Abstract C29: Bladder cancer-associated single nucleotide polymorphisms of vascular endothelial growth factor in 12 human cell lines
Bibliographic record
Abstract
Abstract Introduction: Vascular endothelial growth factor (VEGF), critical in angiogenesis, is important for solid tumor growth and metastasis. Three single nucleotide polymorphisms (SNP) in the promoter (rs833052, rs1109324 and rs1547651) and one in the 5′-UTR regions (rs25648) of VEGF have been associated with increased risk for bladder cancer, and one at intron 2 (rs3024994) with decreased risk in a large-scale case-control study. The genotype frequency of the five bladder cancer-associated SNPs among various ethnic groups is similar based on the dbSNP and the SNP500Cancer databases. The objective of this study was to determine the presence of these variants in a panel of 12 human bladder cancer cell lines. Methods: Twelve bladder cancer cell lines, commonly used in urological research and derived from various ethnic groups, were included in the study. Genotypes of the five SNPs were determined for the12 cell lines by direct PCR sequencing. The basal VEGF secretion by these cell lines in culture was measured by ELISA using a microsphere-based array (Millipore) and Luminex® xMAP technology. Results: The SNP genotype frequency was in agreement with that reported in the databases. The only bladder cancer-associated variant (rs833052: C>A) was detected in UM-UC-3, a cell line with many other genetic alterations. The secreted VEGF level in these cell lines as determined by ELISA varied considerably. No correlation between VEGF production and any particular SNP genotype could be established. Conclusions: The reported bladder cancer associated variants in VEGF was detected in only one of the twelve cell lines. Though these SNPs are all located in the regulatory regions, it appears that they have no effect on basal VEGF production in the cultured cells. Considering the low prevalence of these variants reported, the role of these SNPs in VEGF production and bladder cancer remains to be defined. Citation Information: Mol Cancer Ther 2009;8(12 Suppl):C29.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".