Saturation genome editing maps the functional spectrum of pathogenic VHL alleles.
Journal
Nature genetics
ISSN: 1546-1718
Titre abrégé: Nat Genet
Pays: United States
ID NLM: 9216904
Informations de publication
Date de publication:
05 Jul 2024
05 Jul 2024
Historique:
received:
11
05
2023
accepted:
13
05
2024
medline:
6
7
2024
pubmed:
6
7
2024
entrez:
5
7
2024
Statut:
aheadofprint
Résumé
To maximize the impact of precision medicine approaches, it is critical to identify genetic variants underlying disease and to accurately quantify their functional effects. A gene exemplifying the challenge of variant interpretation is the von Hippel-Lindautumor suppressor (VHL). VHL encodes an E3 ubiquitin ligase that regulates the cellular response to hypoxia. Germline pathogenic variants in VHL predispose patients to tumors including clear cell renal cell carcinoma (ccRCC) and pheochromocytoma, and somatic VHL mutations are frequently observed in sporadic renal cancer. Here we optimize and apply saturation genome editing to assay nearly all possible single-nucleotide variants (SNVs) across VHL's coding sequence. To delineate mechanisms, we quantify mRNA dosage effects and compare functional effects in isogenic cell lines. Function scores for 2,268 VHL SNVs identify a core set of pathogenic alleles driving ccRCC with perfect accuracy, inform differential risk across tumor types and reveal new mechanisms by which variants impact function. These results have immediate utility for classifying VHL variants encountered clinically and illustrate how precise functional measurements can resolve pleiotropic and dosage-dependent genotype-phenotype relationships across complete genes.
Identifiants
pubmed: 38969834
doi: 10.1038/s41588-024-01800-z
pii: 10.1038/s41588-024-01800-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Cancer Research UK (CRUK)
ID : CG-MAVE
Organisme : Wellcome Trust
ID : CC2190
Pays : United Kingdom
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 431984000-SFB 1453
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 431984000-SFB 1453
Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : 431984000-SFB 1453
Informations de copyright
© 2024. The Author(s).
Références
Cerami, E. et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2, 401–404 (2012).
pubmed: 22588877
doi: 10.1158/2159-8290.CD-12-0095
Gao, J. et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci. Signal. 6, pl1 (2013).
pubmed: 23550210
pmcid: 4160307
doi: 10.1126/scisignal.2004088
Landrum, M. J. et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 44, D862–D868 (2016).
pubmed: 26582918
doi: 10.1093/nar/gkv1222
Kuang, D. et al. Prioritizing genes for systematic variant effect mapping. Bioinformatics 36, 5448–5455 (2021).
pubmed: 33300982
doi: 10.1093/bioinformatics/btaa1008
Ioannidis, N. M. et al. REVEL: an ensemble method for predicting the pathogenicity of rare missense variants. Am. J. Hum. Genet. 99, 877–885 (2016).
pubmed: 27666373
pmcid: 5065685
doi: 10.1016/j.ajhg.2016.08.016
Rentzsch, P., Witten, D., Cooper, G. M., Shendure, J. & Kircher, M. CADD: predicting the deleteriousness of variants throughout the human genome. Nucleic Acids Res. 47, D886–D894 (2019).
pubmed: 30371827
doi: 10.1093/nar/gky1016
Frazer, J. et al. Disease variant prediction with deep generative models of evolutionary data. Nature 599, 91–95 (2021).
pubmed: 34707284
doi: 10.1038/s41586-021-04043-8
Muiños, F., Martínez-Jiménez, F., Pich, O., Gonzalez-Perez, A. & Lopez-Bigas, N. In silico saturation mutagenesis of cancer genes. Nature 596, 428–432 (2021).
pubmed: 34321661
doi: 10.1038/s41586-021-03771-1
Wu, Y., Li, R., Sun, S., Weile, J. & Roth, F. P. Improved pathogenicity prediction for rare human missense variants. Am. J. Hum. Genet. 108, 1891–1906 (2021).
pubmed: 34551312
pmcid: 8546039
doi: 10.1016/j.ajhg.2021.08.012
Jaganathan, K. et al. Predicting splicing from primary sequence with deep learning. Cell 176, 535–548 (2019).
pubmed: 30661751
doi: 10.1016/j.cell.2018.12.015
Richards, S. et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet. Med. 17, 405–424 (2015).
pubmed: 25741868
pmcid: 4544753
doi: 10.1038/gim.2015.30
Ludwig, K. K., Neuner, J., Butler, A., Geurts, J. L. & Kong, A. L. Risk reduction and survival benefit of prophylactic surgery in BRCA mutation carriers, a systematic review. Am. J. Surg. 212, 660–669 (2016).
pubmed: 27649974
doi: 10.1016/j.amjsurg.2016.06.010
Rose, M., Burgess, J. T., O’Byrne, K., Richard, D. J. & Bolderson, E. PARP inhibitors: clinical relevance, mechanisms of action and tumor resistance. Front. Cell Dev. Biol. 8, 564601 (2020).
pubmed: 33015058
pmcid: 7509090
doi: 10.3389/fcell.2020.564601
Jonasch, E. et al. Belzutifan for renal cell carcinoma in von Hippel–Lindau disease. N. Engl. J. Med. 385, 2036–2046 (2021).
pubmed: 34818478
pmcid: 9275515
doi: 10.1056/NEJMoa2103425
Findlay, G. M. Linking genome variants to disease: scalable approaches to test the functional impact of human mutations. Hum. Mol. Genet. 30, R187–R197 (2021).
pubmed: 34338757
pmcid: 8490018
doi: 10.1093/hmg/ddab219
Gossage, L., Eisen, T. & Maher, E. R. VHL, the story of a tumour suppressor gene. Nat. Rev. Cancer 15, 55–64 (2015).
pubmed: 25533676
doi: 10.1038/nrc3844
Ohh, M. et al. Ubiquitination of hypoxia-inducible factor requires direct binding to the β-domain of the von Hippel–Lindau protein. Nat. Cell Biol. 2, 423–427 (2000).
pubmed: 10878807
doi: 10.1038/35017054
Tippu, Z., Au, L. & Turajlic, S. Evolution of renal cell carcinoma. Eur. Urol. Focus 7, 148–151 (2021).
pubmed: 32007485
doi: 10.1016/j.euf.2019.12.005
Varshney, N. et al. A review of von Hippel–Lindau syndrome. J. Kidney Cancer VHL 4, 20–29 (2017).
pubmed: 28785532
pmcid: 5541202
doi: 10.15586/jkcvhl.2017.88
Maher, E. R., Neumann, H. P. & Richard, S. von Hippel–Lindau disease: a clinical and scientific review. Eur. J. Hum. Genet. 19, 617–623 (2011).
pubmed: 21386872
pmcid: 3110036
doi: 10.1038/ejhg.2010.175
Tabaro, F. et al. VHLdb: a database of von Hippel–Lindau protein interactors and mutations. Sci. Rep. 6, 31128 (2016).
pubmed: 27511743
pmcid: 4980628
doi: 10.1038/srep31128
Gordeuk, V. R. et al. Congenital disorder of oxygen sensing: association of the homozygous Chuvash polycythemia VHL mutation with thrombosis and vascular abnormalities but not tumors. Blood 103, 3924–3932 (2004).
pubmed: 14726398
doi: 10.1182/blood-2003-07-2535
Perrotta, S. et al. Effects of germline VHL deficiency on growth, metabolism, and mitochondria. N. Engl. J. Med. 382, 835–844 (2020).
pubmed: 32101665
doi: 10.1056/NEJMoa1907362
Zhang, M. et al. von Hippel–Lindau disease type 2 in a Chinese family with a VHL p.W88X truncation. Endocrine 48, 83–88 (2015).
pubmed: 25069792
doi: 10.1007/s12020-014-0368-x
Rentzsch, P., Schubach, M., Shendure, J. & Kircher, M. CADD-splice-improving genome-wide variant effect prediction using deep learning-derived splice scores. Genome Med. 13, 31 (2021).
pubmed: 33618777
pmcid: 7901104
doi: 10.1186/s13073-021-00835-9
Tsherniak, A. et al. Defining a cancer dependency map. Cell 170, 564–576 (2017).
pubmed: 28753430
pmcid: 5667678
doi: 10.1016/j.cell.2017.06.010
Blomen, V. A. et al. Gene essentiality and synthetic lethality in haploid human cells. Science 350, 1092–1096 (2015).
pubmed: 26472760
doi: 10.1126/science.aac7557
Findlay, G. M., Boyle, E. A., Hause, R. J., Klein, J. C. & Shendure, J. Saturation editing of genomic regions by multiplex homology-directed repair. Nature 513, 120–123 (2014).
pubmed: 25141179
pmcid: 4156553
doi: 10.1038/nature13695
Lenglet, M. et al. Identification of a new VHL exon and complex splicing alterations in familial erythrocytosis or von Hippel–Lindau disease. Blood 132, 469–483 (2018).
pubmed: 29891534
doi: 10.1182/blood-2018-03-838235
Buffet, A. et al. Germline mutations in the new E1′ cryptic exon of the VHL gene in patients with tumours of von Hippel–Lindau disease spectrum or with paraganglioma. J. Med. Genet. 57, 752–759 (2020).
pubmed: 31996412
doi: 10.1136/jmedgenet-2019-106519
Findlay, G. M. et al. Accurate classification of BRCA1 variants with saturation genome editing. Nature 562, 217–222 (2018).
pubmed: 30209399
pmcid: 6181777
doi: 10.1038/s41586-018-0461-z
Olbrich, T. et al. A chemical screen identifies compounds capable of selecting for haploidy in mammalian cells. Cell Rep. 28, 597–604.e4 (2019).
pubmed: 31315040
pmcid: 6656781
doi: 10.1016/j.celrep.2019.06.060
Schoenfeld, A., Davidowitz, E. J. & Burk, R. D. A second major native von Hippel–Lindau gene product, initiated from an internal translation start site, functions as a tumor suppressor. Proc. Natl Acad. Sci. USA 95, 8817–8822 (1998).
pubmed: 9671762
pmcid: 21160
doi: 10.1073/pnas.95.15.8817
Flores, S. K. et al. Synonymous but not silent: a synonymous VHL variant in exon 2 confers susceptibility to familial pheochromocytoma and von Hippel–Lindau disease. J. Clin. Endocrinol. Metab. 104, 3826–3834 (2019).
pubmed: 30946460
pmcid: 6660912
doi: 10.1210/jc.2019-00235
Schymkowitz, J. et al. The FoldX web server: an online force field. Nucleic Acids Res. 33, W382–W388 (2005).
pubmed: 15980494
pmcid: 1160148
doi: 10.1093/nar/gki387
Stebbins, C. E., Kaelin, W. G. Jr & Pavletich, N. P. Structure of the VHL-ElonginC-ElonginB complex: implications for VHL tumor suppressor function. Science 284, 455–461 (1999).
pubmed: 10205047
doi: 10.1126/science.284.5413.455
Tirosh, A. et al. Association of VHL genotype with pancreatic neuroendocrine tumor phenotype in patients with von Hippel–Lindau disease. JAMA Oncol. 4, 124–126 (2018).
pubmed: 29075773
doi: 10.1001/jamaoncol.2017.3428
Karczewski, K. J. et al. Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841 UK Biobank exomes. Cell Genom. 2, 100168 (2022).
pubmed: 36778668
pmcid: 9903662
doi: 10.1016/j.xgen.2022.100168
Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020).
pubmed: 32461654
pmcid: 7334197
doi: 10.1038/s41586-020-2308-7
Taliun, D. et al. Sequencing of 53,831 diverse genomes from the NHLBI TOPMed program. Nature 590, 290–299 (2021).
pubmed: 33568819
pmcid: 7875770
doi: 10.1038/s41586-021-03205-y
Clifford, S. C. et al. Contrasting effects on HIF-1α regulation by disease-causing pVHL mutations correlate with patterns of tumourigenesis in von Hippel–Lindau disease. Hum. Mol. Genet. 10, 1029–1038 (2001).
pubmed: 11331613
doi: 10.1093/hmg/10.10.1029
Wangen, J. R. & Green, R. Stop codon context influences genome-wide stimulation of termination codon readthrough by aminoglycosides. eLife 9, e52611 (2020).
pubmed: 31971508
pmcid: 7089771
doi: 10.7554/eLife.52611
Toledano, I., Supek, F. & Lehner, B. Genome-scale quantification and prediction of pathogenic stop codon readthrough by small molecules. Preprint at bioRxiv https://doi.org/10.1101/2023.08.07.552350 (2023).
Lee, S. et al. Neuronal apoptosis linked to EglN3 prolyl hydroxylase and familial pheochromocytoma genes: developmental culling and cancer. Cancer Cell 8, 155–167 (2005).
pubmed: 16098468
doi: 10.1016/j.ccr.2005.06.015
Li, S. et al. EglN3 hydroxylase stabilizes BIM-EL linking VHL type 2C mutations to pheochromocytoma pathogenesis and chemotherapy resistance. Proc. Natl Acad. Sci. USA 116, 16997–17006 (2019).
pubmed: 31375625
pmcid: 6708352
doi: 10.1073/pnas.1900748116
Choueiri, T. K. et al. Inhibition of hypoxia-inducible factor-2α in renal cell carcinoma with belzutifan: a phase 1 trial and biomarker analysis. Nat. Med. 27, 802–805 (2021).
pubmed: 33888901
pmcid: 9128828
doi: 10.1038/s41591-021-01324-7
Erwood, S. et al. Saturation variant interpretation using CRISPR prime editing. Nat. Biotechnol. 40, 885–895 (2022).
pubmed: 35190686
doi: 10.1038/s41587-021-01201-1
Radford, E. J. et al. Saturation genome editing of DDX3X clarifies pathogenicity of germline and somatic variation. Nat. Commun. 14, 7702 (2023).
pubmed: 38057330
pmcid: 10700591
doi: 10.1038/s41467-023-43041-4
Ohh, M., Taber, C. C., Ferens, F. G. & Tarade, D. Hypoxia-inducible factor underlies von Hippel–Lindau disease stigmata. eLife 11, e80774 (2022).
pubmed: 36040300
pmcid: 9427099
doi: 10.7554/eLife.80774
DepMap. Towards mapping the landscape of cancer vulnerabilities across all tumors. depmap.org/portal/depmap/ (2021).
Raval, R. R. et al. Contrasting properties of hypoxia-inducible factor 1 (HIF-1) and HIF-2 in von Hippel–Lindau-associated renal cell carcinoma. Mol. Cell. Biol. 25, 5675–5686 (2005).
pubmed: 15964822
pmcid: 1157001
doi: 10.1128/MCB.25.13.5675-5686.2005
Shen, C. et al. Genetic and functional studies implicate HIF1α as a 14q kidney cancer suppressor gene. Cancer Discov. 1, 222–235 (2011).
pubmed: 22037472
pmcid: 3202343
doi: 10.1158/2159-8290.CD-11-0098
Meléndez-Rodríguez, F. et al. HIF1α suppresses tumor cell proliferation through inhibition of aspartate biosynthesis. Cell Rep. 26, 2257–2265.e4 (2019).
pubmed: 30811976
doi: 10.1016/j.celrep.2019.01.106
Kaelin, W. G. Jr. von Hippel–Lindau disease: insights into oxygen sensing, protein degradation, and cancer. J. Clin. Invest. 132, e162480 (2022).
pubmed: 36106637
pmcid: 9479583
doi: 10.1172/JCI162480
Patel, S. A. et al. The renal lineage factor PAX8 controls oncogenic signalling in kidney cancer. Nature 606, 999–1006 (2022).
pubmed: 35676472
pmcid: 9242860
doi: 10.1038/s41586-022-04809-8
Kuang, D. et al. MaveRegistry: a collaboration platform for multiplexed assays of variant effect. Bioinformatics 37, 3382–3383 (2021).
pubmed: 33774657
pmcid: 8504617
doi: 10.1093/bioinformatics/btab215
Liu, F. et al. Case report: a synonymous VHL mutation (c.414A>G, p.Pro138Pro) causes pathogenic familial hemangioblastoma through dysregulated splicing. BMC Med. Genet. 21, 42 (2020).
pubmed: 32106822
pmcid: 7045488
doi: 10.1186/s12881-020-0976-7
Min, J.-H. et al. Structure of an HIF-1α–pVHL complex: hydroxyproline recognition in signaling. Science 296, 1886–1889 (2002).
pubmed: 12004076
doi: 10.1126/science.1073440
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).
pubmed: 34265844
pmcid: 8371605
doi: 10.1038/s41586-021-03819-2
Ran, F. A. et al. Genome engineering using the CRISPR–Cas9 system. Nat. Protoc. 8, 2281–2308 (2013).
pubmed: 24157548
pmcid: 3969860
doi: 10.1038/nprot.2013.143
Gossage, L. et al. An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma. Hum. Mol. Genet. 23, 5976–5988 (2014).
pubmed: 24969085
pmcid: 4204774
doi: 10.1093/hmg/ddu321
Esposito, D. et al. MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect. Genome Biol. 20, 223 (2019).
pubmed: 31679514
pmcid: 6827219
doi: 10.1186/s13059-019-1845-6
TheGenomeLab. VHL-SGE: code release with publication. Zenodo https://doi.org/10.5281/zenodo.11065771 (2024).