☆ 4.8 Article

Cuproptosis-related gene index: A predictor for pancreatic cancer prognosis, immunotherapy efficacy, and chemosensitivity

FRONTIERS IN IMMUNOLOGY (2022)

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期刊

FRONTIERS IN IMMUNOLOGY
卷 13, 期 -, 页码 -

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FRONTIERS MEDIA SA
DOI: 10.3389/fimmu.2022.978865

关键词

cuproptosis; machine learning; pancreatic cancer; tumor microenvironment; immunotherapy; chemotherapy; gene signature

类别

Immunology

资金

  1. National Research, Development and Innovation Fund of Hungary under the TKP2021-NKTA [TKP2021-NKTA-34]

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This study examines prognostic prediction in pancreatic adenocarcinoma (PAAD) from the standpoint of Cuproptosis. A novel Cuproptosis-related gene index (CRGI) was developed using machine learning algorithms, and its correlation with tumor immunology and chemotherapeutic efficacy was explored. Experimental results indicate that Cuproptosis-related genes may serve as reliable diagnostic biomarkers in PAAD.
Aim: The term Cuproptosis was coined to describe a novel type of cell death triggered by intracellular copper buildup that is fundamentally distinct from other recognized types such as autophagy, ferroptosis, and pyroptosis in recent days. As the underlying mechanism was newly identified, its potential connection to pancreatic adenocarcinoma (PAAD) is still an open issue. Methods: A set of machine learning algorithms was used to develop a Cuproptosis-related gene index (CRGI). Its immunological characteristics were studied by exploring its implications on the expression of the immunological checkpoints, prospective immunotherapy responses, etc. Moreover, the sensitivity to chemotherapeutic drugs was predicted. Unsupervised consensus clustering was performed to more precisely identify different CRGI-based molecular subtypes and investigate the immunotherapy and chemotherapy efficacy. The expression of DLAT, LIPT1 and LIAS were also investigated, through real-time quantitative polymerase chain reaction (RTqPCR), western blot, and immunofluorescence staining (IFS). Results: A novel CRGI was identified and validated. Additionally, correlation analysis revealed major changes in tumor immunology across the high- and low-CRGI groups. Through an in-depth study of each medication, it was determined that the predictive chemotherapeutic efficacy of 32 regularly used anticancer drugs differed between high- and low-CRGI groups. The results of the molecular subtyping provided more support for such theories. Expressional assays performed at transcriptomic and proteomic levels suggested that the aforementioned Cuproptosis-related genes might serve as reliable diagnostic biomarkers in PAAD. Significance: This is, to the best of our knowledge, the first study to examine prognostic prediction in PAAD from the standpoint of Cuproptosis. These findings may benefit future immunotherapy and chemotherapeutic therapies.

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