Evaluation of Oligonucleotide Arrays for Sequencing of the p53 Gene in DNA from Formalin-Fixed, Paraffin-Embedded Breast Cancer Specimens
Bibliographic record
Abstract
BACKGROUND: Routine tissue processing has generated banks of paraffin-embedded tissue that could be used in retrospective cohort studies to study the molecular changes that occur during cancer development. The purpose of this study was to determine whether a p53 microarray could be used to sequence the p53 gene in DNA extracted from formalin-fixed, paraffin-embedded (FFPE) tissues. METHODS: DNA was extracted from 70 FFPE breast cancer tissue specimens. p53 was sequenced with an oligonucleotide microarray (p53 GeneChip; Affymetrix), and the results were compared with the results obtained from direct sequencing. RESULTS: DNA was extracted from 62 of 70 cases. We identified 26 mutations in 24 of the 62 cases by the p53 GeneChip. No polymorphisms were detected, and exon 4 could not be evaluated in 20 cases. There were 43 genetic alterations detected by direct sequencing in 35 of the 62 cases. These consisted of 26 polymorphisms and 17 mutations in exons or splice sites. Fifteen mutations were identified by both methods. Direct sequencing detected significantly more gene alterations (43 of 54) in DNA extracted from FFPE tissue than the p53 GeneChip (26 of 54; P = 0.018). However, if the changes in exon 4 were eliminated from this comparison, the p53 GeneChip detected 26 of 27 mutations compared with direct sequencing, which identified 16 of 27 mutations. (P = 0.016). CONCLUSIONS: A combination of oligonucleotide microarray and direct sequencing may be necessary to accurately identify p53 gene alterations in FFPE breast cancer. The p53 GeneChip cannot be used to detect exon 4 polymorphisms (codon 72) in FFPE breast cancer tissue.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".