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DataSheet1_AVEN: a novel oncogenic biomarker with prognostic significance and implications of AVEN-associated immunophenotypes in lung adenocarcinoma.ZIP

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frontiersin.figshare.com2023-10-16 更新2025-01-22 收录
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https://frontiersin.figshare.com/articles/dataset/DataSheet1_AVEN_a_novel_oncogenic_biomarker_with_prognostic_significance_and_implications_of_AVEN-associated_immunophenotypes_in_lung_adenocarcinoma_ZIP/24313096/1
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Introduction: AVEN, an apoptosis and caspase activation inhibitor, has been associated with adverse clinical outcomes and poor prognosis in Acute myeloid leukemia (AML). Targeting AVEN in AML improves apoptosis sensitivity and chemotherapy efficacy, making it a promising therapeutic target. However, AVEN’s role has not been studied in solid tumors. Therefore, our study investigated AVEN as a prognostic biomarker in a more comprehensive manner and developed an AVEN-derived prognostic model in Lung adenocarcinoma (LUAD).Method: Pan-cancer analysis was performed to examine AVEN expression in 33 cancer types obtained from the TCGA database. GEPIA analysis was used to determine the predictive value of AVEN in each cancer type with cancer-specific AVEN expression. Lung Adenocarcinomas (LUAD) patients were grouped into AVENhigh and AVENlow based on AVEN expression level. Differentially expressed genes (DEGs) and pathway enrichment analysis were performed to gain insight into the biological function of AVEN in LUAD. In addition, several deconvolution tools, including Timer, CIBERSORT, EPIC, xCell, Quanti-seq and MCP-counter were used to explore immune infiltration. AVEN-relevant prognostic genes were identified by Random Survival Forest analysis via univariate Cox regression. The AVEN-derived genomic model was established using a multivariate-Cox regression model and GEO datasets (GSE31210, GSE50081) were used to validate its prognostic effect.Results: AVEN expression was increased in several cancer types compared to normal tissue, but its impact on survival was only significant in LUAD in the TCGA cohort. High AVEN expression was significantly correlated with tumor progression and shorter life span in LUAD patients. Pathway analysis was performed with 838 genes associated with AVEN expression and several oncogenic pathways were altered such as the Cell cycle, VEGFA-VEGFR2 pathway, and epithelial-mesenchymal-transition pathway. Immune infiltration was also analyzed, and less infiltrated B cells was observed in AVENhigh patients. Furthermore, an AVEN-derived genomic model was established, demonstrating a reliable and improved prognostic value in TCGA and GEO databases.Conclusion: This study provided evidence that AVEN is accumulated in LUAD compared to adjacent tissue and is associated with poor survival, high tumor progression, and immune infiltration alteration. Moreover, the study introduced the AVEN-derived prognostic model as a promising prognosis tool for LUAD.

引言:AVEN(凋亡和caspase激活抑制剂)与急性髓系白血病(AML)的恶劣临床结果和不良预后相关联。针对AML中的AVEN可以提高细胞凋亡敏感性和化疗效果,使其成为一项有前景的治疗靶点。然而,AVEN在实体瘤中的作用尚未得到研究。因此,本研究从更全面的角度探讨了AVEN作为预后生物标志物的作用,并在肺腺癌(LUAD)中开发了基于AVEN的预后模型。方法:通过对TCGA数据库中获得的33种癌症类型的全癌分析,检验了AVEN的表达。使用GEPIA分析确定了AVEN在每种癌症类型中的预测价值以及癌症特异性的AVEN表达。根据AVEN的表达水平,将肺腺癌(LUAD)患者分为AVENhigh和AVENlow组。通过差异表达基因(DEGs)和通路富集分析,深入探讨了AVEN在LUAD中的生物学功能。此外,还使用了Timer、CIBERSORT、EPIC、xCell、Quanti-seq和MCP-counter等几种解卷积工具,以探索免疫浸润。通过单变量Cox回归的随机生存森林分析,确定了与AVEN相关的预后基因。利用多变量Cox回归模型和GEO数据集(GSE31210、GSE50081)建立了AVEN衍生的基因组模型,并用于验证其预后效果。结果:与正常组织相比,AVEN在多种癌症类型中的表达增加,但在TCGA队列中其对生存的影响仅在LUAD中显著。高AVEN表达与LUAD患者的肿瘤进展和较短的生命周期显著相关。对与AVEN表达相关的838个基因进行了通路分析,发现细胞周期、VEGFA-VEGFR2通路和上皮-间质转化通路等几个致癌通路发生了改变。免疫浸润分析也表明,在AVENhigh患者中观察到较少的B细胞浸润。此外,建立了基于AVEN的基因组模型,在TCGA和GEO数据库中显示出可靠的预后价值。结论:本研究提供了证据,表明与相邻组织相比,AVEN在LUAD中积累,与不良生存、高肿瘤进展和免疫浸润改变相关。此外,本研究引入的基于AVEN的预后模型,作为LUAD的有前景的预后工具。
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