Integrated analysis identifies cuproptosis-related gene DLAT and its competing endogenous RNAs network to predict the prognosis of pancreatic adenocarcinoma patients

被引:0
|
作者
Zhou, Congya [1 ]
Jin, Long [1 ]
Yu, Jiao [1 ]
Gao, Zhengchao [2 ]
机构
[1] Shaanxi Prov Peoples Hosp, Dept Radiat Oncol, Xian, Peoples R China
[2] Shaanxi Prov Peoples Hosp, Dept Orthopaed, 256 Youyi West Rd, Xian 710068, Shaanxi, Peoples R China
关键词
competing endogenous RNA; cuproptosis; DLAT; pancreatic adenocarcinoma; prognostic signature; SERUM-LEVELS; CANCER; COPPER;
D O I
10.1097/MD.0000000000037322
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Pancreatic adenocarcinoma (PAAD) is a highly malignant tumor with poor prognosis. However, the relationship between cuproptosis-related genes (CRGs) and its competing endogenous RNA (ceRNA) network with the prognosis of PAAD patients remains unclear. To investigate this relationship, we calculated the difference in CRGs between PAAD tissues and normal tissues using the 'limma' R package. Additionally, we employed least absolute shrinkage and selection operator (LASSO) Cox regression analysis to construct a prognostic signature for CRGs. Survival analysis of patients with PAAD was performed using Kaplan-Meier analysis. Furthermore, we used bioinformatics tools to screen for CRGs-related MicroRNA (miRNA) and lncRNAs. To validate these findings, we conducted real-time quantitative polymerase chain reaction (RT-qPCR), CCK-8, colony formation, and Transwell assays to assess the effect of DLAT in vitro. Our results revealed a cuproptosis-related prognostic signature consisting of 3 prognostic genes (DLAT, LIAS, and LIPT1). Notably, patients with a high-risk score for the CRGs signature exhibited poor prognosis in terms of overall survival (OS) (P < .05). The receiver operating characteristic (ROC) curve was used to evaluate the prognostic signature of CRGs. The results showed that the 1-year, 3-year, and 5-year area under the curve values for predicting OS were 0.62, 0.66, and 0.79, respectively. Additionally, the CRGs-related ceRNA network revealed the regulatory axis of LINC00857/has-miR-1179/DLAT in PAAD. In vitro experiments demonstrated that knockdown of LINC00857 and DLAT inhibited the growth and invasion of PAAD cells. This study identified a CRG-related prognostic signature consisting of 3 biomarkers (DLAT, LIAS, and LIPT1) for PAAD. Furthermore, ceRNA network analysis suggested the involvement of the LINC00857/has-miR-1179/DLAT axis in the development of PAAD. Overall, this study provides theoretical support for the investigation of diagnostic and prognostic biomarkers as well as potential therapeutic targets in PAAD.
引用
收藏
页数:12
相关论文
共 33 条
  • [21] The multi-omics analysis identifies a novel cuproptosis-anoikis-related gene signature in prognosis and immune infiltration characterization of lung adenocarcinoma
    Jiang, Guanyu
    Song, Chenghu
    Wang, Xiaokun
    Xu, Yongrui
    Li, Huixing
    He, Zhao
    Cai, Ying
    Zheng, Mingfeng
    Mao, Wenjun
    HELIYON, 2023, 9 (03)
  • [22] Construction of a Competitive Endogenous RNA Network for Pancreatic Adenocarcinoma Based on Weighted Gene Co-expression Network Analysis and a Prognosis Model
    Wang, Jing
    Xiang, Jinzhu
    Li, Xueling
    FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2020, 8
  • [23] A Seven-Long Non-coding RNA Signature Improves Prognosis Prediction of Lung Adenocarcinoma: An Integrated Competing Endogenous RNA Network Analysis
    Li, Rang
    Han, Kedong
    Xu, Dehua
    Chen, Xiaolin
    Lan, Shujin
    Liao, Yuanjun
    Sun, Shengnan
    Rao, Shaoqi
    FRONTIERS IN GENETICS, 2021, 11
  • [24] Cuproptosis-related gene expression is associated with immune infiltration and CD47/CD24 expression in glioblastoma, and a risk score based on these genes can predict the survival and prognosis of patients
    Li, Erliang
    Qiao, Huanhuan
    Sun, Jin
    Ma, Qiong
    Lin, Li
    He, Yixiang
    Li, Shuang
    Mao, Xinggang
    Zhang, Xiaoping
    Liao, Bo
    FRONTIERS IN ONCOLOGY, 2023, 13
  • [25] Integrated analysis of single-cell and bulk RNA-sequencing identifies a metastasis-related gene signature for predicting prognosis in lung adenocarcinoma
    Cao, Xu
    Xi, Jingjing
    Wang, Congyue
    Yu, Wenjie
    Wang, Yanxia
    Zhu, Jingjing
    Xu, Kailin
    Pan, Di
    Chen, Chong
    Han, Zhengxiang
    CLINICAL & TRANSLATIONAL ONCOLOGY, 2024,
  • [26] Integrated bulk and single-cell transcriptomic analysis unveiled a novel cuproptosis-related lipid metabolism gene molecular pattern and a risk index for predicting prognosis and antitumor drug sensitivity in breast cancer
    Zeng, Cheng
    Xu, Chang
    Liu, Shuning
    Wang, Yuanyi
    Wei, Yuhan
    Qi, Yalong
    Wang, Yue
    Wang, Jiani
    Ma, Fei
    DISCOVER ONCOLOGY, 2025, 16 (01)
  • [27] Risk Scores Based on Six Survival-Related RNAs in a Competing Endogenous Network Composed of Differentially Expressed RNAs Between Clear Cell Renal Cell Carcinoma Patients Carrying Wild-Type or Mutant Von Hippel-Lindau Serve Well to Predict Malignancy and Prognosis
    Zhu, Rui
    Li, Xiezhao
    Cai, Zhiduan
    Liang, Siyang
    Yuan, Yaoji
    Xu, Yuyu
    Lai, Dehui
    Zhao, Haibo
    Yang, Weiqing
    Bian, Jun
    Liu, Leyuan
    Xu, Guibin
    FRONTIERS IN ONCOLOGY, 2021, 11
  • [28] Integrated analysis of single-cell sequencing and weighted co-expression network identifies a novel signature based on cellular senescence-related genes to predict prognosis in glioblastoma
    Bao, Qingquan
    Yu, Xuebin
    Qi, Xuchen
    ENVIRONMENTAL TOXICOLOGY, 2024, 39 (02) : 643 - 656
  • [29] Identification of an antigen-presenting cells/T/NK cells-related gene signature to predict prognosis and gene marker CTSL to predict immunotherapeutic response for lung adenocarcinoma: An integrated analysis of bulk and single cell RNA sequencing
    Huang, L.
    Xie, T.
    Shi, Y.
    JOURNAL OF THORACIC ONCOLOGY, 2023, 18 (04) : S140 - S140
  • [30] Glycosylation-Related Genes Predict the Prognosis and Immune Fraction of Ovarian Cancer Patients Based on Weighted Gene Coexpression Network Analysis (WGCNA) and Machine Learning
    Zhao, Chen
    Xiong, Kewei
    Zhao, Fangrui
    Adam, Abdalla
    Li, Xiangpan
    OXIDATIVE MEDICINE AND CELLULAR LONGEVITY, 2022, 2022