Reduced Expression of Hypoxia-Inducible Factor-1α in Perinecrotic Regions of Solid Tumors
Bibliographic record
Abstract
Hypoxia that develops in solid tumors stabilizes the hypoxia-inducible factor-1alpha (HIF-1alpha) subunit of the HIF-1 transcription factor, leading to up-regulation of dozens of hypoxia-regulated genes that increase glycolysis and oxygen delivery. HIF-1alpha and its downstream target gene CA9 have both been used as surrogate hypoxia markers, and, in general, high expression predicts for a poor response to treatment. Combinations of hypoxia markers offer the opportunity to measure changes in tumor oxygenation that may be relevant to tumor response to treatment. We compared the degree of colocalization of two endogenous markers for hypoxia, HIF-1alpha and carbonic anhydrase IX (CAIX), with a chemical marker for hypoxia, pimonidazole. Unexpectedly, expression of HIF-1alpha was reduced in the most hypoxic regions that border necrosis in xenograft tumors composed of SiHa cervical carcinoma, WiDr colon carcinoma, or M006 astrocytoma cells. Similar results were obtained for samples from three cervical cancer biopsies. However, CAIX was present in these perinecrotic cells that were also capable of metabolizing and binding a chemical marker for hypoxia, pimonidazole. In vitro experiments using tumor cells and tumor cubes incubated under anoxic conditions indicated that nutrient deprivation seems to be largely responsible for the lack of HIF-1alpha expression in perinecrotic regions. The half-life of CAIX was sufficiently long that, once formed, it remained for days in the absence of continued HIF-1alpha expression. These results have implications for the use of HIF-1alpha as an indicator of tumor hypoxia and aggressiveness as well as development of hypoxia-directed antitumor therapies based on the expression of HIF-1alpha.
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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".