Evidence map›Paper›PMID 40506464›Full record

ArticleNPJ precision oncology2025

Identification of novel genetic mutations for the treatment prognostication of canine lymphoma.

Josephine Tsang, Qi Jing Yap, Sheena Kapoor, Jerry Cromarty, Sushmita Sen, Minji Kim, George Courcoubetis, Suhyeon Cho, Deanna Swartzfager, Stanley Park and 3 more

Abstract read
In one paragraph

Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Josephine TsangImpriMed, Inc., Mountain View, CA, USA.
Qi Jing YapImpriMed, Inc., Mountain View, CA, USA.
Sheena KapoorImpriMed, Inc., Mountain View, CA, USA.
Jerry CromartyImpriMed, Inc., Mountain View, CA, USA.
Sushmita SenImpriMed, Inc., Mountain View, CA, USA.
Minji Kim *ImpriMedKorea, Inc., Seoul, Republic of Korea.
George Courcoubetis *ImpriMed, Inc., Mountain View, CA, USA.
Suhyeon ChoImpriMed, Inc., Mountain View, CA, USA.
Deanna SwartzfagerImpriMed, Inc., Mountain View, CA, USA.
Stanley ParkImpriMed, Inc., Mountain View, CA, USA.
Sungwon LimImpriMed, Inc., Mountain View, CA, USA.
Ilona HolcombImpriMed, Inc., Mountain View, CA, USA. iholcomb@imprimedicine.com.
Jamin KooImpriMed, Inc., Mountain View, CA, USA. jaminkoo@alumni.stanford.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Canine lymphoma, a phenotypically and genetically heterogeneous disease, represents a significant proportion of canine cancers. We present a large-scale study of 238 dogs with lymphoma to better understand the genetic landscape of canine lymphoma, as well as the relationship to clinical outcomes. Using a targeted next-generation sequencing panel comprising 308 genes, we screened somatic and germline mutations in matched tumor and normal samples. Our findings revealed key associations between genetic alterations and lymphoma subtypes, with certain somatic variants linked to significant differences in response to common chemotherapy regimens. Recurrent mutations in genes such as KMT2C, KMT2D, NOTCH2, TRAF3, CCND1, ARID1A, CREBBP, and TP53 were observed, with TRAF3 mutations standing out for their significant association with prolonged progression-free survival and overall survival in B-cell lymphomas. In contrast, mutations in PIK3CD and CREBBP were associated with inferior outcomes in T-cell lymphomas, highlighting the immunophenotype-specific impact of genetic alterations on treatment responses. These findings support the integration of comprehensive genomic profiling in planning treatment strategies and optimizing clinical outcomes in canine lymphomas.

Identifiers

PMID40506464
PMCPMC12162864

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.