Whole genome sequencing analysis of high confidence variants of B-cell lymphoma in Canis familiaris
Bibliographic record
Abstract
Lymphoma (lymphosarcoma) is the second most frequent cancer in dogs and is clinically comparable to human non-Hodgkin lymphoma. Factors affecting canine lymphoma progression are unknown and complex, but there is evidence that genetic mutations play an important role. We employed Next Gen DNA sequencing of six dogs with multicentric B-cell lymphoma undergoing CHOP chemotherapy to identify genetic variations potentially impacting response. Paired samples from non-neoplastic tissue (blood mononuclear cells) and lymphoma were collected at the time of diagnosis. Cases with progression free survival above the median of 231 days were grouped as 'good' responders and cases below the median were categorized as 'poor' responders. The average number of variants found was 17,138 per case. The variants were filtered to examine those with predicted moderate or high impacts. Many of the genes with variants had human orthologs with links to cancer, but the majority of variants were not previously reported in canine or human lymphoma. Seven genes had variants found in the cancers of at least two 'poor' responders but in no 'good' responders: ATRNL1, BAIAP2L2, ZNF384, ST6GALNAC5, ENSCAFG00000030179 (human ortholog: riboflavin kinase RFK), ENSCAFG00000029320, and ENSCAFG00000007370 (human ortholog: immunoglobin IGKV4-1). Two genes had variants found in the cancers of at least two 'good' responders but in no 'poor' responders: COX18 and ENSCAFG00000030512. ENSCAFG00000030512 has no reported orthologue in any other species. The role of these mutations in the progression of canine lymphoma requires further functional analyses and larger scale study.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".