Loss of heterozygosity and transcriptome analyses of a 1.2 Mb candidate ovarian cancer tumor suppressor locus region at 17q25.1‐q25.2
Bibliographic record
Abstract
Loss of heterozygosity (LOH) analysis was performed in epithelial ovarian cancers (EOC) to further characterize a previously identified candidate tumor suppressor gene (TSG) region encompassing D17S801 at chromosomal region 17q25.1. LOH of at least one informative marker was observed for 100 (71%) of 140 malignant EOC samples in an analysis of 6 polymorphic markers (cen-D17S1839-D17S785-D17S1817-D17S801-D17S751-D17S722-tel). The combined LOH analysis revealed a 453 kilobase (Kb) minimal region of deletion (MRD) bounded by D17S1817 and D17S751. Human and mouse genome assemblies were used to resolve marker inconsistencies in the D17S1839-D17S722 interval and identify candidates. The region contains 32 known and strongly predicted genes, 9 of which overlap the MRD. The reference genomic sequences share nearly identical gene structures and the organization of the region is highly collinear. Although, the region does not show any large internal duplications, a 1.5 Kb inverted duplicated sequence of 87% nucleotide identity was observed in a 13 Kb region surrounding D17S801. Transcriptome analysis by Affymetrix GeneChip and reverse transcription (RT)-polymerase chain reaction (PCR) methods of 3 well characterized EOC cell lines and primary cultures of normal ovarian surface epithelial (NOSE) cells was performed with 32 candidates spanning D17S1839-D17S722 interval. RT-PCR analysis of 8 known or strongly predicted genes residing in the MRD in 10 EOC samples, that exhibited LOH of the MRD, identified FLJ22341 as a strong candidate TSG. The proximal repeat sequence of D17S801 occurs 8 Kb upstream of the putative promoter region of FLJ22341. RT-PCR analysis of the EOC samples and cell lines identified DKFZP434P0316 that maps proximal to the MRD, as a candidate. While Affymetrix technology was useful for initially eliminating less promising candidates, subsequent RT-PCR analysis of well-characterized EOC samples was essential to prioritize TSG candidates for further study.
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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".