DOI: 10.57760/sciencedb.27556
title: ZBED6-Vps34 Autophagic Axis Drives ccRCC Progression via Multi-omics Integration: A Novel Prognostic and Therapeutic Target
title: ZBED6-Vps34 Autophagic Axis Drives ccRCC Progression via Multi-omics Integration: A Novel Prognostic and Therapeutic Target

description: BackgroundClear cell renal cell carcinoma (ccRCC) relies on pro-survival autophagy for therapy resistance and progression, yet upstream regulators of autophagy initiation, particularly the catalytic core Vps34 (PIK3C3), remain poorly defined. We hypothesized that multi-omics integration could identify novel master regulators of Vps34-driven autophagy in ccRCC.Materials and MethodsWe systematically integrated bulk transcriptomics (TCGA, ICGC, ArrayExpress, Target), single-cell RNA-seq (GSE156632), and spatial transcriptomics (GSE210041). Weighted Gene Co-expression Network Analysis (WGCNA) identified Vps34-correlated modules. Ten machine learning algorithms were employed (including Lasso, RSF, CoxBoost) with 10x cross-validation to build prognostic models. In vitro validation used ccRCC cell lines (769-P, Caki-1, ACHN) and normal renal HK-2 cells. Functional assays included qPCR, Western blot, CCK-8 proliferation, wound healing, and Transwell migration/invasion. siRNA knockdown and lentiviral overexpression manipulated ZBED6 expression.ResultsMulti-omics convergence identified the transcription factor ZBED6 as a top upstream regulator strongly correlated with Vps34 expression. Spatial transcriptomics confirmed co-localization of ZBED6 and Vps34 expression domains. ZBED6 directly promoted Vps34 expression and autophagic flux (increased LC3, decreased p62). WGCNA of scRNA-seq data identified a Vps34-associated blue module; intersecting these genes with differential ccRCC genes yielded 23 candidates. Machine learning (Lasso-SuperPC algorithm) constructed a robust 6-gene prognostic signature (ASAH1, ATP1A1, DSTN, EIF1B, PGK1, SCP2) validated across TCGA, ArrayExpress, and RECA cohorts (AUCs up to 0.88). High-risk patients exhibited enriched EMT, inflammatory pathways, immunosuppression (increased Tregs), and poorer response to anti-PD-1 therapy. Functionally, ZBED6 overexpression significantly enhanced ccRCC cell proliferation, migration, invasion, and autophagy, while knockdown suppressed these phenotypes.ConclusionWe identify ZBED6 as a novel master regulator of autophagy initiation in ccRCC via direct transcriptional control of Vps34. The ZBED6-Vps34 axis is critical for ccRCC survival and aggressiveness. Furthermore, the ZBED6/Vps34-derived 6-gene signature provides a powerful prognostic tool and predicts immunotherapy response. Targeting the ZBED6-Vps34 axis represents a promising therapeutic strategy to disrupt pro-tumorigenic autophagy in ccRCC.
description: BackgroundClear cell renal cell carcinoma (ccRCC) relies on pro-survival autophagy for therapy resistance and progression, yet upstream regulators of autophagy initiation, particularly the catalytic core Vps34 (PIK3C3), remain poorly defined. We hypothesized that multi-omics integration could identify novel master regulators of Vps34-driven autophagy in ccRCC.Materials and MethodsWe systematically integrated bulk transcriptomics (TCGA, ICGC, ArrayExpress, Target), single-cell RNA-seq (GSE156632), and spatial transcriptomics (GSE210041). Weighted Gene Co-expression Network Analysis (WGCNA) identified Vps34-correlated modules. Ten machine learning algorithms were employed (including Lasso, RSF, CoxBoost) with 10x cross-validation to build prognostic models. In vitro validation used ccRCC cell lines (769-P, Caki-1, ACHN) and normal renal HK-2 cells. Functional assays included qPCR, Western blot, CCK-8 proliferation, wound healing, and Transwell migration/invasion. siRNA knockdown and lentiviral overexpression manipulated ZBED6 expression.ResultsMulti-omics convergence identified the transcription factor ZBED6 as a top upstream regulator strongly correlated with Vps34 expression. Spatial transcriptomics confirmed co-localization of ZBED6 and Vps34 expression domains. ZBED6 directly promoted Vps34 expression and autophagic flux (increased LC3, decreased p62). WGCNA of scRNA-seq data identified a Vps34-associated blue module; intersecting these genes with differential ccRCC genes yielded 23 candidates. Machine learning (Lasso-SuperPC algorithm) constructed a robust 6-gene prognostic signature (ASAH1, ATP1A1, DSTN, EIF1B, PGK1, SCP2) validated across TCGA, ArrayExpress, and RECA cohorts (AUCs up to 0.88). High-risk patients exhibited enriched EMT, inflammatory pathways, immunosuppression (increased Tregs), and poorer response to anti-PD-1 therapy. Functionally, ZBED6 overexpression significantly enhanced ccRCC cell proliferation, migration, invasion, and autophagy, while knockdown suppressed these phenotypes.ConclusionWe identify ZBED6 as a novel master regulator of autophagy initiation in ccRCC via direct transcriptional control of Vps34. The ZBED6-Vps34 axis is critical for ccRCC survival and aggressiveness. Furthermore, the ZBED6/Vps34-derived 6-gene signature provides a powerful prognostic tool and predicts immunotherapy response. Targeting the ZBED6-Vps34 axis represents a promising therapeutic strategy to disrupt pro-tumorigenic autophagy in ccRCC.