Gene expression signatures and response to imatinib mesylate in gastrointestinal stromal tumor
Why this work is in the frame
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Bibliographic record
Abstract
Despite initial efficacy of imatinib mesylate in most gastrointestinal stromal tumor (GIST) patients, many experience primary/secondary drug resistance. Therefore, clinical management of GIST may benefit from further molecular characterization of tumors before and after imatinib mesylate treatment. As part of a recent phase II trial of neoadjuvant/adjuvant imatinib mesylate treatment for advanced primary and recurrent operable GISTs (Radiation Therapy Oncology Group S0132), gene expression profiling using oligonucleotide microarrays was done on tumor samples obtained before and after imatinib mesylate therapy. Patients were classified according to changes in tumor size after treatment based on computed tomography scan measurements. Gene profiling data were evaluated with Statistical Analysis of Microarrays to identify differentially expressed genes (in pretreatment GIST samples). Based on Statistical Analysis of Microarrays [False Discovery Rate (FDR), 10%], 38 genes were expressed at significantly lower levels in the pretreatment biopsy samples from tumors that significantly responded to 8 to 12 weeks of imatinib mesylate, that is, >25% tumor reduction. Eighteen of these genes encoded Krüppel-associated box (KRAB) domain containing zinc finger (ZNF) transcriptional repressors. Importantly, 10 KRAB-ZNF genes mapped to a single locus on chromosome 19p, and a subset predicted likely response to imatinib mesylate-based therapy in a naïve panel of GIST. Furthermore, we found that modifying expression of genes within this predictive signature can enhance the sensitivity of GIST cells to imatinib mesylate. Using clinical pretreatment biopsy samples from a prospective neoadjuvant phase II trial, we have identified a gene signature that includes KRAB-ZNF 91 subfamily members that may be both predictive of and functionally associated with likely response to short-term imatinib mesylate treatment.
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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) | 0.000 | 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 | 0.000 |
| 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 it