Mitochondrial complex IV defects induce metabolic and signaling perturbations that expose potential vulnerabilities in HCT116 cells
Bibliographic record
Abstract
Mutations in genes encoding cytochrome c oxidase (mitochondrial complex IV) subunits and assembly factors [e.g., synthesis of cytochrome c oxidase 2 (SCO2)] are linked to severe metabolic syndromes. Notwithstanding that SCO2 is under transcriptional control of tumor suppressor p53, the role of mitochondrial complex IV dysfunction in cancer metabolism remains obscure. Herein, we demonstrate that the loss of SCO2 in HCT116 colorectal cancer cells leads to significant metabolic and signaling perturbations. Specifically, abrogation of SCO2 increased NAD+ regenerating reactions and decreased glucose oxidation through citric acid cycle while enhancing pyruvate carboxylation. This was accompanied by a reduction in amino acid levels and the accumulation of lipid droplets. In addition, SCO2 loss resulted in hyperactivation of the insulin‐like growth factor 1 receptor (IGF1R)/AKT axis with paradoxical downregulation of mTOR signaling, which was accompanied by increased AMP‐activated kinase activity. Accordingly, abrogation of SCO2 expression appears to increase the sensitivity of cells to IGF1R and AKT, but not mTOR inhibitors. Finally, the loss of SCO2 was associated with reduced proliferation and enhanced migration of HCT116 cells. Collectively, herein we describe potential adaptive signaling and metabolic perturbations triggered by mitochondrial complex IV dysfunction.
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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".