Veterinary Genomics and Precision Medicine Forum
Welcome to the Vetomics Forum, a collaborative space for veterinary professionals to discuss and share insights on genomics and its applications in animal health.
| Forum Community | Ask and answer questions at your convenience — no scheduling needed |
| Expert Consultation | Direct access to genomic scientists and veterinary oncologists for specialized advice and treatment plans tailored to your dog’s cancer |
| Peer to Peer Collaboration | Community setting for peers to provide practical advice |
| Education Platform | Case highlights, molecular tumor board, workshops, and webinars on cases and topics relevant to our services and selected by the group |
Context Matters: How Canine CGP Outperforms in Tumor Genomic Profiling
Quote from Guannan Wang on November 19, 2024, 3:35 pmWhen comparing results across different genomic testing platforms, it’s clear that Canine CGP delivers a significantly deeper understanding of the tumor genome, and more actionability.
In this hemangiosarcoma case, Canine CGP not only detected all mutations identified by other tests, but also found many other mutations to differentiate putative truncal mutations (present in most tumor cells) from low-level oncogenic mutations (found in a smaller subset). This level of resolution is critical for identifying the key driver mutations and provide multiple lines of high-level therapeutic evidence to guide treatment decisions, including the recommendation of biomarker-stratified immune check point inhibitor, gilvetmab.
This case perfectly demonstrates why comprehensive profiling with Canine CGP offers the most accurate picture of a tumor’s genomic landscape, enabling us to target the mutations most likely to drive the disease, and respond to therapy.
It’s essential to remember that the presence of an oncogenic mutation doesn’t necessarily mean it’s the tumor’s primary driver. Mutations must be assessed within the broader genomic context—a capability uniquely enabled by Canine CGP.
Of course, the real measure of success is how the dog responds to genomic-based treatments, but it’s crucial to start with the right insights!
When comparing results across different genomic testing platforms, it’s clear that Canine CGP delivers a significantly deeper understanding of the tumor genome, and more actionability.
In this hemangiosarcoma case, Canine CGP not only detected all mutations identified by other tests, but also found many other mutations to differentiate putative truncal mutations (present in most tumor cells) from low-level oncogenic mutations (found in a smaller subset). This level of resolution is critical for identifying the key driver mutations and provide multiple lines of high-level therapeutic evidence to guide treatment decisions, including the recommendation of biomarker-stratified immune check point inhibitor, gilvetmab.
This case perfectly demonstrates why comprehensive profiling with Canine CGP offers the most accurate picture of a tumor’s genomic landscape, enabling us to target the mutations most likely to drive the disease, and respond to therapy.
It’s essential to remember that the presence of an oncogenic mutation doesn’t necessarily mean it’s the tumor’s primary driver. Mutations must be assessed within the broader genomic context—a capability uniquely enabled by Canine CGP.
Of course, the real measure of success is how the dog responds to genomic-based treatments, but it’s crucial to start with the right insights!
Quote from Brendan Boostrom on November 21, 2024, 5:42 pmThis is very exciting. As I am an interested vet but not a geneticist, you could kindly explain to me how you differentiate primary driving mutations from background or less relevant mutations in a tumor?
This is very exciting. As I am an interested vet but not a geneticist, you could kindly explain to me how you differentiate primary driving mutations from background or less relevant mutations in a tumor?
Quote from vetomicsinternal@outlook.com on March 3, 2025, 3:05 pmAhh, completely missed it. We need a tagging system 🙂
@brendan-boostrom Great question!
Identifying driver vs. passenger mutations comes down to a few key factors:
1 Recurrence across tumors/speciesA mutation frequently found in cancers or certain cancers (e.g., PIK3CA H1047R in human breast cancer & canine hemangiosarcoma), suggests a driver role. However, distinguishing true somatic, i.e. tumor-specific, mutations from germline population SNPs is crucial.
2 Functional impact prediction based on experimental evidence, or computational prediction
In vitro & in vivo functional experiments demonstrate that PIK3CA H1047R constitutively activates PI3K (p110α), increasing kinase activity and driving uncontrolled proliferation. (PMID: 16322248; PMID: 16432179). In silico predictions also help assess whether a mutation likely alters protein function.
3 Frequency of mutation in the tumor
The variant allele frequency (VAF) or the level of copy number variations matters when determining it’s driver role. For example, PIK3CA H1047R, despite being oncogenic and activating, only present in <3% of tumor cells in this tumor, suggesting it’s a minor clone rather than a primary driver, which impacts its relevance for therapy. Context within the tumor genome is key while presence alone doesn’t guarantee therapeutic response.
Understanding these factors helps prioritize mutations for biological and clinical significance!
Ahh, completely missed it. We need a tagging system 🙂
@brendan-boostrom Great question!
Identifying driver vs. passenger mutations comes down to a few key factors:
1 Recurrence across tumors/species
A mutation frequently found in cancers or certain cancers (e.g., PIK3CA H1047R in human breast cancer & canine hemangiosarcoma), suggests a driver role. However, distinguishing true somatic, i.e. tumor-specific, mutations from germline population SNPs is crucial.
2 Functional impact prediction based on experimental evidence, or computational prediction
In vitro & in vivo functional experiments demonstrate that PIK3CA H1047R constitutively activates PI3K (p110α), increasing kinase activity and driving uncontrolled proliferation. (PMID: 16322248; PMID: 16432179). In silico predictions also help assess whether a mutation likely alters protein function.
3 Frequency of mutation in the tumor
The variant allele frequency (VAF) or the level of copy number variations matters when determining it’s driver role. For example, PIK3CA H1047R, despite being oncogenic and activating, only present in <3% of tumor cells in this tumor, suggesting it’s a minor clone rather than a primary driver, which impacts its relevance for therapy. Context within the tumor genome is key while presence alone doesn’t guarantee therapeutic response.
Understanding these factors helps prioritize mutations for biological and clinical significance!