Longitudinal Study of Transcriptomic Changes Occurring over Six Weeks of CHOP Treatment in Canine Lymphoma Identifies Prognostic Subtypes
Bibliographic record
Abstract
The majority of canine lymphoma patients treated with the standard of care, the CHOP chemotherapy protocol, initially achieve remission but eventually relapse with a multi-drug-resistant phenotype. This study assesses gene expression profiles of canine lymphoma tumor cell populations using RNA-Seq data from 15 matched patient samples taken prior to treatment and again six weeks into treatment with CHOP. Two distinct clusters were present in the t-SNE dimensionality reduction of the gene expression profiles. There was a significant difference in progression-free survival (PFS) between the cluster groups, with a median of 43.5 days in a group of six patients and 185 days in another group of nine patients. Comparing the group with shorter PFS to the group with longer PFS, we identified 265 significantly enriched GO:BP terms in 3874 significantly up-regulated genes and 740 significantly enriched GO:BP terms in 3236 significantly down-regulated genes. Comparing the six-week timepoint against the initial timepoint, in the group with longer PFS, we identified 277 significantly enriched GO:BP terms in 413 significantly up-regulated genes and 222 significantly enriched GO:BP terms in 267 significantly down-regulated genes. In the group with shorter PFS, we only identified 27 significantly differentially expressed genes, for this comparison. We found DNA damage response genes to be enriched in the down-regulated genes in both comparisons. These results identify and characterize two transcriptionally distinct groups of canine lymphoma patients with significantly different responses to CHOP chemotherapy.
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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 | 0.000 | 0.001 |
| 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".