Oxygen‐independent expression of <scp>HIF</scp> ‐1α during the cell cycle in hepatocellular carcinoma cells controls essential metabolic pathways under normoxia
Bibliographic record
Abstract
Intra‐tumoral oxygen deprivation (hypoxia) promotes the activation of hypoxia‐inducible factors (HIFs) that orchestrate the transcriptional adaptation of cancer cells to hypoxia. Hypoxia is prevalent in hepatocellular carcinoma (HCC), a cancer type with limited therapeutic options. In the poorly oxygenated HCC cells, the hypoxia‐inducible factor 1‐alpha (HIF‐1α) subunit is over‐expressed and correlates with poor patient outcome. To investigate the extent of HIF‐1‐mediated changes in HCC cells, we applied CRISPR/Cas9 to generate Huh7 cell lines that do not express endogenous HIF‐1α. A similarly produced HeLa HIF1A −/− line was used for comparison. Initial phenotypic analysis revealed that both HIF1Α −/− cell lines were sensitive to oxygen deprivation. However, under normoxia, only HIF1A −/− Huh7 cells showed increased death and reduced proliferation rates compared to wild‐type Huh7 cells, implying that HIF‐1α is essential for hepatocellular carcinoma cell survival irrespective of oxygen levels. To better understand this phenotype, we used liquid chromatography with tandem mass spectrometry (LC‐MS/MS) proteomic analysis, followed by pathway enrichment and validation of the expression of different proteins. Our results show that, in normoxic Huh7 cells, HIF‐1α is essential as it maintains the expression of proteins involved in glycolysis and steroid/cholesterol biosynthesis. It was also shown that only Huh7 cells exhibit a transient expression of HIF‐1α under normoxia in a cell cycle‐dependent manner. As analysis of publicly available patient data indicated that our normoxic HIF‐1 signature is correlated with poor prognosis, our results suggest that HIF‐1 is crucial in HCC cells: it mediates their metabolic phenotype under both normoxia and hypoxia, while it is also essential for sustaining cellular growth under hypoxia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".