Abstract 125: First report of a full spectrum of de novo induced human breast cancer subtypes generated from oncogene-transduced freshly isolated normal human mammary cells
Bibliographic record
Abstract
Abstract Human breast cancers are genetically and biologically heterogeneous with variable responses to current treatments. As an alternative strategy to identify causal and shared mechanisms, we have been exploring the utility of creating de novo models of human breast cancers from freshly isolated, purified subsets of normal human mammary cells that are lentivirally transduced with defined genes of interest and then transplanted subcutaneously in Matrigel into highly immunodeficient adult female Nonobese-diabetic/Rag1-/--IL2Rγc-/- (NRG) mice. In an initial study using this approach, we discovered that forced expression of KRASG12D alone rapidly generates small (growth-arrested), but polyclonal and serially transplantable invasive ductal carcinomas (IDCs) from both normal basal and luminal progenitor subsets of normal human mammary cells. This outcome is neither replaced nor influenced by transduction of the cells with mutant forms of TP53 or PI3KCA (Nguyen et al Nature 2015). More recently, we have found that transduction of these normal human mammary cells with a cDNA encoding a myristylated form of AKT1 (myrAKT1) produces a model of ductal carcinoma in situ (DCIS), whereas forced expression of BMI1, MYC and TP53R273C with KRASG12D (KBMT) rapidly produces large and aggressive tumors within 6 weeks post-transplant, with intermediate outcomes obtained when either MYC or TP53R273C is omitted. Immunohistochemical staining for estrogen, progesterone and epidermal growth factor receptor 2 suggests that the KBMT tumors are triple negative, and that the proportion of proliferating cells in the KBMT tumors is higher than in the tumors induced by just KRASG12D. The latter finding is consistent with the known role of BMI1 as a positive upstream regulator of proliferation via its ability to inhibit expression of p16INK4a, although the relevance of this activity in the KBMT model has yet to be established. At the opposite end of the spectrum, we have also shown that co-induced suppression of Y-Box binding protein-1 (YBX1) expression blocks the in vivo growth of KRASG12D-induced IDCs and its forced increased expression enhances the growth of myrAKT-induced DCIS cells. Taken together, these findings illustrate the advantages of creating and characterizing de novo models of human breast cancers to identify and manipulate pathways that are required for the acquisition of malignant properties. Citation Format: Susanna Tan, Sylvain Lefort, Amal El-Naggar, Davide Pellacani, Poul H. Sorensen, Connie Eaves. First report of a full spectrum of de novo induced human breast cancer subtypes generated from oncogene-transduced freshly isolated normal human mammary cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 125.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".