Abstract 4069: FGFR2 expression and mutation are rare in papillary renal cell carcinoma.
Bibliographic record
Abstract
Abstract Papillary renal cell carcinoma (pRCC) is the second most common type of renal cell carcinoma (RCC). Fibroblast growth factor receptor (FGFR) 1 signaling has been implicated to play a role in RCC (Tsimafeyeu et al. ASCO meeting 2010). We evaluated expression and mutational activation of FGFR2 as a potential target for therapy of pRCC. Formalin-fixed, paraffin-embedded specimens of removed 71 primary tumors from untreated pRCC patients were evaluated by immunohistochemistry with FGFR2 antibody. FGFR2 mutations were assessed by PCR and direct sequencing, with DNA obtained from 62 paraffin-embedded pRCC samples. Expression of FGFR2 was observed in 8.5% of primary pRCC (6/71). Intensity was 3+ in all cases. 2 of 71 (3%) patients had nuclear FGFR2 expression. FGFR2 S252W mutation was detected at low frequency (1/62, 1.6%) in pRCC (type I). No N549K mutation was detected in pRCC (0/43). FGFR2 expression and mutation are rare across papillary types of RCC. This study was supported by Mr. Sergey Kartashov. Citation Format: Ilya V. Tsimafeyeu, Nigel Wynn, Marat Gordiyev, Alfia Khasanova. FGFR2 expression and mutation are rare in papillary renal cell carcinoma. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4069. doi:10.1158/1538-7445.AM2013-4069
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".