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Di Francesco, Andrea (2018) Identification of molecular biomarkers to discriminate and characterize the different types of rejection in Heart Transplated Patients. [Ph.D. thesis]

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Abstract (italian or english)

Background: Heart Transplantation (HTX) is the only curative treatment available for patients with end-stage heart failure (HF).During the first year post-transplantation more than 25% of patients will go through rejection episodes and will face the risk of developing rejection with consequent graft dysfunction with an increased morbidity and mortality. Preventing and treating acute rejection is the most central task for clinicians working with transplanted patients. The ISHLT 2005 and 2013 working formulations defined the histopathologic profile of three types of rejection: Cellular (ACR) Humoral (AMR) and Mixed (MIX). Nowadays serial endomyocardial biopsies (EMB) at decreasing intervals during the first year after transplantation and laboratory tests, such as Donor Specific Antibody (DSA) measurements, remain the gold-standard in diagnosing and monitoring acute rejection but they are morbid and prone to artefacts of sampling, interpretation and testing methodologies. Therefore this histopathological assessment needs integrative new biomarkers to characterize risk stratification for outcomes in heart transplantation. To date, the exact mechanisms involved in rejection after solid transplantation are not completely understood, so investigating process that contribute to acute allograft rejection and find effective biomarkers to diagnose, monitoring and predicting rejection will be of great value for the development of improved anti-rejection strategies.
The advent of sequencing technology such as Next Generation Sequencing (NGS) is changing medical genomics by accelerating new disease biomarkers discovery. MicroRNAs (miRNAs) are small non-coding RNA molecules (19-24 nucleotides), highly conserved, which regulate genes expression at the post transcriptional level.
Aim: The aim of this study is to identify MicroRNA (miRNAs) expression profile in the first year after heart transplantation (HTX) with Next Generation Sequencing (NGS) technology in formalin fixed paraffin-embedded (FFPE) endomyocardial Biopsies (EMBs), to characterize the three different types of allograft rejection classified as Cellular, Humoral and Mixed.
Methods: Two groups of pts. were included: a study group of 19 pts. and a validation group of 14 pts. For each patient we selected the the first formalin fixed paraffin-embedded (FFPE) monitoring endomyocardial biopsies (EMBs) positive for each types of rejection. We excluded presensitized patients (pts) with previous implantation of Left Ventricular Assistance Device (LVAD) and with previous infections. EMBs were examined for the presence of rejection according to updated international classification criteria (ISHLT 2005 and 2013).The EMBs were classified in four groups: Acute Cellular Rejection (ACR) with 12 pts ACR: >=2R, pAMR:0, DSA: Neg ; Mixed with 6 pts ACR: >=2R, pAMR>1 (i+), DSA: Pos; Antibody Mediated Rejection (AMR) with 5 pts ACR: 0, pAMR>1 (i+), DSA: Pos; Control with 10 pts : ACR:0, pAMR:0, DSA: Neg. Small RNA fraction from the study group was sequenced with NGS Ion Proton in order to define the expression of mature miRNAs. We performed subsequent analysis with edgeR package comparing in pairs the groups to identify differentially expressed miRNAs in the different rejections. We selected 13 microRNAs according to bionformatic analysis as possible biomarckers and they have been confirmed by qRT-PCR in all the pts. With multivariate logistic regression analysis we created unique miRNA signatures as predictive model of each rejection. Moreover in situ PCR was carried out on the same EMBs to detect miRNAs expression and localization in cell types within the EMBs.
Results: The identification of the best method of extraction for short non coding RNAs in FFPE EMBs was the first result I achieved. I tested different methods in house and commercial available kits and I modified the protocols to obtain good quality and adeguate quantity of RNA from FFPE tissue of small EMBs for the downstream application. With NGS we obtained and analysed more than 2257 mature microRNAs in all the biopsies of the study group. The three types of rejection and control groups were compared in pair with the un-supervised analysis showing a typical profile for each group of differentially expressed miRNAs; in particular: Mixed vs AMR: only 2 miRNAs overexpressed in the Mixed group suggesting a similarity between the two types. ACR vs AMR: 18 miRNAs overexpressed and 2 miRNAs under-expressed in the ACR. Mixed vs ACR : 7 miRNAs underexpressed and 39 miRNAs over-expressed in the ACR group. The analysis revealed that there are de-regulated microRNAs between the three rejections confirming our hypothesis that microRNAs can characterize the three pathological conditions. MiRNAs have been selected for further evaluation and validation, based on the number of reads resulting by NGS, on their highly significant FDR (< 0.05) or fold change, p-value and their involvement in relevant processes related to rejection as shown by a bioinformatic analysis based on validated target genes and reported in public databases such as TarBase (version 6.0) (111) , miRTarBase (112) , miRWalk (113), miRecords (114), DIANA-microT-CDS (115) , miRmap (116), miRDB (117) , TargetScan (118), and miRanda (119). At the end we selected 13 microRNAs. To validate the NGS data through qRT-PCR we enrolled other EMBs from 14 pts selected according to our criteria and we tested on all the 33 EMbs, both the study and validation cohort, the selected microRNAs.
The validation analysis has shown a similar expression pattern for all microRNAs in particular: 6 hsa-miRNAs: 29c-3p/-29b-3p/199a-3p/190a-5p/27b-3p/302b-3p can differentiate all rejections compared to controls; 3 hsa-miRNAs: 31-5p/144-3p/218-5p are peculiar of AMR and MIX compared to control and ACR 2 hsa-miRNAs: 451a/208a-5p identify MIX compared to controls. Using miRNAs expression as co-variate and disease status as dependent variable we created logistic regression models: MIX:(miR-208a ,126-5p, 135a-5p); ACR:(miR-27b-3p, 29b-3p,199a-3p, 208a, 302b-3p); AMR: ( miR-208a, 29b-3p, 135a-5p, 144-3p) identifying with high specificity and sensitivity each types of rejection. Finally with in situ PCR we detected some of these microRNAs in different cell types: miR-29b-3p was mostly expressed in smooth muscle cells in ACR; miR-144-3p was expressed in macrophages and in endothelial cells; moreover the expression of this microRNA in macrophages was predominant and diffuse in the ACR compared to AMR. miR-126-5p was expressed in ACR and AMR samples not only in in endothelial cells but also in Cardiomyocytes and smooth muscle cells. For MicroRNA 451a we found a co-localization of signal in endothelial cells and in lymphocytes.
Conclusions: This study demonstrate that MicroRNAs can be obtained easily from FFPE tissues, miRNAs differentially expressed are involved in pathophysiological mechanisms of rejection such as immune system cells cycle regulation and proliferation, , inflammatory pathways NFkB mediated and endothelial remodelling. According to our results the miRNAs up or down expressed modulate these pathways in a way peculiar for the different type of rejection. The regressive models might represent a powerful diagnostic tool and in situ detection of the miRNAs casts new light on the pathophysiological mechanisms of rejection. Moreover the expression of MiRNAs 144-3p, 126-5p, 29b-3p and 451a identified by in situ PCR in endothelial cells, smooth muscle and inflammatory cells are diagnostic and are potential pharmacological targets for rejections.

Abstract (a different language)

Contesto: Il trapianto di cuore è l'unico trattamento curativo disponibile per i pazienti con insufficienza cardiaca allo stadio terminale. Durante il primo anno dopo il trapianto più del 25% dei pazienti può subire episodi di rigetto e affrontare il rischio di sviluppare rigetto con conseguente disfunzione dell’ organo trapiantato con un aumento della morbilità e mortalità. Prevenire e trattare il rigetto acuto è l’ obiettivo principale per i medici che lavorano con pazienti trapiantati. Le linee guida ISHLT 2005 e 2013 hanno definito il profilo istopatologico di tre tipi di rigetto: Cellulare (ACR) Humoral (AMR) e Mixed (MIX). Al giorno d'oggi le biopsie endomiocardiche seriali (EMB) a intervalli decrescenti durante il primo anno dopo il trapianto e gli esami di laboratorio, come le misurazioni di anticorpi donatore specifici (DSA), rimangono parametri di riferimento nella diagnosi e nel monitoraggio del rigetto acuto, ma sono soggetti a artefatti dovuti alle metodologie di campionamento, interpretazione e test. Pertanto questa valutazione istopatologica necessita di nuovi biomarcatori integrativi per caratterizzare la stratificazione del rischio nel rigetto da trapianto di cuore. Ad oggi, i meccanismi esatti coinvolti nel rigetto dopo il trapianto non sono completamente compresi, quindi la ricerca sui processi che governano i meccanismi di rigetto e la scoperta di biomarcatori efficaci per diagnosticare, monitorare e prevedere il rigetto sarà di grande valore per lo sviluppo e miglioramento delle terapie contro il rigetto.
L'avvento della tecnologia di sequenziamento come Next Generation Sequencing (NGS) sta cambiando la genomica medica accelerando la scoperta di nuovi biomarcatori di malattie. I microRNA (miRNA) sono piccole molecole di RNA non codificanti (19-24 nucleotidi), altamente conservate, che regolano l'espressione dei geni a livello post-trascrizionale.
Obiettivo: Lo scopo di questo studio è identificare il profilo di espressione di MicroRNA (miRNA) nel primo anno dopo il trapianto di cuore (HTX) con la tecnologia Next Generation Sequencing (NGS) in biopsie endomiocardiche (EMB) fissate in formalina e incluse in paraffina (FFPE), per caratterizzare i tre diversi tipi di rigetto da trapianto di cuore classificati come Cellulare, Umorale e Misto.
Metodi: due gruppi di pazienti (pz.) sono stati inclusi: un gruppo di studio di 19 pz. e un gruppo di validazione di 14. Per ogni paziente abbiamo selezionato la prima biopsia endomiocardica (EMB) fissata in formalina ed inclusa in paraffina (EMB) per ogni tipo di rigetto. Abbiamo escluso i pz. presensibilizzati con precedente impianto del dispositivo di assistenza ventricolare sinistro (LVAD) e con precedenti episodi di infezione. Le biopsie sono state esaminate per la presenza di rigetto secondo i criteri di classificazione internazionali aggiornati (ISHLT 2005 e 2013). Abbiamo quindi individuato quattro gruppi: Acute Cellular Rejection (ACR) con ACR a 12 punti:> = 2R, pAMR: 0, DSA: Neg; Misto con 6 pts ACR:> = 2R, pAMR> 1 (i +), DSA: Pos; Reiezione mediata da anticorpi (AMR) con 5 punti ACR: 0, pAMR> 1 (i +), DSA: Pos; Controllo con 10 punti: ACR: 0, pAMR: 0, DSA: Neg. La piccola frazione di RNA della coorte di studio è stata sequenziata con NGS Ion Proton per definire l'espressione dei miRNA maturi. Abbiamo eseguito un'analisi successiva con edgeR confrontando a coppie i gruppi per identificare i miRNA espressi differenzialmente nei diversi rigetti. Abbiamo selezionato 13 microRNA secondo l'analisi bionformatica come possibili biomarcatori i quali sono stati confermati da qRT-PCR in tutti i pz. Con l'analisi di regressione logistica multivariata abbiamo identificato gruppi univoci di miRNA come modelli predittivi specifici per ciascun rigetto. Inoltre, la PCR in situ è stata eseguita sulle stesse EMBs per rilevare l'espressione e la localizzazione dei miRNA nei tipi di cellule all'interno delle EMBs.
Risultati: l'identificazione del miglior metodo di estrazione di microRNA da EMBs FFPE è stato il primo risultato che ho raggiunto. Ho testato diversi metodi sia manuali che kit commerciali e ho modificato i protocolli per ottenere una buona qualità e una quantità adeguata di microRNA per l'applicazioni successive. Con NGS abbiamo ottenuto e analizzato oltre 2257 microRNA maturi in tutte le biopsie del gruppo di studio. I tre tipi di gruppi di controllo e di rigetto sono stati confrontati in coppia con l'analisi non supervisionata che mostra per ciascun gruppo un profilo tipico di miRNA differenzialmente espressi; in particolare: Misto vs AMR: solo 2 miRNA sovraespressi nel gruppo Misto suggeriscono una somiglianza tra i due tipi di rigetto. ACR vs AMR: 18 miRNA sovraespressi e 2 miRNA sottoespressi nell'ACR. Mixed vs ACR: 7 miRNAs non sovraespressi e 39 miRNA sovraespressi nel gruppo ACR. L'analisi ha rivelato che ci sono microRNA de-regolati tra i tre tipi di rigetto confermando la nostra ipotesi che i microRNA possano caratterizzare le tre condizioni patologiche. I MiRNA sono stati selezionati per un'ulteriore valutazione e convalida, in base al numero di reads risultanti da NGS, sulla loro FDR significativa (<0,05), fold change, p-value e il loro coinvolgimento in processi rilevanti correlati al rigetto come mostrato dalle analisi bioinformatiche basate su geni target validati e riportati in database pubblici come TarBase (versione 6.0) (111), miRTarBase (112), miRWalk (113), miRecords (114), DIANA-microT-CDS (115), miRmap (116) , miRDB (117), TargetScan (118) e miRanda (119). Alla fine abbiamo selezionato 13 microRNA. Per validare i dati NGS tramite qRT-PCR abbiamo arruolato altri EMBs da 14 pz. selezionati in base ai nostri criteri e abbiamo testato su tutte le 33 EMbs, sia quelle della coorte di studio che quelle della coorte di validazione, i microRNA selezionati.
L'analisi di validazione ha mostrato un pattern di espressione simile per tutti i microRNA in particolare: 6 hsa-miRNA: 29c-3p / -29b-3p / 199a-3p / 190a-5p / 27b-3p / 302b-3p possono differenziare tutti i rigetti rispetto a controlli; 3 hsa-miRNA: 31-5p / 144-3p / 218-5p sono peculiari di AMR e MIX rispetto al controllo e ACR 2 hsa-miRNA: 451a / 208a-5p identificano MIX rispetto ai controlli. Usando l'espressione di miRNA e la condizione patologica come variabili dipendenti abbiamo creato modelli di regressione logistica: MIX: (miR-208a, 126-5p, 135a-5p); ACR: (miR-27b-3p, 29b-3p, 199a-3p, 208a, 302b-3p); AMR: (miR-208a, 29b-3p, 135a-5p, 144-3p) che identificano con alta specificità e sensibilità ciascun tipo di rigetto. Infine con PCR in situ abbiamo rilevato alcuni di questi microRNA in diversi tipi di cellule: miR-29b-3p era principalmente espresso nelle cellule muscolari lisce in ACR; miR-144-3p era espresso nei macrofagi e nelle cellule endoteliali; inoltre l'espressione di questo microRNA nei macrofagi era predominante e diffusa nell'ACR rispetto all'AMR. Il miR-126-5p è risultato espresso in campioni ACR e AMR non solo nelle cellule endoteliali ma anche nei cardiomiociti e nelle cellule muscolari lisce. Per il MicroRNA 451a abbiamo trovato una co-localizzazione del segnale nelle cellule endoteliali e nei linfociti.
Conclusioni: Questo studio dimostra che i microRNA possono essere ottenuti facilmente dai tessuti fissati in formalina e inclusi in paraffina, i miRNA differenzialmente espressi sono coinvolti in meccanismi patofisiologici del rigetto quali regolazione e proliferazione del ciclo cellulare del sistema immunitario, vie infiammatorie mediate da NFkB e rimodellamento endoteliale. Secondo i nostri risultati, i miRNA sovra o sotto espressi hanno mostrato una modulazione di questi processi in un modo peculiare per ciascun tipo di rigetto. I modelli di regressione logistica identificati potrebbero rappresentare un potente strumento diagnostico e il rilevamento in situ dei miRNA getta nuova luce sui meccanismi patofisiologici del rigetto. Inoltre l'espressione di MiRNA 144-3p, 126-5p, 29b-3p e 451a identificati mediante PCR in situ in cellule endoteliali, cellule muscolari lisce e infiammatorie è diagnostica e costituisce un potenziale bersaglio farmacologico contro il rigetto da trapianto di cuore.

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EPrint type:Ph.D. thesis
Tutor:Angelini, Annalisa
Ph.D. course:Ciclo 30 > Corsi 30 > MEDICINA SPECIALISTICA "G.B. MORGAGNI"
Data di deposito della tesi:22 January 2018
Anno di Pubblicazione:22 January 2018
Key Words:Profilo di espressione microRNA mediante NGS; Rigetto cellulare acuto; Rigetto MIX; Rigetto ANTICORPALE; Biopsie fissate in formalina e incluse in paraffina; Trapianto Cardiaco / NGS miRNAs-profiling; Acute Cellular Rejection; MIXED Rejection; Antibody mediated rejection, HTX-FFPE-EMBs.
Settori scientifico-disciplinari MIUR:Area 06 - Scienze mediche > MED/08 Anatomia patologica
Struttura di riferimento:Dipartimenti > Dipartimento di Scienze Cardiologiche, Toraciche e Vascolari
Istituti > Istituto di Anatomia Patologica
Codice ID:11052
Depositato il:25 Oct 2018 15:45
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