Deciphering regulatory non-coding variants for mendelian cancer families
Abhishek Kumar1,*, Asta Försti1,*, Nagarajan Paramasivam2,3, Matthias Schlesner2, Emily P. Slater4, Detlef K. Bartsch4 and Kari Hemminki1.*
1
Molecular Genetic Epidemiology, Deutsches Krebsforschungszentrum (DKFZ),Heidelberg, Germany
2
Division of Theoretical Bioinformatics (B080), German Cancer Research Center (DKFZ), Heidelberg, Germany 3
Medical Faculty of Heidelberg, Heidelberg University, Germany
4
Klinik für Visceral-, Thorax- und Gefäßchirurgie, Philipps-University Marburg, Marburg, Germany *Correspondence: AK -
[email protected]| AF -
[email protected]| KH -
[email protected]
Systematic analysis of germline variants from familial cancer syndromes enhances feasibilities of clinical genetic counseling for hereditary cancers. With rapid advancements in the high-throughput technologies, huge progresses have been made in deciphering the genetic basis of human cancer and several studies have unraveled genetic variants associated with cancer driving genes. At the moment, we have several familial cancer syndrome studies under way using next-generation sequencing methods for case and control samples from the same family. Herein, we take up one example of familial pancreatic cancer. Using whole genome and exome sequencing methods, we have characterized >4000 genetic variants with minor allele frequencies of 10) from Combined Annotation Dependent Depletion (CADD), we have identified a set of genetic variants which represent potentially novel predisposing variants for pancreatic cancer. However, the majority of these variants are in non-coding regions. These variants are further prioritized using in-house pipelines and the “state-of-the-art” tools such as FunSeq2, FATHMM, GWAVA, Haploreg, Oncotactor, regulomeDB, rSNPbase and frequencies in 1000 Genomes, ICGC and COSMIC data in the flanking regions of these variants. Currently, the germline non-coding variant prioritization is challenging, since all known “state-of-the-art” tools are in their infancies. However, combining several tools can be helpful in the ranking of regulatory variants. Our current strategies and results provide further direction into the characterization of such variants.
