ArticleJournal of oncology2022
Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer.
Article in Journal of oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 5 citations in OpenAlex.
- Integrated Multi-Omics Analysis Constructs an Intratumoral Heterogeneity-Corrected Prognostic Signature for Cervical Cancer.International journal of general medicine · 2026Article
- Gene dysregulation in acute HIV-1 infection - early transcriptomic analysis reveals the crucial biological functions affected.Frontiers in cellular and infection microbiology · 2023Article
- Development and validation of cancer-associated fibroblasts-related gene landscape in prognosis and immune microenvironment of bladder cancer.Frontiers in oncology · 2023Article
- Exploration of hub genes, lipid metabolism, and the immune microenvironment in stomach carcinoma and cholangiocarcinoma.Annals of translational medicine · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 (
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Registered trials
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