A prognostic model for uveal melanoma in Asian populations: a comparative analysis of clinical features and gene expression patterns using the TRACE and TCGA data
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Bibliographic record
Abstract
BACKGROUND: Uveal melanoma (UM), the most common primary intraocular malignancy in adults, shows racial disparities in incidence, genetic drivers, and clinical outcomes. While most prognostication models are based on Caucasian populations, Asians demonstrate distinct molecular profiles, necessitating population-specific risk stratification. METHODS: This study analyzed 53 Asian UM tumors, 17 normal choroidal tissues (TRACE database), and 80 Caucasian UM samples (TCGA database). Differential gene analysis, immune microenvironment profiling, and survival modeling were performed. A 7-gene prognostic signature was developed by LASSO regression and validated across cohorts, with drug sensitivity predicted using GDSC2 data. RESULTS: The Asian UM exhibited 3,827 tumor-specific differentially expressed genes (DEGs) compared to the normal choroid, with enrichment in PI3K-Akt signalling, and 3,814 race-specific DEGs compared to Caucasians, suggesting specific disease pathways and variations in the tumor microenvironment. The tumor microenvironment in Asian UM exhibited increased immunological activation (M1 macrophages, PD-L1, CD8; p < 0.05), while Caucasian uveal melanoma was marked by immunosuppressive predominance (M2 macrophages, MDSCs). The seven-gene prognostic model (MMP2, LRAT, NOG, IHH, CDH18, MYH11, and SELE) exhibited strong predictive efficacy in Asians (AUC: 0.979, 0.924, and 0.984 for 1, 3, and 5-year survival) but was less successful in Caucasians. High-risk scores correlated with metastasis (12/26 vs. 4/27; p = 0.02) and had independent prognostic value. CONCLUSIONS: This cross-racial UM study reveals significant molecular and immune differences, indicating that Asian UM may be more responsive to immunotherapy The population-specific prognostic model improves our understanding of molecular differences in Asian and Caucasian UM, warranting further validation in multiethnic cohorts.
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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 | 0.000 |
| 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