The cytoplasmic domain is critical to the tumor suppressor activity of TSLC1 in non-small cell lung cancer.
Bibliographic record
Abstract
The tumor suppressor gene in lung cancer (TSLC1) encodes a membrane glycoprotein containing extensive homology in the extracellular domain with the immunoglobulin-superfamily cell adhesion molecules. The intracellular cytoplasmic domain (CT) contains a protein 4.1 (FERM) binding motif, and a PDZ-interacting motif. Expression of TSLC1 is silenced in non-small cell lung cancer and in other cancers by promoter hypermethylation. Restoration of TSLC1 expression suppresses tumorigenicity of lung cancer cells. We report here the critical role of the FERM-binding and PDZ- interacting domains of TSLC1 in tumor suppressor activity in non-small cell lung cancer. The entire CT domain [amino acid (aa) 398-442], the FERM binding motif (aa 398-410), or the PDZ-interacting motif (aa 432-442) was deleted to generate mutants CT1, CT3, and CT4, respectively. The lung cancer cell line A549, deficient in TSLC1 expression, was stably transfected with the wild-type TSLC1 or the deletion mutants. The cell lines were then injected into athymic (nu/nu) nude mice, and tumor formation at the sites of injection was monitored. A549 cells stably transfected with the empty vector or mutant TSLC1 constructs induced tumors at the sites of injection within 10 days. In contrast, A549 cells expressing wild-type TSLC1 showed the appearance of tumors after 35 days, and the tumors grew substantially slower. A549 cells expressing wild-type TSLC1 also showed suppression of anchorage-independent colony formation in soft agar and markedly increased cell-cell adhesion activity. These results suggest that the cytoplasmic domain of TSLC1 is important in its tumor suppressor activity, and the tumor suppression activity involve protein(s) interacting with the FERM- and PDZ-interacting regions.
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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".