4FISH-IF, a Four-Color Dual-Gene FISH Combined with p63 Immunofluorescence to Evaluate <i>NKX3.1</i> and <i>MYC</i> Status in Prostate Cancer
Bibliographic record
Abstract
NKX3.1 allelic loss and MYC amplification are common events during prostate cancer progression and have been recognized as potential prognostic factors in prostate cancer after radical prostatectomy or precision radiotherapy. We have developed a 4FISH-IF assay (a dual-gene fluorescence in situ hybridization combined with immunofluorescence) to measure both NKX3.1 and MYC status on the same slide. The 4FISH-IF assay contains four probes complementary to chromosome 8 centromere, 8p telomere, 8p21, and 8q24, as well as an antibody targeting the basal cell marker p63 visualized by immunofluorescence. The major advantages of the 4FISH-IF include the distinction between benign and malignant glands directly on the 4FISH-IF slide and the control of truncation artifact. Importantly, this specialized and innovative combined multiprobe and immunofluorescence technique can be performed on diagnostic biopsy specimens, increasing its clinical relevance. Moreover, the assay can be easily performed in a standard clinical molecular pathology laboratory. Globally, the use of 4FISH-IF decreases analytic time, increases confidence in obtained results, and maintains the tissue morphology of the diagnostic specimen.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".