Loss of <i>Phosphatase and Tensin Homologue Deleted on Chromosome 10</i> Engages ErbB3 and Insulin-Like Growth Factor-I Receptor Signaling to Promote Antiestrogen Resistance in Breast Cancer
Bibliographic record
Abstract
Knockdown of the tumor suppressor phosphatase Phosphatase and tensin homologue deleted on chromosome 10 (PTEN) with shRNA in three estrogen receptor (ER)-positive breast cancer cell lines resulted in increased phosphatidylinositol-3 kinase (PI3K) and AKT activities, resistance to tamoxifen and fulvestrant, and hormone-independent growth. PTEN knockdown induced the up-regulation of ER transcriptional activity in MCF-7 cells but decreased ER protein levels and transcriptional activity in T47D and MDA-361 cells. Tamoxifen and fulvestrant treatment inhibited estradiol-induced ER transcriptional activity in all shPTEN cell lines but did not abrogate the increased cell proliferation induced by PTEN knockdown. PTEN knockdown increased basal and ligand-induced activation of the insulin-like growth factor-I (IGF-I) and ErbB3 receptor tyrosine kinases, and prolonged the association of the p85 PI3K subunit with the IGF-I receptor (IGF-IR) effector insulin receptor substrate-1 and with ErbB3, implicating PTEN in the modulation of signaling upstream of PI3K. Consistent with these data, PTEN levels inversely correlated with levels of tyrosine-phosphorylated IGF-IR in tissue lysate arrays of primary breast cancers. Inhibition of IGF-IR and/or ErbB2-mediated activation of ErbB3 with tyrosine kinase inhibitors restored hormone dependence and the growth inhibitory effect of tamoxifen and fulvestrant on shPTEN cells, suggesting that cotargeting both ER and receptor tyrosine kinase pathways holds promise for the treatment of patients with ER+, PTEN-deficient breast cancers.
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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) | 0.001 | 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".