PanDa DETECT
Pankreas Daten und Biomaterial Register
Biobank for pancreatic diseases.
Despite extensive clinical trials in pancreatic cancer in all phases of the disease (screening, neoadjuvant, adjuvant and palliative), the outcome in terms of overall survival (OS) and long-term survival is unsatisfactory and has improved only marginally in recent years. PDAC is expected to be the most common tumour-associated cause of death in 2030. Since the high tumour-associated mortality results, among other things, from late diagnosis, it is also of particular importance here to achieve an improvement in early diagnosis. Biomarkers that fulfil the criteria for successful screening could offer a solution here. It is also highly relevant to be able to clearly define risk groups and offer them a screening programme.
In addition to surgical procedures for locally resectable disease, primary systemic therapies and radiato with the goal of secondary resectability are recommended for advanced, non-metastatic disease. Small molecular subgroups benefit from targeted treatment strategies, such as the PARP inhibitor olaparib in patients with BRCA1 or BRCA2 mutated pancreatic cancer who were stable on first-line platinum-based therapy. This subgroup benefits in PFS compared to the placebo group [45]. However, in contrast to other tumour entities, there are still only a few approaches to targeted therapies in PDAC. A classification of the genetically heterogeneous group into clear, therapeutically relevant molecular subgroups is not yet possible.
Biobank for pancreatic diseases.
Despite extensive clinical trials in pancreatic cancer in all phases of the disease (screening, neoadjuvant, adjuvant and palliative), the outcome in terms of overall survival (OS) and long-term survival is unsatisfactory and has improved only marginally in recent years. PDAC is expected to be the most common tumour-associated cause of death in 2030. Since the high tumour-associated mortality results, among other things, from late diagnosis, it is also of particular importance here to achieve an improvement in early diagnosis. Biomarkers that fulfil the criteria for successful screening could offer a solution here. It is also highly relevant to be able to clearly define risk groups and offer them a screening programme.
In addition to surgical procedures for locally resectable disease, primary systemic therapies and radiato with the goal of secondary resectability are recommended for advanced, non-metastatic disease. Small molecular subgroups benefit from targeted treatment strategies, such as the PARP inhibitor olaparib in patients with BRCA1 or BRCA2 mutated pancreatic cancer who were stable on first-line platinum-based therapy. This subgroup benefits in PFS compared to the placebo group [45]. However, in contrast to other tumour entities, there are still only a few approaches to targeted therapies in PDAC. A classification of the genetically heterogeneous group into clear, therapeutically relevant molecular subgroups is not yet possible.
Aims of the study
- The primary objective of the project is to establish an indefinite longitudinal cohort of patients diagnosed and enrolled prior to or after initiation of the cohort to characterise inflammatory changes and neoplasms of the pancreas, in particular pancreatic cancer and its precursors. For this purpose, a project-related biomaterial collection will be established, which includes clinical data, imaging data, liquid biopsy from blood / punctates and tumour tissue samples.
- The results from studies in this registry will help to better understand the pathogenesis of pancreatic cancer and its precursors and to validate the feasibility and specificity of emerging diagnostic and therapeutic methods.
- Although not all questions are foreseeable at the present time, the preserved samples and clinical data will primarily be available for the following questions:
- Early detection of PDAC and its precursors, development of clinically applicable algorithms.
- Definition of at-risk individuals and establishment of screening strategies
- Establishment of new biomarkers in relation to therapy response / individualised medicine
- Establishment of deep learning strategies to improve early diagnosis/prevention
