FGFR1 overexpression and anti-FGFR compound sensitivity in renal cell carcinoma.
Bibliographic record
Abstract
e15544 Background: Fibroblast growth factor receptor 1 (FGFR1) plays a significant role in renal cell carcinoma (RCC) pathogenesis. There are several compounds targeting FGFR1 on the horizon. Here, we report changes in FGFR1 overexpression/mutation and anti-FGFR compound sensitivity in RCC. Methods: Twenty-eight female NCr nu/nu mice (6-12 weeks of age) were used for xenotransplantation of human clear cell renal carcinoma Caki-1 cell line. Mice with established FGFR1-expressing tumors (an average size of 80-120 mg) received intravenous OM-RCA-01 (humanized anti-FGFR1 monoclonal antibody, 10 mg/kg, twice a week; N=14) or oral ponatinib (pan-FGFR inhibitor, 30 mg/kg, daily; N=14). Tumor sizes were measured in a blind fashion twice a week with a vernier caliper. Additionally, primary tumor and metastatic lesion of 40 RCC patients were accessed. Animal and patient formalin-fixed, paraffin-embedded specimens of tumors were evaluated by immunohistochemistry with FGFR1 antibodies. FGFR1 mutations were assessed by PCR and direct sequencing. Results: At in vivo study termination day (Day 31), there were 6 (43%) and 5 (36%) tumors reached end-point volume of 2000 mm3 in OM-RCA-01 and ponatinib groups, respectively. Nine (82%) of these 11 resistant tumors had no FGFR1 expression (5 and 4 tumors in OM-RCA-01 and ponatinib groups). FGFR1 was highly expressed in all 17 tumors that responded to OM-RCA-01 or ponatinib. Intensity was 3+ in all cases. Expression of FGFR1 was observed in 92.5% (37/40) of primary tumors and in 65% (26/40) of metastasis in RCC patients. FGFR1 expression decreased in 32% (12/37) and increased in 67% (2/3) of metastasis in comparison with primary tumors. No FGFR1 mutations were detected in animal and patient tumors. Conclusions: FGFR1 overexpression could be different in primary RCC and metastasis of same patient. Expression of FGFR1 was found in 100% of renal tumors that responded to anti-FGFR therapy and in 18% of resistant RCC. Further translational studies will provide more information.
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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 | 0.000 | 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 | 0.001 |
| 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".