The Role of BNIP3 in Proliferation and Hypoxia-Induced Autophagy: Implications for Cancer Therapy
Bibliographic record
Abstract
INTRODUCTION: Autophagy is a regulated degradation pathway functioning in both cell survival and cell death. Its role in cancer is controversial since autophagy can be protective or destructive to tumor cells, depending on individual genetic signatures, stage of malignancy and treatment conditions. Hypoxia is a common feature of solid tumors, correlating with poor prognosis and chemoresistance. We have investigated autophagy in hypoxic cancer cells and examined the role of the hypoxia-inducible protein, BNIP3. METHODS: Multiple cancer cell lines were exposed to chronic hypoxia (<1% O2) in the presence or absence of specific inhibitors for autophagy and apoptosis. Cell death was measured by membrane permeability assay, and autophagy was assayed by GFP-LC3 distribution, LC3 processing, electron microscopy, and acidic vacuole formation. BNIP3 was over-expressed by transient transfection, stably induced in a tetracycline-regulated expression system, or knocked down using siRNA. Whole brain morphology, cell proliferation, and hypoxic response were additionally studied in a BNIP3-null mouse model. RESULTS: Autophagic cell death was detected in hypoxic cancer cells, occurring independent of apoptosis through a mechanism involving BNIP3. BNIP3 itself induced autophagic cell death, and loss of BNIP3 protected against hypoxia-induced autophagy and cell death. Loss of BNIP3 also resulted in differential growth and cell cycle progression in vitro, and increased brain cellularity in vivo compared to wild type controls. Potential mediators of resistance to BNIP3-induced cell death were identified using a novel model of BNIP3 resistance. CONCLUSIONS: Taken together, these results support the emerging theory that autophagy represents an alternative cell death pathway that could be targeted in hypoxic and/or apoptosis-resistant tumors. We have specifically identified BNIP3 as a potential target molecule in this pathway. Finally, we have identified a possibly novel role for BNIP3 in brain development and cell cycle regulation. These findings have important clinical applications given the potential for personalized cancer therapy based on individual tumor characteristics including autophagic capacity, hypoxic status, and BNIP3 activity.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".