CNPY4 is a potential promising prognostic-related biomarker and correlated with immune infiltrates in gliomas
Bibliographic record
Abstract
Glioblastomas are classified into primary and secondary; primary glioblastomas develop rapidly and aggressively, whereas secondary glioblastomas are more common in grade II and III gliomas. Here, we aimed to demonstrate the role of the CNPY4 gene as a potential biomarker in immune infiltration in gliomas. Based on gene expression profile interaction analysis (GEPIA), we studied the survival model of CNPY4 and evaluated its effect on patients with glioma. The glioma dataset was downloaded from The Cancer Genome Atlas (TCGA) database. Logistic regression was used to analyze the relationship between clinical data and CNPY4 expression. Univariate and multivariate Cox proportional-hazards models were used to compare clinical features and patient survival. The relationship between CNPY4 and immune infiltration in glioma was studied using GEPIA and CIBERSORT online tools. TCGA data were analyzed using gene set enrichment analysis (GSEA). Finally, TIMER was used to analyze the expression and immune infiltration of CNPY4 in glioma to study the cumulative survival rate. Univariate logistic regression analysis showed that increased CNPY4 expression was associated with tumor age, grade, IDH status, and 1p/19q codeletion. Multivariate analysis showed that that downregulation of CNPY4 expression was an independent and satisfactory prognostic factor. CNPY4 expression was correlated with the infiltration level of dendritic cells in glioblastoma. In contrast, in low-grade gliomas, the infiltration level of B cells, dendritic cells, macrophages, neutrophils, and CD4+ T cells was significantly correlated with CNPY4 expression. The GSEA results showed that CNPY4 played an immunoregulatory role in immune-related phenotypic pathways between lymphoid and nonlymphoid cells. The intestinal immune networks for IgA production, rabbit thyroid disease, primary immunodeficiencies, and cancer immunotherapy were enriched by PD-1 blockade. High CNPY4 expression is a biomarker of glioma prognosis and is associated with the immune invasion of glioma.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".