Abstract
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.
Keywords: KRT80, lung adenocarcinoma, bioinformatics analysis, predictive biomarker, LUAD, RT-qPCR.