Evidence map›Paper›PMID 39430828›Full record

ArticleTranslational cancer research2024

Prognostic value of PLEKHA4 and its correlation with tumor-infiltrating immune cells in breast cancer: a comprehensive study based on bioinformatics and clinical analysis validation.

Liu Li, Zewen Feng, Ye Zhao, Boan Lai, Qingxin Zhang, Zhongtang Xiong, Wei Zhang

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Article in Translational cancer research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Liu Li *Department of Digestion, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Zewen Feng *Department of Pathology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Ye Zhao *Department of Pathology, Zhuhai Hospital of Integrated Traditional Chinese and Western Medicine, Zhuhai, China.
Boan LaiDepartment of Digestion, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Qingxin ZhangDepartment of Digestion, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Zhongtang XiongDepartment of Pathology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.
Wei ZhangDepartment of Pathology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital, Guangzhou Medical University, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pleckstrin homology containing family A, number 4 (PLEKHA4) plays a role in a number of biological processes in human cells, including cell polarization, growth, and proliferation. However, the relationship between PLEKHA4 expression and survival in breast cancer (BC) remains unclear. The aim of this study is to investigate the potential of PLEKHA4 as a prognostic indicator in BC. Methods: We obtained gene expression profiles of BC and normal tissues from the Tumor Immune Estimation Resource (TIMER), UALCAN web. Immunohistochemistry (IHC) staining was performed to investigate the protein expression and prognostic value of PLEKHA4 in BC patients. The prognostic value was analyzed using Kaplan-Meier curve analysis and Cox regression analysis in R software after downloading The Cancer Genome Atlas (TCGA) databases. The correlations between PLEKHA4 and tumor immune infiltrates were investigated via gene set variation analysis (GSVA). Signaling pathways related to PLEKHA4 expression were identified by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Results: Both bioinformatics and IHC results showed that PLEKHA4 was expressed at low levels in BC tissues compared with the adjacent tissues. Furthermore, the expression of PLEKHA4 was negatively correlated with ages (χ Conclusions: The findings indicate that PLEKHA4 is an independent prognostic biomarker associated with key signaling pathways and immune infiltration in BC. Targeting PLEKHA4 may contribute to improving immunotherapy for BC.

Indexed as

breast cancer (BC)immune infiltratesPleckstrin homology containing family A, number 4 (PLEKHA4)prognosistissue microarray (TMA)

Identifiers

PMID39430828
PMCPMC11483419

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