RANK/OPG ratio of expression in primary clear-cell renal cell carcinoma is associated with bone metastasis and prognosis in patients treated with anti-VEGFR-TKIs
Bibliographic record
Abstract
BACKGROUND: Bone metastases (BMs) are associated with poor outcome in metastatic clear-cell renal carcinoma (m-ccRCC) treated with anti-vascular endothelial growth factor tyrosine kinase inhibitors (anti-VEGFR-TKIs). We aimed to investigate whether expression in the primary tumour of genes involved in the development of BM is associated with outcome in m-ccRCC patients treated with anti-VEGFR-TKIs. METHODS: Metastatic clear-cell renal cell carcinoma patients with available fresh-frozen tumour and treated with anti-VEGFR-TKIs. Quantitative real-time PCR (qRT-PCR) for receptor activator of NF-kB (RANK), RANK-ligand (RANKL), osteoprotegerin (OPG), the proto-oncogene SRC and DKK1 (Dickkopf WNT signalling pathway inhibitor-1). Time-to-event analysis by Kaplan-Meier estimates and Cox regression. RESULTS: We included 129 m-ccRCC patients treated between 2005 and 2013. An elevated RANK/OPG ratio was associated with shorter median time to metastasis (HR 0.50 (95% CI 0.29-0.87); P=0.014), shorter time to BM (HR 0.54 (95% CI 0.31-0.97); P=0.037), shorter median overall survival (mOS) since initial diagnosis (HR 2.27 (95% CI 1.44-3.60); P=0.0001), shorter median progression-free survival (HR 0.44 (95% CI 0.28-0.71); P=0.001) and mOS (HR 0.31 (95% CI 0.19-0.52); P<0.0001) on first-line anti-VEGFR-TKIs in the metastatic setting. Higher RANK expression was associated with shorter mOS on first-line anti-VEGFR-TKIs (HR 0.46 (95% CI 0.29-0.73); P=0.001). CONCLUSIONS: RANK/OPG ratio of expression in primary ccRCC is associated with BM and prognosis in patients treated with anti-VEGFR-TKIs. Prospective validation is warranted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".