Integrative bioinformatics analysis of ACS enzymes as candidate prognostic and diagnostic biomarkers in colon adenocarcinoma

被引:3
|
作者
Parsazad, Ehsan [1 ,2 ]
Esrafili, Farina [3 ]
Yazdani, Behnaz [4 ]
Ghafarzadeh, Saghi [5 ]
Razmavar, Namdar [6 ]
Sirous, Hajar [7 ]
机构
[1] Malek Ashtar Univ, Dept Biosci & Biotechnol, Tehran, Iran
[2] Medvac Biopharm Co, Karaj, Alborz Province, Iran
[3] Islamic Azad Univ, Dept Genet, Zanjan Branch, Zanjan, Iran
[4] Islamic Azad Univ, Dept Tissue Engn, Najafabad Branch, Najafabad, Iran
[5] Univ Sci & Culture, Dept Royan Inst, Tehran, Iran
[6] Univ Guilan, Dept Biol, Rasht, Iran
[7] Isfahan Univ Med Sci, Bioinformat Res Ctr, Sch Pharm & Pharmaceut Sci, Esfahan, Iran
关键词
Acyl-CoA synthase; Cancer; Colon adenocarcinoma; Colon cancer; Fatty acid activation; FATTY-ACID-METABOLISM; ACETOACETYL-COA SYNTHETASE; PREDICTS POOR-PROGNOSIS; BODY-UTILIZING ENZYME; COLORECTAL-CANCER; PROSTATE-CANCER; EXPRESSION; CARCINOGENESIS; METASTASIS; OXIDATION;
D O I
10.4103/1735-5362.378088
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Background and purpose: Acyl-CoA synthetase (ACS) enzymes play an important role in the activation of fatty acids. While many studies have found correlations between the expression levels of ACS enzymes with the progression, growth, and survival of cancer cells, their role and expression patterns in colon adenocarcinoma are still greatly unknown and demand further investigation.Experimental approach: The expression data of colon adenocarcinoma samples were downloaded from the Cancer Genome Atlas (TCGA) database. Normalization and differential expression analysis were performed to identify differentially expressed genes (DEGs). Gene set enrichment analysis was applied to identify top enriched genes from ACS enzymes in cancer samples. Gene ontology and protein-protein interaction analyses were performed for the prediction of molecular functions and interactions. Survival analysis and receiver operating characteristic test (ROC) were performed to find potential prognostic and diagnostic biomarkers.Findings/Results: ACSL6 and ACSM5 genes demonstrated more significant differential expression and LogFC value compared to other ACS enzymes and also achieved the highest enrichment scores. Gene ontology analysis predicted the involvement of top DEGs in fatty acids metabolism, while protein-protein interaction network analysis presented strong interactions between ACSLs, ACSSs, ACSMs, and ACSBG enzymes with each other. Survival analysis suggested ACSM3 and ACSM5 as potential prognostic biomarkers, while the ROC test predicted stronger diagnostic potential for ACSM5, ACSS2, and ACSF2 genes.Conclusion and implications: Our findings revealed the expression patterns, prognostic, and diagnostic biomarker potential of ACS enzymes in colon adenocarcinoma. ACSM3, ACSM5, ACSS2, and ACSF2 genes are suggested as possible prognostic and diagnostic biomarkers.
引用
收藏
页码:413 / 429
页数:17
相关论文
共 50 条
  • [1] Comprehensive Analysis for Identifying Diagnostic and Prognostic Biomarkers in Colon Adenocarcinoma
    Liu, Zhisong
    Bai, Yi
    Xie, Fucun
    Miao, Fei
    Du, Fei
    DNA AND CELL BIOLOGY, 2020, 39 (04) : 599 - 614
  • [2] Comprehensive Analysis of Candidate Diagnostic and Prognostic Biomarkers Associated with Lung Adenocarcinoma
    Li, Jingyuan
    Liu, Xingyuan
    Cui, Zan
    Han, Guanying
    MEDICAL SCIENCE MONITOR, 2020, 26
  • [3] Exploration of Prognostic Biomarkers for Lung Adenocarcinoma Through Bioinformatics Analysis
    Tu, Zhengliang
    He, Xiangfeng
    Zeng, Liping
    Meng, Di
    Zhuang, Runzhou
    Zhao, Jiangang
    Dai, Wanrong
    FRONTIERS IN GENETICS, 2021, 12
  • [4] Bioinformatics analysis of microarray data to identify the candidate biomarkers of lung adenocarcinoma
    Guo, Tingting
    Ma, Hongtao
    Zhou, Yubai
    PEERJ, 2019, 7
  • [5] Expression analysis of lncRNA as prognostic biomarkers in colon adenocarcinoma
    Zhang Jian
    Yuan Yujie
    He Yulong
    ANNALS OF ONCOLOGY, 2017, 28
  • [6] Identification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis
    Zhanzhan Xu
    Yu Zhou
    Yexuan Cao
    Thi Lan Anh Dinh
    Jing Wan
    Min Zhao
    Medical Oncology, 2016, 33
  • [7] Identification of candidate biomarkers and analysis of prognostic values in ovarian cancer by integrated bioinformatics analysis
    Xu, Zhanzhan
    Zhou, Yu
    Cao, Yexuan
    Thi Lan Anh Dinh
    Wan, Jing
    Zhao, Min
    MEDICAL ONCOLOGY, 2016, 33 (11)
  • [8] Integrative bioinformatics analysis reveals novel insights into osteoarthritis pathogenesis and diagnostic biomarkers
    Chen, Qipeng
    Li, Xiaodong
    Li, Pengfei
    Liu, Hongpeng
    Zhang, Qi
    He, Linqin
    Tang, Zonghan
    Song, Hanbing
    BMC MUSCULOSKELETAL DISORDERS, 2024, 25 (01)
  • [9] An integrative bioinformatics analysis of microarray data for identifying hub genes as diagnostic biomarkers of preeclampsia
    Liu, Keling
    Fu, Qingmei
    Liu, Yao
    Wang, Chenhong
    BIOSCIENCE REPORTS, 2019, 39
  • [10] Identifying Potential Effective Diagnostic and Prognostic Biomarkers in Sepsis by Bioinformatics Analysis and Validation
    Huang, Xu
    Tan, Jixiang
    Chen, Xiaoying
    Zhao, Lin
    INTERNATIONAL JOURNAL OF GENERAL MEDICINE, 2022, 15 : 6055 - 6071