NAISS 2024/5-39


NAISS Medium Compute

Principal Investigator:

Kerstin Lindblad-Toh


Uppsala universitet

Start Date:


End Date:


Primary Classification:

30107: Medical Genetics



Studies in model organisms can help elucidate the molecular mechanisms causing disease, and the dog is an excellent example as it shares many of the same environment, diseases and genes with humans. Previous studies have suggested that several canine cancers are driven by similar somatic alterations and mechanisms to the human diseases. These studies have, however, focused on large-scale alterations such as copy-number and structural changes as well as protein-coding mutations. We aim to study the role of non-coding mutations in canine and human cancers. Using the same principle as for our previous studies of 39 tumor/normal pairs from human glioblastoma patients and 146 from human medulloblastoma patients (Roy et al., 2023; Sakthikumar et al., 2020), we are now looking for non-coding constraint mutations (NCCMs) in multiple canine cancers, such as osteosarcoma (OSA) and lymphoma. These studies will implicate cancer driver genes based on changes in regulatory elements. We have generated matched tumor and normal whole-genome sequencing (WGS) data from 92 dogs with OSA and combined this with data from 24 tumor/normal pairs from a public repository. We analyzed recurrent coding mutations, copy number alterations and structural variants and found that SETD2 was significantly mutated. SETD2 is a methyltransferase gene and known tumor suppressor. To identify differentially methylated regions resulting from dysfunction of SETD2, we are comparing methylation patterns in three groups that either have no SETD2 mutations, SETD2 coding mutations or NCCMs using Oxford Nanopore Technologies sequencing. We also identified several genes enriched in NCCMs in canine osteosarcoma, several of which have previously been identified by us in human osteosarcoma. These will be studied further during the continuation of this project. For canine multicentric b-cell lymphoma we and collaborators have performed WGS of 108 tumor/normal pairs. Based on our novel data we will see if NCCMs will allow us to subcategorize the tumors on a broader scale. A total of 50 tumor normal pairs have been included in a clinical trial with multiple arms and for a subset of samples we have tumor normal WGS from both treatment naïve samples and samples taken at the time of disease relapse. While our power may not be enough, we will still try to see if coding mutations and/or NCCMs in specific genes may somehow be related to treatment outcome and tumor resistance and patient survival. For both these tumor types we will compare known and novel driver genes with those found in human samples of the same phenotypes, OSA and lymphoma, in the International Cancer Genomics Consortium’s Pancancer analyses of whole-genomes dataset which is analyzed on bianca (Campbell et al., 2020).