Immunophenotyping and Mutation Analysis of Canine Intestinal T‐Cell Lymphoma: A Comparative Pathological Study of Human Enteropathy‐Associated T‐Cell Lymphoma
Bibliographic record
Abstract
Human enteropathy-associated T-cell lymphoma (EATL) is a rare primary aggressive intestinal T-cell lymphoma associated with celiac disease and is considered to be a neoplasm of intraepithelial lymphocytes (IELs) with an innate lymphoid cell (ILC)-like immunophenotype. The lack of an animal model has delayed the elucidation of its pathogenesis. In dogs, the histopathological and immunophenotypic features of intestinal large T-cell lymphoma (ILTCL) are similar to EATL; however, its cell of origin remains unclear. We herein performed detailed immunophenotyping, an RNA expression analysis of selected genes, and gene mutation analysis of 54 cases of ILTCL, including 27 with fresh frozen samples available and 21 of intestinal small T-cell lymphoma (ISTCL) in dogs. Canine ILTCL was characterised by the expression of cytotoxic granules (53/54) and frequent absence of CD4/CD8 (26/27) and T-cell receptors (14/27). The mRNA expression of CD103 (25/35) and NKp46 (15/35) was detected in ILTCL by RNA in situ hybridisation. The gene mutation analysis showed mutations in NFKBIA (ILTCL, 31/54; ISTCL, 10/21), including truncating mutations (ILTCL, 11/54; ISTCL, 3/21). Mutations in STAT3 SH2 were less frequent (ILTCL, 13/54; ISTCL, 3/21) and the hotspot JAK1 mutation of human EATL was not detected. Immunohistochemistry for p-Stat3 showed STAT3 pathway activation in ILTCL cases. These results suggest that canine ILTCL is also a neoplasm of IEL with an ILC-like immunophenotype and STAT3 pathway activation, and loss-of-function mutations in NF-κB pathway inhibitors are associated with its neoplastic changes. Therefore, canine ILTCL has potential as a valuable model for investigating the pathogenesis of EATL.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".