Soluble glypican 3 inhibits the growth of hepatocellular carcinoma <i>in vitro</i> and <i>in vivo</i>
Bibliographic record
Abstract
The heterogeneity of the molecular pathology of HCC poses a formidable obstacle to the development of non-cytotoxic therapies. Several pro-tumorigenic signaling pathways can be aberrantly activated in HCC, including those triggered by Wnts. Glypican-3 (GPC3), a membrane-bound heparan sulfate proteoglycan that is overexpressed in most HCCs, promotes the growth of these tumors by stimulating Wnt signaling. Because GPC3 binds with high affinity to Wnts, and its growth-promoting activity requires attachment to the cell membrane, we have hypothesized that a mutated GPC3 lacking the GPI anchoring domain (sGPC3) will block Wnt signaling and inhibit the growth of Wnt-dependent tumors. In addition, because sGPC3 displays heparan sulfate chains, this secreted glypican could also inhibit HCC growth by blocking the activity of other heparin-binding growth factors. To test this hypothesis, HCC cell lines were infected with an sGPC3-expressing lentivirus or virus control, and the effect of sGPC3 on the in vitro and in vivo growth was investigated. In addition, the signaling pathways targeted by sGPC3 were identified. We observed that sGPC3-expressing cells had lower proliferation rate. In addition, sGPC3 significantly inhibited the in vivo growth of the Huh6, HepG2 and Huh7 HCC cell lines. sGPC3 blocked Wnt signaling in Huh6- and Huh7-derived tumors and Erk1/2 and Akt phosphorylation in tumors generated by Huh7 and HepG2 cells, respectively. An anti-angiogenic effect in Huh7 and HepG2-derived tumors was also observed. We conclude that sGPC3 can inhibit HCC tumorigenicity by blocking the activity of several pro-tumorigenic growth factors.
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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) | 0.001 | 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".