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NDUFA4L2 is a novel biomarker for colorectal cancer through bioinformatics analysis.
Lin, Yuning; Xie, Hongyan; Zhao, Wenzhen; Li, Ying; Zhang, Zhongying.
Afiliação
  • Lin Y; Xiamen Key Laboratory of Biomarker Translational Medicine, Medical Laboratory of Xiamen Humanity Hospital Fujian Medical University, Xiamen, China.
  • Xie H; Xiamen Key Laboratory of Biomarker Translational Medicine, Medical Laboratory of Xiamen Humanity Hospital Fujian Medical University, Xiamen, China.
  • Zhao W; Xiamen Key Laboratory of Biomarker Translational Medicine, Medical Laboratory of Xiamen Humanity Hospital Fujian Medical University, Xiamen, China.
  • Li Y; Ultrasonography Department, Women and Children's Hospital, School of Medicine, Xiamen university, Xiamen, China.
  • Zhang Z; Xiamen Key Laboratory of Biomarker Translational Medicine, Medical Laboratory of Xiamen Humanity Hospital Fujian Medical University, Xiamen, China.
Medicine (Baltimore) ; 102(44): e35893, 2023 Nov 03.
Article em En | MEDLINE | ID: mdl-37933010
ABSTRACT
Colorectal cancer (CRC) is a major cause of cancer-related deaths worldwide. NDUFAL42 is an important mitochondrial respiratory chain subunit that plays a critical role in cellular energy metabolism. However, the role of NDUFA4L2 in CRC remains unclear. Therefore, we used the data obtained from The Cancer Genome Atlas (TCGA) database to prove the relationship between NDUFA4L2 and CRC. The expression levels of NDUFA4L2 in CRC tissues were analyzed by immunohistochemical staining of NDUFA4L2 from the HPA database. Wilcoxon rank sum test, Chi-square test, Fisher exact test and logistic regression were used to evaluate relationships between clinical-pathologic features and NDUFA4L2 expression. Receiver operating characteristic (ROC) curves were used to describe binary classifier value of NDUFA4L2 using area under curve (AUC) score. Kaplan-Meier method and Cox regression analysis were used to evaluate factors contributing to prognosis. Gene oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were used to predict the function of differentially expressed genes associated with NDUFA4L2. Gene set enrichment analysis (GSEA) was used to predict canonical pathways associated with NDUFA4L2.Immune infiltration analysis was performed to identify the significantly involved functions of NDUFA4L2. Protein-protein interaction (PPI) networks were established and 20 hub genes identified with Cytoscape software. Increased NDUFA4L2 expression in CRC was associated with T stage (P = .019), N stage (P < .001), Pathologic stage (P = .020), Residual tumor (P = .023), Perineural invasion (P = .039), Lymphatic invasion (P = .007), Histological type(P < .001), PFI event (P = .007) and DSS event (P = .004).ROC curve suggested the significant diagnostic and prognostic ability of NDUFA4L2 (AUC = 0.878). High NDUFA4L2 expression predicted a poorer Overall-survival (P = .021), poorer progression-free interval (P = .001), and poorer Disease Specific Survival (P = .002). GO, KEGG, GSEA and immune infiltration analysis showed that NDUFA4L2 expression was correlated with regulating the function of DNA and some types of immune infiltrating cells. NDUFA4L2 expression was significantly correlated with poor survival and immune infiltrations in CRC, and it may be a promising prognostic biomarker in CRC.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Biologia Computacional Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Colorretais / Biologia Computacional Limite: Humans Idioma: En Ano de publicação: 2023 Tipo de documento: Article