Impact of MET status on treatment outcomes in papillary renal cell carcinoma: A pooled analysis of historical data
Bibliographic record
Abstract
BACKGROUND: Papillary renal cell carcinoma (PRCC) represents 15% of RCCs but has no indicated therapies, with limited biomarker-based data to inform targeted treatment. MET alterations may be key; > 80% of PRCC tumours show MET upregulation. The objective of this study was to assess MET status in PRCC and its impact on clinical outcomes. METHODS: This retrospective, observational study included patients with locally advanced/metastatic PRCC from three international registries. MET status was determined retrospectively by next generation sequencing (NGS) of archival tissue. MET-driven was defined as MET and/or hepatocyte growth factor amplification, chromosome 7 gain, and/or MET kinase domain mutations. Objectives included progression-free survival (PFS) and overall survival (OS) by MET status using a Cox proportional hazards model. RESULTS: Of 308 patients, 305 received first-line treatment; most commonly sunitinib (n = 208; 68%), then everolimus (n = 40; 13%). Of 179 patients with valid NGS results, 38% had MET-driven and 49% MET-independent tumours (13% unevaluable). In the MET-driven versus MET-independent subgroups, respectively, of sunitinib-treated patients, median PFS was numerically longer, though not statistically significantly; PFS: 9.2 months (95% confidence interval [CI]: 5.4-13.2) versus 5.7 months (95% CI: 4.3-7.4), hazard ratio (HR) = 0.67; 95% CI: 0.41-1.08. There was no difference between the OS of each subgroup. CONCLUSIONS: MET-driven PRCC may respond to targeted agents. However, the presence of MET alterations did not appear to be predictive for outcomes in response to current therapies, which are not biomarker-driven, compared with MET-independent tumours.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".