Cells were transfected using synthetic oligonucleotides miRIDIAN Mimic (Dharma- con; Thermo Fisher Scientific, Waltham, MA, USA) with a final concentration of 25 nM. Transfection was performed using Lipofectamine 2000 (Invitrogen, Life Technologies, Waltham, MA, USA) following the manufacturer’s instructions. To obtain transfection vesicles, the lipofectamine and oligonucleotides were diluted and mixed in an OPTI-MEM medium (Gibco) and incubated for 20 min, then the mix was added to cell cultures and incubated for 12h. Following that, the medium was changed to avoid lipofectamine toxicity. 2.4.2. Proliferation Analysis For the proliferation experiments, 96 h post-transfection cells were seeded at 5 × 103 cells per well on a 96-well plate (n = 6/condition). At the indicated time point, cells were fixed in a 4% formaldehyde solution and stained with 0.5% crystal violet. Crystals were dissolved with 15% acetic acid and the optical density was read at 590 nm using the Epoch Microplate Spectrophotometer (Agilent Technologies, Santa Clara, CA, USA). 2.4.3. Transwell Migration Assay For co-culture experiments, osteoblasts were seeded (5 × 104 /well) at the bottom of a 24-well plate with complete media for 24 h. The following day, PCa cells were seeded (1.0 × 105 cells/ insert) onto transwell inserts (BD Bioscience, San Jose, CA, USA) with 8 µm diameter pore membranes in a medium supplemented with 2% FBS in the presence or absence of osteoblast-containing wells. Cells were allowed to migrate for 20 h at 37 ◦ C and then fixed with 4% formaldehyde for 30 min at room temperature (RT). Cells that had attached to the membrane but not migrated were completely removed using a cotton swab. Migrated cells were stained with 1 µL/mL Hoechst 33258 (Sigma-Aldrich, St Louis, MO, USA) for 10 min at RT and counted. 2.4.4. 30 -UTR Cloning and Luciferase Assay The 30 -UTR regions of VTI1b, PLAG1, JAKMIP2, and PDGFA were defined using GeneArt Strings (TM) and a DNA Fragment Construction system (Thermo Fisher Scientific, Waltham, MA, USA) and were cloned downstream of the luciferase-reporter in the pMIR- REPORT vector (Life Technologies, AM5795M). To measure luciferase activity, phoenix cells (ATCC, CRL-3213) were plated at 80% confluence in 96-well black plates (Corning, NY, USA). After 24 h, cells were transfected with 50 ng of pMIR-REPORT constructs containing the luc-30 -UTR sequences in combination with a Renilla normalization control and 50nM artificial miRIDIAN hsa-miR135b Mimic (Dharmacon; Thermo Fisher Scientific, Waltham, MA, USA) or a miRIDIAN Mimic negative control (Dharmacon; Thermo Fisher Scientific, Waltham, MA, USA, NC-001000-01-05) using the TransIT-X2 transfection reagent (Mirus, MIR6000, Madison, WI, USA). After 24 h, relative luciferase units (RLU) were measured using the Dual-Glo Luciferase Assay System (Promega, Madison, WI, USA) on a GloMax® -Multi+Microplate Multimode Reader (Promega, Madison, WI, USA). Cancers 2021, 13, 6202 6 of 22 2.5. Molecular Characterization of PC3 Bone-Metastatic Subclones 2.5.1. RNA and miRNA Isolation Total RNA including miRNAs was extracted from PCa cells using the miRNeasy Mini Kit (Qiagen, Madrid, Spain) following the instructions provided by the manufac- turer. RNA quality was confirmed using the Agilent RNA 6000 Nano Kit in Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA) and quantified using Nanodrop 1000 Spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA). Total RNA including miRNAs was extracted from FFPE human tissue samples using the miRNeasy FFPE kit (Qiagen, Madrid, Spain) following the instructions provided by the manufacturer. Relative miRNA expression was performed by RT-qPCR as mentioned below (see Section 2.5.4 Gene and miRNA expression). A pre-amplification step was added after cDNA obtention: 2.5 µL of diluted cDNA (1:8 in 0.1 × TE) was mixed with 22.5 µL of a mix containing TaqMan PreAmp Master Mix (Thermo Fisher Scientific, Waltham, MA, USA) and a pool of selected TaqMan miRNA assays (Thermo Fisher Scientific, Waltham, MA, USA). Reaction conditions were 95 ◦ C for 10 min, 55 ◦ C for 2 min, and 72 ◦ C for 2 min, followed by 12 cycles of 95 ◦ C for 15 s and 60 ◦ C for 4 min, and finally 99.9 ◦ C for 10 min. 2.5.2. MicroRNA Profiling Analysis Total RNA was reverse transcribed using an ABI TaqMan miRNA reverse transcription kit (Thermo Fisher Scientific, Waltham, MA, USA). MiRNA expression was profiled using the TaqMan® Array Human MicroRNA A and B Cards Set v3.0 (Applied Biosystems, Waltham, MA, USA). Each card contains 377 human miRNAs, three endogenous small RNA controls (RNU6, RNU44, and RNU48), and a negative control (Ath-miR159a). All reactions were performed as specified in the manufacturer’s protocols. Cards were run in a 7900HT Fast Real-Time PCR System (Applied Biosystems) under the following thermal cycler conditions: 55 ◦ C for 2 min and 95 ◦ C for 10 min, followed by 40 cycles of 95 ◦ C for 15 s and 55 ◦ C for 1 min. Relative expression levels were calculated according to the 2ˆ-∆∆Ct method normalized by RNU48 snRNA. To compare expression levels between groups, the Student’s t test was used. The cut-off for statistical significance in the miRNA analysis was a p-value ≤ 0.05. 2.5.3. Transcriptomic Array For gene expression microarray analysis, RNAs were amplified, labelled, and hy- bridized to an Affymetrix GeneChip® Human Gene 1.0 ST Array (Affymetrix, High Wycombe, UK). Images were processed using the Microarray Analysis Suite 5.0 (Affymetrix). Data from CEL files were normalized and processed using the robust multichip-averaged (RMA) algorithm. The analysis to select differentially expressed genes was based on ad- justing a linear model with empirical Bayes moderation of the variance (p-value). The selection of differentially expressed genes was based on adjusted p-values (false discovery rate (FDR)) <0.001 and absolute LogFC value > 2. MiRNA and transcriptomic data have been deposited in the Gene Expression Omnibus database (Accession number GSE86917). 2.5.4. Gene and miRNA Expression The reverse transcription of miRNAs was conducted using the TaqMan miRNA re- verse transcription kit (Applied Biosystems). For gene expression, 3 µg of RNA was reversed transcribed to first-strand cDNA using the High-Capacity cDNA Archive Kit (Applied Biosystems). Commercially available TaqMan hydrolysis probes (Applied Biosys- tems) and SYBR Green I were used together with paired primers (KiCqStart® SYBR® Green Primers; Sigma) to analyze the expression of miRNA and gene candidates (listed in the Tables S3 and S4), respectively, in an ABI Prism 7900HT qPCR system (Applied Biosystems). Relative miRNA and gene expression levels were calculated according to the 2ˆ-∆∆Ct method normalized using RNU48 snRNA and the average between GAPDH and HMBS, respectively. Cancers 2021, 13, 6202 7 of 22 2.5.5. miRNA Expression in Plasma Total RNA was extracted from 500 µL of plasma using a Maxwell RSC miRNA Plasma and Serum Kit (Promega, Madison, WI, USA) following the manufacturer’s instructions and eluted in 40 µL of RNase free water. All samples were spiked with 25 fmol/µL of Caenorhabditis elegans miR-39 for use as a normalizer in downstream analyses. miRNA expression levels were evaluated using individual Taqman Advanced miRNA as- says (Thermo Fisher Scientific, Waltham, MA, USA, #A25576): hsa-miR-135b (ID 478581_mir) and cel-miR-39 (ID 478293_mir). According to the manufacturer’s instructions, 10 ng of total RNA was first poly-A tailed and, after adaptor ligation and reverse transcription, pre-amplified for 20 cycles. The pre-amplification product was subsequently diluted 1/5 in 0.1% TE buffer, pH 8.0. A qPCR test was performed using a Taqman Fast Advanced Master mix on a QuantStudio 7 Pro realtime PCR device (Thermo Fisher Scientific, Waltham, MA, USA). Relative expression levels were calculated according to the 2ˆ-∆∆Ct method. To compare expression levels between groups, the nonparametric Mann–Whitney U test was used. 2.6. Bioinformatics Analysis 2.6.1. Pathway Analysis Gene pathway analysis was carried out by the Anaxomics Biotech Company, consid- ering gene expression data from the transcriptomics array and ranking genes according to their statistical significance (LogFC). The enrichment was run over several sets including GO terms (Biological Process, Cellular Component, Molecular Function) according to EMBL-EBI/UniProt-GO [43], KEGG pathways [44], pathological conditions, and motives included in de BED (Anaxomics property database) [45], PharmaGKB pathways [46], the pathways from Small Molecules Pathway database (SMPDB) [47], and the transcription factor profiles included in the TRUST database [48]. Only the sets that showed statistically significant enrichment after multi-testing using the Benjamini–Hochberg correction are presented (FDR < 0.05). 2.6.2. Analysis of miRNA Targets In silico prediction of potentially miR-135b target genes was performed using a miRWalk platform by four independent algorithms (TargetScan [49], miRanda [50], miR- Walk [51], and RNAhybrid [52]). Only targets that were predicted by four algorithms were considered for subsequent studies. KEGG pathways and GO (biological process (BP)) gene sets were also downloaded from miRWalk platform and used to analyze the biological significance of miR-135b predicted targets. A p-value ≤ 0.05 was considered statistically significant. 2.6.3. Analysis of PCa Genomic and Transcriptomic Datasets The TCGA dataset repositories and datasets from different studies with PCa patients were interrogated using the cBioportal website [53]. The clinical information regarding overall and disease-free survival was considered to be correlated with the expression levels of miR-135b target genes. Kaplan–Meier Pots and Logrank Test p-values were obtained. 3. Results 3.1. In Vivo Selection for Bone-Metastasizing PC3 Cells Tumors contain heterogeneous populations with different abilities to metastasize to distant organs such as bones. In order to isolate highly metastatic subpopulations that attach preferably to bone, we generated a bone-seeking variant of the PC3 cell line using in vivo passaging in immunodeficient mice. To this end, PC3 luciferase-expressing cells were inoculated intracardiacally (i.c.). Mice developed bone lesions two weeks after cell inoculation and animals were monitored using bioluminescence (BLI) imaging until the end of the study. After the sacrifice, we isolated PC3-derived metastasis cells from the long bones (femur and tibia), which were shortly expanded in cultures and injected into a new Cancers 2021, 13, x 8 of 24 Cancers 2021, 13, 6202 8 of 22 Tumors contain heterogeneous populations with different abilities to metastasize to distant organs such as bones. In order to isolate highly metastatic subpopulations that attach preferably to bone, we generated a bone-seeking variant of the PC3 cell line using in vivo passaging in immunodeficient mice. To this end, PC3 luciferase-expressing cells group of micewere (Figure 1A,B). inoculated The metastatic intracardiacally subclone (i.c.). Mice developed named bone lesions PC3-BM, two weeks after cell isolated from the inoculation and animals were monitored using bioluminescence (BLI) imaging until the third in vivo round, presented a higher incidence of metastasis end of the study. After the sacrifice, we isolated PC3-derived metastasis cells from the to long bones compared with the parental PC3(femur long bones cellandline (PC3-P) tibia), which were (i.e., 100% shortly versus expanded 20%) in cultures and(Figure 1C). Moreover, the injected into a new group of mice (Figure 1A,B). The metastatic subclone named PC3-BM, isolated from distribution and number of bone metastases generated by PC3-BM the third in vivo round, presented a higher incidence of metastasis to long bones com- cells was higher in leg, spinal cord, paredand scapula with the areas parental PC3 compared cell line (PC3-P) (i.e., with other 100% versus 20%)bones (Figure (Figure 1C). Moreo- 1D). As expected, ver, the distribution and number of bone metastases generated by PC3-BM cells was PC3 cells growing higher ininto thecord, leg, spinal bones caused and scapula areasosteolytic compared withlesions other bonesas analyzed (Figure 1D). As using micro-CT imaging and expected, 3D modelling (Figure PC3 cells growing 1E). into the These bones causedresults suggest osteolytic lesions that PC3-BM as analyzed using cells display micro-CT imaging and 3D modelling (Figure 1E). These results suggest that PC3-BM cells higher efficiency in nesting to the bone and growing into the bone display higher efficiency in nesting to the bone and growing into the bone environment. environment. A Cancers 2021, 13, x 9 of 24 Spinal cord Figure 1.Figure Selection Selection of1.human of tumor PC3 prostate human PC3 cells with prostate increased tumorphenotype. bone metastatic cells with increased (A) View bone metastatic phenotype. of the sequen- tial method for the in vivo selection of PCa cells with bone tropism. (B) Representative bioluminescence imaging (BLI) of (A) View the metastatic of the distribution sequential pattern method of parental and PC3-BM forcells the in vivo over time. selection (C) Incidence ofmetastases of bone PCa cells with for PC3 bone tropism. (B) Represen- cells in long bones after the indicated rounds of in vivo selection. Results are expressed as the percentages of metastases in long bones per total number of long bones in analyzed mice. (D) Distribution and incidence of metastases in the different parental and PC3-BM cells tative bioluminescence imaging (BLI) of the metastatic distribution pattern of isolated bones. overResults time.are(C) expressed as the percentages Incidence of bone of metastases metastases detected by BLI for PC3 imaging cellsperintotal longnumber of animals bones after the indicated rounds of injected in each round. (E) Representative micro-CT images and 3D modelling showing osteolytic lesions caused by PCa inand cells. Black vivo selection. yellow arrows show Results are expressed the metastatic lesions. as the percentages of metastases in long bones per total number of long bones3.2.inTranscriptional analyzedAnalysismice. of(D) Distribution PC3-BM Cells Revealed and incidence Multiple of metastases Bone Metastatic-Related Genes in the different isolated bones. Results are Toexpressed as the percentages describe the molecular of metastases changes associated detected with cells’ ability byto BLI to migrate imaging per total number the bone tissue, we performed a whole-genome expression microarray analysis comparing PC3-P of animals injected in each round. (E) Representative micro-CT images and PC3-BM cells. Principal component analysis segregated both cell lines, which indi- and 3D modelling showing osteolytic lesions caused by PCa cells. Black and yellow arrows show the metastatic lesions. cated a different transcriptional pattern (Figure 2A). This comparison yielded a list of 95 differentially expressed genes with an absolute log FC value ≥ 2 and an adjusted p-value (FDR) < 0.001 (Figure 2B). Among them, 61 genes were found to be upregulated in PC-3- BM cells, whereas 34 were downregulated (Table S5). To better understand the role of those deregulated genes in bone metastasis develop- ment, we performed a KEGG pathway analysis among other analyses (see Section 2) (Ta- ble S6). The differentially expressed genes were grouped into different up and down can- cer-related general processes (Figure 2C,D). We observed enrichment in functions related Cancers 2021, 13, 6202 9 of 22 3.2. Transcriptional Analysis of PC3-BM Cells Revealed Multiple Bone Metastatic-Related Genes To describe the molecular changes associated with cells’ ability to migrate to the bone tissue, we performed a whole-genome expression microarray analysis comparing PC3-P and PC3-BM cells. Principal component analysis segregated both cell lines, which indicated a different transcriptional pattern (Figure 2A). This comparison yielded a list of 95 differentially expressed genes with an absolute log FC value ≥ 2 and an adjusted p-value (FDR) < 0.001 (Figure 2B). Among them, 61 genes were found to be10upregulated Cancers 2021, 13, x of 24 in PC-3-BM cells, whereas 34 were downregulated (Table S5). A PC3-P cells B PC3-BM cells UPREGULATED CANCER-RELATED GENERAL PROCESS Cancer Metastasis Cell division Immune system Bone-related process Angiogenesis Endomembrane system Cholesterol metabolism Extracellular matrix Glucose metabolism 0 5 10 15 20 C D Number of enriched gene sets UPREGULATED CANCER-RELATED GENERAL PROCESS DOWNREGULATED CANCER-RELATED GENERAL PROCESS Cancer Metastasis Translation Cell division DNA biology Immune system Cell division Bone-related process DNA repair Angiogenesis Respiratory metabolism Endomembrane system Mitochondrion biology Cholesterol metabolism Genome inestability Extracellular matrix Glucose metabolism DNA replication 0 5 10 15 20 0 2 4 6 Number of enriched gene sets Number of enriched gene sets DOWNREGULATED CANCER-RELATED GENERAL PROCESS E Cancer Translation Metastasis Bone-related Angiogenesis gene DNA biology sets gene sets gene sets BM1 Cell BM2 division C1 C2 BM BM C C BM1 BM2 C1 C2 ANGPT2 DNA repair PDGFA ANGPT2 RGS9 Respiratory SYNE2 metabolism HGF TNFSF15 Mitochondrion CCL2 biology CSF1 CCL2 ITGA10 LOX Genome inestability SERPINE1 COL6A3 CXCR4 DNA replication PDGFA TBC1D8B CD82 SERPINE1 0 2 4 MERTK 6 ENO2 PDGFA Number of enriched gene sets CSF1 EDN1 FBXO32 PTGER2 LOX HGF HMGCS1 NT5E FGF7 DDIT4 HSD17B7 CXCR4 CSF1 GAS6 EDN1 LPAR6 ITGB4 PPARA SLCO1B3 PTGER2 LOX 0.07 0 -0.1 NT5E logFC ≥ 1.5 RGS4 0.12 0 -0.16 CXCR4 logFC ≥ 1.5 BAMBI CYR61 FAM13A CD82 MERTK EDN1 PPARA OSMR RASGRP3 CCNE2 ITGB4 0.12 0 -0.16 logFC ≥ 1.5 Figure Figure Gene expression 2. expression 2. Gene analysis analysis of the of the bone metastatic bone metastatic subclone. subclone. (A) Principal component (A) illustrates analysis Principal component analysis segrega- tion of distinct expression profiles of bone metastatic subclone PC3-BM and PC3-P cell lines. (B) Volcano illustrates segregation of distinct expression profiles of bone metastatic subclone PC3-BM and PC3-P plot of differential cell lines. (B) Volcano plot of differential expression analysis of PC3-BM compared with PC3-P cell line. (C,D) Analysis of cancer-related gene sets using the transcriptome data. Graphs represent the total number of statistically significant up-and down-regulated enriched gene sets after multi- testing Benjamini–Hochberg correction, with FDR < 0.05, assigned to different cancer-related general process. (E) Heat maps indicating the genes included in the most relevant enriched gene sets for bone metastasis development. The color key shows relative expression levels of the differentially expressed genes, BM: PC3-BM and C: PC3-P cells. Cancers 2021, 13, x 11 of 24 Cancers 2021, 13, 6202 10 of 22 expression analysis of PC3-BM compared with PC3-P cell line. (C,D) Analysis of cancer-related gene sets using the tran- scriptome data. Graphs represent the total number of statistically significant up-and down-regulated enriched gene sets To bettercorrection, after multi-testing Benjamini–Hochberg understand with the FDRrole ofassigned < 0.05, those deregulated genes in bone to different cancer-related metastasis general process. devel- (E) Heat maps indicatingopment, we performed the genes included a KEGG in the most relevant pathway analysis enriched gene sets for among other analyses bone metastasis (seeThe development. Section 2) color key shows relative (Table expression S6).levels Theofdifferentially the differentially expressed genes expressed genes, BM: were PC3-BM and C: grouped PC3-P into cells. up and down different cancer-related general processes (Figure 2C,D). We observed enrichment in functions re- 3.3. to lated Differential miRNA Expression tumor aggressiveness, Profile such of In Vivo as cancer Selected Metastatic metastasis, Prostateimmune cell division, Cancer Cells system, To identify the differentially expressed miRNA profiles in PCa cells that bone-related process, and angiogenesis in PC3-BM cells. Heatmaps depict the significantly could medi- ate tumor progression deregulated genes in thewithin the bone process most relevant microenvironment, we compared related to bone metastasis the miRNA (Figure pro- 2E). Thus, files of PC3-BM and PC3-P cells using TaqMan Array MicroFluidic Cards. the gene expression analysis of the PC3-BM cells compared with the parental PC3 cell We identified 16revealed line differentially expressedofmiRNAs the presence distinctwith a FC >1.5 and transcriptional a p-value patterns ≤ 0.05;to related 11the miRNAs were acquired bone downregulated whereas tropism of these cells. 5 were upregulated in the bone metastatic cell line compared with the parental one (Figure 3A,B). Microarray results were further validated by RT- 3.3.qPCR and confirmed Differential miRNA that miR-135b, Expression miR-200b, Profile miR-18a, of In Vivo miR-425, Selected miR-194, Metastatic andCancer Prostate miR-19a Cells were downregulated in PC3-BM cells (Figure 3C). To identify the differentially expressed miRNA profiles in PCa cells that could me- We then analyzed the expression of the selected miRNAs in a cohort of 42 primary diate tumor progression within the bone microenvironment, we compared the miRNA formalin-fixed paraffin-embedded (FFPE) PCa samples from radical prostatectomies se- profiles of PC3-BM and PC3-P cells using TaqMan Array MicroFluidic Cards. We identified lected by the Pathology Department of Vall Hebron University Hospital (Table S1). Pa- 16 tients differentially expressed were followed miRNAs up for with 7–10 years a FC after >1.5 and surgery a p-value and divided ≤ two into 0.05;groups: 11 miRNAs were with or downregulated whereas 5 were upregulated in the bone metastatic cell line without biochemical recurrence (BCR). MiR-135b, miR-194, and miR-19a presented signif- compared with the parental icantly one (Figure lower expressions in 3A,B). Microarray patients with worseresults were(BCR) prognoses further validated (Figure by RT-qPCR 3D, p-value < and confirmed that miR-135b, miR-200b, miR-18a, miR-425, miR-194, and miR-19a 0.05). Following to the results obtained in the cell line model and patient samples, we were downregulated chose miR-135b, in miR-200b, PC3-BM cells (Figure 3C). and miR-19a for further functional studies. A B 1.8 miR-18a miR-210 Differentially expressed miRNAs between PC3-BM and PC3-P cell lines miR-200b miR-425 miR-34a 1.6 miRNA FC p-value miR-95 miR-135b miR-126 miR-195 hsa-miR-200b-3p -299.259 0.027 miR-494 miR-296 miR-582 1.4 miR-382 miR-422a hsa-miR-135b-5p -23.503 0.036 -log10 (p-value) miR-19a 1.2 hsa-miR-382-5p -12.669 0.050 miR-194 hsa-miR-194-5p -5.459 0.050 1 hsa-miR-422a -3.263 0.052 0.8 hsa-miR-425-5p -2.675 0.027 hsa-miR-126-3p -2.618 0.031 0.6 hsa-miR-494-3p -2.530 0.036 0.4 hsa-miR-195-3p -2.403 0.031 hsa-miR-18a-5p -2.131 0.020 0.2 hsa-miR-19a-3p -1.738 0.050 0 hsa-miR-95-3p 2.366 0.023 hsa-miR-210-3p 2.621 0.020 -3 -2.5 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 hsa-miR-296-5p 2.880 0.040 log FC hsa-miR-582-5p 5.968 0.046 hsa-miR-34a-5p 7.119 0.018 C D 20 15 Array 10 qPCR Relative expression (2^-DDCt) 6 mRNA (Fold Change) 5 0 4 ** ** ** -5 2 -10 0 -15 -100 R R R R R R R R R R R R R R R R R R R R BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC BC o o o o No o o o o No N N N N N N N N -200 135b 422a 200b 18a 425 195 494 382 194 19a -300 5b 2a 0b 8a 25 95 94 82 94 9a 3 2 0 -1 -4 -1 -4 -3 -1 -1 -1 -4 -2 iR iR iR iR iR iR iR iR iR iR m m m m m m m m m m Figure 3. Selection Figure of miRNAs 3. Selection of miRNAswith withpotential potentialroles rolesin inbone bone metastasis (A)Volcano metastasis (A) Volcanoplot plotofofmiRNA miRNA profiling profiling analysis analysis of of PC3-BM PC3-BM compared with PC3-P cell line. (B) Differentially expressed miRNAs between PC3-BM and PC3-P cell line. TheThe compared with PC3-P cell line. (B) Differentially expressed miRNAs between PC3-BM and PC3-P cell line. table represents the statistically significant deregulated microRNAs by t-Student analysis with p-value ≤ 0.05 and FC > 1.5. (C) RT-qPCR analysis validation of the microarray results. (D) Relative miRNA expression levels in primary tumors from PCa patients with and without biochemical recurrence (BCR) after radical prostatectomy. RNU48 was used as an endogenous control for all miRNA expression analyses. Values that are significantly different by t-test analysis are indicated by ** < 0.01. Cancers 2021, 13, 6202 11 of 22 We then analyzed the expression of the selected miRNAs in a cohort of 42 primary formalin-fixed paraffin-embedded (FFPE) PCa samples from radical prostatectomies se- lected by the Pathology Department of Vall Hebron University Hospital (Table S1). Patients were followed up for 7–10 years after surgery and divided into two groups: with or without biochemical recurrence (BCR). MiR-135b, miR-194, and miR-19a presented significantly lower expressions in patients with worse prognoses (BCR) (Figure 3D, p-value < 0.05). Following Cancers 2021, 13, x to the results obtained in the cell line model and patient samples, 12 of 24 we chose miR-135b, miR-200b, and miR-19a for further functional studies. table represents the statistically significant deregulated microRNAs by t-Student analysis with p-value ≤ 0.05 and FC > 1.5. 3.4. Overexpression (C) RT-qPCR ofofmiR-135b, analysis validation miR-200b, the microarray results. and (D) Relative miR-19a miRNA expressionDecreases Migration levels in primary tumors from of PC3-BM Cells PCa patients with and without biochemical recurrence (BCR) after radical prostatectomy. RNU48 was used as an endog- enous control for all miRNA expression analyses. Values that are significantly different by t-test analysis are indicated by To study the role of the selected miRNAs in promoting the growth of tumor cells in the ** < 0.01. bone, we first co-cultured PC3-BM cells with osteoblasts cells (hFOB) or their conditioned media and tested3.4. Overexpression of miR-135b, miR-200b, and miR-19a Decreases Migration of PC3-BM Cells whether the bone microenvironment had an impact on their migration To study the role of the selected miRNAs in promoting the growth of tumor cells in capacity. The presence the bone,of weosteoblasts first co-cultured or their PC3-BM conditioned cells with osteoblasts media cells (hFOB)significantly or their condi- increases the migratory capacity tioned ofmedia PC3-BM and tested whether cells the bone4A). (Figure microenvironment This effect hadwas an impact on their mi- osteoblast-specific, since gration capacity. The presence of osteoblasts or their conditioned media significantly in- the conditioned media creases the ofmigratory two other non-tumoral capacity of PC3-BM cells (Figurecell lines 4A). This (i.e., effectHEK293 and Het1A) did was osteoblast- not produce the same specific,effect since the(Figure conditioned4A). media of two other non-tumoral cell lines (i.e., HEK293 and Het1A) did not produce the same effect (Figure 4A). A B Mimic Bright Transfection field GFP Control ** Relative expression (2^-DDCt) 105 Relative expression (2^-DDCt) Relative expression (2^-DDCt) *** 10 7 ** *** 104 *** PC3-BM Migrated Cells (%) 400 104 10 6 10 5 103 103 300 10 4 102 102 10 3 200 101 10 2 101 10 1 100 100 100 10 0 10-1 10-1 10-1 NC miR-135b NC miR-200b NC miR-19a 0 M M M NC OB -C C C hF B- A- 93 O -1 hF 2 et EK H H C D * 150 ** ns % proliferation of PC3-BM 120 90 60 30 ### PC3-BM Migrated Cells (%) 500 ### 0 400 *** b b a K NC 35 00 9 C -1 MO -1 -2 R R R mi 300 mi mi 200 * 100 0 - + - + - + - + hFOB NC miR-135b miR-200b miR-19a Figure Figure 4. 4. Functional Functional studymiRNAs. study of selected of selected miRNAs. (A) Boyden (A) Boyden chamber migration chamber assay. hFOB: migration human osteoblast assay. hFOB: human cell line. CM: conditioned media. (B) Relative miRNA expressions of miR-135b, miR-200b and miR-19a in transfected cells com- osteoblast cell line.with pared to cells transfected CM: conditioned mimic. media. Confirmed to have (B) minimal Relative sequence miRNA identity with miRNAsexpressions of miR-135b, miR-200b in human (negative control: NC). Images are representative of PC3-BM cells transduced with the firefly luciferase gene-coding region cloned and miR-19a in transfected cells compared to cells transfected with mimic. Confirmed to have minimal upstream of the green fluorescent protein (GFP). Red fluorescence was used to monitor miRNA transfection efficiency of Dy547-labelled sequence miRIDIAN identity microRNA with miRNAsMimic Transfection in humanControl. (C) Boyden (negative chamber control: migration NC). assays are Images with representative PC3-MB of PC3-BM cells transduced with the firefly luciferase gene-coding region cloned upstream of the green fluorescent protein (GFP). Red fluorescence was used to monitor miRNA transfection efficiency of Dy547-labelled miRIDIAN microRNA Mimic Transfection Control. (C) Boyden chamber migration assays with PC3-MB transfected cells with NC or with miR-135b, miR-200, and miR-19a microRNA mimics and stablishing co-culture system with hFOB. (D) Proliferation assay of PC3-BM non-transfected (MOCK) or after NC, miR-135b, miR-200, and miR-19a transfection at 96 h (n = 6/condition). All bar graphs and plots represent the mean ± SEM of three independent experiments. Values that are significantly different by t-test analysis are indicated by * < 0.05, ** < 0.01, and *** < 0.001 or ### < 0.001, ns: no statistically significant. P: PC3 cells; BM: PC3-BM cells; hFOB: osteoblast cell line; CM: conditioned media. Cancers 2021, 13, 6202 12 of 22 Next, we further analyzed the impact of overexpressing miR-135b, miR-200b, and miR-19a on the migratory capacity of PC3-BM cells using a transwell migration assay. When miR-135b and miR-19a were overexpressed in PC3-BM cells in the presence of osteoblasts, we observed a reduction in the migratory capacity of PC3-BM cells compared with miRNA-control-transfected cells (Figure 4C, p-value < 0.001). The overexpression of miR-200b showed a similar trend but did not reach statistical significance. To rule out the conclusion that the observed effect on migration was not due to impaired proliferation, a cell proliferation assay was performed under the same experimental design. As observed in Figure 4D, miRNA overexpression decreased PC3-BM viability by less than 10% compared to the negative control (NC), ensuring that the observed reduction of cell migration was not due to a reduction in the cell number. Taken together, these results indicate that miR-135b and miR-19a downregulation observed in bone metastatic clones may be involved in the development or progression of bone metastasis of PCa. 3.5. Integration Data Analysis Identifies Biomarkers of Metastasis and Pathways Related to PCa Bone Metastases Dysregulation of miR-135b levels has been associated with cancer invasion and the migratory abilities of multiple cancer types [28,34,37,54]; however, its role and the molecu- lar mechanism of its target genes in the regulation of bone metastasis of PCa remain to be elucidated. The fact that miR-135b showed no effects on proliferation, coupled with these observations, led us to focus our next studies on this particular miRNA. Our findings on reduced miR-135b levels in the highly bone-metastatic cell line prompted us to analyze the landscape of molecular pathways to which this non-coding RNA could be related, concerning PCa pathogenesis. To this end, a whole transcriptome 30 UTR search for miR-135b binding sites using the miRWalk2.0 platform [51], followed by a pathway analysis of the predicted miR-135b target genes (Table S7), was conducted. Relevant molecular pathways for the bone metastasis phenotype are summarized in Figure 5A; they are represented by the number of genes in each set with a p-value ≤ 0.01. Among them, functions related to cancer, and especially to disseminative and invasive processes such as cell–cell or cell–matrix adhesion, cell motility, and cytokine-mediated signaling pathways, were enriched. In accordance with our model, genes related directly to the bone, such as osteoclast differentiation, calcium signaling pathway and mineral absorption, were overrepresented some of them obtained by both sources, i.e., KEGG and GO term (Biological Function) (Figure 5A). To further investigate molecular mechanisms under miR-135b regulation, we screened the overlap between the putative miR-135b target genes, obtained from four different algorithms (TargetScan, miRWalk, RNAhybrid, and miRanda) (Table S8), and our tran- scriptomic array data (Table S5). Interestingly, miR-135b target genes ANGPT2, JAKMIP2, PLAG1, GRID2, VTI1B, PDGFA, and CYBRD1 were also found to be significantly up- regulated in PC3-BM compared with PC3-P cells (Figure 5B). Consequently, the relative expression levels of these targets were technically validated by RT-qPCR, confirming that all of them presented significantly higher levels in the bone metastatic clone (Figure 5C). However, GRID2 and CYBRD1 were not considered for later studies due to their low expression levels. Cancers 2021, 13, x 14 of 24 Cancers 2021, 13, 6202 13 of 22 A B Gene Set Enritchment Analysis of miR-135b Predicted T argets miRanda RNAhybrid Pathways in cancer _KEGG PI3K-Akt signaling pathway _KEGG Ras signaling pathway _KEGG Calcium signaling pathway _KEGG Focal adhesion _KEGG Wnt signaling pathway _KEGG Cell adhesion molecules (CAMs) _KEGG Cellular senescence _KEGG Osteoclast differentiation _KEGG Apoptosis _KEGG Autophagy _KEGG Adherens junction _KEGG VEGF signaling pathway _KEGG Mineral absorption _KEGG p53 signaling pathway _KEGG Cell adhesion _GO:BF Cytokine-mediated signaling pathway _GO:BF Cell-cell adhesion _GO:BF Regulation of cell proliferation _GO:BF Protein glycosylation _GO:BF miRWalk TargetScan Integrin-mediated signaling pathway _GO:BF Cell-matrix adhesion _GO:BF Locomotory behavior _GO:BF Positive regulation of endothelial cell proliferation _GO:BF Gene logFC Positive regulation of endothelial cell migration _GO:BF Symbol Focal adhesion assembly _GO:BF Cell motility _GO:BF ANGPT2 4.67 Negative regulation of apoptosis _GO:BF JAKMIP2 2.19 Regulation of calcium ion transport _GO:BF Positive regulation of mitotic cell cycle _GO:BF PLAG1 2.04 Plood vessel remodeling _GO:BF GRID2 2.74 Osteoclast differentiation _GO:BF VTI1B 2.65 0 10 20 30 40 50 60 PDGFA 2.24 Hits CYBRD1 2.17 C 1500 1000 ** Gene expression (2^-DDCt) 500 * 100 80 60 * 40 * *** 20 5 4 3 2 1 0 P BM P BM P BM P BM P BM P BM P BM ANGPT2 VTI1b JAKMIP2 PLAG1 GRID2 PDGFA CYBRD1 D E 1.5 Relative Luciferase Activity Relative expression (2^-DDCt) 1.5 1.0 *** *** *** 1.0 *** 0.5 0.5 *** ** * NC miR-135b 0.0 ** 0.0 ANGPT2 VIT1b JAKMIP2 PLAG1 PDGFA pMIR-EV VTI1b JAKMIP2 PLAG1 PDGFA pMIR Report TM - 3’UTR FigureFigure 5. MiRNA-135b 5. MiRNA-135b target target genes genes involved involved ininbone bonemetastasis. metastasis. (A) (A) Cancer-and Cancer-and metastasis-related metastasis-relatedenriched gene gene enriched sets sets with p-value with p-value ≤ 0.01 ≤ 0.01 fromfrom miRNA-135bpredicted-target miRNA-135b predicted-target genes. genes.KEGG KEGGpathways and GO pathways andterm GO (biological function: BF) term (biological gene BF) function: sets were downloaded from the miRWalk platform and used for the pathways analysis. (B) Venn diagram illustrating the gene sets were downloaded from the miRWalk platform and used for the pathways analysis. (B) Venn diagram illustrating overlap among the miR-135b-predicted target genes of four different algorithms (TargetScan, miRanda, miRWalk and the overlap amongusing RNAhybrid) the miR-135b-predicted target miRWalk platform. The genes table of four shows thosedifferent algorithms target genes (TargetScan, significantly miRanda, over-expressed miRWalk in the tran- and scriptomic RNAhybrid) usingdata of PC3-BM miRWalk compared platform. Thewith tablePC3-P showsfound thoseintarget common geneswith the predicted significantly target gene set. over-expressed (C) transcriptomic in the RT-qPCR data ofanalyses PC3-BM of genes that are compared predicted with PC3-Ptargets foundof in miR-135b common in PC3-BM with the compared with predicted PC3-P. target (D) Relative gene set. (C)mRNA RT-qPCRexpression analyses of genes that are predicted targets of miR-135b in PC3-BM compared with PC3-P. (D) Relative mRNA expression levels of the indicated putative miR-135b target genes at 48h post-transfection with miR-135b mimic and miR-Control (NC) in PC3-B©ells. (E) Luciferase assay performed in phoenix cells co-transfected with the indicated 30 UTR luciferase-reporter vectors and miR-135b mimic or miR-Control (NC). Graph represents luciferase activity normalized to the renilla internal control (n = 5). All bar graphs represent the mean ± SEM. Values that are significantly different by t-test analysis from NC group are indicated by * < 0.05, ** < 0.01, and *** < 0.001. Cancers 2021, 13, 6202 14 of 22 3.6. miR-135b Regulates JAKMIP2, PLAG1, PDGFA, and VTI1 Levels To further confirm the direct relationship between miR-135b and its putative dif- ferentially expressed target genes, the levels of miR-135b were modulated by transient transfection of miRIDIAN Mimics. Upon miR-135b overexpression PLAG1, JAKMIP2, PDGFA, and VTI1b levels were significantly decreased in PC3-BM cells compared with control transfected cells (Figure 5D). Furthermore, luciferase-reporter assays carried out after miR-135b overexpression showed a significant reduction in luciferase activity for all 30 UTR-engineered regions, indicating a direct modulation of these genes by miR-135b (Figure 5E). Together, these results suggest that the altered expression of PLAG1, JAKMIP2, PDGFA, and VTI1b is due, at least in part, to the reduction of miR-135b expression levels in bone metastasis. 3.7. miR-135b and Its Targets, JAKMIP2, PLAG1, and PDGFA, Correlate with Poor Prognosis of PCa Patients As miR-135b expression levels were significantly lower in FFPE samples from patients with biochemical recurrence (Figure 3D), we wanted to further evaluate the miR-135b levels as a potential predictor of aggressiveness in PCa human samples. To test this, 40 plasma samples from PCa patients, including localized (n = 11), locally advanced (n = 9), and metastatic disease (n = 20) and 9 healthy controls, were selected to analyze circulating levels of miR-135b. As shown in Figure 6A, circulating levels of miR-135b were significantly lower in blood samples from patients with locally advanced and metastatic disease compared with samples from patients with localized disease. In particular, miR-135b circulating levels were lower in T3-4N0M0 and T1-4N0-1M1(Figure 6A). Furthermore, when miR-135b levels were studied based on their Gleason scores, their correlation with advanced PCa was once again observed: miR-135b expression levels were significantly lower in patients Cancers 2021, 13, x 16 of 24 with higher Gleason scores (Figure 6B). A B * 10 10 * ** Relative expression (2^-DDCt) Relative expression (2^-DDCt) * *** 5 5 0 0 NC L LA Met NC 6-7 8-10 Gleason Score C D PLAG1-JAKMIP2-PDGFA-VTI1b PLAG1-JAKMIP2-PDGFA-VTI1b Disease Free Overall p-value: 2.441e-5 p-value: 3.33e-3 Disease Free (month) Overall Survival (month) Figure 6. miR-135b and its targets JAKMIP2, PLAG1, and PDGFA as prognostic biomarkers. (A) Relative expression levels Figure 6. miR-135b and its targets JAKMIP2, PLAG1, and PDGFA as prognostic biomarkers. (A) Relative of miR-135b in plasma from healthy controls (NC) and patients with localized PCa (L; T1-2N0M0), locally advanced PCa expression levels of miR-135b in plasma from healthy controls (NC) and patients with localized PCa (LA; T3-4N0M0), and metastatic PCa (M; T1-4N0-1M1). (B) Relative expression levels of miR-135b in plasma from healthy controls (NC) and patients with different Gleason scores. (C) Correlation between disease-free time (in months) and (D) (L; T1-2N0M0), locally advanced PCa (LA; T3-4N0M0), and metastatic PCa (M; T1-4N0-1M1). (B) Rel- overall survival with the expression levels of miR-135b-validated targets. Patients’ data were retrieved from different PCa studies and TCGA Repository using the cBioportal Visualization platform. Values that are significantly different by Mann– ative expression levels of miR-135b in plasma from healthy controls (NC) and patients with different Whitney U test analysis are indicated by * < 0.05, ** < 0.01, and *** < 0.001. Gleason scores. (C) Correlation between disease-free time (in months) and (D) overall survival with the 4. Discussion expression levels of miR-135b-validated Although the survival of PCatargets. patients hasPatients’ datathewere improved over retrieved last two from different PCa studies decades, once the disease disseminates to distant organs such as bone, the prognosis drastically worsens, and TCGA Repository with only 30% of patients surviving more than 5 years [2]. Bone metastasis represents aare significantly different using the cBioportal Visualization platform. Values that scenario that is difficult to treat due to pain, fracture risk, and decreased quality of life. It by Mann–Whitney U test analysis are indicated by * < 0.05, ** < 0.01, and *** < 0.001. is increasingly appreciated that the microenvironment is crucial in supporting metastases formation; disseminated tumoral cells must acquire the capability to reprogram in their new microenvironment to support their growth and enhance the formation of clinically relevant metastases [55]. Thus, bone-specific metastasis likely results from both tumor- cell-intrinsic mechanisms and the microenvironment provided by the bone. Having in mind the “seed and soil” hypothesis described by Paget, which explained why certain cancers favored developing metastasis in specific organs [56,57], understanding the dis- tinct organ-specific mechanisms that enable metastatic growth is of crucial importance. Cancers 2021, 13, 6202 15 of 22 Finally, data mining of publicly available PCa-gene-expression datasets (i.e., TCGA repository) was conducted to find out whether the identified miR-135b target genes corre- lated with clinical variables in PCa. The combined expression of the four candidate genes (PLAG1, JAKMIP2, PDGFA, and VTI1b) correlated with disease-free time (p-value = 0.00002, 95% CI) (Figure 6C). Patients with abnormal levels of those four genes (n = 64) showed a significant decrease in disease-free time when compared with patients with unaltered levels (n = 1267). Individual analyses of the Kaplan–Meier curves for each gene (Figure S1) revealed that this prognostic value was mainly associated with high levels of PLAG1, JAKMIP2, and PDGFA. Similar results were obtained when overall survival was evaluated, with a significant shortening (20%) of the 10-year survival rate in the group of patients with altered levels of the four studied genes (n = 110) compared with the unaltered group (n = 1366) (p-value = 0.003, 95% CI) (Figure 6D). In this case, the effect seemed to be related to high levels of PLAG1 and PDGFA (Figure S1). Our results support the clinical relevance of the identified miR-135b and their target genes in bone metastasis patients of PCa. 4. Discussion Although the survival of PCa patients has improved over the last two decades, once the disease disseminates to distant organs such as bone, the prognosis drastically worsens, with only 30% of patients surviving more than 5 years [2]. Bone metastasis represents a scenario that is difficult to treat due to pain, fracture risk, and decreased quality of life. It is increasingly appreciated that the microenvironment is crucial in supporting metastases formation; disseminated tumoral cells must acquire the capability to reprogram in their new microenvironment to support their growth and enhance the formation of clinically relevant metastases [55]. Thus, bone-specific metastasis likely results from both tumor- cell-intrinsic mechanisms and the microenvironment provided by the bone. Having in mind the “seed and soil” hypothesis described by Paget, which explained why certain cancers favored developing metastasis in specific organs [56,57], understanding the distinct organ-specific mechanisms that enable metastatic growth is of crucial importance. Our study reveals novel molecules involved in osteotropism and/or in creating a permissive pre-metastatic niche for PCa cells. A better understanding of these mechanisms would lead to the development of more specific therapeutic strategies to hinder or prevent the establishment of bone metastatic lesions and consequently improve clinical outcomes for patients with PCa. Animal models of skeletal metastasis are essential to study the molecular pathways of cancer spread. In this study, we used a preclinical model based on intracardiac injec- tion of PCa cells into nude mice to faithfully reproduce the dissemination steps of bone metastasis [58]. Cancer cells established in the bone niche showed an increased incidence of bone lesions (up to 100%) after three rounds of in vivo selection, compared to a 20% incidence of cells prior to in vivo passaging. Interestingly, the PC3-BM cells metastasize with high penetrance to long bones, spine, and ribs, as has been described in metastatic PCa patients [5]. In vivo results suggest that the parental PC3 cells were reprogrammed as a conse- quence of the interaction with the bone microenvironment, which underpins the ability of PC3-BM to disrupt bone homeostasis, instigate bone degradation, and form a more hospitable metastatic niche. We therefore took advantage of both cell populations to elu- cidate the mechanisms enabling the capacity to metastasize to the bone. By carrying out a comparative whole-genome gene expression analysis, we revealed an upregulation of a set of genes related to cancer metastasis, angiogenesis, the extracellular matrix, and bone-related processes. Looking into detail in each of these categories, genes previously related to bone tropism were found to be overexpressed in PC3-BM cells, such as CXCR4 and its ligand CSF1, as well as CCL2, all of them directly involved in signaling pathways regulating circulating tumor cells (CTCs) homing to bone [59,60]. Moreover, ANGPT2 and PDGF are also relevant molecules for cancer-cell-survival in the bone marrow niche for ER+ breast and PCa cells, respectively [61,62]. The acquired gene expression profile Cancers 2021, 13, 6202 16 of 22 of PC3-BM cells notarized the reliability of our preclinical model and could explain, at least in part, the distinct efficacy of current treatments on disease progression due to the intratumor heterogeneity. Giving the relevance of miRNAs as key post-transcriptional gene repressors in mul- tiple steps of cancer progression, including those osteotropic cancers [38], we further extended the study to evaluate changes to these molecules. As these small non-coding RNAs are able to regulate several targets simultaneously, we consider them to be promising future therapeutic candidates to target advanced PCa disease. Using high-throughput analysis, we obtained a set of top differentially expressed miRNAs when the PC3-BM profile was compared with the parental cell line. To validate our findings, we performed a bibliographic review to study our dataset of miRNA candidates (p-value ≤ 0.05) (Table S9). All miRNAs had previously been related to cancer and metastasis; 50% of them were described in PCa metastasis and specifically miR-200b, miR-34a, miR-194, or miR-210, among others, had been previously related to the bone metastasis process, thus indicating that our model was representative of the disease [25,37,63–83]. Furthermore, we explored the association between those miRNAs significantly down- regulated in the PC3-BM subclone (miR-135b, miR-422a, miR-200b, miR-18a, miR-425, miR-194, and miR-19a) and the prognosis of PCa in a cohort of primary tumors. Interest- ingly, those patients that had developed BCR (worse prognosis) also presented significant less expression of miR-135b, miR-194, and miR-19a compared with patients without BCR. This indicates that these miRNAs could bear a potential prognostic value. In particular, miR-135b had previously been associated with both an oncogenic and a tumor-suppressor role in a context-dependent manner [84,85]. Wang et al. [37] analyzed the expression of miR- 135b in primary PCa samples and nonmalignant samples using RT-qPCR; their findings revealed that miR-135b was significantly down-regulated in PCa tissues compared with noncancerous tissues. Their results also indicated that the expression levels of miR-135b correlated with the pathological T stages of PCa and demonstrated significant inverse correlations between the expression of miR-135b and the levels of total and free PSA. In our work, the circulating levels of miR-135b have been determined for the first time, and the results indicate, once again, that this miRNA has potential as a biomarker and, after appropriate validation in a larger cohort of patients, it could potentially be used in clinical practice as a tool to assess patients’ prognoses. On the other hand, miR-135b has been identified as a direct regulator of androgen receptor (AR)-protein-levels in PCa [34–36]. Although, in our model based on PC3, the cell line that presents undetectable levels of AR, the effect of miR-135b on the selection of bone as a metastatic niche would most likely not be mediated by AR. It is important to mention that further studies should be conducted to elucidate the potential role of miR-135b in the acquisition of PCa which is resistant to androgen deprivation therapy. Previous studies have reported that miR-135b may contribute to cell migration and invasion in PCa cells; however, its role in the development of bone metastasis has not been documented thus far. To this end, in vitro functional assays analyzing miR-135b’s role in migration using an osteoblast cell line were carried out. It is known that prostate tumor cells enter in touch with bone lining cells when located in the bone marrow. Bone lining cells are quiescent or premature osteoblasts; and therefore, the immature human hFOB cell line is a particularly good model for co-culture studies using PCa cells [86]. Our results demonstrate that PC3-BM cancer cells had a significantly increased migra- tion capacity when they were co-cultured with the osteoblast cell line compared with the parental cells. This phenotype reinforces our in vivo model of bone homing and the colo- nization potential of PC3-BM cells. Interestingly, this effect was reversed when miR-135b was overexpressed, which suggests that this miRNA could be involved, at least in part, in the bone-homing process. This result evokes, for the first time, the possible implication of miR-135b in the bone metastasis process of PCa. Furthermore, the released factors that mediate the crosstalk between the primary tumor cells and those from metastatic niche are crucial [87], providing the exosomes with a Cancers 2021, 13, 6202 17 of 22 relevant role in this intercellular communication [88]. Recently, the signature of aberrantly expressed miRNAs has been identified in PCa- tumor-derived exosomes. Among them, miR-135b was found infra-expressed in hypoxia-related biomarkers in PCa [63]. Since it has been shown how exosomes are directed to the specific metastatic organs enabling organotropic metastatic growth [88,89], the deregulated expression of miR-135b in this intercellular communication system could partly explain its role in bone tropism. To unveil the landscape of molecular pathways in which miR-135b target genes are involved we extended our study to analyze the differentially expressed genes in the more metastatic cell line. miR-135b-predicted targets were enriched in oncogenic signaling pathways, metastasis, and bone remodeling-related genes in PC3-BM cells. After the overlapping of miR-135b-predicted targets with our transcriptomic data, VIT1b, JAKMIP2, PLAG1, and PDGFA were validated as direct targets of miR-135b. Additionally, data mining of PCa gene expression analysis showed that patients who presented higher levels of the four candidate genes (PLAG1, JAKMIP2, PDGFA, and VTI1b) had worse overall survival compared with those patients with unaltered levels. In concordance with that, high levels of PDGFA have previously been related to tumorigenesis, progression of PCa, and the biology of bone tissue. Moreover, PDGFA has long been associated with poor prognosis and metastasis [90], cell proliferation, and migration [91], and it has also been described as an osteogenesis-associated gene in PCa progression [92,93]. Otherwise, to date, it has not been reported the involvement of PLAG1, JAKMIP2, and VTI1b in PCa disease. However, PLAG1 is a zinc-finger transcription factor that has been described as an oncogene in other type of tumors. Previous studies demonstrated that it could promote anoikis resistance and tumor metastasis in lung cancer [94], and its silencing also promoted cell-chemosensitivity in ovarian cancer [95]. The oncogenic capability of PLAG1 seemed to be mediated, at least partly, by the IGF-II-mitogenic signaling pathway [95,96]. Interestingly, JAKMIP2 (Janus Kinase and Microtubule Interacting Protein 2) and VTI1b (Vesicle Transport Through Interaction With T-SNAREs 1B) have been linked to vesicle transport. JAKMIP2 was reported to be a component of Golgi matrix and acting as a Golgi protein by negatively regulating transit of secretory cargo [97]. On the other hand, VTI1b mediates vesicle transport pathways and vesicle trafficking. For instance, it has been shown that the levels of VTI1b accommodate the volume and timing of post-Golgi cytokine trafficking in macrophages [98,99]. Since it has been well established that circulating tumor cells are selectively and actively modified by the primary tumor before metastatic spread has even occurred [100], the vesicle-related function of both JAKMIP2 and VTI1b could be relevant for the tumor cells localized at the primary site, which need to prepare the future-tissue colonization through the establishment of the pre-metastatic niche. In summary, our results show that PCa cells that metastasize to bone possess features that enable them to efficiently utilize the bone microenvironment, creating a permissive pre-metastatic niche for PCa cells. Therapeutic strategies based on miRNA modulation are shown to be promising approaches for treatment of heterogeneous disease such as cancer [40]. In this sense, a comprehensive group of miRNAs associated with bone homing and tumor aggressiveness were recovered in the osteotropic tumor subclone supporting the robustness of our metastatic in vivo model of PCa. Specifically, our results suggest that the deregulation of miR-135b could be essential for bone selection as a metastatic niche for PCa, and its targets PLAG1, JAKMIP2, PDGFA, and VTI1b could also be mediating the establishment of bone metastasis. miR-135b and its target genes could potentially be considered as predictive biomarkers of bone dissemination, having a determining impact on clinical decisions and therefore improving PCa patients’ outcomes. 5. Conclusions The clinical management of PCa patients with bone metastases remains a challenge due to the inability to obtain long-term benefits post treatment and the development of resistance to current standard therapies. The process of metastasis requires multiple steps which include local tumor invasion, intravasation, survival in the bloodstream, ex- Cancers 2021, 13, 6202 18 of 22 travasation, and the colonization of the distal sites, which leads us to think that, to deal with this phenomenon, it would be convenient to design a therapeutic strategy that en- compasses the different factors involved. We suggest that the modulation of miRNAs achieved at the primary tumor may be a promising approach to prevent skeletal metas- tasis. Specifically, our findings reveal that miR-135b could play an important role in the selection of bone as a metastatic niche, and this effect could be mediated by its target genes, PLAG1, JAKMIP2, PDGFA, and VTI1b. Furthermore, miR-135b showed potential as a poor prognostic biomarker. Supplementary Materials: The following are available online at https://www.mdpi.com/article/10 .3390/cancers13246202/s1, Figure S1: Correlation between diseases-free time (in months) and overall survival, with the expression levels of miR-135b-validated targets; Table S1: Clinico-pathological data of the cohort of PCa patients included in the study of miRNA expression levels in FFPE samples from radical prostatectomies; Table S2: Clinico-pathological data of the cohort of PCa patients included in the study of miRNA expression levels in plasma samples; Table S3: miRNA probes for miRNA-expression analysis detected by RT-qPCR; Table S4: Sequences of primers for genes detected by RT-qPCR; Table S5: Differentially expressed genes (adj p-value < 0.001 and logFC > 2) between PC3-BM and PC3-P; Table S6: Gene set analyses with all differentially expressed genes of transcriptomic array data; Table S7: Pathway analysis of miR-135b-predicted target genes; Table S8: Predicted target genes of miR-135b by four different algorithms using the miRWalk platform; and Table S9: Bibliographic review of differentially expressed miRNAs identified in the miRNA array. Author Contributions: Conceptualization: M.O., M.G. (Marta Garcia), R.R.G., R.R.-B. and A.S.; Study design: M.O., M.G. (Marta Garcia), M.F.S. and A.S.; Formal analysis: M.O., M.G. (Marta Garcia), X.d.l.C. and R.R.G.; Funding acquisition: J.R., J.M., R.R.-B. and A.S.; Investigation: M.O., M.G. (Marta Garcia), L.S., L.G., O.M., M.R., I.d.T., J.P. and R.R.-B.; Methodology: M.O., M.G. (Marta Garcia), M.G. (Marc Guiu) and R.R.G.; Writing—original draft: M.O. and M.G. (Marta Garcia); Writing— review and editing: M.F.S., R.R.-B. and A.S. All authors have read and agreed to the published version of the manuscript. Funding: The study was supported by grants CPII18/00027 and PI18/01017 to A.S.; PI17/02248 to J.M.; grants PI09/00496, PI13/00173 and postdoctoral fellowship CD12/00475 of Instituto de Salud Carlos III (ISCIII), pre-doctoral fellowship of Vall d’Hebron Research Institute (VHIR), postdoctoral fellowship PERIS of Departament de Salut Govern de Catalunya to M.O.; BBVA and PID2019- 104948RB-100 to M.G. (Marc Guiu) and R.R.G.; RD12/0036/0035 of Red Temática de investigación cooperativa en cancer (RTICC), and 2014SGR1330 from “Secretaria d’Universitats i Recerca del Departament d’Economia i Coneixement de la Generalitat de Catalunya”. Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Clinical Research Ethics Committee from Vall Hebron University Hospital (PR(AG)96-2015). Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. 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