Targeting of solid tumors and blood malignancies by antibody-based therapies — EGFR-pathway as an example
Bibliographic record
Abstract
Abstract A well-coordinated interaction between extracellular signals and intracellular response forms the basis of life within multicellular organisms, with growth factors playing a crucial role in these interactions. Discoveries in recent years have shown that components of the Epidermal Growth Factor (EGF) signaling system have frequently been used by cancer cells to autonomously provide survival and proliferation signals. The main focus of this review is the ErbB epidermal growth factor receptor (EGFR) family of receptor tyrosine kinases including ErbB1/EGFR, ErbB2/HER2/neu, ErbB3/HER3, and ErbB4/HER4 as therapeutic targets. Since the ErbB receptor family regulates cell proliferation through the Ras-mitogen-activated protein kinase (RAS/MAPK) pathway, and cell survival and transformation through the phosphatidylinositol 3-kinase (PI3K/AKT) pathway, pharmacological targeting of these pathways is also discussed. We will also address the clinical studies that have been conducted to evaluate antibody-based therapies mostly on solid tumors and hematologic malignancies.
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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".