Target Modulation by a Kinase Inhibitor Engineered to Induce a Tandem Blockade of the Epidermal Growth Factor Receptor (EGFR) and c-Src: The Concept of Type III Combi-Targeting
Bibliographic record
Abstract
Cancer cells are characterized by a complex network of interrelated and compensatory signaling driven by multiple kinases that reduce their sensitivity to targeted therapy. Therefore, strategies directed at inhibiting two or more kinases are required to robustly block the growth of refractory tumour cells. Here we report on a novel strategy to promote sustained inhibition of two oncogenic kinases (Kin-1 and Kin-2) by designing a molecule K1-K2, termed "combi-molecule", to induce a tandem blockade of Kin-1 and Kin-2, as an intact structure and to be further hydrolyzed to two inhibitors K1 and K2 directed at Kin-1 and Kin-2, respectively. We chose to target EGFR (Kin-1) and c-Src (Kin-2), two tyrosine kinases known to synergize to promote tumour growth and progression. Variation of K1-K2 linkers led to AL776, our first optimized EGFR-c-Src targeting prototype. Here we showed that: (a) AL776 blocked EGFR and c-Src as an intact structure using an in vitro kinase assay (IC50 EGFR = 0.12 μM and IC50 c-Src = 3 nM), (b) it could release K1 (AL621, a nanomolar EGFR inhibitor) and K2 (dasatinib, a clinically approved Abl/c-Src inhibitor) by hydrolytic cleavage both in vitro and in vivo, (c) it could robustly inhibit phosphorylation of EGFR and c-Src (0.25-1 μM) in cells, (d) it induced 2-4 fold stronger growth inhibition than gefitinib or dasatinib and apoptosis at concentrations as low as 1 μM, and, (e) blocked motility and invasion at sub-micromolar doses in the highly invasive 4T1 and MDA-MB-231 cells. Despite its size (MW = 1032), AL776 blocked phosphorylation of EGFR and c-Src in 4T1 tumours in vivo. We now term this new targeting model consisting of designing a kinase inhibitor K1-K2 to target Kin-1 and Kin-2, and to further release two inhibitors K1 and K2 of the latter kinases, "type III combi-targeting".
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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".