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.
Zengli FangWei WangYuan LiuJie HuaChen LiangJiang LiuBo ZhangXianjun YuXianjun YuQingcai MengJin XuPublished in: Current oncology (Toronto, Ont.) (2023)
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.
Keyphrases
- papillary thyroid
- immune response
- cell death
- single cell
- squamous cell
- poor prognosis
- emergency department
- small molecule
- gene expression
- electronic health record
- dendritic cells
- artificial intelligence
- machine learning
- big data
- deep learning
- signaling pathway
- young adults
- stress induced
- childhood cancer
- high glucose
- cell cycle arrest
- replacement therapy