Genomic profiling of NETs: a comprehensive analysis of the RADIANT trials
Why this work is in the frame
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Bibliographic record
Abstract
Neuroendocrine tumors (NETs) have historically been subcategorized according to histologic features and the site of anatomic origin. Here, we characterize the genomic alterations in patients enrolled in 3 phase 3 clinical trials of NET of different anatomic origins and assessed the potential correlation with clinical outcomes. Whole-exome and targeted panel sequencing was used to characterize 225 NET samples collected in the RADIANT series of clinical trials. Genomic profiling of NET was analyzed along with nongenomic biomarker data on tumor grade and circulating chromogranin A (CgA) and neuron specific enolase (NSE) levels from these patients enrolled in clinical trials. Our results highlight recurrent large-scale chromosomal alterations as a common theme among NET. Although the specific pattern of chromosomal alterations differed between tumor subtypes, the evidence for generalized chromosomal instability (CIN) was observed across all primary sites of NET. In pancreatic NET, although the P-value was not significant, higher CIN suggests a trend towards longer survival (HR, 0.55, P=0.077); whereas in the gastrointestinal NET, lower CIN was associated with longer survival (HR, 0.44, P=0.0006). Our multivariate analyses demonstrated that when combined with other clinical data among patients with progressive advanced NETs, chromosomal level alteration adds important prognostic information. Large-scale CIN is a common feature of NET, and specific patterns of chromosomal gain and loss appeared to have independent prognostic value in NET subtypes. However, whether CIN in general has clinical significance in NET requires validation in larger patient cohort and warrants further mechanistic studies.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| 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 it