Abstract 241: Transcription factor RBP-J-mediated signaling regulates basal cell carcinoma growth
Bibliographic record
Abstract
Abstract Hair follicles (HF) and basal cell carcinomas (BCCs) can be regarded as ordered and disordered skin appendages respectively. They may utilize similar molecular mechanisms of growth. We examined the similarities and differences in gene expression between BCCs and HFs to define common and unique signaling pathways that distinguish an ordered skin appendage from a disordered skin growth. Nodular BCCs, non-follicular skin epithelium, and HF between the sebaceous gland and bulb region were microdissected and examined using microarrays. Selected genes were validated using quantitative PCR, immunohistochemistry and in vitro studies. Two differentially expressed gene sets were identified by significance analysis of microarray (SAM) in BCC and HF versus skin epithelium respectively. Subsequently, multiple signaling pathway analyses were conducted. The results indicated that Notch and Hedgehog signaling pathways were active in the growth of both HF and BCCs. However, Notch signaling, including tumor suppressor genes NOTCH1, NOTCH2, ligands JAG1, JAG2, signaling inhibitor NUMB, and downstream Notch pathway genes DTX1, DTX2, RBP-J, LFNG, HR, and HES7, all showed significant differential expression in BCCs compared to HF. The data suggests downstream gene expression in the Notch signaling pathway is suppressed in BCCs. We tested the effect of transcription factor RBP-J and found transcription factor RBP-J-mediated signaling suppresses BCC cell growth and induces cell apoptosis in vitro. Our data suggest that RBP-J serves as a tumor suppressor in BCC and BCCs deficient in RBP-J lose tumor repression activity. Modulation of the Notch pathway may be a focus for the development of BCC treatments. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 241. doi:10.1158/1538-7445.AM2011-241
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".