ArticleFrontiers in surgery2022
Prognostic value and immunological role of BAIAP2L2 in liver hepatocellular carcinoma: A pan-cancer analysis.
Article in Frontiers in surgery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- BAIAP2L2 facilitates hepatocellular carcinoma progression and immune evasion of via targeting JAK1-mediated pathway and PD-L1 expression.Cancer gene therapy · 2025Article
- Establishment of a Lactylation-Related Gene Signature for Hepatocellular Carcinoma Applying Bulk and Single-Cell RNA Sequencing Analysis.International journal of genomics · 2025Article
- Identification of HPV oncogene and host cell differentiation associated cellular heterogeneity in cervical cancer via single-cell transcriptomic analysis.bioRxiv : the preprint server for biology · 2023Article
- BAIAP2L2 is a novel prognostic biomarker related to migration and invasion of HCC and associated with cuprotosis.Scientific reports · 2023Article
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Abstract
Background: In recent years, the role of BAI1-associated protein 2-like 2 (BAIAP2L2) in the prognosis and immune microenvironment of various cancers has attracted increasing attention. However, its clinical value and immune infiltration in liver hepatocellular carcinoma (LIHC) remain unclear. Objective: To investigate the prognostic value of BAIAP2L2 and its correlation with immune infiltration in LIHC, we conducted corresponding data mining. Methods: In this study, The Cancer Genome Atlas, GTEx, StarBase, UALCAN, TIMER, GEPIA, Human Protein Atlas, Kaplan-Meier Plotter, cBioPortal, LinkedOmics, STRING and BioGPS databases were used to analyze BAIAP2L2 in cancers. Logistic regression and Cox regression were performed to analyze the correlation between clinical features and BAIAP2L2 expression in LIHC. In addition, the diagnostic and prognostic values of BAIAP2L2 in LIHC were determined by receiver operating characteristic (ROC) curves and nomograms. Single-sample gene set enrichment analysis (ssGSEA), BioGPS and TIMER were used to analyze the correlation between BAIAP2L2 and immune infiltration. More importantly, quantitative real-time polymerase chain reaction was used to verify BAIAP2L2 expression in a liver cancer cell line and a normal cell line. Visualization of data was mostly achieved using R language, version 3.6.3. Results: High BAIAP2L2 levels indicated poor overall survival (OS) and disease-free survival (DFS) of patients with LIHC. Abnormally increased expression of BAIAP2L2 in LIHC may be the result of both genetic alterations and lower DNA methylation levels. Furthermore, Cox regression analysis showed that high BAIAP2L2 expression was an independent risk factor for OS and DFS in patients with liver cancer. ROC curves and nomograms also confirmed the diagnostic and prognostic values of BAIAP2L2 in LIHC. Additionally, a PPI network of BAIAP2L2 was established and results implyed that BAIAP2L2 interacts with MTSS1, AMPH, FCHO1, SYT9, PDK2, MTSS1L, PM20D1, CHST4 and PALM3. ssGSEA showed that BAIAP2L2 was associated with T cells and natural killer cells. Simultaneously, the TIMER database showed that the expression of BAIAP2L2 in LIHC was positively correlated with tumor infiltrating cells, including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells. Conclusions: Through pan-cancer analysis, prognostic and immunological value of BAIAP2L2 in LIHC was identified. This is the first report on the potential of BAIAP2L2 as a prognostic biomarker and its correlation with immune infiltration in LIHC.
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