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H3K4 demethylase KDM5B regulates cancer cell identity and epigenetic plasticity

Abstract

The H3K4 demethylase KDM5B is overexpressed in multiple cancer types, and elevated expression levels of KDM5B is associated with decreased survival. However, the underlying mechanistic contribution of dysregulated expression of KDM5B and H3K4 demethylation in cancer is poorly understood. Our results show that loss of KDM5B in multiple types of cancer cells leads to increased proliferation and elevated expression of cancer stem cell markers. In addition, we observed enhanced tumor formation following KDM5B depletion in a subset of representative cancer cell lines. Our findings also support a role for KDM5B in regulating epigenetic plasticity, where loss of KDM5B in cancer cells with elevated KDM5B expression leads to alterations in activity of chromatin states, which facilitate activation or repression of alternative transcriptional programs. In addition, we define KDM5B-centric epigenetic and transcriptional patterns that support cancer cell plasticity, where KDM5B depleted cancer cells exhibit altered epigenetic and transcriptional profiles resembling a more primitive cellular state. This study also provides a resource for evaluating associations between alterations in epigenetic patterning upon depletion of KDM5B and gene expression in a diverse set of cancer cells.

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Fig. 1: KDM5B expression in cancer and establishment of cancer cell models.
Fig. 2: KDM5B regulates the transcriptional repertoire of cancer cells.
Fig. 3: Integrative transcriptome analysis reveals that loss of KDM5B leads to increased expression of stemness genes and an expression signature consistent with multiple cancers.
Fig. 4: Loss of KDM5B leads to epigenetic reprogramming of H3K4me3 in cancer cells.
Fig. 5: Breadth of H3K4me3 domains is linked to cancer cell identity.
Fig. 6: Functional and morphological characteristics of KDM5B depleted cancer cells.
Fig. 7: Altered expression of cancer stem cell markers following loss of KDM5B.

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Data availability

The sequencing data from this study have been submitted to the NCBI Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo) under accession no. GSE165959.

References

  1. Dawson MA, Kouzarides T. Cancer epigenetics: from mechanism to therapy. Cell. 2012;150:12–27.

    Article  CAS  PubMed  Google Scholar 

  2. Gopi LK, Kidder BL. Integrative pan cancer analysis reveals epigenomic variation in cancer type and cell specific chromatin domains. Nat Commun. 2021;12:1419.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Hansen KD, Timp W, Bravo HC, Sabunciyan S, Langmead B, McDonald OG, et al. Increased methylation variation in epigenetic domains across cancer types. Nat Genet. 2011;43:768–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Jones PA, Baylin SB. The fundamental role of epigenetic events in cancer. Nat Rev Genet. 2002;3:415–28.

    Article  CAS  PubMed  Google Scholar 

  5. McGranahan N, Swanton C. Clonal heterogeneity and tumor evolution: past, present, and the future. Cell. 2017;168:613–28.

    Article  CAS  PubMed  Google Scholar 

  6. Muntean AG, Hess JL. Epigenetic dysregulation in cancer. Am J Pathol. 2009;175:1353–61.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Timp W, Feinberg AP. Cancer as a dysregulated epigenome allowing cellular growth advantage at the expense of the host. Nat Rev Cancer. 2013;13:497–510.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Barski A, Cuddapah S, Cui K, Roh TY, Schones DE, Wang Z, et al. High-resolution profiling of histone methylations in the human genome. Cell. 2007;129:823–37.

    Article  CAS  PubMed  Google Scholar 

  9. Kidder BL, Hu G, Zhao K. KDM5B focuses H3K4 methylation near promoters and enhancers during embryonic stem cell self-renewal and differentiation. Genome Biol. 2014;15:R32.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Santos-Rosa H, Schneider R, Bannister AJ, Sherriff J, Bernstein BE, Emre NC, et al. Active genes are tri-methylated at K4 of histone H3. Nature. 2002;419:407–11.

    Article  CAS  PubMed  Google Scholar 

  11. Schneider R, Bannister AJ, Myers FA, Thorne AW, Crane-Robinson C, Kouzarides T. Histone H3 lysine 4 methylation patterns in higher eukaryotic genes. Nat Cell Biol. 2004;6:73–77.

    Article  CAS  PubMed  Google Scholar 

  12. Sims RJ 3rd, Nishioka K, Reinberg D. Histone lysine methylation: a signature for chromatin function. Trends Genet. 2003;19:629–39.

    Article  CAS  PubMed  Google Scholar 

  13. Albert M, Schmitz SU, Kooistra SM, Malatesta M, Morales Torres C, Rekling JC, et al. The histone demethylase Jarid1b ensures faithful mouse development by protecting developmental genes from aberrant H3K4me3. PLoS Genet. 2013;9:e1003461.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Catchpole S, Spencer-Dene B, Hall D, Santangelo S, Rosewell I, Guenatri M, et al. PLU-1/JARID1B/KDM5B is required for embryonic survival and contributes to cell proliferation in the mammary gland and in ER+ breast cancer cells. Int J Oncol. 2011;38:1267–77.

    CAS  PubMed  Google Scholar 

  15. Dey BK, Stalker L, Schnerch A, Bhatia M, Taylor-Papidimitriou J, Wynder C. The histone demethylase KDM5b/JARID1b plays a role in cell fate decisions by blocking terminal differentiation. Mol Cell Biol. 2008;28:5312–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Frankenberg S, Smith L, Greenfield A, Zernicka-Goetz M. Novel gene expression patterns along the proximo-distal axis of the mouse embryo before gastrulation. BMC Dev Biol. 2007;7:8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Kidder BL, Hu G, Yu ZX, Liu C, Zhao K. Extended self-renewal and accelerated reprogramming in the absence of Kdm5b. Mol Cell Biol. 2013;33:4793–810.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Schmitz SU, Albert M, Malatesta M, Morey L, Johansen JV, Bak M, et al. Jarid1b targets genes regulating development and is involved in neural differentiation. EMBO J. 2011;30:4586–600.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Xie L, Pelz C, Wang W, Bashar A, Varlamova O, Shadle S, et al. KDM5B regulates embryonic stem cell self-renewal and represses cryptic intragenic transcription. EMBO J. 2011;30:1473–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lu PJ, Sundquist K, Baeckstrom D, Poulsom R, Hanby A, Meier-Ewert S, et al. A novel gene (PLU-1) containing highly conserved putative DNA/chromatin binding motifs is specifically up-regulated in breast cancer. J Biol Chem. 1999;274:15633–45.

    Article  CAS  PubMed  Google Scholar 

  21. Roesch A, Fukunaga-Kalabis M, Schmidt EC, Zabierowski SE, Brafford PA, Vultur A, et al. A temporarily distinct subpopulation of slow-cycling melanoma cells is required for continuous tumor growth. Cell. 2010;141:583–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Xiang Y, Zhu Z, Han G, Ye X, Xu B, Peng Z, et al. JARID1B is a histone H3 lysine 4 demethylase up-regulated in prostate cancer. Proc Natl Acad Sci USA. 2007;104:19226–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wang L, Mao Y, Du G, He C, Han S. Overexpression of JARID1B is associated with poor prognosis and chemotherapy resistance in epithelial ovarian cancer. Tumour Biol. 2015;36:2465–72.

    Article  CAS  PubMed  Google Scholar 

  24. Barrett A, Madsen B, Copier J, Lu PJ, Cooper L, Scibetta AG, et al. PLU-1 nuclear protein, which is upregulated in breast cancer, shows restricted expression in normal human adult tissues: a new cancer/testis antigen? Int J Cancer. 2002;101:581–8.

    Article  CAS  PubMed  Google Scholar 

  25. Yamamoto S, Wu Z, Russnes HG, Takagi S, Peluffo G, Vaske C, et al. JARID1B is a luminal lineage-driving oncogene in breast cancer. Cancer Cell. 2014;25:762–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Hayami S, Yoshimatsu M, Veerakumarasivam A, Unoki M, Iwai Y, Tsunoda T, et al. Overexpression of the JmjC histone demethylase KDM5B in human carcinogenesis: involvement in the proliferation of cancer cells through the E2F/RB pathway. Mol Cancer. 2010;9:59.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. Li X, Su Y, Pan J, Zhou Z, Song B, Xiong E, et al. Connexin 26 is down-regulated by KDM5B in the progression of bladder cancer. Int J Mol Sci. 2013;14:7866–79.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Roesch A, Becker B, Schneider-Brachert W, Hagen I, Landthaler M, Vogt T. Re-expression of the retinoblastoma-binding protein 2-homolog 1 reveals tumor-suppressive functions in highly metastatic melanoma cells. J Invest Dermatol. 2006;126:1850–9.

    Article  CAS  PubMed  Google Scholar 

  29. Ohta K, Haraguchi N, Kano Y, Kagawa Y, Konno M, Nishikawa S, et al. Depletion of JARID1B induces cellular senescence in human colorectal cancer. Int J Oncol. 2013;42:1212–8.

    Article  CAS  PubMed  Google Scholar 

  30. Wang Z, Tang F, Qi G, Yuan S, Zhang G, Tang B, et al. KDM5B is overexpressed in gastric cancer and is required for gastric cancer cell proliferation and metastasis. Am J Cancer Res. 2015;5:87–100.

    PubMed  Google Scholar 

  31. Dai B, Hu Z, Huang H, Zhu G, Xiao Z, Wan W, et al. Overexpressed KDM5B is associated with the progression of glioma and promotes glioma cell growth via downregulating p21. Biochem Biophys Res Commun. 2014;454:221–7.

    Article  CAS  PubMed  Google Scholar 

  32. Shigekawa Y, Hayami S, Ueno M, Miyamoto A, Suzaki N, Kawai M, et al. Overexpression of KDM5B/JARID1B is associated with poor prognosis in hepatocellular carcinoma. Oncotarget. 2018;9:34320–35.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Hinohara K, Wu HJ, Vigneau S, McDonald TO, Igarashi KJ, Yamamoto KN, et al. KDM5 histone demethylase activity links cellular transcriptomic heterogeneity to therapeutic resistance. Cancer Cell. 2018;34:939–53 e939.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Roesch A, Vultur A, Bogeski I, Wang H, Zimmermann KM, Speicher D, et al. Overcoming intrinsic multidrug resistance in melanoma by blocking the mitochondrial respiratory chain of slow-cycling JARID1B(high) cells. Cancer Cell. 2013;23:811–25.

    Article  CAS  PubMed  Google Scholar 

  35. Rhodes DR, Kalyana-Sundaram S, Mahavisno V, Varambally R, Yu J, Briggs BB, et al. Oncomine 3.0: genes, pathways, and networks in a collection of 18,000 cancer gene expression profiles. Neoplasia. 2007;9:166–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Rhodes DR, Yu J, Shanker K, Deshpande N, Varambally R, Ghosh D, et al. ONCOMINE: a cancer microarray database and integrated data-mining platform. Neoplasia. 2004;6:1–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Stinson SF, Alley MC, Kopp WC, Fiebig HH, Mullendore LA, Pittman AF, et al. Morphological and immunocytochemical characteristics of human tumor cell lines for use in a disease-oriented anticancer drug screen. Anticancer Res. 1992;12:1035–53.

    CAS  PubMed  Google Scholar 

  38. Reinhold WC, Varma S, Sunshine M, Elloumi F, Ofori-Atta K, Lee S, et al. RNA sequencing of the NCI-60: integration into cellminer and cellminer CDB. Cancer Res. 2019;79:3514–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics. 2009;26:139–40.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC, et al. DAVID: database for annotation, visualization, and integrated discovery. Genome Biol. 2003;4:P3.

    Article  PubMed  Google Scholar 

  41. Yu G, Li F, Qin Y, Bo X, Wu Y, Wang S. GOSemSim: an R package for measuring semantic similarity among GO terms and gene products. Bioinformatics. 2010;26:976–8.

    Article  CAS  PubMed  Google Scholar 

  42. Supek F, Bosnjak M, Skunca N, Smuc T. REVIGO summarizes and visualizes long lists of gene ontology terms. PLoS ONE. 2011;6:e21800.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351:2817–26.

    Article  CAS  PubMed  Google Scholar 

  44. Cheng CJ, Lin YC, Tsai MT, Chen CS, Hsieh MC, Chen CL, et al. SCUBE2 suppresses breast tumor cell proliferation and confers a favorable prognosis in invasive breast cancer. Cancer Res. 2009;69:3634–41.

    Article  CAS  PubMed  Google Scholar 

  45. Bhattacharya B, Miura T, Brandenberger R, Mejido J, Luo Y, Yang AX, et al. Gene expression in human embryonic stem cell lines: unique molecular signature. Blood. 2004;103:2956–64.

    Article  CAS  PubMed  Google Scholar 

  46. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005;102:15545–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Khan A, Mathelier A. Intervene: a tool for intersection and visualization of multiple gene or genomic region sets. BMC Bioinforma. 2017;18:287.

    Article  CAS  Google Scholar 

  48. Heinz S, Benner C, Spann N, Bertolino E, Lin YC, Laslo P, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38:576–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Zang C, Schones DE, Zeng C, Cui K, Zhao K, Peng W. A clustering approach for identification of enriched domains from histone modification ChIP-Seq data. Bioinformatics. 2009;25:1952–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Abaan OD, Polley EC, Davis SR, Zhu YJ, Bilke S, Walker RL, et al. The exomes of the NCI-60 panel: a genomic resource for cancer biology and systems pharmacology. Cancer Res. 2013;73:4372–82.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Tate JG, Bamford S, Jubb HC, Sondka Z, Beare DM, Bindal N, et al. COSMIC: the catalogue of somatic mutations in cancer. Nucleic Acids Res. 2019;47:D941–7.

    Article  CAS  PubMed  Google Scholar 

  52. Reinhold WC, Sunshine M, Liu H, Varma S, Kohn KW, Morris J, et al. CellMiner: a web-based suite of genomic and pharmacologic tools to explore transcript and drug patterns in the NCI-60 cell line set. Cancer Res. 2012;72:3499–511.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Benayoun BA, Pollina EA, Ucar D, Mahmoudi S, Karra K, Wong ED, et al. H3K4me3 breadth is linked to cell identity and transcriptional consistency. Cell. 2014;158:673–88.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Chen K, Chen Z, Wu D, Zhang L, Lin X, Su J, et al. Broad H3K4me3 is associated with increased transcription elongation and enhancer activity at tumor-suppressor genes. Nat Genet. 2015;47:1149–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Davoli T, Xu AW, Mengwasser KE, Sack LM, Yoon JC, Park PJ, et al. Cumulative haploinsufficiency and triplosensitivity drive aneuploidy patterns and shape the cancer genome. Cell. 2013;155:948–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Eisenberg E, Levanon EY. Human housekeeping genes, revisited. Trends Genet. 2013;29:569–74.

    Article  CAS  PubMed  Google Scholar 

  57. O’Brien CA, Kreso A, Jamieson CH. Cancer stem cells and self-renewal. Clin Cancer Res. 2010;16:3113–20.

    Article  PubMed  Google Scholar 

  58. Kreso A, Dick JE. Evolution of the cancer stem cell model. Cell Stem Cell. 2014;14:275–91.

    Article  CAS  PubMed  Google Scholar 

  59. Medema JP. Cancer stem cells: the challenges ahead. Nat Cell Biol. 2013;15:338–44.

    Article  CAS  PubMed  Google Scholar 

  60. Oskarsson T, Batlle E, Massague J. Metastatic stem cells: sources, niches, and vital pathways. Cell Stem Cell. 2014;14:306–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Stuelten CH, Mertins SD, Busch JI, Gowens M, Scudiero DA, Burkett MW, et al. Complex display of putative tumor stem cell markers in the NCI60 tumor cell line panel. Stem Cells. 2010;28:649–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Taylor-Papadimitriou J, Burchell J. JARID1/KDM5 demethylases as cancer targets? Expert Opin Ther Targets. 2017;21:5–7.

    Article  PubMed  Google Scholar 

  63. Vinogradova M, Gehling VS, Gustafson A, Arora S, Tindell CA, Wilson C, et al. An inhibitor of KDM5 demethylases reduces survival of drug-tolerant cancer cells. Nat Chem Biol. 2016;12:531–8.

    Article  CAS  PubMed  Google Scholar 

  64. Xhabija B, Kidder BL. KDM5B is a master regulator of the H3K4-methylome in stem cells, development and cancer. Semin Cancer Biol. 2019;57:79–85.

    Article  CAS  PubMed  Google Scholar 

  65. Facompre ND, Harmeyer KM, Sole X, Kabraji S, Belden Z, Sahu V, et al. JARID1B enables transit between distinct states of the stem-like cell population in oral cancers. Cancer Res. 2016;76:5538–49.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Chen J, Li Y, Yu TS, McKay RM, Burns DK, Kernie SG, et al. A restricted cell population propagates glioblastoma growth after chemotherapy. Nature. 2012;488:522–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Kreso A, O’Brien CA, van Galen P, Gan OI, Notta F, Brown AM, et al. Variable clonal repopulation dynamics influence chemotherapy response in colorectal cancer. Science. 2013;339:543–8.

    Article  CAS  PubMed  Google Scholar 

  68. Oshimori N, Oristian D, Fuchs E. TGF-beta promotes heterogeneity and drug resistance in squamous cell carcinoma. Cell. 2015;160:963–76.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. min M, Spencer SL. Spontaneously slow-cycling subpopulations of human cells originate from activation of stress-response pathways. PLoS Biol. 2019;17:e3000178.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Evertts AG, Manning AL, Wang X, Dyson NJ, Garcia BA, Coller HA. H4K20 methylation regulates quiescence and chromatin compaction. Mol Biol Cell. 2013;24:3025–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Shibue T, Weinberg RA. EMT, CSCs, and drug resistance: the mechanistic link and clinical implications. Nat Rev Clin Oncol. 2017;14:611–29.

    Article  PubMed  PubMed Central  Google Scholar 

  72. Liu H, D’Andrade P, Fulmer-Smentek S, Lorenzi P, Kohn KW, Weinstein JN, et al. mRNA and microRNA expression profiles of the NCI-60 integrated with drug activities. Mol Cancer Ther. 2010;9:1080–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Kidder BL, Hu G, Cui K, Zhao K. SMYD5 regulates H4K20me3-marked heterochromatin to safeguard ES cell self-renewal and prevent spurious differentiation. Epigenetics Chromatin. 2017;10:8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  74. He R, Kidder BL. Culture of haploid blastocysts in FGF4 favors the derivation of epiblast stem cells with a primed epigenetic and transcriptional landscape. Sci Rep. 2018;8:10775.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  75. Xu J, Kidder BL. KDM5B decommissions the H3K4 methylation landscape of self-renewal genes during trophoblast stem cell differentiation. Biol Open. 2018;7:bio031245.

  76. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  77. Hu G, Zhao K. Correlating histone modification patterns with gene expression data during hematopoiesis. Methods Mol Biol. 2014;1150:175–87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008;5:621–8.

    Article  CAS  PubMed  Google Scholar 

  79. Dyrskjot L, Kruhoffer M, Thykjaer T, Marcussen N, Jensen JL, Moller K, et al. Gene expression in the urinary bladder: a common carcinoma in situ gene expression signature exists disregarding histopathological classification. Cancer Res. 2004;64:4040–8.

    Article  CAS  PubMed  Google Scholar 

  80. Haferlach T, Kohlmann A, Wieczorek L, Basso G, Kronnie GT, Bene MC, et al. Clinical utility of microarray-based gene expression profiling in the diagnosis and subclassification of leukemia: report from the International Microarray Innovations in Leukemia Study Group. J Clin Oncol. 2010;28:2529–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Bhattacharjee A, Richards WG, Staunton J, Li C, Monti S, Vasa P, et al. Classification of human lung carcinomas by mRNA expression profiling reveals distinct adenocarcinoma subclasses. Proc Natl Acad Sci USA. 2001;98:13790–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  82. Badea L, Herlea V, Dima SO, Dumitrascu T, Popescu I. Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia. Hepatogastroenterology. 2008;55:2016–27.

    CAS  PubMed  Google Scholar 

  83. Grasso CS, Wu YM, Robinson DR, Cao X, Dhanasekaran SM, Khan AP, et al. The mutational landscape of lethal castration-resistant prostate cancer. Nature. 2012;487:239–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Cutcliffe C, Kersey D, Huang CC, Zeng Y, Walterhouse D, Perlman EJ, et al. Clear cell sarcoma of the kidney: up-regulation of neural markers with activation of the sonic hedgehog and Akt pathways. Clin Cancer Res. 2005;11:7986–94.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

This work utilized the Wayne State University High Performance Computing Grid for computational resources (https://www.grid.wayne.edu/). Flow cytometry was performed in the Microscopy, Imaging, and Cytometry Resources (MICR) core at the Karmanos Cancer Institute and Wayne State University. We thank Lisa Polin for helpful discussions.

Funding

This work was supported by Wayne State University, Karmanos Cancer Institute, and a grant from the Elsa U. Pardee Foundation awarded to BLK.

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BLK conceived of the study, designed, and performed experiments, analyzed the data, and drafted the manuscript. RH, BX, and ZX performed experiments. LKG and JTK assisted with computational analyses.

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Correspondence to Benjamin L. Kidder.

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He, R., Xhabija, B., Gopi, L.K. et al. H3K4 demethylase KDM5B regulates cancer cell identity and epigenetic plasticity. Oncogene 41, 2958–2972 (2022). https://doi.org/10.1038/s41388-022-02311-z

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