Solving the genetic aetiology of hereditary gastrointestinal tumour syndromes- a collaborative multicentre endeavour within the project Solve-RD

Sommer, Anna K.; Te Paske, Iris B.A.W.; Garcia-Pelaez, José; Laner, Andreas; Holinski-Feder, Elke; Steinke-Lange, Verena; Peters, Sophia; Valle, Laura; Spier, Isabel; Huntsman, David; Solve-RD-GENTURIS group; Oliveira, Carla; de Voer, Richarda M.; Hoogerbrugge, Nicoline; Aretz, Stefan

doi:http://dx.doi.org/10.1016/j.ejmg.2022.104475

Solving the genetic aetiology of hereditary gastrointestinal tumour syndromes- a collaborative multicentre endeavour within the project Solve-RD

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Sommer AK, Te Paske IBAW, Garcia-Pelaez J, Laner A, Holinski-Feder E, Steinke-Lange V, Peters S, Valle L, Spier I, Huntsman D; Solve-RD-GENTURIS group, Oliveira C, de Voer RM, Hoogerbrugge N, Aretz S. Solving the genetic aetiology of hereditary gastrointestinal tumour syndromes- a collaborative multicentre endeavour within the project Solve-RD. Eur J Med Genet. 2022 May;65(5):104475. DOI: 10.1016/j.ejmg.2022.104475

Abstract

Background: Patients and families with suspected, but genetically unexplained (unsolved) genetic tumour risk syndromes lack appropriate treatment and prevention, leading to preventable morbidity and mortality. To tackle this problem, patients from the European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS) are analysed in the European Commission's research project "Solving the unsolved rare diseases" (Solve-RD). The aim is to uncover known and novel cancer predisposing genes by reanalysing available whole-exome sequencing (WES) data of large cohorts in a combined manner, and applying a multidimensional omics approach. Approach: Around 500 genetically unsolved cases with suspected hereditary gastrointestinal tumour syndromes (polyposis, early-onset/familial colorectal cancer and gastric cancer) from multiple European centres are aimed to be included. Currently, clinical and germline WES data from 294 cases have been analysed. In addition, an extensive molecular profiling of gastrointestinal tumours from these patients is planned and deep learning techniques will be applied. The ambitious, multidisciplinary project is accompanied by a number of methodical, technical, and logistic challenges, which require the development and implementation of new analysis tools, the standardisation of bioinformatics pipelines, and strategies to exchange data and knowledge. Results: and Outlook. The first re-analysis of 229 known and proposed cancer predisposition genes allowed solving 2-3% of previously unsolved GENTURIS cases. The integration of expert knowledge and new technologies will help to identify the genetic basis of additional unsolved cases within the ongoing project. The ERN GENTURIS approach might serve as a model for other genomic initiatives.