Publications

A list of publications related with our COST Action

TRANSPAN special issue in “Seminars on Cancer Biology”

VSI Transpan – YSCBI

This thematic issue will benefit from the experience of well-known experts in the field of pancreatic cancer research. The pool of corresponding authors is multidisciplinary and covers all spectrum of the most relevant aspects of this disease. We have critical expertise in surgery, oncology, gastroenterology, pharmacology, genetics, epidemiology, Information technology, molecular biology, pathology.

Guest Editor:Dr. Luca Morelli(No Organisation – Home based – 0648100, , , )

https://www.sciencedirect.com/special-issue/10T075Z5XK9

Publications related to TRANSPAN special issue in "Seminars on Cancer Biology"

Genomic instability, DNA damage response and telomere homeostasis in pancreatic cancer

Saba Selvi 1, Carmen Macías Real 2, Manuel Gentiluomo 3, Katerina Balounova 4, Klara Vokacova 5, Andrea Cumova 6, Beatrice Mohlenikova-Duchonova 7, Cosmeri Rizzato 3, Erika Halasova 8, Ludmila Vodickova 9, Bozena Smolkova 6, Kari Hemminki 10, Daniele Campa 3, Pavel Vodicka 11

PMID: 40378535
DOI: 10.1016/j.semcancer.2025.05.005

Pancreatic cancer (PC) is becoming one of the most serious health problems at present, but its causes and risk factors are still unclear. One of the drivers in pancreatic carcinogenesis is altered genomic (DNA) integrity with subsequent genomic instability in cancer cells. The latter comprises a) DNA damage response and DNA repair mechanisms, b) DNA replication and mitosis, c) epigenetic regulation, and d) telomere maintenance. In our review we addressed the above aspects in relation to the most abundant and severe form of PC, pancreatic ductal adenocarcinoma (PDAC). In summary, the interactions between the DNA damage response, telomere homeostasis and mitotic regulation are not comprehensively understood at present, including the epigenetic factors entering the trait of genomic stability maintenance. In addition, the complexity of telomere homeostasis in relation to PDAC risk, prognosis and prediction also warrants further investigations.

Keywords: DNA damage; DNA repair; Epigenetic regulation of genome integrity; Mitotic regulation; Pancreatic Cancer; Telomere homeostasis.

Targeting pancreatic cancer screening by identification of pathogenic variants of BRCA2/ BRCA1 in healthy individuals who have no known family history of pancreatic cancer: The arguments for and against.

Julie Earl ^a, Agapi Kataki ^b, Federico Canzian ^c, Eithne Costello ^d, Daniele Campa ^e, William Greenhalf d

Biomarkers and Personalized Approach to Cancer (BIOPAC) Group, Ramón y Cajal Health Research Institute (IRYCIS), CIBERONC, Carretera Colmenar Km 9,100, Madrid 28034, Spain
Department of Propaeudeutic Surgery, Breast Unit, Medical School, National and Kapodistrian University of Athens, Greece
Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany
Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Liverpool, UK
Department of Biology, University of Pisa, Italy

DOI: 10.1016/j.semcancer.2025.05.001

The majority of patients with pancreatic ductal adenocarcinoma (PDAC) are no longer suitable for treatment with curable intent at the time of diagnosis resulting in a 5-year survival of less than 10 %. Imaging of asymptomatic individuals could identify early cancers, but only with a risk of falsely identifying a benign lesion as malignant. Screening of an unselected population would result in far more such false positives than true early cancers. Selection before screening is therefore essential, but there are very few populations at high enough risk to make screening more beneficial than counterproductive. These populations include carriers of specific mutations in BRCA2, and arguably BRCA1, who have a family history of PDAC. These pathogenic mutations all have a predictable effect in making loss of Homologous Recombination Repair (HRR) likely in a carrier’s lifetime. In this review the impact of such loss of HRR function on the likelihood of PDAC development will be discussed. Furthermore, it will be discussed whether the identification of a germline pathogenic mutation is sufficient to justify carrier surveillance for the development of the malignancy, or whether the current practice of screening only those carriers with a close relative diagnosed with PDAC is justifiable, as only a proportion of carriers are at high risk. The review will go beyond this to discuss whether there is an essential need to better define and stratify those at high risk, so that only high-risk carriers are put on surveillance.

Keywords: Screening; Surveillance; Germline mutation; Cancer risk; BRCA2; BRCA1

The exposome and pancreatic cancer, lifestyle and environmental risk factors for PDAC

Giulia Peduzzi 1, Livia Archibugi 2, Riccardo Farinella 1, Ruggero Ponz de Leon Pisani 2, Ludmila Vodickova 3, Pavel Vodicka 3, Bledar Kraja 4, Juan Sainz 5, David Bars-Cortina 6, Neil Daniel 7, Roberto Silvestri 1, Pinar Uysal-Onganer 8, Stefano Landi 1, Joanna Dulińska-Litewka 9, Annalisa Comandatore 10, Daniele Campa 1, David J Hughes 7, Cosmeri Rizzato 11

PMID: 40368260
DOI: 10.1016/j.semcancer.2025.05.004

Pancreatic cancer (PC), particularly pancreatic ductal adenocarcinoma (PDAC), is a significant global health issue with high mortality rates. PDAC, though only 3 % of cancer diagnoses, causes 7 % of cancer deaths due to its severity and asymptomatic early stages. Risk factors include lifestyle choices, environmental exposures, and genetic predispositions. Conditions like new-onset type 2 diabetes and chronic pancreatitis also contribute significantly. Modifiable risk factors include smoking, alcohol consumption, non-alcoholic fatty pancreatic disease (NAFPD), and obesity. Smoking and heavy alcohol consumption increase PC risk, while NAFPD and obesity, particularly central adiposity, contribute through chronic inflammation and insulin resistance. Refined sugar and sugar-sweetened beverages (SSBs) are also linked to increased PC risk, especially among younger individuals. Hormonal treatments and medications like statins, aspirin, and metformin have mixed results on PC risk, with some showing protective effects. The gut microbiome influences PC through the gut-pancreas axis, with disruptions leading to inflammation and carcinogenesis. Exposure to toxic substances, including heavy metals and chemicals, is associated with increased PC risk. Glycome changes, such as abnormal glycosylation patterns, are significant in PDAC development and offer potential for early diagnosis. Interactions between environmental and genetic factors are crucial in PDAC susceptibility. Genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) linked to PDAC, but gene-environment interactions remain largely unexplored. Future research should focus on polygenic risk scores (PRS) and large-scale studies to better understand these interactions and their impact on PDAC risk.

Keywords: Exposome; Pancreatic Cancer; Risk factors.

Pancreatic neuroendocrine neoplasms (pNENs): Genetic and environmental biomarkers for risk of occurrence and prognosis

Matteo Tacelli¹, Manuel Gentiluomo², Paolo Biamonte³, Justo P Castano⁴, Maja Cigrovski Berković⁵, Mauro Cives⁶, Sanja Kapitanović⁷, Ilaria Marinoni⁸, Sonja Marinovic⁷, Ilias Nikas⁹, Lenka Nosáková¹⁰, Sergio Pedraza-Arevalo⁴, Eleonora Pellè¹¹, Aurel Perren⁸, Jonathan Strosberg¹¹, Daniele Campa², Gabriele Capurso¹²

PMID: 40158764

DOI: 10.1016/j.semcancer.2025.03.005

Abstract

Pancreatic neuroendocrine neoplasms (pNENs) are rare and heterogeneous tumors arising from neuroendocrine cells, representing approximately 10% of all Gastro-Entero-Pancreatic neuroendocrine neoplasms. While most pNENs are sporadic, a subset is associated with genetic syndromes such as multiple endocrine neoplasia type 1 (MEN1) or von Hippel-Lindau disease (VHL). pNENs are further classified into functioning and non-functioning tumors, with distinct clinical behaviors, prognoses, and treatment approaches. This review explores genetic and environmental biomarkers that influence the risk, prognosis, and therapeutic responses in pNENs. The epidemiology of pNENs reveals an increasing incidence, primarily due to advancements in imaging techniques. Genetic factors play a pivotal role, with germline mutations in MEN1, VHL, and other genes contributing to familial pNENs. Somatic mutations, including alterations in the mTOR pathway and DNA maintenance genes such as DAXX and ATRX, are critical in sporadic pNENs. These mutations, along with epigenetic dysregulation and transcriptomic alterations, underpin the diverse clinical and molecular phenotypes of pNENs. Emerging evidence suggests that epigenetic changes, including DNA methylation profiles, can stratify pNEN subtypes and predict disease progression. Environmental and lifestyle factors, such as diabetes, smoking, and chronic pancreatitis, have been linked to an increased risk of sporadic pNENs. While the association between these factors and tumor progression is still under investigation, their potential role in influencing therapeutic outcomes warrants further study. Advances in systemic therapies, including somatostatin analogs, mTOR inhibitors, and tyrosine kinase inhibitors, have improved disease management. Biomarkers such as Ki-67, somatostatin receptor expression, and O6-methylguanine-DNA methyltransferase (MGMT) status are being evaluated for their predictive value. Novel approaches, including the use of circulating biomarkers (NETest, circulating tumor cells, and ctDNA) and polygenic risk scores, offer promising avenues for non-invasive diagnosis and monitoring. Despite these advancements, challenges remain, including the need for large, well-annotated datasets and validated biomarkers. Future research should integrate multi-omics approaches and leverage liquid biopsy technologies to refine diagnostic, prognostic, and therapeutic strategies. Interdisciplinary collaborations and global consortia are crucial for overcoming current limitations and translating research findings into clinical practice. These insights hold promise for improving prevention, early detection, and tailored treatments, ultimately enhancing patient outcomes.

Keywords: Genetic; NEN; NET; Neuroendocrine neoplasms; PNET; PanNEN; Radioligand; Risk factors; Somatostatin.

The relationship of the microbiome, associated metabolites and the gut barrier with pancreatic cancer

Neil Daniel¹, Riccardo Farinella², Flavia Belluomini², Almir Fajkic³, Cosmeri Rizzato², Pavel Souček⁴, Daniele Campa², David J Hughes⁵

PMID: 40154652

DOI: 10.1016/j.semcancer.2025.03.002

Abstract

Pancreatic cancers have high mortality and rising incidence rates which may be related to unhealthy western-type dietary and lifestyle patterns as well as increasing body weights and obesity rates. Recent data also suggest a role for the gut microbiome in the development of pancreatic cancer. Here, we review the experimental and observational evidence for the roles of the oral, gut and intratumoural microbiomes, impaired gut barrier function and exposure to inflammatory compounds as well as metabolic dysfunction as contributors to pancreatic disease with a focus on pancreatic ductal adenocarcinoma (PDAC) initiation and progression. We also highlight some emerging gut microbiome editing techniques currently being investigated in the context of pancreatic disease. Notably, while the gut microbiome is significantly altered in PDAC and its precursor diseases, its utility as a diagnostic and prognostic tool is hindered by a lack of reproducibility and the potential for reverse causality in case-control cohorts. Future research should emphasise longitudinal and mechanistic studies as well as integrating lifestyle exposure and multi-omics data to unravel complex host-microbiome interactions. This will allow for deeper aetiologic and mechanistic insights that can inform treatments and guide public health recommendations.

Keywords: Bacterial metabolites; Diet; Microbiome; Pancreatic ductal adenocarcinoma.

From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction

Riccardo Farinella¹, Alessio Felici¹, Giulia Peduzzi¹, Sabrina Gloria Giulia Testoni², Eithne Costello³, Paolo Aretini⁴, Ricardo Blazquez-Encinas⁵, Elif Oz⁶, Aldo Pastore⁴, Matteo Tacelli⁷, Burçak Otlu⁸, Daniele Campa¹, Manuel Gentiluomo⁹

PMID: 40147701

DOI: 10.1016/j.semcancer.2025.03.004

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, characterized by late-stage diagnosis and limited therapeutic options. Risk stratification has traditionally been performed using epidemiological studies and genetic analyses, through which key risk factors, including smoking, diabetes, chronic pancreatitis, and inherited predispositions, have been identified. However, the multifactorial nature of PDAC has often been insufficiently addressed by these methods, leading to limited precision in individualized risk assessments. Advances in artificial intelligence (AI) have been proposed as a transformative approach, allowing the integration of diverse datasets-spanning genetic, clinical, lifestyle, and imaging data into dynamic models capable of uncovering novel interactions and risk profiles. In this review, the evolution of PDAC risk stratification is explored, with classical epidemiological frameworks compared to AI-driven methodologies. Genetic insights, including genome-wide association studies and polygenic risk scores, are discussed, alongside AI models such as machine learning, radiomics, and deep learning. Strengths and limitations of these approaches are evaluated, with challenges in clinical translation, such as data scarcity, model interpretability, and external validation, addressed. Finally, future directions are proposed for combining classical and AI-driven methodologies to develop scalable, personalized predictive tools for PDAC, with the goal of improving early detection and patient outcomes.

Keywords: Artificial intelligence; Early detection; Genetic susceptibility; Pancreatic cancer; Risk stratification.

Biomarkers, omics and artificial intelligence for early detection of pancreatic cancer

Kate Murray¹, Lucy Oldfield¹, Irena Stefanova¹, Manuel Gentiluomo², Paolo Aretini³, Rachel O’Sullivan¹, William Greenhalf¹, Salvatore Paiella⁴, Mateus N Aoki⁵, Aldo Pastore⁶, James Birch-Ford¹, Bhavana Hemantha Rao⁷, Pinar Uysal-Onganer⁸, Caoimhe M Walsh⁹, George B Hanna⁹, Jagriti Narang¹⁰, Pradakshina Sharma¹⁰, Daniele Campa², Cosmeri Rizzato², Andrei Turtoi¹¹, Elif Arik Sever¹², Alessio Felici², Ceren Sucularli¹³, Giulia Peduzzi², Elif Öz¹⁴, Osman Uğur Sezerman¹⁴, Robert Van der Meer¹⁵, Nathan Thompson¹⁵, Eithne Costello¹⁶

PMID: 39986585

DOI: 10.1016/j.semcancer.2025.02.009

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is frequently diagnosed in its late stages when treatment options are limited. Unlike other common cancers, there are no population-wide screening programmes for PDAC. Thus, early disease detection, although urgently needed, remains elusive. Individuals in certain high-risk groups are, however, offered screening or surveillance. Here we explore advances in understanding high-risk groups for PDAC and efforts to implement biomarker-driven detection of PDAC in these groups. We review current approaches to early detection biomarker development and the use of artificial intelligence as applied to electronic health records (EHRs) and social media. Finally, we address the cost-effectiveness of applying biomarker strategies for early detection of PDAC.

Keywords: Artificial intelligence; Biomarkers; Early detection; Omics; Pancreatic cancer.

Leveraging epigenetic alterations in pancreatic ductal adenocarcinoma for clinical applications

Jorg Tost¹, Secil Ak-Aksoy², Daniele Campa³, Chiara Corradi⁴, Riccardo Farinella⁵, Alejandro Ibáñez-Costa⁶, Juan Dubrot⁷, Julie Earl⁸, Emma Barreto Melian⁹, Agapi Kataki¹⁰, Georgina Kolnikova¹¹, Gjorgji Madjarov¹², Marija Chaushevska¹³, Jan Strnadel¹⁴, Miljana Tanić¹⁵, Miroslav Tomas¹⁶, Peter Dubovan¹⁷, Maria Urbanova¹⁸, Verona Buocikova¹⁹, Bozena Smolkova²⁰

PMID: 39863139

DOI: 10.1016/j.semcancer.2025.01.003

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by late detection and poor prognosis. Recent research highlights the pivotal role of epigenetic alterations in driving PDAC development and progression. These changes, in conjunction with genetic mutations, contribute to the intricate molecular landscape of the disease. Specific modifications in DNA methylation, histone marks, and non-coding RNAs are emerging as robust predictors of disease progression and patient survival, offering the potential for more precise prognostic tools compared to conventional clinical staging. Moreover, the detection of epigenetic alterations in blood and other non-invasive samples holds promise for earlier diagnosis and improved management of PDAC. This review comprehensively summarises current epigenetic research in PDAC and identifies persisting challenges. These include the complex nature of epigenetic profiles, tumour heterogeneity, limited access to early-stage samples, and the need for highly sensitive liquid biopsy technologies. Addressing these challenges requires the standardisation of methodologies, integration of multi-omics data, and leveraging advanced computational tools such as machine learning and artificial intelligence. While resource-intensive, these efforts are essential for unravelling the functional consequences of epigenetic changes and translating this knowledge into clinical applications. By overcoming these hurdles, epigenetic research has the potential to revolutionise the management of PDAC and improve patient outcomes.

Keywords: Biomarker; DNA methylation; Epigenetic regulation; Non-coding RNA; Pancreatic ductal adenocarcinoma.

Multi-omic markers of intraductal papillary mucinous neoplasms progression into pancreatic cancer

Chiara Corradi¹, Manuel Gentiluomo¹, Volkan Adsay², Juan Sainz³, Paolo Riccardo Camisa⁴, Barbara Wlodarczyk⁵, Stefano Crippa⁴, Francesca Tavano⁶, Gabriele Capurso⁷, Daniele Campa⁸

PMID: 39733817

DOI: 10.1016/j.semcancer.2024.12.005

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is the most lethal and common form of pancreatic cancer, it has no specific symptoms, and most of the patients are diagnosed when the disease is already at an advanced stage. Chemotherapy typically has only a modest effect, making surgery the most effective treatment option. However, only a small percentage of patients are amenable to surgery. One viable strategy to reduce PDAC death burden associated with the disease is to focus on precursor lesions and identify markers able to predict who will evolve into PDAC. While most PDACs are believed to be preceded by pancreatic intraepithelial neoplasms (PanINs), 5-10 % arise from Intraductal papillary mucinous neoplasms (IPMNs), which are mass-forming cystic lesions that are very common in the general population. IPMNs offer an invaluable model of pancreatic carcinogenesis for researchers to analyse, as well as a target population for PDAC early detection by clinicians. The evolution of IPMN into cancer is a complex and multistep process, therefore the identification of individual markers will not be the solution. In recent years, multiple omics technologies have been instrumental to identify possible biomarkers of IPMN progression and carcinogenesis. The only foreseeable strategy will be to integrate multi-omics data, alongside clinical and morphological features, into a progression score or signature using either standard epidemiologic tools or artificial intelligence. The aim of this manuscript is to review the current knowledge on genetic biomarkers and to briefly mention also additional omics, such as metabolomics, the exposome, the miRNome and epigenomics of IPMNs.

Keywords: Exposome; Intraductal papillary mucinous neoplasm; Metabolomics; MicroRNA; Polymorphisms.

Unravelling the complexities of resistance mechanism in pancreatic cancer: Insights from in vitro and ex-vivo model systems

Giulia Lencioni¹, Alessandro Gregori², Belén Toledo³, Rita Rebelo⁴, Benoît Immordino⁵, Manoj Amrutkar⁶, Cristina P R Xavier⁷, Anja Kocijančič⁸, Deo Prakash Pandey⁸, Macarena Perán⁹, Justo P Castaño¹⁰, Naomi Walsh¹¹, Elisa Giovannetti¹²

PMID: 39299411

DOI: 10.1016/j.semcancer.2024.09.002

Abstract

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive cancer with poor prognosis and rising global deaths. Late diagnosis, due to absent early symptoms and biomarkers, limits treatment mainly to chemotherapy, which soon encounters resistance. PDAC treatment innovation is hampered by its complex and heterogeneous resistant nature, including mutations in key genes and a stromal-rich, immunosuppressive tumour microenvironment. Recent studies on PDAC resistance stress the need for suitable in vitro and ex vivo models to replicate its complex molecular and microenvironmental landscape. This review summarises advances in these models, which can aid in combating chemoresistance and serve as platforms for discovering new therapeutics. Immortalised cell lines offer homogeneity, unlimited proliferation, and reproducibility, but while many gemcitabine-resistant PDAC cell lines exist, fewer models are available for resistance to other drugs. Organoids from PDAC patients show promise in mimicking tumour heterogeneity and chemosensitivity. Bioreactors, co-culture systems and organotypic slices, incorporating stromal and immune cells, are being developed to understand tumour-stroma interactions and the tumour microenvironment’s role in drug resistance. Lastly, another innovative approach is three-dimensional bioprinting, which creates tissue-like structures resembling PDAC architecture, allowing for drug screening. These advanced models can guide researchers in selecting optimal in vitro tests, potentially improving therapeutic strategies and patient outcomes.

Keywords: Chemoresistance; In vitro models; Organoids; Organotypic slices; Pancreatic cancer.

Organoids, tissue slices and organotypic cultures: Advancing our understanding of pancreatic ductal adenocarcinoma through in vitro and ex vivo models

Secil Ak Aksoy¹, Julie Earl², Jelena Grahovac³, Didem Karakas⁴, Giulia Lencioni⁵, Sıla Sığırlı⁴, Maarten F Bijlsma⁶

PMID: 39730107

DOI: 10.1016/j.semcancer.2024.12.003

Abstract

Pancreatic ductal adenocarcinoma (PDAC) has one of the worst prognoses of all common solid cancers. For the large majority of PDAC patients, only systemic therapies with very limited efficacy are indicated. In addition, immunotherapies have not brought the advances seen in other cancer types. Several key characteristics of PDAC contribute to poor treatment outcomes, and in this review, we will discuss how these characteristics are best captured in currently available ex vivo or in vitro model systems. For instance, PDAC is hallmarked by a highly desmoplastic and immune-suppressed tumor microenvironment that impacts disease progression and therapy resistance. Also, large differences in tumor biology exist between and within tumors, complicating treatment decisions. Furthermore, PDAC has a very high propensity for locally invasive and metastatic growth. The use of animal models is often not desirable or feasible and several in vitro and ex vivo model systems have been developed, such as organotypic cocultures and tissue slices, among others. However, the absence of a full host organism impacts the ability of these models to accurately capture the characteristics that contribute to poor outcomes in PDAC. We will discuss the caveats and advantages of these model systems in the context of PDAC’s key characteristics and provide recommendations on model choice and the possibilities for optimization. These considerations should be of use to researchers aiming to study PDAC in the in vitro setting.

Keywords: Experimental models; Metastasis; Organoids; Pancreatic cancer; Therapy resistance.

This is a collection of Publications related to our COST Action

Raman spectroscopy based diagnosis of pancreatic ductal adenocarcinoma

Gianmarco Lazzini 1, Raffele Gaeta 2, Luca Emanuele Pollina 2, Annalisa Comandatore 3 4, Niccolò Furbetta 4, Luca Morelli 4, Mario D’Acunto 5

PMID: 40247119
PMCID: PMC12006465
DOI: 10.1038/s41598-025-98122-9

Pancreatic ductal adenocarcinoma is currently the 12th most frequent form of cancer worldwide, characterized by a very low 5-year survival rate. Although several therapeutic approaches have been proposed to treat this form of pancreatic cancer, surgical resection is still commonly recognized as the most effective technique to slow down the disease progression and maximize the 5-year survival rate. Analogously, one critical issue is the ability of current diagnostic methodologies to distinguish between irregular growth of the tumor mass and surrounding inflammatory tissues. In this pilot study, we apply Raman spectroscopy, supported by a series of machine learning techniques, to distinguish among healthy, pancreatitis and ductal adenocarcinoma tissues, respectively, for a total of 15 cases. Raman spectroscopy is a label-free, non-destructive spectral technique exploiting Raman scattering. In turn, by applying a combination of principal component analysis and random forest classifier on the Raman spectral dataset, we achieved a maximum accuracy of up to 96%. Our findings clearly indicate that Raman spectroscopy could become a powerful spectral technique to support pathologists in improving pancreatic cancer diagnosis.

Keywords: Gaussian Naive-Bayes; Pancreatic ductal adenocarcinoma; Raman spectroscopy; Random forest classifier; SPectral SELection.

Polymorphisms within autophagy-related genes as susceptibility biomarkers for pancreatic cancer: A meta-analysis of three large European cohorts and functional characterization

Fernando Gálvez-Montosa¹, Giulia Peduzzi², José Manuel Sanchez-Maldonado^3 4 5 6, Rob Ter Horst^7 8, Antonio J Cabrera-Serrano^4 5, Manuel Gentiluomo², Angelica Macauda⁶, Natalia Luque¹, Pelin Ünal⁶, Francisco José García-Verdejo¹, Yang Li^7 8, José Antonio López López¹, Angelika Stein⁶, H Bas Bueno-de-Mesquita^#⁹, Paolo Giorgio Arcidiacono¹⁰, Dalila Luciola Zanette¹¹, Christoph Kahlert¹², Francesco Perri¹³, Pavel Soucek¹⁴, Renata Talar-Wojnarowska¹⁵, George E Theodoropoulos¹⁶, Jakob R Izbicki¹⁷, Hussein Tamás^18 19, Hanneke Van Laarhoven^20 21, Gennaro Nappo^22 23, Maria Chiara Petrone¹⁰, Martin Lovecek²⁴, Roel C H Vermeulen²⁵, Kestutis Adamonis²⁶, Fernando Jesus Reyes-Zurita³, Bernd Holleczek^27 28, Jolanta Sumskiene²⁶, Beatrice Mohelníková-Duchoňová²⁹, Rita T Lawlor^30 31, Raffaele Pezzilli³², Mateus Nobrega Aoki¹¹, Claudio Pasquali³³, Vitalija Petrenkiene²⁶, Daniela Basso³⁴, Stefania Bunduc^{18 19 35 36}, Annalisa Comandatore³⁷, Hermann Brenner^28 38, Stefano Ermini², Giuseppe Vanella^39 40, Mara R Goetz¹⁷, Livia Archibugi^39 40, Maurizio Lucchesi⁴¹, Faik Guntac Uzunoglu¹⁷, Olivier Busch^21 42, Anna Caterina Milanetto³³, Marta Puzzono⁴³, Juozas Kupcinskas²⁶, Luca Morelli³⁷, Cosimo Sperti³³, Silvia Carrara⁴⁴, Gabriele Capurso^39 40, Casper H J van Eijck⁴⁵, Martin Oliverius⁴⁶, Susanne Roth¹², Francesca Tavano¹³, Rudolf Kaaks⁴⁷, Andrea Szentesi⁴⁸, Ludmila Vodickova^49 50 51, Claudio Luchini^30 52, Ben Schöttker²⁸, Stefano Landi², Orsolya Dohan¹⁹, Matteo Tacelli¹⁰, William Greenhalf⁵³, Maria Gazouli⁵⁴, John P Neoptolemos¹², Giulia Martina Cavestro⁴³, Ugo Boggi⁵⁵, Anna Latiano¹³, Péter Hegyi^{18 19 48 56}, Laura Ginocchi⁴¹, Mihai G Netea^57 58, Pedro Sánchez-Rovira¹, Federico Canzian⁶, Daniele Campa², Juan Sainz^3 4 5 59

Int J Cancer. 2025 Jan 15;156(2):339-352

https://doi.org/10.1002/ijc.35196

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers with patients having unresectable or metastatic disease at diagnosis, with poor prognosis and very short survival. Given that genetic variation within autophagy-related genes influences autophagic flux and susceptibility to solid cancers, we decided to investigate whether 55,583 single nucleotide polymorphisms (SNPs) within 234 autophagy-related genes could influence the risk of developing PDAC in three large independent cohorts of European ancestry including 12,754 PDAC cases and 324,926 controls. The meta-analysis of these populations identified, for the first time, the association of the BID_rs9604789 variant with an increased risk of developing the disease (OR_Meta = 1.31, p = 9.67 × 10^-6). We also confirmed the association of TP63_rs1515496 and TP63_rs35389543 variants with PDAC risk (OR = 0.89, p = 6.27 × 10^-8 and OR = 1.16, p = 2.74 × 10^-5). Although it is known that BID induces autophagy and TP63 promotes cell growth, cell motility and invasion, we also found that carriers of the TP63_rs1515496G allele had increased numbers of FOXP3+ Helios+ T regulatory cells and CD45RA+ T regulatory cells (p = 7.67 × 10^-4 and p = 1.56 × 10^-3), but also decreased levels of CD4+ T regulatory cells (p = 7.86 × 10^-4). These results were in agreement with research suggesting that the TP63_rs1515496 variant alters binding sites for FOXA1 and CTCF, which are transcription factors involved in modulating specific subsets of regulatory T cells. In conclusion, this study identifies BID as new susceptibility locus for PDAC and confirms previous studies suggesting that the TP63 gene is involved in the development of PDAC. This study also suggests new pathogenic mechanisms of the TP63 locus in PDAC.

Physical Activity, Sedentary Behavior, and Pancreatic Cancer Risk: A Mendelian Randomization Study

Manuel Gentiluomo, Suzanne C Dixon-Suen, Riccardo Farinella, Giulia Peduzzi, Federico Canzian, Roger L Milne, Brigid M Lynch, Daniele Campa

Journal of the Endocrine Society vol. 8,4 bvae017. 29 Feb. 2024

https://doi.org/10.1210/jendso/bvae017

Pancreatic cancer is currently the seventh leading cause of cancer death worldwide. Understanding whether modifiable factors increase or decrease the risk of this disease is central to facilitating primary prevention. Several epidemiological studies have described the benefits of physical activity, and the risks associated with sedentary behavior, in relation to cancer. This study aimed to assess evidence of causal effects of physical activity and sedentary behavior on pancreatic cancer risk. We conducted a two-sample Mendelian randomization study using publicly available data for genetic variants associated with physical activity and sedentary behavior traits and genetic data from the Pancreatic Cancer Cohort Consortium (PanScan), the Pancreatic Cancer Case-Control Consortium (PanC4), and the FinnGen study for a total of 10 018 pancreatic cancer cases and 266 638 controls. We also investigated the role of body mass index (BMI) as a possible mediator between physical activity and sedentary traits and risk of developing pancreatic cancer. We found evidence of a causal association between genetically determined hours spent watching television (hours per day) and increased risk of pancreatic cancer for each hour increment (PanScan-PanC4 odds ratio = 1.52, 95% confidence interval 1.17-1.98, P = .002). Additionally, mediation analysis showed that genetically determined television-watching time was strongly associated with BMI, and the estimated proportion of the effect of television-watching time on pancreatic cancer risk mediated by BMI was 54%. This study reports the first Mendelian randomization-based evidence of a causal association between a measure of sedentary behavior (television-watching time) and risk of pancreatic cancer and that this is strongly mediated by BMI.

Potential association between PSCA rs2976395 functional variant and pancreatic cancer risk

Chiara Corradi, Giulia Lencioni, Alessio Felici, Cosmeri Rizzato, Manuel Gentiluomo, Stefano Ermini, Livia Archibugi, Antanas Mickevicius, Maurizio Lucchesi, Ewa Malecka-Wojciesko, Daniela Basso, Paolo Giorgio Arcidiacono, Maria Chiara Petrone, Silvia Carrara, Mara Götz, Stefania Bunduc, Bernd Holleczek, Mateus Nóbrega Aoki, Faik G. Uzunoglu, Dalila Lucíola Zanette, Andrea Mambrini, Krzysztof Jamroziak, Martin Oliverius, Martin Lovecek, Giulia Martina Cavestro, Anna Caterina Milanetto, Giulia Peduzzi, Beatrice Mohelnikova Duchonova, Jakob R. Izbicki, Rimantas Zalinkevicius, Viktor Hlavac, Casper H. J. van Eijck, Hermann Brenner, Giuseppe Vanella, Klara Vokacova, Pavel Soucek, Francesca Tavano, Francesco Perri, Gabriele Capurso, Tamás Hussein, Mindaugas Kiudelis, Juozas Kupcinskas, Olivier R. Busch, Luca Morelli, George E. Theodoropoulos, Sabrina Gloria Giulia Testoni, Kestutis Adamonis, John P. Neoptolemos, Maria Gazouli, Claudio Pasquali, Zita Kormos, Pavel Skalicky, Raffaele Pezzilli, Cosimo Sperti, Emanuele Kauffmann, Markus W. Büchler, Ben Schöttker, Péter Hegyi, Giovanni Capretti, Rita T. Lawlor, Federico Canzian, Daniele Campa

International journal of cancer vol. 155,8 (2024): 1432-1442

https://doi.org/10.1002/ijc.35046

Correlated regions of systemic interindividual variation (CoRSIV) represent a small proportion of the human genome showing DNA methylation patterns that are the same in all human tissues, are different among individuals, and are partially regulated by genetic variants in cis. In this study we aimed at investigating single-nucleotide polymorphisms (SNPs) within CoRSIVs and their involvement with pancreatic ductal adenocarcinoma (PDAC) risk. We analyzed 29,099 CoRSIV-SNPs and 133,615 CoRSIV-mQTLs in 14,394 cases and 247,022 controls of European and Asian descent. We observed that the A allele of the rs2976395 SNP was associated with increased PDAC risk in Europeans (p = 2.81 × 10⁻⁵). This SNP lies in the prostate stem cell antigen gene and is in perfect linkage disequilibrium with a variant (rs2294008) that has been reported to be associated with risk of many other cancer types. The A allele is associated with the DNA methylation level of the gene according to the PanCan-meQTL database and with overexpression according to QTLbase. The expression of the gene has been observed to be deregulated in many tumors of the gastrointestinal tract including pancreatic cancer; however, functional studies are needed to elucidate the function relevance of the association.

Genetically predicted gut bacteria, circulating bacteria-associated metabolites and pancreatic ductal adenocarcinoma: a Mendelian randomisation study

Neil Daniel, Riccardo Farinella, Anastasia Chrysovalantou Chatziioannou, Mazda Jenab, Ana-Lucia Mayén, Cosmeri Rizzato, Flavia Belluomini, Federico Canzian, Arianna Tavanti, Pekka Keski-Rahkonen, David J. Hughes & Daniele Campa

Sci Rep 14, 25144 (2024)

https://doi.org/10.1038/s41598-024-77431-5

Pancreatic ductal adenocarcinoma (PDAC) has high mortality and rising incidence rates. Recent data indicate that the gut microbiome and associated metabolites may play a role in the development of PDAC. To complement and inform observational studies, we investigated associations of genetically predicted abundances of individual gut bacteria and genetically predicted circulating concentrations of microbiome-associated metabolites with PDAC using Mendelian randomisation (MR). Gut microbiome-associated metabolites were identified through a comprehensive search of Pubmed, Exposome Explorer and Human Metabolome Database. Single Nucleotide Polymorphisms (SNPs) associated by Genome-Wide Association Studies (GWAS) with circulating levels of 109 of these metabolites were collated from Pubmed and the GWAS catalogue. SNPs for 119 taxonomically defined gut genera were selected from a meta-analysis performed by the MiBioGen consortium. Two-sample MR was conducted using GWAS summary statistics from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including a total of 8,769 cases and 7,055 controls. Inverse variance-weighted MR analyses were performed along with sensitivity analyses to assess potential violations of MR assumptions. Nominally significant associations were noted for genetically predicted circulating concentrations of mannitol (odds ratio per standard deviation [OR_SD] = 0.97; 95% confidence interval [CI]: 0.95–0.99, p = 0.006), methionine (OR_SD= 0.97; 95%CI: 0.94-1.00, p = 0.031), stearic acid (OR_SD= 0.93; 95%CI: 0.87–0.99, p = 0.027), carnitine = (OR_SD=1.01; 95% CI: 1.00-1.03, p = 0.027), hippuric acid (OR_SD= 1.02; 95%CI: 1.00-1.04, p = 0.038) and 3-methylhistidine (OR_SD= 1.05; 95%CI: 1.01–1.10, p = 0.02). Two gut microbiome genera were associated with reduced PDAC risk; Clostridium sensu stricto 1 (OR: 0.88; 95%CI: 0.78–0.99, p = 0.027) and Romboutsia (OR: 0.87; 95%CI: 0.80–0.96, p = 0.004). These results, though based only on genetically predicted gut microbiome characteristics and circulating bacteria-related metabolite concentrations, provide evidence for causal associations with pancreatic carcinogenesis.

An integrative RNA spliceosomic landscape of pancreatic neuroendocrine tumors unveils novel clinicomolecular associations

Ricardo Blázquez-Encinas, Víctor García-Vioque, Andrea Mafficini, Luca Landoni, María Trinidad Moreno-Montilla, Nicolas Alcala, Sebastián Ventura, Eduardo Eyras, Salvatore Paiella, Roberto Salvia, Vita Rovite, Matthieu Foll, Claudio Luchini, Lynnette Fernandez-Cuesta, Rita T. Lawlor, Aldo Scarpa, Alejandro Ibáñez-Costa, Sergio Pedraza-Arevalo, Justo P. Castaño

bioRxiv preprint

https://doi.org/10.1101/2024.10.30.621040

Alterations in alternative splicing are emerging as a novel hallmark in cancer biology, offering new insights. However, integrative analyses of splicing are still scarce, particularly in rare cancers such as pancreatic neuroendocrine tumors (PanNETs). These tumors are highly heterogeneous, complicating diagnosis and treatment. This study is the first to comprehensively investigate the RNA splicing landscape in PanNETs, identifying distinct spliceosomic profiles correlated with unique clinical and molecular characteristics. We analyzed RNA-seq data from 174 samples, identifying three distinct spliceosomic groups (SPN1, SPN2, SPN3) with unique clinical and molecular characteristics. SPN1 exhibited intermediate clinical features and specific splicing machinery profile, SPN2 was associated with frequent mutations in MEN1 and DAXX/ATRX genes, and SPN3 showed a prevalence of well-differentiated tumors with distinct splicing patterns. These groups were linked to different clinical outcomes and activated key biological processes like mTOR signaling and hormone secretion pathways. Our findings underscore the significant impact of RNA splicing on PanNET heterogeneity and suggest that detailed splicing profiles could serve as valuable tools for identifying novel biomarkers and therapeutic targets. This study provides crucial insights into PanNET molecular biology and paves the way for personalized therapies based on splicing features.

Thermal Liquid Biopsy: A Promising Tool for the Differential Diagnosis of Pancreatic Cystic Lesions and Malignancy Detection

Judith Millastre, Sonia Hermoso-Durán, María Ortiz de Solórzano, Nicolas Fraunhoffer, Guillermo García-Rayado, Sonia Vega, Luis Bujanda, Carlos Sostres, Ángel Lanas, Adrián Velázquez-Campoy, Olga Abian

Cancers 2024, 16, 4024

https://doi.org/10.3390/cancers16234024

Mucinous epithelial pancreatic cystic lesions (PCLs) are premalignant lesions detectable through imaging techniques; however, distinguishing them from other PCLs with lower malignancy potential is challenging. Current methods like biochemical markers and genomic studies are not always reliable. Thermal liquid biopsy (TLB) is an innovative tool that analyzes the thermal profile of biological samples to detect disease-related alterations. In a retrospective study of 35 intracystic fluid samples obtained via fine needle aspiration, predictive models were developed using machine learning algorithms. Two classification models were created: TLB1, which differentiates mucinous from non-mucinous PCLs, demonstrating 92% sensitivity and 86% negative predictive value, and TLB2, which identifies benign and malignant mucinous lesions, achieving an area under the curve of 1.00. TLB shows promise in improving the differential diagnosis of PCLs and in detecting malignant transformations.

Darifenacin: a promising chitinase 3-like 1 inhibitor to tackle drug resistance in pancreatic ductal adenocarcinoma

Sofia M. Sousa, Helena Branco, Amir Avan, Andreia Palmeira, Luca Morelli, Lúcio L. Santos, Elisa Giovannetti, M. Helena Vasconcelos & Cristina P. R. Xavier

Cancer Chemother Pharmacol 94, 585–597 (2024)

https://doi.org/10.1007/s00280-024-04712-1

Pancreatic ductal adenocarcinoma (PDAC) is among the most aggressive malignancies. Our previous work revealed Chitinase 3-like 1 (CHI3L1) involvement in PDAC resistance to gemcitabine, identifying it as a promising therapeutic target. Here, we aimed to identify putative CHI3L1 inhibitors and to investigate their chemosensitizing potential in PDAC.

Prognostic value of microRNA-21 in intra- and extrahepatic cholangiocarcinoma after radical resection: cohort study

Lenka N C Boyd, Mahsoem Ali, Annalisa Comandatore, Giovanni Brandi, Simona Tavolari, Raffaele Gaeta, Laura L Meijer, Tessa Y S Le Large, Mattia Riefolo, Francesco Vasuri, Luca Morelli, Hanneke W M van Laarhoven, Elisa Giovannetti, Geert Kazemier, Ingrid Garajová

BJS Open, Volume 8, Issue 2, April 2024

https://doi.org/10.1093/bjsopen/zrae031

The clinical outcomes of patients with cholangiocarcinoma are poor, with a median survival of 17–38 months after resection, depending on the anatomical location of the primary tumour and the presence of high-risk features (for example positive resection margins and lymph node metastases)^1,2.

Incorporating biomarkers such as microRNAs into prognostic models for cholangiocarcinoma might improve patient risk assessment, enable personalized clinical decision-making and provide more precise prognosis estimates. A previous meta-analysis identified microRNA-21 (miR-21) as an ‘ideal prognostic marker for clinical decision-making’ but it did not compare its performance with commonly used clinicopathological variables such as resection margin and tumour grade. Previous studies revealed that the prognostic value of a novel biomarker can be substantially reduced after correcting for commonly measured prognostic variables^3–5.

The aim of this study was to assess the association between miRNA-21 and overall survival (OS) in cholangiocarcinoma and assess its performance in prognostic prediction models.

Proteomics analysis of circulating small extracellular vesicles: Focus on the contribution of EVs to tumor metabolism

Federica Anastasi, Asia Botto, Benoit Immordino, Elisa Giovannetti, Liam A. McDonnell

Cytokine & Growth Factor Reviews volume 73, October 2023

https://doi.org/10.1016/j.cytogfr.2023.08.003

The term small extracellular vesicle (sEV) is a comprehensive term that includes any type of cell-derived, membrane-delimited particle that has a diameter < 200 nm, and which includes exosomes and smaller microvesicles. sEVs transfer bioactive molecules between cells and are crucial for cellular homeostasis and particularly during tumor development, where sEVs provide important contributions to the formation of the premetastic niche and to their altered metabolism. sEVs are thus legitimate targets for intervention and have also gained increasing interest as an easily accessible source of biomarkers because they can be rapidly isolated from serum/plasma and their molecular cargo provides information on their cell-of origin. To target sEVs that are specific for a given cell/disease it is essential to identify EV surface proteins that are characteristic of that cell/disease. Mass-spectrometry based proteomics is widely used for the identification and quantification of sEV proteins. The methods used for isolating the sEVs, preparing the sEV sample for proteomics analysis, and mass spectrometry analysis, can have a strong influence on the results and requires careful consideration. This review provides an overview of the approaches used for sEV proteomics and discusses the inherent compromises regarding EV purity versus depth of coverage. Additionally, it discusses the practical applications of the methods to unravel the involvement of sEVs in regulating the metabolism of pancreatic ductal adenocarcinoma (PDAC). The metabolic reprogramming in PDAC includes enhanced glycolysis, elevated glutamine metabolism, alterations in lipid metabolism, mitochondrial dysfunction and hypoxia, all of which are crucial in promoting tumor cell growth. A thorough understanding of these metabolic adaptations is imperative for the development of targeted therapies to exploit PDAC’s vulnerabilities.

Deciphering the performance of macrophages in tumour microenvironment: a call for precision immunotherapy

Belén Toledo, Linrui Zhu Chen, María Paniagua-Sancho, Juan Antonio Marchal, Macarena Perán & Elisa Giovannetti

Journal of hematology & oncology vol. 17,1 44. 11 Jun. 2024

https://doi.org/10.1186/s13045-024-01559-0

Macrophages infiltrating tumour tissues or residing in the microenvironment of solid tumours are known as tumour-associated macrophages (TAMs). These specialized immune cells play crucial roles in tumour growth, angiogenesis, immune regulation, metastasis, and chemoresistance. TAMs encompass various subpopulations, primarily classified into M1 and M2 subtypes based on their differentiation and activities. M1 macrophages, characterized by a pro-inflammatory phenotype, exert anti-tumoural effects, while M2 macrophages, with an anti-inflammatory phenotype, function as protumoural regulators. These highly versatile cells respond to stimuli from tumour cells and other constituents within the tumour microenvironment (TME), such as growth factors, cytokines, chemokines, and enzymes. These stimuli induce their polarization towards one phenotype or another, leading to complex interactions with TME components and influencing both pro-tumour and anti-tumour processes.

This review comprehensively and deeply covers the literature on macrophages, their origin and function as well as the intricate interplay between macrophages and the TME, influencing the dual nature of TAMs in promoting both pro- and anti-tumour processes. Moreover, the review delves into the primary pathways implicated in macrophage polarization, examining the diverse stimuli that regulate this process. These stimuli play a crucial role in shaping the phenotype and functions of macrophages. In addition, the advantages and limitations of current macrophage based clinical interventions are reviewed, including enhancing TAM phagocytosis, inducing TAM exhaustion, inhibiting TAM recruitment, and polarizing TAMs towards an M1-like phenotype. In conclusion, while the treatment strategies targeting macrophages in precision medicine show promise, overcoming several obstacles is still necessary to achieve an accessible and efficient immunotherapy.

Unravelling the complexities of resistance mechanism in pancreatic cancer: Insights from in vitro and ex-vivo model systems

Giulia Lencioni, Alessandro Gregori, Belén Toledo, Rita Rebelo, Benoît Immordino, Manoj Amrutkar, Cristina P.R. Xavier, Anja Kocijančič, Deo Prakash Pandey, Macarena Perán, Justo P. Castaño, Naomi Walsh, Elisa Giovannetti

Semin Cancer Biol. 2024 Nov;106-107:217-233

http://dx.doi.org/10.1016/j.semcancer.2024.09.002

Development of a Machine-Learning Model for Diagnosis of Pancreatic Cancer from Serum Samples Analyzed by Thermal Liquid Biopsy

Sonia Hermoso-Durán, Nicolas Fraunhoffer, Judith Millastre-Bocos, Oscar Sanchez-Gracia, Pablo F. Garrido, Sonia Vega, Ángel Lanas, Juan Iovanna, Adrián Velázquez-Campoy,* and Olga Abian*

DOI: 10.1002/aisy.202400308

Pancreatic ductal adenocarcinoma (PDAC) poses a considerable diagnostic and therapeutic challenge due to the lack of specific biomarkers and late diagnosis. Early detection is crucial for improving prognosis, but current techniques are insufficient. An innovative approach based on differential scanning calorimetry (DSC) of blood serum samples, thermal liquid biopsy (TLB), combined with machine-learning (ML) analysis, may offer a more efficient method for diagnosing PDAC. Serum samples from a cohort of 212 PDAC patients and 184 healthy controls are studied. DSC thermograms are analyzed using ML models. The generated models are built applying algorithms based on penalized regression, resampling, categorization, cross validation, and variable selection. The MLbased model demonstrates outstanding ability to discriminate between PDAC patients and control subjects, with a sensitivity of 90% and an area under the ROC receiver operating characteristic curve of 0.83 in the training and test groups. Application of the model to an independent validation cohort of 113 PDAC patients confirms its robustness and utility as a diagnosis tool. The application of ML to serum TLB data emerges as a promising methodology for early diagnosis, representing a significant advance for detecting and managing PDAC, envisaging a minimally invasive and more efficient methodology for identifying biomarkers.

The PANcreatic Disease ReseArch (PANDoRA) consortium turns 10! A summary of their main findings can be found in this anniversary paper

The PANcreatic Disease ReseArch (PANDoRA) consortium turns 10! A summary of their main findings can be found in this anniversary paper -> https://doi.org/10.1016/j.critrevonc.2023.104020

Pancreatic disease research (PANDoRA) is dedicated to the identification of pancreatic cancer risk loci and is the largest such consortium in Europe. PANDoRA is spread across 12 European countries, Brazil and Japan, bringing together 29 basic and clinical research groups. In the last ten years, PANDoRA has contributed to the discovery of 25 susceptibility loci, a feat that will be instrumental in stratifying the population by risk and optimizing preventive strategies.

Fibroblasts in pancreatic cancer: molecular and clinical perspectives

Rebelo R, Xavier CPR, Giovannetti E, Vasconcelos MH.

Trends Mol Med. 2023 Jun;29(6):439-453. doi: 10.1016/j.molmed.2023.03.002. Epub 2023 Apr 24.

PMID: 37100646

https://pubmed.ncbi.nlm.nih.gov/37100646/

Exploring the Neandertal legacy of pancreatic ductal adenocarcinoma risk in Eurasians

Piccardi M, Gentiluomo M, Bertoncini S, Pezzilli R, Erőss B, Bunduc S, Uzunoglu FG, Talar-Wojnarowska R, Vanagas T, Sperti C, Oliverius M, Aoki MN, Ermini S, Hussein T, Boggi U, Jamroziak K, Maiello E, Morelli L, Vodickova L, Di Franco G, Landi S, Szentesi A, Lovecek M, Puzzono M, Tavano F, van Laarhoven HWM, Zerbi A, Mohelnikova-Duchonova B, Stocker H, Costello E, Capurso G, Ginocchi L, Lawlor RT, Vanella G, Bazzocchi F, Izbicki JR, Latiano A, Bueno-de-Mesquita B, Ponz de Leon Pisani R, Schöttker B, Soucek P, Hegyi P, Gazouli M, Hackert T, Kupcinskas J, Poskiene L, Tacelli M, Roth S, Carrara S, Perri F, Hlavac V, Theodoropoulos GE, Busch OR, Mambrini A, van Eijck CHJ, Arcidiacono P, Scarpa A, Pasquali C, Basso D, Lucchesi M, Milanetto AC, Neoptolemos JP, Cavestro GM, Janciauskas D, Chen X, Chammas R, Goetz M, Brenner H, Archibugi L, Dannemann M, Canzian F, Tofanelli S, Campa D.

Biol Res. 2023 Aug 13;56(1):46. doi: 10.1186/s40659-023-00457-y.

PMID: 37574541

https://pubmed.ncbi.nlm.nih.gov/37574541/

Nanomedicine and epigenetics: New alliances to increase the odds in pancreatic cancer survival

Urbanova M, Cihova M, Buocikova V, Slopovsky J, Dubovan P, Pindak D, Tomas M, García-Bermejo L, Rodríguez-Garrote M, Earl J, Kohl Y, Kataki A, Dusinska M, Sainz B Jr, Smolkova B, Gabelova A.

Biomed Pharmacother. 2023 Sep;165:115179. doi: 10.1016/j.biopha.2023.115179. Epub 2023 Jul 21.

PMID: 37481927

https://pubmed.ncbi.nlm.nih.gov/37481927/

Analysis of exposome and genetic variability suggests stress as a major contributor for development of pancreatic ductal adenocarcinoma.

Peduzzi G, Felici A, Pellungrini R, Giorgolo F, Farinella R, Gentiluomo M, Spinelli A, Capurso G, Monreale A, Canzian F, Calderisi M, Campa D.

Dig Liver Dis. 2023 Nov 18:S1590-8658(23)01004-6. doi: 10.1016/j.dld.2023.10.015. Online ahead of print.

PMID: 37985251

https://pubmed.ncbi.nlm.nih.gov/37985251/

Thinking small to win big? A critical review on the potential application of extracellular vesicles for biomarker discovery and new therapeutic approaches in pancreatic cancer

Vahabi M, Comandatore A, Centra C, Blandino G, Morelli L, Giovannetti E.

Semin Cancer Biol. 2023 Dec;97:50-67. doi: 10.1016/j.semcancer.2023.11.003. Epub 2023 Nov 11.

PMID: 37956937

https://pubmed.ncbi.nlm.nih.gov/37956937/

Polymorphisms in transcription factor binding sites and enhancer regions and pancreatic ductal adenocarcinoma risk

Ünal P, Lu Y, Bueno-de-Mesquita B, van Eijck CHJ, Talar-Wojnarowska R, Szentesi A, Gazouli M, Kreivenaite E, Tavano F, Małecka-Wojciesko E, Erőss B, Oliverius M, Bunduc S, Nóbrega Aoki M, Vodickova L, Boggi U, Giaccherini M, Kondrackiene J, Chammas R, Palmieri O, Theodoropoulos GE, Bijlsma MF, Basso D, Mohelnikova-Duchonova B, Soucek P, Izbicki JR, Kiudelis V, Vanella G, Arcidiacono PG, Włodarczyk B, Hackert T, Schöttker B, Uzunoglu FG, Bambi F, Goetz M, Hlavac V, Brenner H, Perri F, Carrara S, Landi S, Hegyi P, Dijk F, Maiello E, Capretti G, Testoni SGG, Petrone MC, Stocker H, Ermini S, Archibugi L, Gentiluomo M, Cavestro GM, Pezzilli R, Di Franco G, Milanetto AC, Sperti C, Neoptolemos JP, Morelli L, Vokacova K, Pasquali C, Lawlor RT, Bazzocchi F, Kupcinskas J, Capurso G, Campa D, Canzian F.

Hum Genomics. 2024 Feb 2;18(1):12. doi: 10.1186/s40246-024-00576-x.

PMID: 38308339

https://pubmed.ncbi.nlm.nih.gov/38308339/

Treatment resistance in pancreatic and biliary tract cancer: molecular and clinical pharmacology perspectives

Toledo B, Deiana C, Scianò F, Brandi G, Marchal JA, Perán M, Giovannetti E.

Expert Rev Clin Pharmacol. 2024 Mar 15:1-25. doi: 10.1080/17512433.2024.2319340. Online ahead of print.

PMID: 38413373

https://pubmed.ncbi.nlm.nih.gov/38413373/

Spliceosomic dysregulation in pancreatic cancer uncovers splicing factors PRPF8 and RBMX as novel candidate actionable targets

Alors-Pérez E, Blázquez-Encinas R, Moreno-Montilla MT, García-Vioque V, Jiménez-Vacas JM, Mafficini A, González-Borja I, Luchini C, Sánchez-Hidalgo JM, Sánchez-Frías ME, Pedraza-Arevalo S, Romero-Ruiz A, Lawlor RT, Viúdez A, Gahete MD, Scarpa A, Arjona-Sánchez Á, Luque RM, Ibáñez-Costa A, Castaño JP

Mol Oncol. 2024 May 24. doi: 10.1002/1878-0261.13658. Epub ahead of print

PMID: 38790138

https://pubmed.ncbi.nlm.nih.gov/38790138/

Splicing alterations in pancreatic ductal adenocarcinoma: a new molecular landscape with translational potential

Alors-Pérez E, Pedraza-Arevalo S, Blázquez-Encinas R, Moreno-Montilla MT, García-Vioque V, Berbel I, Luque RM, Sainz B Jr, Ibáñez-Costa A, Castaño JP

J Exp Clin Cancer Res. 2023 Oct 26;42(1):282. doi: 10.1186/s13046-023-02858-z

PMID: 37880792

PMCID: PMC10601233

https://pubmed.ncbi.nlm.nih.gov/37880792/