The putative tumor suppressor gene<i>EphA3</i>fails to demonstrate a crucial role in murine lung tumorigenesis or morphogenesis
Bibliographic record
Abstract
Treatment of non-small cell lung cancer (NSCLC) is based on histological analysis and molecular profiling of targetable driver oncogenes. Therapeutic responses are further defined by the landscape of passenger mutations, or loss of tumor suppressor genes. We report here a thorough study to address the physiological role of the putative lung cancer tumor suppressor EPH receptor A3 (EPHA3), a gene that is frequently mutated in human lung adenocarcinomas. Our data shows that homozygous or heterozygous loss of EphA3 does not alter the progression of murine adenocarcinomas that result from Kras mutation or loss of Trp53, and we detected negligible postnatal expression of EphA3 in adult wild-type lungs. Yet, EphA3 was expressed in the distal mesenchyme of developing mouse lungs, neighboring the epithelial expression of its Efna1 ligand; this is consistent with the known roles of EPH receptors in embryonic development. However, the partial loss of EphA3 leads only to subtle changes in epithelial Nkx2-1, endothelial Cd31 and mesenchymal Fgf10 RNA expression levels, and no macroscopic phenotypic effects on lung epithelial branching, mesenchymal cell proliferation, or abundance and localization of CD31-positive endothelia. The lack of a discernible lung phenotype in EphA3-null mice might indicate lack of an overt role for EPHA3 in the murine lung, or imply functional redundancy between EPHA receptors. Our study shows how biological complexity can challenge in vivo functional validation of mutations identified in sequencing efforts, and provides an incentive for the design of knock-in or conditional models to assign the role of EPHA3 mutation during lung tumorigenesis.
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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 | 0.000 |
| 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".