Abstract 2199: Associations of genetic polymorphisms in <i>VEGFR1</i> with progression-free and overall survival in patients with neuroendocrine tumors treated with the VEGFA inhibitor bevacizumab.
Bibliographic record
Abstract
Abstract Background: Neuroendocrine tumors (NET) have been shown to be responsive to treatment with VEGF pathway inhibitors. We hypothesized that genetic variation in VEGFA, VEGFR1 or VEGFR2 is associated with progression free survival (PFS) and/or overall survival (OS) in patients with metastatic NET treated with bevacizumab, a monoclonal antibody targeting VEGFA. Methods: We selected 61 functional and tagging SNPs with a minor allele frequency of 5% or greater, with full gene coverage of VEGFA, VEGFR1 and VEGFR2. We pooled data from two genotyped datasets, selecting 82 patients with metastatic NET who received bevacizumab administered either as a single agent or as part of a combination regimen. Using a Cox proportional hazards regression analysis, and an additive genetic model, we tested the SNPs’ associations with PFS and OS adjusting for age and stage at diagnosis, gender, tumor origin, grade of differentiation, and genotyping dataset. Results: We found that 4 intronic tagging SNPs in VEGFR1, rs7987649, rs9508021, rs9513095 and rs2104330 were associated with PFS at p<0.05. The association between rs7987649 and PFS (multivariate Hazard Ratio 0.55 (0.38, 0.81) p=0.002) remained significant after adjusting for multiple testing. One of the four SNPs associated with PFS, rs7987649, as well as another SNP in VEGFR1, rs3794339, were associated with OS at p<0.05 although these associations did not remain significant after multiple testing adjustment. No SNPs in either VEGFR2 or VEGFA were associated with PFS or OS. Conclusions: In patients with neuroendocrine tumors treated with bevacizumab, the VEGFR1 SNP rs7987649 appears to be associated with progression-free survival. We note that three SNPs identified in our analysis, rs9508021, rs9513095 and rs2104330, are in strong linkage disequilibrium with SNPs rs7993418 and rs9582036, which have been associated with increased VEGFR1 expression and with PFS and OS in pancreatic adenocarcinoma (Lambrechts, 2012). Further study of loci within this region of VEGFR1 is warranted to discover potential causal variants affecting NET survival. Citation Format: Monica Ter-Minassian, ZhiRong R. Qian, Jennifer A. Chan, Susanne M. Hooshmand, Lauren K. Brais, Rachel Heafield, Xihong Lin, Geoffrey Liu, David C. Christiani, Matthew H. Kulke. Associations of genetic polymorphisms in VEGFR1 with progression-free and overall survival in patients with neuroendocrine tumors treated with the VEGFA inhibitor bevacizumab. [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 2199. doi:10.1158/1538-7445.AM2013-2199
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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 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".