Abstract 2921: The retinoblastoma protein regulates hypoxia-inducible factor-1α-mediated transcriptional programs, tumor cell invasiveness, tumor growth and metastasis in human breast cancer cells
Bibliographic record
Abstract
Abstract The retinoblastoma protein (Rb) is capable of attenuating the hypoxic response in tumor cells. This process is mediated by the hypoxia inducible factor 1α/2α (HIF1α/2α) and its dimerization partner the aryl hydrocarbon receptor nuclear translocator (ARNT/ HIF1β). Rb modulates HIF activity by virtue of its association with the thyroid hormone receptor/retinoblastoma interacting protein 230 (TRIP230), an essential cofactor of the HIF1α/ARNT transcriptional complex. We used short hairpin RNA (shRNA) technology and microarray analysis to interrogate the Rb-negative and wild-type MCF7 cell transcriptomes and generated lists of genes that were either up- or downregulated in response to both loss of Rb and hypoxia. We found that loss of Rb enhances the expression of hypoxia-regulated genes involved in invasion and epithelial-to-mesenchymal transition and significantly decreases the expression of genes involved in cell anchoring and differentiation in MCF7 and MDA-MB-231 breast cancer cells. Genes were validated using both qRT-PCR and immuno-blot analysis. Additionally, gene ontology analysis revealed that AKT and ERK1/2 are downstream effectors of hypoxic gene programs that are sensitive to loss of Rb. Furthermore, these factors regulate the acquisition of a more invasive phenotype in breast cancer cells. Finally, we found that Rb knockdown in combination with pre-treatment of cells with hypoxia increased growth of tumor foci in the lungs after i.v. injection and increased the development of spontaneous metastases from orthotopically implanted breast tumor cells in female NOD-SCID mice. Primary tumors lacking Rb demonstrated enriched protein levels of genes identified in our arrays when compared to negative control tumors. These results show that Rb is a negative modulator of hypoxia-regulated genetic programs by virtue of its direct effects on the HIF-complex. Understanding the HIF complex and the molecular mechanisms controlling the progression from benign tumors to metastasized and lethal forms will allow us to develop more specific breast cancer therapies. Citation Format: Mandeep K. Takhar, Mark P. Labrecque, Kevin J. Tam, Anne Haegert, Robert H. Bell, Manuel Altamirano-Dimas, Colin C. Collins, Gratien G. Prefontaine, Michael E. Cox, Kevin L. Bennewith, Timothy V. Beischlag. The retinoblastoma protein regulates hypoxia-inducible factor-1α-mediated transcriptional programs, tumor cell invasiveness, tumor growth and metastasis in human breast cancer cells. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2921.
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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 | 0.001 |
| 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) | 0.002 | 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".