Oligonucleotide microarray analysis of chromosome-X gene expression in human epithelial ovarian cancer cell lines
Bibliographic record
Abstract
Microarray expression analysis was applied as an approach for identifying cancer-related genes on chromosome-X (CHR-X) in epithelial ovarian cancer (EOC). The Hu6800 and U133A GeneChipsRTM were used to evaluate the expression of 446 CHR-X genes in an in vitro EOC model system comprising 4 EOC cell lines and 12 primary cultures of normal ovary surface epithelia. Fifty-one new candidate CHR-X genes were identified in addition to 49 genes previously implicated in cancer. Many genes map to regions with frequent genetic aberrations in EOC tumours, or interact with the known EOC tumour suppressors BRCA1 and BRCA2. Candidate genes described in this study may provide novel markers for histopathological subtypes, or the tumourigenic potential of EOC tumours. The X-inactive-specific-transcript (XIST) was absent in two highly tumourigenic EOC cell lines, TOV21G and TOV112D. XIST mRNA is important for the stability of X-chromosome-inactivation (XCI), as its absence destabilizes the silencing of genes on the inactive-X. Aberrant bi-allelic expression of FHL1, a gene subjected to XCI was detected in the cell line TOV21G but not in the cell line TOV112D. Genotyping assays using polymorphic microsattelite markers suggested that TOV21G has retained heterozygosity of CHR-X. The majority of alleles tested for TOV112D were consistent with loss of heterozygosity of CHR-X. Taken together these findings are consistent with two proposed mechanisms mediating XIST loss-of-expression in cancer: (1) Duplication of the active-X followed by loss of the inactive-X (TOV112D); or (2) Reactivation of the previously inactive-X (TOV21G).
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
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".