The molecular mechanism and therapeutic landscape of copper and cuproptosis in cancer
Bibliographic record
Abstract
Copper, an essential micronutrient, plays significant roles in numerous biological functions. Recent studies have identified imbalances in copper homeostasis across various cancers, along with the emergence of cuproptosis, a novel copper-dependent form of cell death that is crucial for tumor suppression and therapeutic resistance. As a result, manipulating copper levels has garnered increasing interest as an innovative approach to cancer therapy. In this review, we first delineate copper homeostasis at both cellular and systemic levels, clarifying copper's protumorigenic and antitumorigenic functions in cancer. We then outline the key milestones and molecular mechanisms of cuproptosis, including both mitochondria-dependent and independent pathways. Next, we explore the roles of cuproptosis in cancer biology, as well as the interactions mediated by cuproptosis between cancer cells and the immune system. We also summarize emerging therapeutic opportunities targeting copper and discuss the clinical associations of cuproptosis-related genes. Finally, we examine potential biomarkers for cuproptosis and put forward the existing challenges and future prospects for leveraging cuproptosis in cancer therapy. Overall, this review enhances our understanding of the molecular mechanisms and therapeutic landscape of copper and cuproptosis in cancer, highlighting the potential of copper- or cuproptosis-based therapies for cancer treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".