Identification of Altered Primary Immunodeficiency-Associated Genes and Their Implications in Pediatric Cancers
Bibliographic record
Abstract
BACKGROUND: Cancer is the leading cause of disease-related mortality in children and malignancies are more frequently observed in individuals with primary immunodeficiencies (PIDs). This study aimed to identify and highlight the molecular mechanisms, such as oncogenesis and immune evasion, by which PID-related genes may lead to the development of pediatric cancers. METHOD: We implemented a novel bioinformatics framework using patient data from the TARGET database and performed a comparative transcriptome analysis of PID-related genes in pediatric cancers between normal and cancer tissues, gene ontology enrichment, and protein-protein interaction analyses, and determined the prognostic impacts of commonly mutated and differentially expressed PID-related genes. RESULTS: From the Fulgent Genetics Comprehensive Primary Immunodeficiency panel of 472 PID-related genes, 89 genes were significantly differentially expressed between normal and cancer tissues, and 20 genes were mutated in two or more patients. Enrichment analysis highlighted many immune system processes as well as additional pathways in the mutated PID-related genes related to oncogenesis. Survival outcomes for patients with altered PID-related genes were significantly different for 75 of the 89 DEGs, often resulting in a poorer prognosis. CONCLUSIONS: Overall, multiple PID-related genes demonstrated the connection between PIDs and cancer development and should be studied further, with hopes of identifying new therapeutic targets.
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How this classification was reachedexpand
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 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".