Predictive Biomarkers for Early Diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC)
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Pancreatic Ductal Adenocarcinoma (PDAC), Intraductal Papillary Mucinous Neoplasm of Pancreas, Pancreatic Intraepithelial Neoplasia. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Center list to be confirmed — check the primary protocol.
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
Pancreatic ductal adenocarcinoma (PDAC) is one of the cancers with the poorest prognosis and is often diagnosed at an advanced stage, resulting in very low 5-year survival rates. Many PDACs arise from non-invasive precursor lesions that develop over years, including pancreatic intraepithelial neoplasia (PanIN) and intraductal papillary mucinous neoplasms (IPMN). Only a minority of pancreatic cystic lesions progress to invasive carcinoma, and current clinical and radiologic criteria have limited accuracy in predicting which patients are at high risk. This observational translational study will enroll adult patients undergoing pancreatic surgical resection for suspected pancreatic neoplasm (IPMN, PanIN, or PDAC) at IRCCS "Saverio de Bellis". Residual tumor tissue not required for diagnostic purposes, and when available adjacent non-neoplastic tissue, will be collected, coded, and pseudonymized for molecular analyses. Tumor cells will be used to generate three-dimensional cultures (tumorspheres and organoids) and will undergo genomic characterization by next-generation sequencing, RNA-sequencing-based transcriptomic profiling, protein expression analyses, advanced imaging, and in-vitro drug response assays. The main goal is to identify and validate molecular biomarkers predictive of progression to PDAC, improve risk stratification of patients with pancreatic precursor lesions, and support the development of innovative precision medicine strategies.
Detailed description
Pancreatic ductal adenocarcinoma (PDAC) is currently one of the leading causes of cancer-related mortality worldwide and is characterized by late diagnosis, high biological aggressiveness, and marked resistance to systemic therapies. Epidemiologic projections indicate that, by 2030, PDAC will become the second most common cause of cancer death in Western countries, highlighting the need for improved early-diagnosis strategies and therapeutic interventions. Most PDACs arise from non-invasive precursor lesions through a multistep neoplastic transformation process. Key precursor entities include pancreatic intraepithelial neoplasia (PanIN) and mucinous cystic lesions, particularly intraductal papillary mucinous neoplasms (IPMN), which are clinically detectable by imaging, biologically heterogeneous, and associated with variable malignant potential. The widespread use of high-resolution imaging has increased incidental detection of pancreatic cysts, but only a subset of these lesions will progress to invasive carcinoma, making clinical management challenging.
In this context, the identification of reliable molecular biomarkers capable of predicting progression to invasive carcinoma is a clinical and scientific priority. This single-center, prospective observational translational study will include three arms: patients with IPMN, patients with PanIN, and patients with PDAC confirmed by histopathologic examination after pancreatic resection. Residual tissue not needed for diagnostic histopathology will be processed following standardized procedures to ensure high-quality biospecimens and full traceability. Fresh samples will be used for isolation of tumor stem-like cells and establishment of three-dimensional cultures (tumorspheres and organoids); additional material will be fixed in formalin and embedded in paraffin (FFPE) for histopathologic and immunohistochemical analyses.
Molecular analyses will comprise next-generation sequencing (NGS) to identify somatic mutations, genomic instability, tumor mutational burden (TMB), and alterations in key oncogenic genes and pathways; RNA-sequencing (RNA-seq) to characterize transcriptional programs associated with neoplastic transformation; protein expression studies by immunofluorescence, immunohistochemistry, and Western blot focusing on proliferation, apoptosis, and tumor stemness markers; advanced cellular imaging to study proliferation, survival, invasiveness, and metabolic adaptation under stress; and in-vitro pharmacologic assays to assess sensitivity of patient-derived models to inhibitors targeting the identified biomarkers. Statistical analyses will include Monte Carlo-based sample-size estimation, group comparisons using parametric and non-parametric tests, logistic regression models, ROC curve analyses, and high-dimensional bioinformatic pipelines for differential expression, clustering, and multivariate pattern recognition. The ultimate aim is to define and validate molecular signatures predictive of progression toward PDAC, correlate them with clinical and pathological features, and generate organoid models for preclinical studies in precision oncology.
Primary outcome measures
- Molecular biomarkers predictive of progression to pancreatic ductal adenocarcinoma (PDAC [Time frame: Up to 36 months from surgery]
Secondary outcome measures (3)
- Protein level validation of candidate biomarkers [Time frame: Up to 36 months from surgery]
- Association between biomarker profiles and tumor progression [Time frame: Up to 36 months]
- Establishment of patient derived organoid models for preclinical studies [Time frame: Up to 36 months]
Eligibility criteria
Inclusion criteria
- Age ≥ 18 years.
- Patients undergoing pancreatic surgical resection for suspected pancreatic neoplasm.
- Histopathologic diagnosis of intraductal papillary mucinous neoplasm (IPMN), pancreatic intraepithelial neoplasia (PanIN), or pancreatic ductal adenocarcinoma (PDAC).
- Availability of residual tumor tissue from the surgical procedure not required for diagnostic purposes.
- Signed written informed consent for the use of biological samples for research purposes
Exclusion criteria
- Age < 18 years.
- Surgical procedure performed for neoplasms other than IPMN, PanIN, or PDAC.
- Absence of written informed consent.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Observational model
- Cohort
Study locations
Center list to be confirmed — check the primary protocol.
Publications
- Marsoner K, Haybaeck J, Csengeri D, Waha JE, Schagerl J, Langeder R, Mischinger HJ, Kornprat P. Pancreatic resection for intraductal papillary mucinous neoplasm- a thirteen-year single center experience. BMC Cancer. 2016 Nov 4;16(1):844. doi: 10.1186/s12885-016-2887-8. PMID 27809876
- Rahib L, Coffin T, Kenner B. Factors Driving Pancreatic Cancer Survival Rates. Pancreas. 2025 Jul 1;54(6):e530-e536. doi: 10.1097/MPA.0000000000002489. PMID 40245290
- Muraki T, Jang KT, Reid MD, Pehlivanoglu B, Memis B, Basturk O, Mittal P, Kooby D, Maithel SK, Sarmiento JM, Christians K, Tsai S, Evans D, Adsay V. Pancreatic ductal adenocarcinomas associated with intraductal papillary mucinous neoplasms (IPMNs) versus pseudo-IPMNs: relative frequency, clinicopathologic characteristics and differential diagnosis. Mod Pathol. 2022 Jan;35(1):96-105. doi: 10.1038/s PMID 34518632
- Taherian M, Wang H, Wang H. Pancreatic Ductal Adenocarcinoma: Molecular Pathology and Predictive Biomarkers. Cells. 2022 Sep 29;11(19):3068. doi: 10.3390/cells11193068. PMID 36231030
- Siegel RL, Miller KD, Fuchs HE, Jemal A. Cancer statistics, 2022. CA Cancer J Clin. 2022 Jan;72(1):7-33. doi: 10.3322/caac.21708. Epub 2022 Jan 12. PMID 35020204
Identifiers
NCT: NCT07709052 · RC 2025 - PDAC