Post-transcriptional regulation of MRE11 expression in muscle-invasive bladder tumours
Bibliographic record
Abstract
// Rebecca M. Martin 1 , Martin Kerr 1 , Mark T.W. Teo 2 , Sarah J. Jevons 1 , Marianne Koritzinsky 3 , Bradly G. Wouters 3 , Selina Bhattarai 4 , Anne E. Kiltie 1 1 Gray Institute for Radiation Oncology and Biology, Department of Oncology, University of Oxford, Oxford, UK 2 Section of Epidemiology and Biostatistics, Leeds Institute of Cancer and Pathology, Leeds, UK 3 Princess Margaret Cancer Centre, University Health Network, Toronto, Canada and Department of Radiation Oncology, University of Toronto, Toronto, Canada 4 Department of Histopathology and Molecular Pathology, St James’s University Hospital, Leeds, UK Correspondence: Anne E Kiltie, email: // Key words : MRE11, bladder cancer, post-transcriptional regulation, microRNA, miR-153, protein stability Received : November 25, 2013 Accepted : January 14, 2014 Published : January 14, 2014 Abstract Predictive assays are needed to help optimise treatment in muscle-invasive bladder cancer, where patients can be treated by either cystectomy or radical radiotherapy. Our finding that low tumour MRE11 expression is predictive of poor response to radiotherapy but not cystectomy was recently independently validated. Here we investigated further the mechanism underlying low MRE11 expression seen in poorly-responding patients. MRE11 RNA and protein levels were measured in 88 bladder tumour patient samples, by real-time PCR and immunohistochemistry respectively, and a panel of eight bladder cancer cell lines was screened for MRE11, RAD50 and NBS1 mRNA and protein expression. There was no correlation between bladder tumour MRE11 protein and RNA scores (Spearman’s rho 0.064, p=0.65), suggesting MRE11 is controlled post-transcriptionally, a pattern confirmed in eight bladder cancer cell lines. In contrast, NBS1 and RAD50 mRNA and protein levels were correlated (p=0.01 and p=0.03, respectively), suggesting primary regulation at the level of transcription. MRE11 protein levels were correlated with NBS1 and RAD50 mRNA and protein levels, implicating MRN complex formation as an important determinant of MRE11 expression, driven by RAD50 and NBS1 expression. Our findings of the post-transcriptional nature of the control of MRE11 imply that any predictive assays used in patients need to be performed at the protein level rather than the mRNA level.
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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 | 0.001 |
| 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 | 0.001 | 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".