Identification of KRT80 as a Novel Prognostic and Predictive Biomarker of Human Lung Adenocarcinoma via Bioinformatics Approaches

被引:1
作者
Jiang, Jing [1 ,2 ]
Lu, Jinhua [3 ]
Feng, Yuqian [3 ]
Zhao, Ying [2 ]
Su, Jingyang [2 ]
Zeng, Tianni [2 ]
Chen, Yin [2 ]
Shen, Kezhan [3 ]
Jia, Yewei [4 ,5 ]
Lin, Shengyou [1 ]
机构
[1] Zhejiang Chinese Med Univ, Affiliated Hosp 1, Zhejiang Prov Hosp Chinese Med, Dept Oncol, Hangzhou 310000, Peoples R China
[2] Zhejiang Chinese Med Univ, Clin Med Coll 3, Hangzhou 310000, Peoples R China
[3] Zhejiang Chinese Med Univ, Hangzhou Tradit Chinese Med TCM Hosp, Dept Oncol, Hangzhou 310000, Peoples R China
[4] Friedrich Alexander Univ Erlangen Nurnberg FAU, Dept Internal Med 3, D-91054 Erlangen, Germany
[5] Univ Klinikum Erlangen, D-91054 Erlangen, Germany
关键词
KRT80; lung adenocarcinoma; bioinformatics analysis; predictive biomarker; LUAD; RT-qPCR; GENE-EXPRESSION; SINGLE-ARM; OPEN-LABEL; CANCER; KERATINS; CROSSTALK; CHEMOTHERAPY; MULTICENTER; VARIANTS; BIOLOGY;
D O I
10.2174/0113862073294339240603103623
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Background: According to the 2022 Global Cancer Statistics, lung cancer is the leading cause of cancer-related mortality worldwide. Lung adenocarcinoma (LUAD), which is a histological subtype of Non-Small Cell Lung Cancer (NSCLC), accounts for 40% of primary lung cancer. Therefore, there is an urgent need to identify new prognostic markers as clinical predictive markers for LUAD. Objective: This study aimed to investigate the role of Keratin 80 (KRT80) in the prognosis of LUAD and its underlying mechanisms. Methods: Bioinformatics analysis was conducted using data retrieved from The Cancer Genome Atlas (TCGA) databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were employed to predict the involved biological processes and signaling pathways, respectively. The LinkedOmics database was utilized to identify differentially expressed genes (DEGs) correlated with KRT80. Nomograms and Kaplan-Meier plots were constructed to evaluate the survival outcomes of patients diagnosed with LUAD. Moreover, TIMER was employed to conduct correlation analyses between KRT80 expression and immune cell infiltration, shedding light on the intricate interplay between KRT80 and the tumor microenvironment in LUAD. To ascertain the RNA and protein expression levels of KRT80 in LUAD and adjacent normal tissues, Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR) and immunohistochemistry techniques were employed, respectively. Results: Scrutiny of the TCGA dataset revealed KRT80 up-regulation across pan-cancer tissues, notably elevated in LUAD compared to healthy lung tissues. This finding was validated in our clinical samples, where Kaplan-Meier survival curves indicated poorer survival rates for high KRT80 expression in LUAD. A positive correlation was found between the transcription level of KRT80 in LUAD samples and clinical parameters, such as lymph node metastasis stage, distant metastasis, and pathological stage. Survival, logistic regression, and Cox regression analyses emphasized the clinical prognostic significance of high KRT80 expression in LUAD. Nomogram results underscored the robust predictive potential of KRT80 for the survival of LUAD patients. Gene functional enrichment analyses mainly associated KRT80 with cytokine-cytokine receptor interactions, cell cycle, apoptosis, and chemokine signaling pathways. Based on the results of the immune infiltration analysis, it can be found that the expression of KRT80 is related to the immune cell subsets and survival rate of patients with LUAD. Conclusion: Our research revealed a significant upregulation of KRT80 in LUAD, with heightened KRT80 expression correlating with unfavorable prognosis. This study represents a comprehensive and systematic evaluation of KRT80 expression in LUAD, encompassing its prognostic and diagnostic significance, as well as underlying mechanisms. Our findings suggest that KRT80 may emerge as a novel prognostic and predictive biomarker in LUAD.
引用
收藏
页数:16
相关论文
共 75 条
[31]   Comprehensive analyses of tumor immunity: implications for cancer immunotherapy [J].
Li, Bo ;
Severson, Eric ;
Pignon, Jean-Christophe ;
Zhao, Haoquan ;
Li, Taiwen ;
Novak, Jesse ;
Jiang, Peng ;
Shen, Hui ;
Aster, Jon C. ;
Rodig, Scott ;
Signoretti, Sabina ;
Liu, Jun S. ;
Liu, X. Shirley .
GENOME BIOLOGY, 2016, 17
[32]   Keratin 80 promotes migration and invasion of colorectal carcinoma by interacting with PRKDC via activating the AKT pathway [J].
Li, Changcan ;
Liu, Xisheng ;
Liu, Yuan ;
Liu, Xueni ;
Wang, Rangrang ;
Liao, Jianhua ;
Wu, Shaohan ;
Fan, Junwei ;
Peng, Zhihai ;
Li, Bin ;
Wang, Zhaowen .
CELL DEATH & DISEASE, 2018, 9
[33]   Keratin gene signature expression drives epithelial-mesenchymal transition through enhanced TGF-β signaling pathway activation and correlates with adverse prognosis in lung adenocarcinoma [J].
Li, Gang ;
Guo, Jinbao ;
Mou, Yunfei ;
Luo, Qingsong ;
Wang, Xuehai ;
Xue, Wei ;
Hou, Ting ;
Zeng, Tianyang ;
Yang, Yi .
HELIYON, 2024, 10 (03)
[34]   The role of macrophages-mediated communications among cell compositions of tumor microenvironment in cancer progression [J].
Li, Mengyuan ;
Jiang, Ping ;
Wei, Shuhua ;
Wang, Junjie ;
Li, Chunxiao .
FRONTIERS IN IMMUNOLOGY, 2023, 14
[35]   TIMER: A Web Server for Comprehensive Analysis of Tumor-Infiltrating Immune Cells [J].
Li, Taiwen ;
Fan, Jingyu ;
Wang, Binbin ;
Traugh, Nicole ;
Chen, Qianming ;
Liu, Jun S. ;
Li, Bo ;
Liu, X. Shirley .
CANCER RESEARCH, 2017, 77 (21) :E108-E110
[36]   Keratin 80 regulated by miR-206/ETS1 promotes tumor progression via the MEK/ERK pathway in ovarian cancer [J].
Liu, Ouxuan ;
Wang, Caixia ;
Wang, Shuang ;
Hu, Yuexin ;
Gou, Rui ;
Dong, Hui ;
Li, Siting ;
Li, Xiao ;
Lin, Bei .
JOURNAL OF CANCER, 2021, 12 (22) :6835-6850
[37]   Clinical relevance of mutant-allele tumor heterogeneity and lung adenocarcinoma [J].
Mao, Hengyu .
ANNALS OF TRANSLATIONAL MEDICINE, 2019, 7 (18)
[38]   Upregulated expression of glucose transporter isoform 1 in invasive and metastatic extramammary Paget's disease [J].
Matsumoto, Mika ;
Rokunohe, Daiki ;
Sasaki, Takanori ;
Matsuzaki, Yasushi ;
Nakano, Hajime ;
Mizukami, Hiroki ;
Akasaka, Eijiro ;
Sawamura, Daisuke .
EXPERIMENTAL AND THERAPEUTIC MEDICINE, 2024, 27 (05)
[39]   An Approach for Systems-Level Understanding of Prostate Cancer from High-Throughput Data Integration to Pathway Modeling and Simulation [J].
Mobashir, Mohammad ;
Turunen, S. Pauliina ;
Izhari, Mohammad Asrar ;
Ashankyty, Ibraheem Mohammed ;
Helleday, Thomas ;
Lehti, Kaisa .
CELLS, 2022, 11 (24)
[40]   The human keratins: biology and pathology [J].
Moll, Roland ;
Divo, Markus ;
Langbein, Lutz .
HISTOCHEMISTRY AND CELL BIOLOGY, 2008, 129 (06) :705-733