Low KCNQ1 expression is associated with unfavorable outcome and metabolism of gastric cancer
AJTR Copyright © 2023..
BACKGROUND: Potassium voltage-gated channel subfamily Q member 1 (KCNQ1), is implicated in the onset and progression of gastric carcinoma (GC), one of the most common types of stomach malignancies. This research aims to investigate the potential prognostic implications of KCNQ1 mRNA in GC using various databases such as The Cancer Genome Atlas (TCGA), The Human Protein Atlas (HPA), LinkedOmics, TISIDB, ESTIMATE, and TIMER.
METHODS: We searched the HPA database to obtain information on KCNQ1 levels in human normal tissues, organs, and cell lines as well as in pan-cancer tissues. Then, we used TIMER and UALCAN to comparatively analyze the KCNQ1 mRNA levels in different types of cancers relative to their adjacent normal counterparts. Based on TCGA and Gene Expression Omnibus, the correlation of clinical information with KCNQ1 expression was analyzed using logistic regression model. Univariable and Multivariate Cox analyses were then carried out to compare differences in survival among patients with different clinical characteristics. The multivariate methods, such as Kaplan-Meier plotter and GEPIA survival curves, were further employed to identify the correlation of KCNQ1 expression with overall survival (OS). Besides, LinkedOmics was used to identify differentially expressed genes for functional enrichment analysis.
RESULTS: KCNQ1 exhibited tissue-specific imprinting and expression in human normal tissues, organs and cell lines, while it was aberrantly expressed in pan-cancer tissues. Lower KCNQ1 mRNA expression was determined in GC tissue samples versus normal counterparts. In GC cases, elevated KCNQ1 levels were strongly linked to a longer OS and strongly correlated with invasion depth (χ2=12.631, P=0.006), TNM stage (χ2=8.750, P=0.033), differentiation grade (χ2=7.426, P=0.024), and vital status (χ2=5.676, P=0.017). Furthermore, KCNQ1 was identified by univariable and multivariate Cox analyses as an independent risk factor for GC. Based on Gene Ontology analysis, digestion as well as tricarboxylic acid metabolic, carbohydrate catabolic, and small molecule catabolic processes were differentially enriched in the up-regulated KCNQ1 phenotypic pathway. While carbon metabolism, fatty acid degradation, peroxisome, and citrate cycle (TCA cycle) were identified by the Kyoto Encyclopedia of Genes and Genomes-based analysis as pathways with differential enrichment.
CONCLUSION: Being a prognostic biomarker, KCNQ1 may play an inhibitory role and involve in the metabolic process of GC.
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
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| Enthalten in: |
American journal of translational research - 15(2023), 6 vom: 30., Seite 3992-4005 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Yang, Zhenyu [VerfasserIn] |
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| Themen: |
Bioinformatics |
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| Anmerkungen: |
Date Revised 18.07.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| Förderinstitution / Projekttitel: |
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NLM359356710 |
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| 100 | 1 | |a Yang, Zhenyu |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Low KCNQ1 expression is associated with unfavorable outcome and metabolism of gastric cancer |
| 264 | 1 | |c 2023 | |
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| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a AJTR Copyright © 2023. | ||
| 520 | |a BACKGROUND: Potassium voltage-gated channel subfamily Q member 1 (KCNQ1), is implicated in the onset and progression of gastric carcinoma (GC), one of the most common types of stomach malignancies. This research aims to investigate the potential prognostic implications of KCNQ1 mRNA in GC using various databases such as The Cancer Genome Atlas (TCGA), The Human Protein Atlas (HPA), LinkedOmics, TISIDB, ESTIMATE, and TIMER | ||
| 520 | |a METHODS: We searched the HPA database to obtain information on KCNQ1 levels in human normal tissues, organs, and cell lines as well as in pan-cancer tissues. Then, we used TIMER and UALCAN to comparatively analyze the KCNQ1 mRNA levels in different types of cancers relative to their adjacent normal counterparts. Based on TCGA and Gene Expression Omnibus, the correlation of clinical information with KCNQ1 expression was analyzed using logistic regression model. Univariable and Multivariate Cox analyses were then carried out to compare differences in survival among patients with different clinical characteristics. The multivariate methods, such as Kaplan-Meier plotter and GEPIA survival curves, were further employed to identify the correlation of KCNQ1 expression with overall survival (OS). Besides, LinkedOmics was used to identify differentially expressed genes for functional enrichment analysis | ||
| 520 | |a RESULTS: KCNQ1 exhibited tissue-specific imprinting and expression in human normal tissues, organs and cell lines, while it was aberrantly expressed in pan-cancer tissues. Lower KCNQ1 mRNA expression was determined in GC tissue samples versus normal counterparts. In GC cases, elevated KCNQ1 levels were strongly linked to a longer OS and strongly correlated with invasion depth (χ2=12.631, P=0.006), TNM stage (χ2=8.750, P=0.033), differentiation grade (χ2=7.426, P=0.024), and vital status (χ2=5.676, P=0.017). Furthermore, KCNQ1 was identified by univariable and multivariate Cox analyses as an independent risk factor for GC. Based on Gene Ontology analysis, digestion as well as tricarboxylic acid metabolic, carbohydrate catabolic, and small molecule catabolic processes were differentially enriched in the up-regulated KCNQ1 phenotypic pathway. While carbon metabolism, fatty acid degradation, peroxisome, and citrate cycle (TCA cycle) were identified by the Kyoto Encyclopedia of Genes and Genomes-based analysis as pathways with differential enrichment | ||
| 520 | |a CONCLUSION: Being a prognostic biomarker, KCNQ1 may play an inhibitory role and involve in the metabolic process of GC | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a KCNQ1 | |
| 650 | 4 | |a TCGA | |
| 650 | 4 | |a bioinformatics | |
| 650 | 4 | |a gastric carcinoma (GC) | |
| 650 | 4 | |a metabolic process | |
| 650 | 4 | |a prognosis | |
| 700 | 1 | |a Duan, Sensen |e verfasserin |4 aut | |
| 700 | 1 | |a Hu, Xi'e |e verfasserin |4 aut | |
| 700 | 1 | |a Dai, Baishu |e verfasserin |4 aut | |
| 700 | 1 | |a Bao, Guoqiang |e verfasserin |4 aut | |
| 700 | 1 | |a Xin, Wei |e verfasserin |4 aut | |
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