<i>APOBEC3B</i> expression in breast cancer reflects cellular proliferation, while a deletion polymorphism is associated with immune activation
Bibliographic record
Abstract
Genomic sequencing studies of breast and other cancers have identified patterns of mutations that have been attributed to the endogenous mutator activity of APOBEC3B (A3B), a member of the AID/APOBEC family of cytidine deaminases. A3B gene expression is increased in many cancers, but its upstream drivers remain undefined. Furthermore, there exists a common germ-line deletion polymorphism (A3B(del)), which has been associated with a paradoxical increase in breast cancer risk. To examine causes and consequences of A3B expression and its constitutive absence in breast cancer, we analyzed two large clinically annotated genomic datasets [The Cancer Genome Atlas (TCGA) and the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC)]. We confirmed that A3B expression is associated with aggressive clinicopathologic characteristics and adverse outcomes and show that A3B expression is highly correlated with proliferative features (mitosis and cell cycle-related gene expression) in breast and 15 of 16 other solid tumor types. However, breast cancers arising in homozygous A3B(del) individuals with A3B absent did not differ in these features, indicating that A3B expression is a reflection rather than a direct cause of increased proliferation. Using gene set enrichment analysis (GSEA), we detected a pattern of immune activation in A3B(del) breast cancers, which seems to be related to hypermutation arising in A3B(del) carriers. Together, these results provide an explanation for A3B overexpression and its prognostic effect, giving context to additional study of this mutator as a cancer biomarker or putative drug target. In addition, although immune features of A3B(del) require additional study, these findings nominate the A3B(del) polymorphism as a potential predictor for cancer immunotherapy.
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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 | 0.002 |
| 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".