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pmid:32284751

Prognostic Value of ANXA8 in Gastric Carcinoma.

Fangqi Ma · Xiaowei Li · Haiming Fang · Yueping Jin · Qin Sun · Xuejun Li

Journal of Cancer · 2020 doi:10.7150/jca.40010

Paper

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Experiment

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Data

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Prognostic Value of ANXA8 in Gastric Carcinoma.
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10.7150/jca.40010
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Fangqi Ma
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Xiaowei Li
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Haiming Fang
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Yueping Jin
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Qin Sun
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Xuejun Li
journal
Journal of Cancer
year
2020
abstract
Gastric carcinoma (GC) remains one of the most common and deadly cancers worldwide. In China, the incidence and mortality rates related to GC were quite high. Annexin A8 (ANXA8) is a member of the annexins family of calcium-dependent membrane phospholipid binding proteins. According to recent research, the up-regulation of ANXA8 is closely associated with various types of tumors. However, the specific role of ANXA8 in GC remains unclear. In our study, we explored the prognostic value of ANXA8 in GC. Here, with the data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets (GSE19826 and GSE13861) analyzed, we further performed quantitative real-time polymerase chain reaction (qRT-PCR) using 58 pairs of fresh-frozen tissues. We also subjected 152 pairs of formalin-fixed, paraffin-embedded GC tumor tissues from patients, and the adjacent normal gastric tissues (ANGTs) to immunohistochemical (IHC) analysis. Hence, we found an elevated expression of ANXA8 in tumor tissues with bioinformatics analyses, qRT-PCR, western blot and IHC. Over-expression of ANXA8 was strongly correlated with TNM stages and differentiation grades. Kaplan-Meier and cox proportional-hazard analyses showed that the increased expression of ANXA8 was strongly associated with overall survival (OS) and disease-free survival (DFS) in GC patients. Moreover, we found that ANXA8 is an independent prognostic factor of GC patients' OS and DFS. In brief, those results suggest that ANXA8 can act as an oncogene of GC development and can serve as a potential prognostic biomarker for GC treatment.
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To determine the prognostic value of ANXA8 in GC patients, we performed Kaplan-Meier (KM) analysis.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32284751", "kind": "science-record", "revision": 9, "content_hash": "sha256:1484f7253ca22da57377ed9f75290e27de196152696889256060eec7ced6ce90", "created_at": "2026-11-01T15:40:59Z", "updated_at": "2026-11-01T22:44:44Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Prognostic Value of ANXA8 in Gastric Carcinoma.", "doi": "10.7150/jca.40010", "pmid": "32284751", "authors": ["Fangqi Ma", "Xiaowei Li", "Haiming Fang", "Yueping Jin", "Qin Sun", "Xuejun Li"], "journal": "Journal of Cancer", "year": 2020, "abstract": "Gastric carcinoma (GC) remains one of the most common and deadly cancers worldwide. In China, the incidence and mortality rates related to GC were quite high. Annexin A8 (ANXA8) is a member of the annexins family of calcium-dependent membrane phospholipid binding proteins. According to recent research, the up-regulation of ANXA8 is closely associated with various types of tumors. However, the specific role of ANXA8 in GC remains unclear. In our study, we explored the prognostic value of ANXA8 in GC. Here, with the data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets (GSE19826 and GSE13861) analyzed, we further performed quantitative real-time polymerase chain reaction (qRT-PCR) using 58 pairs of fresh-frozen tissues. We also subjected 152 pairs of formalin-fixed, paraffin-embedded GC tumor tissues from patients, and the adjacent normal gastric tissues (ANGTs) to immunohistochemical (IHC) analysis. Hence, we found an elevated expression of ANXA8 in tumor tissues with bioinformatics analyses, qRT-PCR, western blot and IHC. Over-expression of ANXA8 was strongly correlated with TNM stages and differentiation grades. Kaplan-Meier and cox proportional-hazard analyses showed that the increased expression of ANXA8 was strongly associated with overall survival (OS) and disease-free survival (DFS) in GC patients. Moreover, we found that ANXA8 is an independent prognostic factor of GC patients' OS and DFS. In brief, those results suggest that ANXA8 can act as an oncogene of GC development and can serve as a potential prognostic biomarker for GC treatment.", "claims": [{"id": "claim-method", "statement": "To determine the prognostic value of ANXA8 in GC patients, we performed Kaplan-Meier (KM) analysis.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32284751", "locator": "sections[12] \"Elevated expression of ANXA8 indicated poor prognosis in GC patients\" paragraph 2", "quote": "To determine the prognostic value of ANXA8 in GC patients, we performed Kaplan-Meier (KM) analysis."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The expression data and corresponding clinical information for GC was obtained from The Cancer Genome Atlas (TCGA) (http://gdc.cancer.gov), Gene Expression Omnibus (GEO) GSE19826 and GSE13861 (http://www.ncbi.nlm.nih.gov/geo) datasets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32284751", "locator": "sections[3] \"High-throughput data processing\" paragraph 2", "quote": "The expression data and corresponding clinical information for GC was obtained from The Cancer Genome Atlas (TCGA) (http://gdc.cancer.gov), Gene Expression Omnibus (GEO) GSE19826 and GSE13861 (http://www.ncbi.nlm.nih.gov/geo) datasets."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:32284751"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13861"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE13861"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32284751", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7150/jca.40010", "sha256": 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"analysis": {"state": "partial", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "To determine the prognostic value of ANXA8 in GC patients, we performed Kaplan-Meier (KM) analysis."}}, {"id": "method-2", "family": "group_comparison", "specific": "student_t_test", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["student_t"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Student's t-test"}}, {"id": "method-3", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, 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