Cuproptosis-Related Gene DLAT as a Novel Biomarker Correlated with Prognosis, Chemoresistance, and Immune Infiltration in Pancreatic Adenocarcinoma: A Preliminary Study Based on Bioinformatics Analysis
Bibliographic record
Abstract
A novel form of cell death, cuproptosis, was recently identified to be mediated by the binding of copper to lipoylated enzymes of the tricarboxylic acid cycle. Cuproptosis-related genes (CRGs) may play a crucial role in the progression of pancreatic adenocarcinoma (PAAD), which often exhibits metabolic reprogramming. In the present study, univariate Cox regression analysis and Kaplan–Meier survival analysis were performed to identify prognostic CRGs. Data from the Cancer Therapeutics Response Portal and the Genomics of Drug Sensitivity in Cancer database were downloaded for drug sensitivity analysis. DLAT was identified as the only prognostic CRG in PAAD (HR = 2.72; 95% CI, 1.10–6.74). Functional enrichment analyses indicated that the basic function of DLAT is closely related to metabolism, and multiple tumor-promoting and immune response-related pathways were enriched in DLAT-high PAAD samples. The influence of DLAT and related genes on cancer immunity was evaluated by comprehensive immune infiltration analyses, which revealed the value of these genes as biomarkers for evaluating the sensitivity to immunotherapy. Additionally, high DLAT expression induced drug resistance, and significantly increased resistance to commonly used chemotherapeutics in PAAD, such as gemcitabine, oxaliplatin, 5-fluorouracil, and irinotecan. In conclusion, our study preliminarily revealed the prognostic value of DLAT, which is correlated with PAAD progression, chemoresistance, and immune infiltration, providing a valuable reference for PAAD treatment. However, our findings need to be confirmed by further in vivo and in vitro experiments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".