bioRxivCancer BiologyPreprint
The shared selection landscape of dog and human cancers
Diane P. GenereuxiD, Kate MegquieriD, Ross SwoffordiD, Jason Turner-MaieriD, Michelle E. WhiteiD, Vista SohrabiD, Christopher R. HustediD, Heather Gardner, Corrie PainteriD, Cheryl A. LondoniD, Elinor K. KarlssoniD
Abstract
Cancers in pet dogs are prevalent, progress rapidly, and closely resemble human cancers, positioning them as powerful models for precision oncology. While genetic drivers of human cancer often transcend histologic boundaries, most comparative studies have focused on matched cancer types, leaving the broader scope of genomic similarity unresolved. We performed the first exome-wide, histology-agnostic comparison of canine and human cancers, analyzing 429 dog and 14,966 human tumors across 39 types. Mutational signatures and genes under selection are widely shared between species, and cancer types are as genomically similar between species as within species, with no greater similarity within dog breeds than between breeds. Machine-learning models identify genetic features shared by dog and human tumors of different histologies, mirroring cross-histology patterns in human cancer. These findings establish dog cancer as a powerful system for genomics-informed precision oncology and support pan-cancer approaches to discover translationally relevant models beyond histologic classification.
- organism: human
- organism: mouse
- assay: whole-exome sequencing
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: machine learning (classical)
- Citations
- 1
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