The Tyrphostin NT157 Suppresses Insulin Receptor Substrates and Augments Therapeutic Response of Prostate Cancer
Bibliographic record
Abstract
Insulin-like growth factor (IGF) signaling is associated with castrate-resistant prostate cancer (CRPC) progression. Insulin receptor substrates 1 and 2 (IRS1/2) mediate mitogenic and antiapoptotic signaling from IGF1 receptor (IGF1R), insulin receptor, and other oncoproteins. This study demonstrates that IRS1/2 expression is increased in prostate cancer, and persists in CRPC. Furthermore, this study assesses the anticancer activity of NT157, a small molecule tyrphostin targeting IRS proteins, using androgen-responsive (LNCaP) and -independent (PC3) prostate cancer cells in vitro and in vivo. NT157 treatment resulted in dose-dependent inhibition of IGF1R activation, suppression of IRS protein expression, inhibition of IGF1-induced AKT activation, but increased ERK activation in NT157-treated cells in vitro. These effects were correlated with decreased proliferation and increasing apoptosis of LNCaP cells and increasing G2-M arrest in PC3 cells. NT157 also suppressed androgen-responsive growth, delayed CRPC progression of LNCaP xenografts, and suppressed PC3 tumor growth alone and in combination with docetaxel. This study reports the first preclinical proof-of-principle data that this novel small molecule tyrosine kinase inhibitor suppresses IRS1/2 expression, delays CRPC progression, and suppresses growth of CRPC tumors in vitro and in vivo. Demonstration that IRS expression can be increased in response to a variety of stressors that may lead to resistance or reduced effect of the therapies indicate that NT157-mediated IRS1/2 downregulation is a novel therapeutic approach for management of advanced prostate cancer.
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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".