Treatment decision based on organoids in gastric cancer

The estimated global incidence of gastric cancer (GC) is rising with more than 1 million new cases in 2020. In Europe, despite its advanced medical care, the overall 5-year survival rate of GC is only 26%. GC is still mainly treated with classical cytotoxic chemotherapy, and there is an urgent need to develop more efficient, individually tailored therapies for patients. In our program, we are deriving patient- derived organoids (PDOs) from biopsies to establish and guide personalised treatment and enable predicting mutations causing drug resistance. Using mini organs in a petri dish, we are modelling the patients disease and investigating clonal evolution causing a rise of therapy-resistant mutations. Even with targeted therapy, using drugs specifically selected according to the patients tumor type, treatment success is often short-lived, since the selective pressure of therapy leads to emergence of resistant tumour cells. We model those aspects with our organoids, capturing clonal evolution and escape mechanisms, all while the patient is still receiving therapy. Thus, treatment can be adjusted and fine-tuned to achieve the best possible outcome for the patient. Our multidisciplinary REDESIGN team is led by Dr. Daniel Stange from the TU Dresden. His team has already generated a large gastrointestinal PDO biobank, where every organoid faithfully recapitulates the features of the primary cancer and serves as a living avatar of the patients tumour. Dr. Bon- Kyoung Koos team at IMBA in Vienna is using organoids to understand the clonal behaviour of cells and to track and follow up arising mutations, allowing us to model treatment resistance. Dr. Steffen Rulands group at MPI in Dresden works on theoretical modelling of clonal evolution, on the analysis and modelling of next generation sequencing data. Completing our team is Dr. Mette Svendsen from the University of Copenhagen, who leads one of the biggest European social science groups investigating the ethics of personalised medicine. Current clinical trial designs do not sufficiently consider the patients. Human organoid technology is still in its infancy and has not been widely accepted yet in clinic and public. We will observe how patients are informed about trial participation and become involved in clinical decision-making. We will perform structured interviews with patients, health professionals and researchers during the trial. Through our multidisciplinary approach we will come closer to the realisation of PDO-based personalised therapy in GC, which we believe can then be translated to other gastrointestinal cancers.

Cells usually depend on signals from nearby sources to survive and grow. However, cancer cells can break free from this dependence and promote their own growth, and our study shows how this happens in stomach cancers. In a healthy stomach, support "niche" cells surrounding the tissue provide an important growth signal called WNT. We found that stomach cancer cells carrying alterations in the KRAS pathway can learn to produce their own WNT signals, especially a molecule called WNT7B. This allows the cancer to become self-sufficient and continue growing even when support from surrounding tissues is removed. To make this discovery, we combined advanced mouse genetic models, patient-derived mini-tumors (organoids), and cutting-edge genomic technologies that measure gene activity and DNA regulation in individual cells. We showed that the same mechanism is present in human stomach cancers and is particularly common in tumors with KRAS activation or high HER2 activity. Importantly, although these tumors produce their own WNT signals, they still rely on the WNT production process. Drugs that block WNT secretion were able to stop the growth of many of these tumor models. This suggests a new therapeutic opportunity for selected patients with gastric cancer. Overall, our findings improve understanding of how stomach cancer develops, reveal a previously unknown vulnerability in these tumors, and open new possibilities for more personalized cancer treatments in the future.