Functional analysis of Prolyl Hydroxylase X in drug resistance
Bibliographic record
Abstract
A novel gene, named as the PHDX gene, had been previously identified while screening genes for their involvement in resistance to the chemotherapeutic drug etoposide and to hydrogen peroxide, using the methodology of retrovirus promoter trap mutagenesis. This study was undertaken for the purpose of testing whether the loss of PHDX gene is responsible for drug resistance in CHO-E-126 cell line which was created from Chinese hamster ovary cells having a retroviral receptor and selected for etoposide resistance. The PHDX gene resides on mouse chromosome 11 and has homology with the prolyl hydroxylase gene family. We hypothesized that the inactivation of the PHDX gene by promoter trap mutagenesis will confer resistance to etoposide and hydrogen peroxide in the E-126 cell line. In addition, the alteration of the cellular hydroxyproline levels by the loss of the gene might influence the drug response through the production of oxygen free radicals. To study the involvement of the PHDX gene in etoposide and hydrogen peroxide induced drug-resistance, we used two experimental approaches to modulate the function of the gene in cells. First, we silenced the expression of this gene by RNA interference (RNAi) through stable and transient knockdown experiments in the parental Chinese hamster ovary (CHO-K1)cells, and second, we overexpressed the gene in CHO-Cl-22 and CHO-E-126 cells. We assessed the effect of the knockdown by RT-PCR. The effect of etoposide and hydrogen peroxide was determined by the clonogenic crystal violet staining assay and the MTT assay. Through our siRNAi knockdown studies, we were able to demonstrate the involvement of the gene in drug resistance. We were unable to show that the overexpression of the gene was capable of reverting to the drug sensitive phenotype.
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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".