Abstract A10: Oncogenomic analysis of IGF-IR driven mammary tumors identifies a potential cell of origin and mechanisms of tumor recurrence
Bibliographic record
Abstract
Abstract Genetically engineered mice are valuable tools for understanding the genetic events that contribute to breast cancer development and progression. We have previously generated a doxycycline (Dox) inducible model of breast cancer, MTB-IGFIR, in which overexpression of the human type-I IGF receptor (IGF-IR) leads to the rapid induction of ER-mammary tumors with mixed luminal and basal features. Following Dox withdrawal and subsequent transgene downregulation, a subset of tumors escape IGF-IR dependence and spontaneously recur with evidence of an epithelial-mesenchymal transition (EMT). To gain insight into the molecular pathways that drive primary and recurrent tumor growth in MTB-IGFIR mice, we carried out gene expression profiling and DNA copy number analysis. Gene-set enrichment analysis (GSEA) revealed expression of an Akt oncogenic signature in primary tumors, consistent with downstream signaling mediated by IGF-IR. Interestingly, primary tumors also expressed a luminal progenitor gene signature suggesting a potential cell of origin. Accordingly, flow cytometric analysis of Dox-pulsed mice showed that high expression of the IGF-IR transgene was confined to EpCAM+/high Sca-1− cells, a putative ER- alveolar progenitor population. Recurrent tumors were found to express a mammary stem cell (MaSC) gene signature, which is consistent with their more mesenchymal phenotype as well as increased cell cycle pathway activity. While aCGH analysis identified few genomic changes in primary tumors, recurrent tumors exhibited gains and losses in known oncogenes and tumor suppressors including MET receptor, YAP1 and p16Ink4a/p19ARF. Integration of mRNA and copy number data confirmed altered expression of these genes at the transcriptional level. Taken together, these results suggest IGF-IR drives tumor initiation in an ER- luminal progenitor cell population in part through activation of the Akt pathway and that multiple genetic alterations contribute to the acquisition of oncogene independence and tumor relapse. Citation Format: Robert A. Jones, Craig I. Campbell, Katrina L. Watson, Roger A. Moorehead. Oncogenomic analysis of IGF-IR driven mammary tumors identifies a potential cell of origin and mechanisms of tumor recurrence. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Breast Cancer Research; Oct 17-20, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(2_Suppl):Abstract nr A10.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".