Uridine phosphorylase 1 is a novel immune‐related target and predicts worse survival in brain glioma
Bibliographic record
Abstract
Uridine phosphorylase 1 (UPP1) has been reported as an oncogene in several malignancies. In glioma, the role of UPP1 remains unclear. This study was performed to explore its role in glioma at transcriptional level. Totally, 998 glioma patients with clinical data were enrolled, including 301 mRNA microarray data from Chinese Glioma Genome Atlas (CGGA) dataset and 697 RNAseq data from The Cancer Genome Atlas (TCGA) dataset. Statistical analysis was performed with R language. UPP1 expression level was positively correlated with WHO grade of glioma. UPP1 was significantly upregulated in mesenchymal subtype and could serve as a potential biomarker for this subtype. Based on most correlated genes of UPP1, Gene ontology analysis revealed that UPP1 was profoundly associated with immune and inflammatory response. Gene Sets Variation Analysis was further performed and showed that UPP1 was particularly correlated with MHC-II and LCK, which were mainly associated with activities of antigen-presenting cells and T cells. Moreover, UPP1 was found to be synergistic with various immune checkpoint members, especially with PD1 pathway and B7-H3. Finally, Kaplan-Meier curves revealed that higher UPP1 indicated significantly shorter survival for glioma patients. Taken together, UPP1 played an oncogenic role in glioma via suppressing tumor-related immune response.
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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 | 0.001 | 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) | 0.001 | 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".