Pancreatic cancer is widely considered to be lethal malignancy with incidence increase of1,23 fold
in the last 6 years (2010-2016)(1, 2), number of pancreatic cancer deaths
is estimated to overpass Colorectal and breast cancer deaths by the year 2030 (3).Therefore; Emerged the urgent need
for new treatment approaches and also pre-clinical validation tools for such a breakthrough. A system modelling
the development and biology of pancreatic carcinoma is needed, multiple methods
have been tested and all led to valuable clinical insights: Monolayer cell
lines(4), Genetically engineered murine model(5) ,Xenograft(6) and three dimensional cultures (7).
Recently Organotypic models have been introduced as system
replicating the complex 3D organization of Pancreatic adenocarcinoma(PDA) using
Matrigel (8, 9). However, only limited trials to test
therapeutic approaches using Pancreatic organoids(10) compared to comprehensive model of Intestinal
and colonic organoids(11).
We propose to investigate retrospectively the ability of pancreatic
organoid model to predict therapeutic outcome using survival assays: gamma H2ax,
Apoptosis and Colony forming assay (CFA) to detect Patients radiation resistance
and correlate it to the available clinical outcome dataset of organoids source
patients as we hypotheses that tested Pancreatic organoid radiation therapy sensitivity/resistance
will have a good correlation to actual tumour response/progression. If such a study
were successful for Pancreatic cancer, then a prospective trial should follow on
the way to identify the personalized optimal treatment.
The Proposed work will be done as a master thesis project for
6 months (May-November 2018) and targeting to test 10-22 patient’s organoids sample
in a cooperation with Internal medicine department, Klinikum rechts der Isar, Technical
University of Munich where a living Organoids Bio Bank from Pancreatic cancer patient
is already established using fine needle aspirations (FNS) or resected
pancreatic tissue and is planned to be a part of academic research paper.