AUTHOR=Fan Dengxia , Yang Moses , Lee Hye Jung , Lee Jeong Hee , Kim Hong Sook 

TITLE=AVEN: a novel oncogenic biomarker with prognostic significance and implications of AVEN-associated immunophenotypes in lung adenocarcinoma

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=10

YEAR=2023

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2023.1265359

DOI=10.3389/fmolb.2023.1265359

ISSN=2296-889X

ABSTRACT=<p><bold>Introduction:</bold> 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).</p><p><bold>Method:</bold> 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 AVEN<sup>high</sup> and AVEN<sup>low</sup> 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.</p><p><bold>Results:</bold> 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 AVEN<sup>high</sup> patients. Furthermore, an AVEN-derived genomic model was established, demonstrating a reliable and improved prognostic value in TCGA and GEO databases.</p><p><bold>Conclusion:</bold> 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.</p>