Pan-cancer multi-omics reveals DCAF7 as an immune-modulating prognostic driver and Wnt/β-catenin activator in hepatocellular carcinoma

Abstract

Background: DDB1 and CUL4-associated factor 7 (DCAF7) is a WD-repeat adaptor that recruits substrates to the CUL4DDB1 ubiquitinligase complex, but its pan-cancer relevance and mechanistic contribution to tumor progression remain unclear.

Methods: Multi-omics datasets (genomic, transcriptomic, epigenomic, proteomic and single-cell) from 33 tumor types were integrated to define DCAF7 expression, regulation, and clinical significance. Somatic alterations and copy-number variation were analysed across cohorts, and promoter methylation and RNA modification signatures were interrogated. Immune associations were assessed by computational deconvolution and checkpoint-gene profiling. Pathway and network analyses were performed to infer DCAF7-linked programmes. Mechanistic and functional validation was conducted in hepatocellular carcinoma (LIHC) cell lines (HepG2, Huh7) using DCAF7 perturbation and pharmacologic Wnt inhibition.

Results: DCAF7 was overexpressed in most cancers, consistent with copy-number gain, focal promoter hypomethylation and putative m⁶A-linked post-transcriptional regulation, whereas hypermethylation at two CpG loci predicted poor prognosis in LIHC. DCAF7 alterations, predominantly amplifications, were associated with shorter overall survival in LIHC and positively correlated with DCAF7 mRNA abundance across cohorts. Immunogenomic analyses linked high DCAF7 to CD4⁺ T-cell enrichment, broad upregulation of checkpoint genes (PD-1/PD-L1, CTLA-4, TIGIT), and increased tumour mutational burden, microsatellite instability and neoantigen load, suggesting an immune-evasive phenotype. Network and enrichment analyses converged on canonical Wnt/β-catenin, Hippo and cell-cycle programs. In vitro, DCAF7 promoted LIHC cell proliferation and migration by stabilising β-catenin via increased inhibitory Ser9 phosphorylation of GSK-3β, thereby inducing c-Myc and cyclin D1; DCAF7 knockdown or the Wnt inhibitor XAV939 attenuated these effects. Drug-response modelling further predicted increased sensitivity of DCAF7-high tumours to 17-AAG, docetaxel and alsterpaullone.

Conclusions: DCAF7 is frequently activated by genetic and epigenetic mechanisms across cancers, associates with an immunotherapy-relevant tumour immune milieu, and drives Wnt/β-catenindependent malignant phenotypes in LIHC. These findings support DCAF7 as a prognostic biomarker and a candidate therapeutic target, particularly for stratified intervention in LIHC.

Keywords

DCAF7 / hepatocellular carcinoma / immune infiltration / pan-cancer / Wnt signalling

References

[1] Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024; 74(3): 229-263.

[2] Bray F, Laversanne M, Weiderpass E, Soerjomataram I. The ever-increasing importance of cancer as a leading cause of premature death worldwide. Cancer. 2021; 127(16): 3029-3030.

[3] Chen S, Cao Z, Prettner K, et al. Estimates and projections of the global economic cost of 29 cancers in 204 countries and territories from 2020 to 2050. JAMA Oncol. 2023; 9(4): 465-472.

[4] Srivastava S, Hanash S. Pan-cancer early detection: hype or hope?. Cancer Cell. 2020; 38(1): 23-24.

[5] Vis DJ, Jaaks P, Aben N, et al. A pan-cancer screen identifies drug combination benefit in cancer cell lines at the individual and population level. Cell Rep Med. 2024; 5(8):101687.

[6] Wegmann R, Bankel L, Festl Y, et al. Molecular and functional landscape of malignant serous effusions for precision oncology. Nat Commun. 2024; 15(1): 8544.

[7] DiRusso CJ, Dashtiahangar M, Gilmore TD. Scaffold proteins as dynamic integrators of biological processes. J Biol Chem. 2022; 298(12):102628.

[8] Faux MC, Scott JD. Molecular glue: kinase anchoring and scaffold proteins. Cell. 1996; 85(1): 9-12.

[9] Shaw AS, Filbert EL. Scaffold proteins and immune-cell signalling. Nat Rev Immunol. 2009; 9(1): 47-56.

[10] Stirnimann CU, Petsalaki E, Russell RB, Müller CW. WD40 proteins propel cellular networks. Trends Biochem Sci. 2010; 35(10): 565-574.

[11] Peng Z, Liao Z, Matsumoto Y, Yang A, Tomkinson AE. Human DNA ligase I interacts with and is targeted for degradation by the DCAF7 specificity factor of the Cul4-DDB1 ubiquitin ligase complex. J Biol Chem. 2016; 291(42): 21893-21902.

[12] Xu J, Ye Z, Zhuo Q, et al. MEN1 degradation induced by neddylation and the CUL4B-DCAF7 axis promotes pancreatic neuroendocrine tumor progression. Cancer Res. 2023; 83(13): 2226-2247.

[13] Li QJ, Fang XL, Li YQ, et al. DCAF7 acts as a scaffold to recruit USP10 for G3BP1 deubiquitylation and facilitates chemoresistance and metastasis in nasopharyngeal carcinoma. Adv Sci (Weinh). 2024; 11(36):e2403262.

[14] Glenewinkel F, Cohen MJ, King CR, et al. The adaptor protein DCAF7 mediates the interaction of the adenovirus E1A oncoprotein with the protein kinases DYRK1A and HIPK2. Sci Rep. 2016; 6:28241.

[15] Kiri S, Ryba T. Cancer, metastasis, and the epigenome. Mol Cancer. 2024; 23(1): 154.

[16] Smith ZD, Hetzel S, Meissner A. DNA methylation in mammalian development and disease. Nat Rev Genet. 2025; 26(1): 7-30.

[17] Lin S, Kuang M. RNA modification-mediated mRNA translation regulation in liver cancer: mechanisms and clinical perspectives. Nat Rev Gastroenterol Hepatol. 2024; 21(4): 267-281.

[18] Zhao BS, Roundtree IA, He C. Post-transcriptional gene regulation by mRNA modifications. Nat Rev Mol Cell Biol. 2017; 18(1): 31-42.

[19] Flamand MN, Tegowski M, Meyer KD. The proteins of mRNA modification: writers, readers, and erasers. Annu Rev Biochem. 2023; 92: 145-173.

[20] Elhanani O, Ben-Uri R, Keren L. Spatial profiling technologies illuminate the tumor microenvironment. Cancer Cell. 2023; 41(3): 404-420.

[21] Kureshi CT, Dougan SK. Cytokines in cancer. Cancer Cell. 2025; 43(1): 15-35.

[22] Liu Y, Wang Y, Yang Y, et al. Emerging phagocytosis checkpoints in cancer immunotherapy. Signal Transduct Target Ther. 2023; 8(1): 104.

[23] Xie N, Shen G, Gao W, Huang Z, Huang C, Fu L. Neoantigens: promising targets for cancer therapy. Signal Transduct Target Ther. 2023; 8(1): 9.

[24] Wang X, Lamberti G, Di Federico A, et al. Tumor mutational burden for the prediction of PD-(L)1 blockade efficacy in cancer: challenges and opportunities. Ann Oncol. 2024; 35(6): 508-522.

[25] Zhao P, Li L, Jiang X, Li Q. Mismatch repair deficiency/microsatellite instability-high as a predictor for anti-PD-1/PD-L1 immunotherapy efficacy. J Hematol Oncol. 2019; 12(1): 54.

[26] Frame S, Cohen P, Biondi RM. A common phosphate binding site explains the unique substrate specificity of GSK3 and its inactivation by phosphorylation. Mol Cell. 2001; 7(6): 1321-1327.

[27] de Vetten N, Quattrocchio F, Mol J, Koes R. The an11 locus controlling flower pigmentation in petunia encodes a novel WD-repeat protein conserved in yeast, plants, and animals. Genes Dev. 1997; 11(11): 1422-1434.

[28] Nissen RM, Amsterdam A, Hopkins N. A zebrafish screen for craniofacial mutants identifies wdr68 as a highly conserved gene required for endothelin-1 expression. BMC Dev Biol. 2006; 6: 28.

[29] Morriss GR, Jaramillo CT, Mikolajczak CM, Duong S, Jaramillo MS, Cripps RM. The Drosophila wings apart gene anchors a novel, evolutionarily conserved pathway of neuromuscular development. Genetics. 2013; 195(3): 927-940.

[30] Morita K, Lo Celso C, Spencer-Dene B, Zouboulis CC, Watt FM. HAN11 binds mDia1 and controls GLI1 transcriptional activity. J Dermatol Sci. 2006; 44(1): 11-20.

[31] Ritterhoff S, Farah CM, Grabitzki J, Lochnit G, Skurat AV, Schmitz ML. The WD40-repeat protein Han11 functions as a scaffold protein to control HIPK2 and MEKK1 kinase functions. EMBO J. 2010; 29(22): 3750-3761.

[32] Yu D, Cattoglio C, Xue Y, Zhou Q. A complex between DYRK1A and DCAF7 phosphorylates the C-terminal domain of RNA polymerase II to promote myogenesis. Nucleic Acids Res. 2019; 47(9): 4462-4475.

[33] Frendo-Cumbo S, Li T, Ammendolia DA, et al. DCAF7 regulates cell proliferation through IRS1-FOXO1 signaling. iScience. 2022; 25(10):105188.

[34] Qin Q, Ruan H, Zhang H, et al. Deubiquitinase MYSM1: an important tissue development and function regulator. Int J Mol Sci. 2024; 25(23).

[35] Ju Y, Fang S, Liu L, Ma H, Zheng L. The function of the ELF3 gene and its mechanism in cancers. Life Sci. 2024; 346:122637.

[36] Li Y, Porta-Pardo E, Tokheim C, et al. Pan-cancer proteogenomics connects oncogenic drivers to functional states. Cell. 2023; 186(18): 3921-3944. e25.

[37] Martincorena I, Campbell PJ. Somatic mutation in cancer and normal cells. Science. 2015; 349(6255): 1483-1489.

[38] Dawson MA, Kouzarides T. Cancer epigenetics: from mechanism to therapy. Cell. 2012; 150(1): 12-27.

[39] Nishiyama A, Nakanishi M. Navigating the DNA methylation landscape of cancer. Trends Genet. 2021; 37(11): 1012-1027.

[40] Hinshaw DC, Shevde LA. The tumor microenvironment innately modulates cancer progression. Cancer Res. 2019; 79(18): 4557-4566.

[41] Glaviano A, Lau HS, Carter LM, et al. Harnessing the tumor microenvironment: targeted cancer therapies through modulation of epithelial-mesenchymal transition. J Hematol Oncol. 2025; 18(1): 6.

[42] He X, Xu C. Immune checkpoint signaling and cancer immunotherapy. Cell Res. 2020; 30(8): 660-669.

[43] Angers S, Moon RT. Proximal events in Wnt signal transduction. Nat Rev Mol Cell Biol. 2009; 10(7): 468-477.

[44] Ruiz de Galarreta M, Bresnahan E, Molina-Sánchez P, et al. β-Catenin activation promotes immune escape and resistance to anti-PD-1 therapy in hepatocellular carcinoma. Cancer Discov. 2019; 9(8): 1124-1141.

[45] Xu C, Xu Z, Zhang Y, Evert M, Calvisi DF, Chen X. Catenin signaling in hepatocellular carcinoma. J Clin Invest. 2022; 132(4).

[46] Mariotti L, Pollock K, Guettler S. Regulation of Wnt/β-catenin signalling by tankyrase-dependent poly(ADP-ribosyl)ation and scaffolding. Br J Pharmacol. 2017; 174(24): 4611-4636.

[47] Goldman MJ, Craft B, Hastie M, et al. Visualizing and interpreting cancer genomics data via the Xena platform. Nat Biotechnol. 2020; 38(6): 675-678.

[48] Vivian J, Rao AA, Nothaft FA, et al. Toil enables reproducible, open source, big biomedical data analyses. Nat Biotechnol. 2017; 35(4): 314-316.

[49] Li T, Fu J, Zeng Z, et al. TIMER2.0 for analysis of tumor-infiltrating immune cells. Nucleic Acids Res. 2020; 48(W1): W509-w514.

[50] Chandrashekar DS, Karthikeyan SK, Korla PK, et al. UALCAN: an update to the integrated cancer data analysis platform. Neoplasia. 2022; 25: 18-27.

[51] Thul PJ, Lindskog C. The human protein atlas: a spatial map of the human proteome. Protein Sci. 2018; 27(1): 233-244.

[52] Liu J, Lichtenberg T, Hoadley KA, et al. An integrated TCGA pan-cancer clinical data resource to drive high-quality survival outcome analytics. Cell. 2018; 173(2): 400-416. e11.

[53] Cerami E, Gao J, Dogrusoz U, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012; 2(5): 401-404.

[54] Liu CJ, Hu FF, Xie GY, et al. GSCA: an integrated platform for gene set cancer analysis at genomic, pharmacogenomic and immunogenomic levels. Brief Bioinform. 2023; 24(1).

[55] Modhukur V, Iljasenko T, Metsalu T, Lokk K, Laisk-Podar T, Vilo J. MethSurv: a web tool to perform multivariable survival analysis using DNA methylation data. Epigenomics. 2018; 10(3): 277-288.

[56] Zhou Y, Zeng P, Li YH, Zhang Z, Cui Q. SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features. Nucleic Acids Res. 2016; 44(10):e91.

[57] Bindea G, Mlecnik B, Tosolini M, et al. Spatiotemporal dynamics of intratumoral immune cells reveal the immune landscape in human cancer. Immunity. 2013; 39(4): 782-795.

[58] Hänzelmann S, Castelo R, Guinney J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics. 2013; 14.

[59] Yoshihara K, Shahmoradgoli M, Martínez E, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nat Commun. 2013; 4: 2612.

[60] Sun D, Wang J, Han Y, et al. TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment. Nucleic Acids Res. 2021; 49(D1): D1420-d1430.

[61] Newman AM, Liu CL, Green MR, et al. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015; 12(5): 453-457.

[62] Tang Z, Kang B, Li C, Chen T, Zhang Z. GEPIA2: an enhanced web server for large-scale expression profiling and interactive analysis. Nucleic Acids Res. 2019; 47(W1): W556-w560.

[63] Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012; 16(5): 284-287.

[64] Yang W, Soares J, Greninger P, et al. Genomics of drug sensitivity in cancer (GDSC): a resource for therapeutic biomarker discovery in cancer cells. Nucleic Acids Res. 2013; 41(Database issue): D955-61.

[65] Gu Z, Gu L, Eils R, Schlesner M, Brors B. circlize Implements and enhances circular visualization in R. Bioinformatics. 2014; 30(19): 2811-2812.

[66] Kuleshov MV, Jones MR, Rouillard AD, et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 2016; 44(W1): W90-97.

[67] Zhou G, Soufan O, Ewald J, Hancock REW, Basu N, Xia J. NetworkAnalyst 3.0: a visual analytics platform for comprehensive gene expression profiling and meta-analysis. Nucleic Acids Res. 2019; 47(W1): W234-w241.

[68] Davis AP, Wiegers TC, Johnson RJ, Sciaky D, Wiegers J, Mattingly CJ. Comparative toxicogenomics database (CTD): update 2023. Nucleic Acids Res. 2023; 51(D1): D1257-d1262.

[69] Yuan H, Yan M, Zhang G, et al. CancerSEA: a cancer single-cell state atlas. Nucleic Acids Res. 2019; 47(D1): D900-d908.

[70] Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014; 15(12): 550.

[71] Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P. The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst. 2015; 1(6): 417-425.

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