Nuclear localisation of nuclear factor-kappaB transcription factors in prostate cancer: an immunohistochemical study
Bibliographic record
Abstract
Several reports suggest that the canonical nuclear factor-kappaB (NF-kappaB) pathway is constitutively activated in a subset of prostate cancer cells. However, except for RelA (p65), little is known about the status of NF-kappaB transcription factors in prostate cancer tissues. To clarify the status of NF-kappaB subunits, we analysed the expression and subcellular localisation of RelA, RelB, c-Rel, p50, and p52 on tissue array sections containing respectively 344, 346, 369, 343, and 344 cores from 75 patients. The subcellular localisation of NF-kappaB factors was tested against relevant clinical parameters (preoperative prostate-specific antigen, pathological stage, and postoperative Gleason grade). With the exception of c-Rel, each subunit was detected in the nucleus of cancer cells: significant nuclear expression of RelB, RelA, p52, and p50 was seen in 26.6, 15.6, 10.7, and 10.5% of cores, respectively. Surprisingly, cores expressing both nuclear RelA and p50 canonical pathway proteins were less frequently observed than cores expressing other subunit combinations such as RelB-p52 and RelA-RelB. In addition, the nuclear localisation of RelB correlated with patient's Gleason scores (Spearman correlation: 0.167; P=0.018). The nuclear localisation of both canonical and noncanonical NF-kappaB subunits in prostate cancer cells suggests for the first time that different NF-kappaB pathways and dimers may be activated in the progression of the disease.
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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 | 0.000 |
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".