Abstract 3459: BRCA1 controls the cell division axis and governs ploidy and phenotype in human mammary cells
Bibliographic record
Abstract
Abstract BRCA1 deficiency alters the relative proportions of progenitor cells in preneoplastic mammary tissue, and typically associates with breast cancers characterized by genomic instability and a basal-like cell phenotype. Oriented division of progenitor cells is one mechanism these cells use to maintain tissue homeostasis, and to suppress tumor formation. We now show that shRNA-mediated reduction of BRCA1 levels in non-tumorigenic and immortalized or freshly isolated, normal human mammary cells alters their plane of division with graded consequences that include the induction of aneuploidy in progeny cells, perturbation of polarity in spheroid cultures, and inhibition of clonal growth with favored expression of basal features. We also demonstrate a requirement for BRCA1 in establishing cortical asymmetry of NUMA-dynein complexes. Mutation of a single BRCA1 allele (BRCA1 185delAG/+) altered the division axis of isolated cells but their deficient spindle positioning was supervised by CDH1-positive adherens, which sustained oriented divisions and produced colonies with luminal features. These findings reveal a previously unrecognized consequence of mutant BRCA1 on the cell division axis, post-mitotic integrity and phenotype control in normal human mammary epithelial cells. Note: This abstract was not presented at the meeting. Citation Format: Zhengcheng He, Oksana Nemirovsky, Nagarajan Kannan, Connie Eaves, Christopher A. Maxwell. BRCA1 controls the cell division axis and governs ploidy and phenotype in human mammary cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3459. doi:10.1158/1538-7445.AM2017-3459
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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 | 0.000 |
| 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) | 0.007 | 0.002 |
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".