Evidence map›Paper›PMID 38910478›Full record

ArticleCombinatorial chemistry & high throughput screening2025

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

Jing Jiang, Jinhua Lu, Yuqian Feng, Ying Zhao, Jingyang Su, Tianni Zeng, Yin Chen, Kezhan Shen, Yewei Jia, Shengyou Lin

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Article in Combinatorial chemistry & high throughput screening, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing papers in PubMed
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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Jing JiangDepartment of Oncology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), 310000, Hangzhou, China.
Jinhua LuDepartment of Oncology, Hangzhou Traditional Chinese Medicine (TCM) Hospital Affiliated to Zhejiang Chinese Medical University, 310000, Hangzhou, China.
Yuqian FengDepartment of Oncology, Hangzhou Traditional Chinese Medicine (TCM) Hospital Affiliated to Zhejiang Chinese Medical University, 310000, Hangzhou, China.
Ying ZhaoThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310000, Hangzhou, China.
Jingyang SuThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310000, Hangzhou, China.
Tianni ZengThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310000, Hangzhou, China.
Yin ChenThe Third Clinical Medical College, Zhejiang Chinese Medical University, 310000, Hangzhou, China.
Kezhan ShenDepartment of Oncology, Hangzhou Traditional Chinese Medicine (TCM) Hospital Affiliated to Zhejiang Chinese Medical University, 310000, Hangzhou, China.
Yewei JiaDepartment of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, 91054, Erlangen, Germany.
Shengyou LinDepartment of Oncology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), 310000, Hangzhou, China.

Funding

Basic Public Welfare Research Plan of Zhejiang Province LY24H290001construction fund of Zhejiang SL's famous traditional Chinese medicine expert inheritance studio project GZS202002special scientific research project of the affiliated hospital of Zhejiang Chinese Medical University 2023FSYYZY02
6 · The paper itself

Abstract

backgroundAccording 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.

objectiveThis study aimed to investigate the role of Keratin 80 (KRT80) in the prognosis of LUAD and its underlying mechanisms.

methodsBioinformatics 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.

resultsScrutiny 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.

conclusionOur 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.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorComputational BiologyLung NeoplasmsHumansKeratins, Type IIPrognosisBiomarkers, TumorKeratins, Type IIbioinformatics analysisKRT80LUADlung adenocarcinomapredictive biomarkerRT-qPCR.

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.