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Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer

ARMCX1 (Armadillo repeat containing X-linked 1) is identified to be the novel tumor suppressor gene related to multiple tumor types. Nonetheless, its effect on gastric cancer (GC) is still poorly understood. The present work determined ARMCX1 level within GC and the relation with clinicopathological...

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Detalles Bibliográficos
Autores principales: Xie, Aosi, Wang, Puyu, Chen, Diqun, Zhang, Hongxia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9098325/
https://www.ncbi.nlm.nih.gov/pubmed/35571487
http://dx.doi.org/10.1155/2022/9348917
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author Xie, Aosi
Wang, Puyu
Chen, Diqun
Zhang, Hongxia
author_facet Xie, Aosi
Wang, Puyu
Chen, Diqun
Zhang, Hongxia
author_sort Xie, Aosi
collection PubMed
description ARMCX1 (Armadillo repeat containing X-linked 1) is identified to be the novel tumor suppressor gene related to multiple tumor types. Nonetheless, its effect on gastric cancer (GC) is still poorly understood. The present work determined ARMCX1 level within GC and the relation with clinicopathological characteristics. This work also collected relevant information in The Cancer Genome Atlas (TCGA) database for investigating associations of ARMCX1 with clinicopathologic variables and then validated in our GC cohort. Receiver operating characteristic (ROC) curves were plotted for assessing whether ARMCX1 expression was significant in diagnosing GC. Kaplan-Meier (KM) and Cox regression analyses were conducted for assessing clinicopathological characteristics associated with overall survival (OS) of GC cases. The data from the Human Protein Atlas (HPA) and Gene Expression Omnibus (GEO) databases was also analyzed for further validation, and biological processes (BPs) were identified by gene set enrichment analysis (GSEA). GC tissues showed markedly decreased ARMCX1 level relative to healthy counterparts (P < 0.001). Interestingly, ARMCX1 upregulation predicted low differentiation, poor OS, increased invasion, and late tumor stage. In addition, the area under ROC curve (AUC) and P value were 0.747 and <0.001, separately. Cases showing ARMCX1 upregulation showed significantly poor prognostic outcome compared with patients showing downregulation (P = 0.007). Furthermore, multivariate analysis showed that ARMCX1 upregulation independently predicted the risk of OS (P = 0.0017, hazard ratio, 1.089). GSEA analysis identified that several cancer-related pathways, such as focal adhesion, ECM receptor interaction, JAK/STAT, melanoma, WNT, and cancer, were enriched in GCs. We conclude that ARMCX1 serves as the possibly independent biomarker to diagnose and predict GC prognostic outcome.
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spelling pubmed-90983252022-05-13 Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer Xie, Aosi Wang, Puyu Chen, Diqun Zhang, Hongxia J Oncol Research Article ARMCX1 (Armadillo repeat containing X-linked 1) is identified to be the novel tumor suppressor gene related to multiple tumor types. Nonetheless, its effect on gastric cancer (GC) is still poorly understood. The present work determined ARMCX1 level within GC and the relation with clinicopathological characteristics. This work also collected relevant information in The Cancer Genome Atlas (TCGA) database for investigating associations of ARMCX1 with clinicopathologic variables and then validated in our GC cohort. Receiver operating characteristic (ROC) curves were plotted for assessing whether ARMCX1 expression was significant in diagnosing GC. Kaplan-Meier (KM) and Cox regression analyses were conducted for assessing clinicopathological characteristics associated with overall survival (OS) of GC cases. The data from the Human Protein Atlas (HPA) and Gene Expression Omnibus (GEO) databases was also analyzed for further validation, and biological processes (BPs) were identified by gene set enrichment analysis (GSEA). GC tissues showed markedly decreased ARMCX1 level relative to healthy counterparts (P < 0.001). Interestingly, ARMCX1 upregulation predicted low differentiation, poor OS, increased invasion, and late tumor stage. In addition, the area under ROC curve (AUC) and P value were 0.747 and <0.001, separately. Cases showing ARMCX1 upregulation showed significantly poor prognostic outcome compared with patients showing downregulation (P = 0.007). Furthermore, multivariate analysis showed that ARMCX1 upregulation independently predicted the risk of OS (P = 0.0017, hazard ratio, 1.089). GSEA analysis identified that several cancer-related pathways, such as focal adhesion, ECM receptor interaction, JAK/STAT, melanoma, WNT, and cancer, were enriched in GCs. We conclude that ARMCX1 serves as the possibly independent biomarker to diagnose and predict GC prognostic outcome. Hindawi 2022-05-05 /pmc/articles/PMC9098325/ /pubmed/35571487 http://dx.doi.org/10.1155/2022/9348917 Text en Copyright © 2022 Aosi Xie et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Xie, Aosi
Wang, Puyu
Chen, Diqun
Zhang, Hongxia
Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer
title Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer
title_full Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer
title_fullStr Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer
title_full_unstemmed Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer
title_short Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer
title_sort aberrant armcx1 expression is an independent predictor of poor prognosis in gastric cancer
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9098325/
https://www.ncbi.nlm.nih.gov/pubmed/35571487
http://dx.doi.org/10.1155/2022/9348917
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