HIF-1α mRNA and protein upregulation involves Rho GTPase expression during hypoxia in renal cell carcinoma
Bibliographic record
Abstract
The small G proteins of the Rho family are involved in reorganization of the actin cytoskeleton, cell migration and in the regulation of gene transcription. Hypoxia-induced ATP depletion results in the disruption of actin organization which could affect Rho functions. In solid tumors, regions with low oxygen tension stimulate angiogenesis in order to increase oxygen and nutrient supply. This process is mediated by stabilization of the transcriptional factor hypoxia inducible factor 1 (HIF-1), which increases vascular endothelial growth factor (VEGF) production. In this study, we investigated the activities of Rho proteins, which are key regulators of cytoskeleton organization during hypoxia in renal cell carcinoma. Caki-1 cells were exposed to hypoxia (1% O2) and exhibited increased Cdc42, Rac1 and RhoA protein expression. Immunoprecipitation of metabolically labelled RhoA showed that overexpression was at least due to neo-synthesis. The Rho GTPases overexpressed during hypoxia were mainly located at membranes and pull-down assays demonstrated that they were active since they bound GTP. RT-PCR analysis indicated that the increase in RhoA protein expression was also reflected at the mRNA level. Overexpression and activation of Rho proteins were downstream of, and dependent on, the production of reactive oxygen species (ROS) since, in the presence of an inhibitor, both the rise of ROS and upregulation of Rho proteins were abolished. Importantly, preincubation of cells with the toxin C3, which inhibits RhoA, reduced HIF-1alpha protein accumulation by 84% during hypoxia. Together, these results support a model where ROS upregulate Rho protein expression and where active RhoA is required for HIF-1alpha accumulation during hypoxia.
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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".