The Heparan Sulfate Proteoglycan <i>GPC3</i> Is a Potential Lung Tumor Suppressor
Bibliographic record
Abstract
Recently, we used gene expression profiling of lung adenocarcinoma and paired normal tissue from smokers and nonsmokers to identify genes and molecular pathways associated with cigarette smoking and lung carcinogenesis. The gene encoding Glypican 3, a glycosylphosphatidylinositol-linked heparan sulfate proteoglycan, was decreased in lung adenocarcinoma. Within nonmalignant lung, GPC3 expression was decreased in smokers compared with nonsmokers; indicating that expression is associated with cigarette smoking. Microarray results were confirmed using an independent cohort of tumors and nonmalignant lung tissues. Immunohistochemical studies localized Glypican 3 protein expression to the apical surface of lung bronchiolar epithelial cells, potential cells of origin for adenocarcinoma. Northern blot analysis demonstrated expression was absent in all tested non-small cell lung carcinoma lines. Pharmacologic treatment of lung cell lines indicated that GPC3 expression was epigenetically silenced by promoter hypermethylation. Human lung carcinoma tumor cells ectopically expressing GPC3 demonstrated increased apoptosis response when exposed to etoposide and growth inhibition when implanted in nude mice. These findings suggest that GPC3 is a candidate lung tumor suppressor gene whose expression may be regulated by exposure to cigarette smoke and functions to modulate cellular response to exogenous damage.
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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) | 0.000 | 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 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".