Abstract 1305: Alternative splicing of the metabolic regulator Estrogen-Related Receptor alpha (ERRα) in colon carcinogenesis
Bibliographic record
Abstract
Abstract The nuclear receptor ERRα acts principally in pair with its coactivator PGC-1α as a regulator of metabolic processes particularly in tissues subjected to high-energy demand. Besides its implication in energy metabolism and mitochondrial biogenesis, ERRα was recently associated with tumorigenesis. Increased expression of ERRα was noted in different cancerous tissues as breast, ovary and colon. Also, a new form of ERRα lacking the exon5 (ERRα Δ5) was recently identified and suggested to be a dominant negative of ERRα and interestingly to be differently expressed in normal and cancerous tissues. Since a protumorigenic role is emerging for this metabolic regulator, we investigated the role of ERRα and its spliced form ERRα β5 in colon carcinogenesis. METHODS: shRNA-mediated silencing of ERRα and overexpression of ERRα β5 were performed by lentivirus infection in DLD1 and HCT116 human colon cancer cells. The interaction between both proteins was investigated as well as their respective roles in various tumorigenic processes. RESULTS: Silencing of ERRα by shRNA reduced proliferation of DLD1 and HCT116 cells as measured by growth kinetics and growth assays in soft agar and reduced tumor formation in NUDE mice. Furthermore, FACS-scan analysis revealed that ERRα silencing delays G1-S phase transition in colon cancer cells. Differential expression of a splice variant of ERRα (ERRα Δ5) in cancer vs normal tissues would support the importance of ERRα in colorectal carcinogenesis. This is the case at least for colon tumors as cancerous samples display lower amount of ERRα β5 and higher amount of ERRα compared to adjacent normal tissues. Also, the ERRα β5 expression is surprisingly regulated by proteosomal degradation in normal and colon cancer cell lines and this could explain the low abundance of the ERRα spliced form. Interaction between both variants has been characterized by immunoprecipitation assays, confirming the conserved dimerization potential of ERRα β5 variant with ERRα. Furthermore, luciferase assays revealed that ERRα β5 is transcriptionaly inactive and its expression inhibits the transcriptional activity of ERRα on its target genes, suggesting that this variant acts as a dominant negative for ERRα. Interestingly, the reexpression of ERRα β5 in colon cancer cells reduces soft agar colony formation. CONCLUSION: Strong ERRα expression is associated with cancerous tissues and is required for the intense proliferation of colon cancer cells. Interestingly, the poorly active splice variant ERRα β5 is lost in cancerous colon tissues and has antiproliferative properties when reintroduced in colon cancer cells. Since this splice variant could interact with ERRα and inhibit its activity, ERRα β5 reduction of expression in cancerous tissue could allow ERRα to fully promote colon cancer cell proliferation. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1305. doi:1538-7445.AM2012-1305
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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) | 0.002 | 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".