Mechanisms Contributing to Tyrosin Kinase Inhibitor Resistance in GISTs: Toward a Personalized Therapy

Gastrointestinal stromal tumors (GISTs) are the most common mesenchymal tumors in the gastrointestinal tract. This work considers the pharmacological response in GIST patients treated with imatinib by two different angles: the genetic and somatic point of view. We analyzed polymorphisms influence on treatment outcome, keeping in consideration SNPs in genes involved in drug transport and folate pathway. Naturally, all these intriguing results cannot be considered as the only main mechanism in imatinib response. GIST mainly depends by oncogenic gain of function mutations in tyrosin kinase receptor genes, KIT or PDGFRA, and the mutational status of these two genes or acquisition of secondary mutation is considered the main player in GIST development and progression. To this purpose we analyzed the secondary mutations to better understand how these are involved in imatinib resistance. In our analysis we considered both imatinib and the second line treatment, sunitinib, in a subset of progressive patients. KIT/PDGFRA mutation analysis is an important tool for physicians, as specific mutations may guide therapeutic choices. Currently, the only adaptations in treatment strategy include imatinib starting dose of 800 mg/daily in KIT exon-9-mutated GISTs. In the attempt to individualize treatment, genetic polymorphisms represent a novelty in the definition of biomarkers of imatinib response in addition to the use of tumor genotype. Accumulating data indicate a contributing role of pharmacokinetics in imatinib efficacy, as well as initial response, time to progression and acquired resistance. At the same time it is becoming evident that genetic host factors may contribute to the observed pharmacokinetic inter-patient variability. Genetic polymorphisms in transporters and metabolism may affect the activity or stability of the encoded enzymes. Thus, integrating pharmacogenetic data of imatinib transporters and metabolizing genes, whose interplay has yet to be fully unraveled, has the potential to provide further insight into imatinib response/resistance mechanisms.

Hypertension, hypercholesterolemia, hyperaldosteronism: a genetic perspective for personalized therapy.

Essential, primary, or idiopathic hypertension is defined as high BP in which secondary causes such as renovascular disease, renal failure, pheochromocytoma, hyperaldosteronism, or other causes of secondary hypertension are not present. Essential hypertension accounts for 80-90% of all cases of hypertension; it is a heterogeneous disorder, with different patients having different causal factors that may lead to high BP. Life-style, diet, race, physical activity, smoke, cultural level, environmental factors, age, sex and genetic characteristics play a key role in the increasing risk. Conversely to the essential hypertension, secondary hypertension is often associated with the presence of other pathological conditions such as dyslipidaemia, hypercholesterolemia, diabetes mellitus, obesity and primary aldosteronism. Amongst them, primary aldosteronism represents one of the most common cause of secondary hypertension, with a prevalence of 5-15% depending on the severity of blood pressure. Besides high blood pressure values, a principal feature of primary aldosteronism is the hypersecretion of mineralcorticoid hormone, aldosterone, in a manner that is fairly autonomous of the renin-angiotensin system. Primary aldosteronism is a heterogeneous pathology that may be divided essentially in two groups, idiopathic and familial form. Despite all this knowledge, there are so many hypertensive cases that cannot be explained. These individuals apparently seem to be healthy, but they have a great risk to develop CVD. The lack of known risk factors makes difficult their classification in a scale of risk. Over the last three decades a good help has been given by the pharmacogenetics/pharmacogenomics, a new area of the traditional pharmacology that try to explain and find correlations between genetic variation, (rare variations, SNPs, mutations), and the risk to develop a particular disease.

Cancer omics strategies for personalized treatments

The Consensus Molecular Subtypes (CMSs) classification stratifies colorectal cancer (CRC) into four well-defined molecular subgroups, providing incredible support to personalized medicine. Indeed, the huge inter-patient heterogeneity observed in CRC makes it difficult to define a therapeutic strategy from which every patient can benefit. Unfortunately, so far really few targetable biomarkers are known in the CRC setting, leading to an urgent need for new targeted therapies. Here we performed a bioinformatic meta-analysis over a cohort of 1700 CMS-stratified CRC patients, identifying a negative correlation between high levels of anaplastic lymphoma kinase (ALK) expression and relapse-free survival, exclusively in the CMS1 subtype. No correlation with ALK expression was pointed out in the other three subgroups. The association of ALK with CMS1 led to generate the hypothesis that ALK pharmacological inhibition may elicit therapeutic potential in this subgroup. Thus, we tested ALK inhibitors and an ALK-directed ADC on several CRC in vitro models, stratified according to the CMS classification as well as on CRC patient-derived organoids and mice. ALK interception strongly inhibited CMS1-cells, organoids, and tumor proliferation and was responsible for the dampening of ALK activation along with the downstream. Mechanistically, we found that CMS1 cells display several mRNA copies of both ALK and ALKAL2 ligand, suggesting a role for ALK abundance in the differential response to its inhibition. Collectively, these findings support the hypothesis that ALK may represent an attractive target for CMS1 colorectal cancer therapy.

Wireless systems for the fourth generation

Today, third generation networks are consolidated realities, and user expectations on new applications and services are becoming higher and higher. Therefore, new systems and technologies are necessary to move towards the market needs and the user requirements. This has driven the development of fourth generation networks. ”Wireless network for the fourth generation” is the expression used to describe the next step in wireless communications. There is no formal definition for what these fourth generation networks are; however, we can say that the next generation networks will be based on the coexistence of heterogeneous networks, on the integration with the existing radio access network (e.g. GPRS, UMTS, WIFI, ...) and, in particular, on new emerging architectures that are obtaining more and more relevance, as Wireless Ad Hoc and Sensor Networks (WASN). Thanks to their characteristics, fourth generation wireless systems will be able to offer custom-made solutions and applications personalized according to the user requirements; they will offer all types of services at an affordable cost, and solutions characterized by flexibility, scalability and reconfigurability. This PhD’s work has been focused on WASNs, autoconfiguring networks which are not based on a fixed infrastructure, but are characterized by being infrastructure less, where devices have to automatically generate the network in the initial phase, and maintain it through reconfiguration procedures (if nodes’ mobility, or energy drain, etc..., cause disconnections). The main part of the PhD activity has been focused on an analytical study on connectivity models for wireless ad hoc and sensor networks, nevertheless a small part of my work was experimental. Anyway, both the theoretical and experimental activities have had a common aim, related to the performance evaluation of WASNs. Concerning the theoretical analysis, the objective of the connectivity studies has been the evaluation of models for the interference estimation. This is due to the fact that interference is the most important performance degradation cause in WASNs. As a consequence, is very important to find an accurate model that allows its investigation, and I’ve tried to obtain a model the most realistic and general as possible, in particular for the evaluation of the interference coming from bounded interfering areas (i.e. a WiFi hot spot, a wireless covered research laboratory, ...). On the other hand, the experimental activity has led to Throughput and Packet Error Rare measurements on a real IEEE802.15.4 Wireless Sensor Network.

Valutazione dell'impatto della farmacogenetica in ambito di Sanità Pubblica. Analisi del polimorfismo genetico dell'enzima CYP2D6 metabolizzante xenobiotici.

Pharmacogenetic testing provides an outstanding opportunity to improve prescribing safety and efficacy. In Public health policy pharmacogenetics is relevant for personalized therapy and to maximize therapeutic benefit minimizing adverse events. CYP2D6 is known to be a key enzyme responsible for the biotransformation of about 25-30% of extensively used drugs and genetic variations in genes coding for drug-metabolizing enzymes might lead to adverse drug reactions, toxicity or therapeutic failure of pharmacotherapy. Significant interethnic differences in CYP2D6 allele distribution are well established, but immigration is reshaping the genetic background due to interethnic admixture which introduces variations in individual ancestry resulting in distinct level of population structure. The present thesis deals with the genetic determination of the CYP2D6 alleles actually present in the Emilia-Romagna resident population providing insights into the admixture process. A random sample of 122 natives and 175 immigrants from Africa, Asia and South America where characterized considering the present scenario of migration and back migration events. The results are consistent with the known interethnic genetic variation, but introduction of ethnic specific variants by immigrants predicts a heterogeneous admixed population scenario requiring, for drugs prescription and pharmacogenetics studies, an interdisciplinary approach applied in a properly biogeographical and anthropological frame. To translate pharmacogenetics knowledge into clinical practice requires appropriated public health policies, possibly guiding clinicians to evaluate prospectively which patients have the greatest probability of expressing a variant genotype.

Il corpo e l'individuo tra proprietà ed autodeterminazione. Con particolare riferimento al fenomeno delle biobanche

La bioetica è il luogo ideale per cercare risposte ai grandi interrogativi concernenti la vita, la morte e la cura dell'essere umano. I recenti dibattiti sull'uso, ed il temuto abuso, del corpo umano in medicina hanno messo in evidenza la necessità di una discussione approfondita sul potere di scelta che l'individuo può esercitare sulla propria mente e sul proprio corpo. Spinta dal desidero di indagare l'estensione di tale potere di scelta ho voluto analizzare le tematiche riguardanti “il corpo”, “l'individuo”, “la proprietà” e “l'autodeterminazione”. L'analisi è stata condotta individuando alcuni dei differenti significati che questi termini assumono nei diversi ambiti che la bioetica lambisce e mostrando, in particolare, la visione di tale realtà attraverso le lenti del giurista. A chi appartiene il corpo? Chi ha il potere di decidere su di esso? Il potere di scelta valica gli antichi i confini legati al corpo del paziente e coinvolge tessuti, organi e cellule staccati dal corpo umano, parti che un tempo erano considerati scarti operatori sono oggi divenuti tesori inestimabili per la ricerca. L'importanza assunta dai campioni biologici ha portato alla creazione di biobanche nelle quali sono raccolti, catalogati e il DNA studiato in campioni biologici Le biobanche riflettono le tensioni della bioetica e del biodititto. Lo studio delle biobanche riguarda, tra l'altro, la riceca dell'equilibrio tra le diverse esigenze meritevoli di tutela: in primo luogo il diritto alla privacy, diritto a che le “proprie informazioni” non vengano divulgate ed il diritto a non essere discriminato ed in secondo luogo le necessità dettate dalla ricerca e dalla scienza medica. Nel 2009 la rivista Times messo biobanche tra le 10 idee in grado di cambiare il mondo anche in considarazione della medicina personalizzata e del fatto che costituiscono una la speranza per la ricerca contro le malattie attuali e future.

Nanotechnology control of self organized biomolecules and biomaterials for medical research

Nanotechnology entails the manufacturing and manipulation of matter at length scales ranging from single atoms to micron-sized objects. The ability to address properties on the biologically-relevant nanometer scale has made nanotechnology attractive for Nanomedicine. This is perceived as a great opportunity in healthcare especially in diagnostics, therapeutics and more in general to develop personalized medicine. Nanomedicine has the potential to enable early detection and prevention, and to improve diagnosis, mass screening, treatment and follow-up of many diseases. From the biological standpoint, nanomaterials match the typical size of naturally occurring functional units or components of living organisms and, for this reason, enable more effective interaction with biological systems. Nanomaterials have the potential to influence the functionality and cell fate in the regeneration of organs and tissues. To this aim, nanotechnology provides an arsenal of techniques for intervening, fabricate, and modulate the environment where cells live and function. Unconventional micro- and nano-fabrication techniques allow patterning biomolecules and biocompatible materials down to the level of a few nanometer feature size. Patterning is not simply a deterministic placement of a material; in a more extended acception it allows a controlled fabrication of structures and gradients of different nature. Gradients are emerging as one of the key factors guiding cell adhesion, proliferation, migration and even differentiation in the case of stem cells. The main goal of this thesis has been to devise a nanotechnology-based strategy and tools to spatially and temporally control biologically-relevant phenomena in-vitro which are important in some fields of medical research.

Analisi fosfo-proteomica di campioni di tumore: il problema della stratificazione dei pazienti ed eterogeneità intra-tumorale nell'era della terapia personalizzata

Nella presente tesi indaghiamo la potenzialità di LCM e Reverse Phase Protein microarray negli studi clinici. Si analizza la possibilità di creare una bio banca con line cellular primarie, al fine di conseguire drug test di sensibilità prima di decidere il trattamento da somministrare ai singoli pazienti. Sono stati ottenuti profili proteomici da biopsie pre e post terapia. I risultati dimostrano che questa piattaforma mostra il meccanismo di resistenza acquisito durante la terapia biologica. Questo ci ha portato ad analizzare una possibile stratificazione per pazienti con mCRC . I dati hanno rivelato distinti pathway di attivazione tra metastasi resecabile e non resecabili. I risultati mostrano inoltre due potenziali bersagli farmacologici. Ma la valutazione dell'intero tumore tramite singole biopsie sembra essere un problema a causa dell’eterogeneità intratumorale a livello genomico. Abbiamo indagato questo problema a livello dell'architettura del segnale in campioni di mCRC e ccRCC . I risultati indicano una somiglianza complessiva nei profili proteomici all'interno dello stesso tumore. Considerando che una singola biopsia è rappresentativa di un intera lesione , abbiamo studiato la possibilità di creare linee di cellule primarie, per valutare il profilo molecolare di ogni paziente. Fino ad oggi non c'era un protocollo per creare linee cellulari immortalizzate senza alcuna variazione genetica . abbiamo cosiderato, però, l'approccio innovativo delle CRCs. Ad oggi , non è ancora chiaro se tali cellule mimino il profilo dei tessuti oppure I passaggi in vitro modifichino i loro pathways . Sulla base di un modello di topo , i nostri dati mostrano un profilo di proteomica simile tra le linee di cellule e tessuti di topo LCM. In conclusione, i nostri dati dimostrano l'utilità della piattaforma LCM / RPPA nella sperimentazione clinica e la possibilità di creare una bio - banca di linee cellulari primarie, per migliorare la decisione del trattamento.

Epigenetics of nutrition in aging

There is a need to identify factors that are able to influence health in old age and to develop interventions that could slow down the process of aging and its associated pathologies. Lifestyle modifications, and especially nutrition, appear to be promising strategies to promote healthy aging. Their impact on aging biomarkers has been poorly investigated. In the first part of this work, we evaluated the impact of a one-year Mediterranean-like diet, delivered within the framework of the NU-AGE project in 120 elderly subjects, on epigenetic age acceleration measures assessed with Horvath’s clock. We observed a rejuvenation of participants after nutritional intervention. The effect was more marked in the group of Polish females and in subjects who were epigenetically older at baseline. In the second part of this work, we developed a new model of epigenetic biomarker, based on a gene-targeted approach with the EpiTYPER® system. We selected six regions of interest (associated with ELOVL2, NHLRC1, SIRT7/MAFG, AIM2, EDARADD and TFAP2E genes) and constructed our model through a ridge regression analysis. In controls, estimation of chronological age was accurate, with a correlation coefficient between predicted and chronological age of 0.92 and a mean absolute deviation of 4.70 years. Our model was able to capture phenomena of accelerated or decelerated aging, in Down syndrome subjects and centenarians and offspring respectively. Applying our model to samples of the NU-AGE project, we observed similar results to the ones obtained with the canonical epigenetic clock, with a rejuvenation of the individuals after one-year of nutritional intervention. Together, our findings indicate that nutrition can promote epigenetic rejuvenation and that epigenetic age acceleration measures could be suitable biomarkers to evaluate their impact. We demonstrated that the effect of the dietary intervention is country-, sex- and individual-specific, thus suggesting the need for a personalized approach to nutritional interventions.

Applications of metrological techniques for clinical implementation of dosimetry and radiobiology in molecular radiotherapy

Molecular radiotherapy (MRT) is a fast developing and promising treatment for metastasised neuroendocrine tumours. Efficacy of MRT is based on the capability to selectively "deliver" radiation to tumour cells, minimizing administered dose to normal tissues. Outcome of MRT depends on the individual patient characteristics. For that reason, personalized treatment planning is important to improve outcomes of therapy. Dosimetry plays a key role in this setting, as it is the main physical quantity related to radiation effects on cells. Dosimetry in MRT consists in a complex series of procedures ranging from imaging quantification to dose calculation. This doctoral thesis focused on several aspects concerning the clinical implementation of absorbed dose calculations in MRT. Accuracy of SPECT/CT quantification was assessed in order to determine the optimal reconstruction parameters. A model of PVE correction was developed in order to improve the activity quantification in small volume, such us lesions in clinical patterns. Advanced dosimetric methods were compared with the aim of defining the most accurate modality, applicable in clinical routine. Also, for the first time on a large number of clinical cases, the overall uncertainty of tumour dose calculation was assessed. As part of the MRTDosimetry project, protocols for calibration of SPECT/CT systems and implementation of dosimetry were drawn up in order to provide standard guidelines to the clinics offering MRT. To estimate the risk of experiencing radio-toxicity side effects and the chance of inducing damage on neoplastic cells is crucial for patient selection and treatment planning. In this thesis, the NTCP and TCP models were derived based on clinical data as help to clinicians to decide the pharmaceutical dosage in relation to the therapy control and the limitation of damage to healthy tissues. Moreover, a model for tumour response prediction based on Machine Learning analysis was developed.

Development of a patient-specific model for stroke risk assessment in atrial fibrillation patients

Atrial fibrillation is associated with a five-fold increase in the risk of cerebrovascular events,being responsible of 15-18% of all strokes.The morphological and functional remodelling of the left atrium caused by atrial fibrillation favours blood stasis and, consequently, stroke risk. In this context, several clinical studies suggest that stroke risk stratification could be improved by using haemodynamic information on the left atrium (LA) and the left atrial appendage (LAA). The goal of this study was to develop a personalized computational fluid-dynamics (CFD) model of the left atrium which could clarify the haemodynamic implications of atrial fibrillation on a patient specific basis. The developed CFD model was first applied to better understand the role of LAA in stroke risk. Infact, the interplay of the LAA geometric parameters such as LAA length, tortuosity, surface area and volume with the fluid-dynamics parameters and the effects of the LAA closure have not been investigated. Results demonstrated the capabilities of the CFD model to reproduce the real physiological behaviour of the blood flow dynamics inside the LA and the LAA. Finally, we determined that the fluid-dynamics parameters enhanced in this research project could be used as new quantitative indexes to describe the different types of AF and open new scenarios for the patient-specific stroke risk stratification.

Unbalanced R-loops and micronuclei induced by DNA topoisomerase I poisons in cancer cells

Topoisomerase I (Top1) poisons are among the most clinically-effective drugs used for colon, ovary and lung cancers. Unpublished data from our lab have recently revealed that the structurally-unrelated Top1 poisons, Camptothecin (CPT) and Indimitecan (LMP776), induce the formation of micronuclei (MNi) in human cancer cells. In addition, MNi trigger an innate immune gene response by stimulating the cGAS/STING pathway. As the mechanisms of MNi formation are not fully determined, our aim is here to establish how MNi form after Top1 poisoning. Using immunofluorescence assays and EdU labelling of nascent DNAs, our results show that, after 24 hours of recovery, a short treatment with sub-cytotoxic doses of Top1 poisons induces the formation of MNi that do not contain newly synthetized (EdU+) DNA. We also saw that Top1 poisons delay replication machinery reducing EdU incorporation and produce significant levels of the damage markers γH2AX and p53BP1 in S-phase cells but not in G1 and G2/M cells. The results also show that MNi formation is dependent on R-loops, as RNaseH1 overexpression markedly reduces Top1 induced MNi. Genome-wide mapping of R-loops by DRIP-seq technique revealed that R-loop levels are both decreased and increased by CPT. In particular, increased R-loops are mainly found at active genes and always overlapped with Top1cc sites. We also found that increased R-loops overlap with lamina-associated chromatin domains while decreased R-loops correlate with replication origin sites. Overall, our data are consistent with the formation of MNi due to R-loop increase and under-replication at specific regions caused by Top1 poisons. These results will eventually help in developing new strategies for effective personalized interventions by using Top1-targeted compounds as immuno-modulators in cancer patients.

Distributed optimization and games over networks: a system theoretical perspective

Several decision and control tasks involve networks of cyber-physical systems that need to be coordinated and controlled according to a fully-distributed paradigm involving only local communications without any central unit. This thesis focuses on distributed optimization and games over networks from a system theoretical perspective. In the addressed frameworks, we consider agents communicating only with neighbors and running distributed algorithms with optimization-oriented goals. The distinctive feature of this thesis is to interpret these algorithms as dynamical systems and, thus, to resort to powerful system theoretical tools for both their analysis and design. We first address the so-called consensus optimization setup. In this context, we provide an original system theoretical analysis of the well-known Gradient Tracking algorithm in the general case of nonconvex objective functions. Then, inspired by this method, we provide and study a series of extensions to improve the performance and to deal with more challenging settings like, e.g., the derivative-free framework or the online one. Subsequently, we tackle the recently emerged framework named distributed aggregative optimization. For this setup, we develop and analyze novel schemes to handle (i) online instances of the problem, (ii) ``personalized'' optimization frameworks, and (iii) feedback optimization settings. Finally, we adopt a system theoretical approach to address aggregative games over networks both in the presence or absence of linear coupling constraints among the decision variables of the players. In this context, we design and inspect novel fully-distributed algorithms, based on tracking mechanisms, that outperform state-of-the-art methods in finding the Nash equilibrium of the game.

Specificità, efficacia e risposte adattative mediate da mutazioni dell'oncosoppressore TP53 degli inibitori del Complesso I mitocondriale nella terapia oncologica personalizzata: dai meccanismi molecolari allo sviluppo di modelli preclinici avanzati

L'inibizione del complesso respiratorio I (CI) è una strategia antitumorale emergente, sebbene la specificità e l’efficacia di nuovi farmaci restino poco investigate. La generazione di modelli cellulari tumorali nulli per il CI rivela la specificità di EVP 4593 e BAY 872243 nell’indurre gli effetti antiproliferativi non associati all’apoptosi, selettivamente via CI, riducendo eventuali effetti collaterali. Studi preliminari in vivo evidenziano un rallentamento della crescita tumorale negli animali trattati con EVP 4593, il quale emerge come l’inibitore più potente. Per il suo ruolo nella riprogrammazione metabolica, e la sua elevata frequenza di mutazioni nelle neoplasie umane, sono stati investigati i potenziali meccanismi di adattamento alla terapia anti-CI sulla base dello stato mutazionale di TP53. L’auxotrofia da aspartato, un hallmark metabolico delle cellule tumorali con un danno al CI, causa un blocco della sintesi proteica mTORC1-dipendente nelle linee cellulari con una p53 mutata o nulla, inducendo un collasso metabolico. Viceversa, l'attivazione del sensore energetico AMPK promuove un recupero parziale della sintesi di aspartato in linee cellulari con la forma wild type di P53, che è in grado di sostenere una migliore anaplerosi attraverso SCO2, fattore di assemblaggio del complesso respiratorio IV. Al fine di traslare questi risultati in un modello preclinico, si è ottimizzato l’ottenimento di colture di tumori umani espiantati tramite il bioreattore U-CUP. Il modello scelto è stato quello di carcinoma sieroso ad alto grado dell’ovaio (HGSOC), a partire da tessuto congelato, per l’elevata frequenza di mutazioni driver in TP53. I tessuti congelati preservano l'eterogeneità delle componenti cellulari del tessuto di origine e sono caratterizzati da cellule in attiva proliferazione senza attivazione di apoptosi. Dati preliminari mostrano un trend di riduzione dell’area tumorale nei tessuti trattati con EVP 4593 e supportano l’utilizzo del modello preclinico nello studio di nuovi inibitori del CI sfruttando materiale primario di pazienti oncologici.

Analysis of extracellular vesicles from patients with advanced pancreatic cancer identifies miRNAs with predictive value for treatment with gemcitabine + nab-paclitaxel

Pancreatic cancer (PC) is the seventh leading cause of cancer death. Despite recent therapy advancements, 5-year survival is 11%. Resistance to therapy is common, and no predictive factors, except for BRCA1/2 and PALB2 mutations, can drive treatment selection. Based on the easy isolation of extracellular vesicles (EVs) from blood and the role of EV-borne miRNAs in chemoresistance, we analyzed EVs and their miRNA content in order to identify predictive factors. First, we analyzed samples from 28 PC patients and 7 healthy subjects, in order to establish methods for isolation and analysis of EVs and their miRNA content. We observed a significantly different expression of 28 miRNAs, including oncogenic or tumor suppressor miRNAs, showing the ability of our approach to detect candidate biomarkers. Then, we analyzed samples of 21 advanced PC patients, collected before first-line treatment with gemcitabine + nab-paclitaxel, and compared findings in responders and non-responders. EVs have been analyzed with Nanoparticle tracking analysis, flow cytometry and RNA-Seq; then, laboratory results have been matched with clinical data. Nanoparticle tracking analysis did not show any significant difference. Flow cytometry showed a lower expression of SSE4 and CD81 in responders. Finally, miRNA analysis showed 25 upregulated and 19 downregulated miRNAs in responders. In particular, in responders we observed upregulation of miR-141-3p, miR-141-5p, miR-200a-3p, miR-200b-3p, miR-200c-3p, miR-375-3p, miR-429, miR-545-5p. These miRNAs have targets with a previously reported role in PC. In conclusion, we show the feasibility of the proposed approach to identify EV-derived biomarkers with predictive value for therapy with gemcitabine + nab-paclitaxel in PC. Our findings highlight the possibility to exploit liquid biopsy for personalized treatment in PC, in order to maximize chances of response and patients’ outcome. These findings are worthy of further investigation: in the same setting, with different chemotherapy schedules, and in different disease settings such as preoperative therapy.