Clinical Research Directory

A Multicenter, Prospective Blood Collection Study in a Kidney Transplant Population

The purpose of this research is to collect blood samples and data from kidney transplant patients. The samples and data will be used for research and development of non-invasive test to detect donor-derived cell-free DNA (dd-cfDNA) in kidney transplant patients to evaluate the status of the transplanted organ.

Integrating Tumor Genomics and Urinary Exosomal Proteomics to Establish a Multi-Layer Biomarker Framework for Early Risk Stratification and Post-Treatment Surveillance in Fresh Thyroid Cancer Patients

Thyroid cancer is the most common endocrine malignancy, and although differentiated thyroid cancer (DTC) generally confers favorable outcomes, 10-20% of patients still face substantial postoperative risks, including local recurrence, distant metastasis, and inadequate response to radioactive iodine therapy. Current risk stratification, largely based on tumor size, lymph node involvement, and histopathology, fails to adequately represent tumor heterogeneity and evolutionary changes, potentially resulting in both overtreatment and undertreatment. Next-generation sequencing (NGS) has revealed a stepwise accumulation of genomic alterations from early driver mutations (e.g., BRAF, RAS, RET/PTC, PAX8-PPARG) to late-stage progression events (e.g., TERT promoter, TP53, PI3K/AKT/mTOR), while metastatic lesions often harbor high-risk mutations absent in primary tumors, underscoring the limitations of single-time-point tissue sampling. Furthermore, serum thyroglobulin (Tg) surveillance is hindered in patients with anti-Tg antibodies. Extracellular vesicles (EVs), particularly those obtained from urine, provide a compelling liquid biopsy modality due to their non-invasiveness, repeatability, and reduced interference by abundant serum proteins. The investigators' previous findings demonstrate that urinary exosomal peptides-including U-Ex Tg, ANXA2, TIMP, and Angiopoietin-1-correlate with malignancy, capsular invasion, and nodal metastasis, and exhibit dynamic postoperative variation, suggesting their utility in detecting molecular residual disease. This prospective study will recruit 100 fresh thyroid cancer cases and integrate tumor genomic profiling, urinary exosomal proteomics via LC-MRM/MS, and clinical phenotype assessment-including nodal involvement, subsequent therapies, and long-term outcomes-to delineate causal links between genomic drivers, proteomic execution signals, and clinical progression. The overarching aim is to establish an early risk-stratification and molecular recurrence-alerting model capable of identifying high-risk trajectories earlier than conventional approaches, thereby enhancing surveillance precision and enabling timely intervention. This multi-layered biomarker framework holds strong potential to redefine postoperative monitoring standards and advance the clinical and policy implementation of precision medicine in thyroid cancer.

Performance Indicators and Impact on the Care Pathway of Sequencing on the SeqOIA and AURAGEN (Seqogen) Platforms for Oncology Patients

As part of the French Genomic Medicine Plan 2025 (FGM), the SeqOIA and AURAGEN platforms were selected to perform high-throughput genomic sequencing. The SONCO (Sequencing Oncology Cohort) project combines their medical and economic evaluations into a single national cohort. Its objective is to assess the impact of genomic sequencing on care pathways and treatment recommendations by collecting indicators related to quality, turnaround time, and patient information. Clinical data are gathered from molecular tumor board reports (via SPICE and HYGEN) and from hospital medical records. This cohort is intended to support public health decision-making and help anticipate the organization of future genomic platforms.

Primary Resistance Mechanisms of ALK TKIs

Anaplastic lymphoma kinase (ALK) gene rearrangement is a known oncogenic driver in non-small cell lung cancer (NSCLC). ALK tyrosine kinase inhibitors (TKIs) have been clearly shown to produce excellent therapeutic effects and prolong survival in patients with this gene mutation. According to current treatment guidelines, ALK inhibitors are the first-line treatment of choice for ALK-positive advanced NSCLC patients. However, although ALK TKIs are very effective, there is still a small group of patients who do not achieve good treatment outcomes, developing resistance and tumor progression within 3 to 6 months of initial ALK TKI use. This is called primary resistance. Intrinsic resistance to ALK inhibition occurs when the best clinical response after first-generation and second/third-generation TKI treatment is disease progression. Approximately 5-7% of cases after crizotinib treatment, 9% after ceritinib treatment, and 25% after lorlatinib treatment show no response to treatment, and no specific ALK mutation has been found to explain the occurrence of primary resistance. Currently, many different resistance mechanisms are known, some of which are still ALK-related, while others are ALK-independent alternative survival pathways. However, most research focuses on acquired resistance, with very few studies on primary resistance, only a few case reports. Therefore, this study aims to explore the primary ALK TKI resistance mechanisms. The investigators plan to explore the incidence and mechanisms of primary ALK TKI resistance in ALK-positive advanced NSCLC patients who develop primary resistance or rapid progression (within 3-6 months) during ALK inhibitor treatment by re-obtaining tumor samples for genetic analysis.

Diagnostic Value of Next-Generation Sequencing Analysis in Biliary Tract Tumours

The aim of this study is to identify a dysplasia- and CCA-specific NGS panel to increase the diagnostic sensitivity of histological and/or cytological examination of biliary tract stenosis.

TORNADO-Omics Techniques and Neural Networks for the Development of Predictive Risk Models

The goal of this observational study is to define a personalized risk model in the super healthy and homogeneous population of Italian Air Force high-performance pilots. This peculiar cohort conducts dynamic activities in an extreme environment, compared to a population of military people not involved in flight activity. The study integrates the analyses of biological samples (urine, blood, and saliva), clinical records, and occupational data collected at different time points and analyzed by omic-based approaches supported by Artificial Intelligence. Data resulting from the study will clarify many etiopathological mechanisms of diseases, allowing the creation of a model of analyses that can be extended to the civilian population and patient cohorts for the potentiation of precision and preventive medicine.