p66Shc deletion confers apoptotic resistance to loss of EGFR-ERK signalling in neural stem cells
Bibliographic record
Abstract
Growth factor signalling, through epidermal growth factor (EGF) and its receptor (EGFR), governs neural stem cell (NSC) proliferation, differentiation, and survival. The Src Homology and Collagen (SHC1) adaptor protein mediates EGFR survival-signalling in NSCs via its two shorter isoforms. However, the role of its longest isoform, p66Shc, in NSCs remains unclear. In this study, we investigated the role of p66Shc in NSC apoptosis by generating p66Shc knockout (p66KO) NSCs and assessing their responses to EGF withdrawal, EGFR inhibition, and MEK inhibition. We found that p66KO NSCs resisted apoptosis induced by EGF deprivation and EGFR-ERK pathway inhibition. In contrast, p66KO NSCs maintained their sensitivity to staurosporine, a general apoptosis inducer. Furthermore, p66KO NSCs subjected to prolonged MEK inhibition continued to differentiate into neurons, demonstrating their ability to evade apoptosis and progress through neuronal differentiation. These findings identify p66Shc as a pivotal regulator of NSC apoptosis in response to disrupted EGFR-ERK signalling. The ability of p66KO NSCs to resist apoptosis and differentiate without EGFR-ERK signalling highlights the potential of targeting p66Shc in conditions where growth factor signalling is disrupted, such as neurodegenerative diseases or brain injuries. Additionally, the role of p66Shc in modulating survival pathways may have broader implications for NSC-like cancers, where assessing p66Shc levels could provide prognostic value for the sensitivity of cancers to EGFR- or MEK-inhibition-based chemotherapies.
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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) | 0.002 | 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".