Samenvatting van de aanvraag

Dit item is dichtgeklapt
Dit item is opengeklapt


In contrast to more common cancer types like lung and breast cancer, tumor biology in pancreatic cancer and esophagogastric is hardly taken into account in treatment decisions. In absence of clinically validated molecular parameters, clinicians can currently only base their choice on performance status and treatment wish of the patient. Within this project, we take on the challenge to demonstrate that implementation of advanced sequencing technologies for patients depending on conventional treatments (i.e. cytotoxic drugs, in contrast to novel therapies such as immunotherapy) is feasible and cost-effective.



We have developed a 162-gene classifier that distinguishes four gene expression-based subgroups: epithelial, compound pancreatic, secretory and mesenchymal, of which especially the latter has a grim prognosis. We propose that implementation of this 162-gene classifier conveys clinical benefit for a very vulnerable patient population, in a cost-effective manner.



The study itself is a straightforward observational cohort study, without randomization or intervention. It will subject tumors from patients with pancreatic and esophagogastric cancer (resectable and metastatic) to RNA-seq, and if applicable to WGS (mesenchymal subtype) to further optimize the prediction profile and generate tailored treatment strategies.



The study will include patients with pancreatic or esophagogastric cancer in both the resectable as the metastatic setting, included through AMC and CPCT.



Primary outcome will be survival, secondary outcome will be progression free survival and quality of life, and for esophagogastric cancer also response to treatment (Mandard score).



For each group, 120 patients will be included (4x120=480). Sequencing will be performed at the HMF, using the routine pipelines based on open source tools that are widely used in the genomics research community.

Naar boven
Direct naar: InhoudDirect naar: NavigatieDirect naar: Onderkant website