The cancer-testis antigen MAGE-A3 is a target of FGFR2 and fibronectin signaling in thyroid cancer progression
Bibliographic record
Abstract
AACR Annual Meeting-- Apr 12-16, 2008; San Diego, CA 3592 We have previously shown that members of the fibroblast growth factor receptor (FGFR) family of tyrosine kinases and the adhesion molecule fibronectin (FN) are important in thyroid cancer cell proliferation, migration, and invasion. The IIIb isoform of FGFR2 is expressed in normal human thyroid tissue and is silenced epigenetically in thyroid cancer. FN is over-expressed in well-differentiated thyroid carcinoma, but expression is reduced or lost in invasive tumor cells and in poorly differentiated and anaplastic carcinomas. Forced expression of FGFR2-IIIb results in diminished or down-regulation of tumor cell proliferation; FN inhibits cell invasion and migration while enhancing adhesion. To identify targets that mediate the action of these cell surface proteins, we performed cDNA profiling of cells that over- or under-express FGFR2-IIIb or FN. A common target gene that emerged as a potential mediator of their action is the cancer-testis antigen/melanoma associated antigen (MAGE-A3) that is reciprocally expressed with FGFR2 or FN in thyroid cancer cell lines. MAGE-A3 is expressed in primary human thyroid carcinomas but not in normal thyroid tissue. Forced MAGE-A3 expression down-regulates p21 and enhances Rb phosphorylation to promote cell cycle entry in vitro; and tumor progression and lung metastasis in mouse xenografts. FGFR2 signaling through its dedicated ligand FGF7 results in enhanced histone 3 methylation and diminished acetylation, leading to transcriptional silencing of the 5’ MAGE-A3 promoter. These findings highlight MAGE-A3 as a novel target of FGFR2 and FN action in thyroid cancer and provide new evidence for histone modifications in the control of the balance between genes of opposing functions.
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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) | 0.006 | 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".