EP300 mutation is associated with tumor mutation burden and promotes antitumor immunity in bladder cancer patients

Gongmin Zhu, Lijiao Pei, Yuan Li, Xin Gou, Gongmin Zhu, Lijiao Pei, Yuan Li, Xin Gou

Abstract

Bladder cancer is a leading cause of morbidity and mortality worldwide. Currently, immunotherapy has become a worthwhile therapy for bladder cancer. Tumor mutation burden (TMB) has been regarded as the most prevalent biomarker to predict immunotherapy. Bladder cancer is reported to have the third highest mutation rate. However, whether these gene mutations are related to TMB and immune response remain unknown. In this study, we downloaded somatic mutation data of bladder cancer from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) datasets, and found 11 frequently mutated genes were covered by both two cohorts including FGFR3, TTN, XIRP2, CREBBP, PIK3CA, TP53, MUC16, EP300 (E1A binding protein P300), ARID1A, ERBB2, and KDM6A. Among them, EP300 mutation was associated with higher TMB and indicated a favorable clinical prognosis. Furthermore, based on Gene set enrichment analysis (GSEA) and CIBERSORT algorithm, we observed that EP300 mutation upregulated signaling pathways involved in immune system and enhanced antitumor immune response. In conclusion, EP300 is frequently mutated in bladder cancer, and its mutation is associated with increased TMB and promotes antitumor immunity, which may serve as a biomarker to predict immune response.

Keywords: EP300; bladder cancer; prognosis; tumor mutation burden; tumor-infiltrating immune cells.

Conflict of interest statement

CONFLICTS OF INTEREST: The authors declare that there are no conflicts of interest

Figures

Figure 1
Figure 1
Landscapes of frequently mutated genes in bladder cancer. (A) Oncoplot depicts the frequently mutated genes in bladder cancer from TCGA cohort. The left panel shows mutation frequency, and genes are ordered by their mutation frequencies. The bottom panel presents different mutation types. (B) Waterfall plot displays the frequently mutated genes in bladder cancer from ICGC cohort. The left panel shows the genes ordered by their mutation frequencies. The right panel presents different mutation types. (C) Venn diagram of frequently mutated genes covered by both TCGA and ICGC cohorts.
Figure 2
Figure 2
Gene mutations are associated with TMB and clinical prognosis. (A) Most gene mutations are associated with a higher TMB. ** p<0.01; *** p<0.001. (B) Kaplan-Meier survival analysis of patients with gene mutations. Only patients with complete clinical information were included (n=402). The p-value is marked in each graph. WT, wild type; MT, mutant type.
Figure 3
Figure 3
Significantly enriched pathways associated with EP300 mutation. Gene set enrichment analysis has been performed with TCGA. Gene enrichment plots shows that a series of gene sets including (A) Biocarta IL2 Pathway, (B) Biocarta Insulin Pathway, (C) Kegg Natural Killer Cell Mediated Cytotoxicity, (D) Pid IL12 Stat4 Pathway, (E) Reactome Cytokine Signaling in Immune System, and (F) Reactome MHC II Antigen Presentation are enriched in EP300-mutant group. NES, normalized enrichment score. The p-value is marked in each plot.
Figure 4
Figure 4
EP300 mutation is correlated with tumor-infiltrating immune cells. (A) Stacked bar chart shows distribution of 22 immune cells in each sample. (B) Violin plot displays the differentially infiltrated immune cells between EP300-mutant groups and EP300-wild group. Blue color represents EP300-wild group, and red color represents EP300-mutant group. (C) Correlation matrix of immune cell proportions. The red color represents positive correlation and the blue color represents negative correlation.

References

    1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018; 68:394–424. 10.3322/caac.21492
    1. Cookson MS, Herr HW, Zhang ZF, Soloway S, Sogani PC, Fair WR. The treated natural history of high risk superficial bladder cancer: 15-year outcome. J Urol. 1997; 158:62–67. 10.1097/00005392-199707000-00017
    1. Milowsky MI, Rumble RB, Booth CM, Gilligan T, Eapen LJ, Hauke RJ, Boumansour P, Lee CT. Guideline on Muscle-Invasive and Metastatic Bladder Cancer (European Association of Urology Guideline): American Society of Clinical Oncology Clinical Practice Guideline Endorsement. J Clin Oncol. 2016; 34:1945–52. 10.1200/JCO.2015.65.9797
    1. Ploussard G, Shariat SF, Dragomir A, Kluth LA, Xylinas E, Masson-Lecomte A, Rieken M, Rink M, Matsumoto K, Kikuchi E, Klatte T, Boorjian SA, Lotan Y, et al.. Conditional survival after radical cystectomy for bladder cancer: evidence for a patient changing risk profile over time. Eur Urol. 2014; 66:361–70. 10.1016/j.eururo.2013.09.050
    1. Dash A, Galsky MD, Vickers AJ, Serio AM, Koppie TM, Dalbagni G, Bochner BH. Impact of renal impairment on eligibility for adjuvant cisplatin-based chemotherapy in patients with urothelial carcinoma of the bladder. Cancer. 2006; 107:506–13. 10.1002/cncr.22031
    1. Morales A, Eidinger D, Bruce AW. Intracavitary Bacillus Calmette-Guerin in the Treatment of Superficial Bladder Tumors. J Urol. 2017; 197:S142–45. 10.1016/j.juro.2016.10.101
    1. Necchi A, Anichini A, Raggi D, Briganti A, Massa S, Lucianò R, Colecchia M, Giannatempo P, Mortarini R, Bianchi M, Farè E, Monopoli F, Colombo R, et al.. Pembrolizumab as Neoadjuvant Therapy Before Radical Cystectomy in Patients With Muscle-Invasive Urothelial Bladder Carcinoma (PURE-01): An Open-Label, Single-Arm, Phase II Study. J Clin Oncol. 2018; 36:JCO1801148. 10.1200/JCO.18.01148
    1. Braun DA, Burke KP, Van Allen EM. Genomic Approaches to Understanding Response and Resistance to Immunotherapy. Clin Cancer Res. 2016; 22:5642–50. 10.1158/1078-0432.CCR-16-0066
    1. Goodman AM, Kato S, Bazhenova L, Patel SP, Frampton GM, Miller V, Stephens PJ, Daniels GA, Kurzrock R. Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers. Mol Cancer Ther. 2017; 16:2598–608. 10.1158/1535-7163.MCT-17-0386
    1. Rizvi NA, Hellmann MD, Snyder A, Kvistborg P, Makarov V, Havel JJ, Lee W, Yuan J, Wong P, Ho TS, Miller ML, Rekhtman N, Moreira AL, et al.. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015; 348:124–28. 10.1126/science.aaa1348
    1. Gubin MM, Artyomov MN, Mardis ER, Schreiber RD. Tumor neoantigens: building a framework for personalized cancer immunotherapy. J Clin Invest. 2015; 125:3413–21. 10.1172/JCI80008
    1. Chen L, Flies DB. Molecular mechanisms of T cell co-stimulation and co-inhibition. Nat Rev Immunol. 2013; 13:227–42. 10.1038/nri3405
    1. Chen H, Chong W, Wu Q, Yao Y, Mao M, Wang X. Association of LRP1B Mutation With Tumor Mutation Burden and Outcomes in Melanoma and Non-small Cell Lung Cancer Patients Treated With Immune Check-Point Blockades. Front Immunol. 2019; 10:1113. 10.3389/fimmu.2019.01113
    1. Chen Y, Liu Q, Chen Z, Wang Y, Yang W, Hu Y, Han W, Zeng H, Ma H, Dai J, Zhang H. PD-L1 expression and tumor mutational burden status for prediction of response to chemotherapy and targeted therapy in non-small cell lung cancer. J Exp Clin Cancer Res. 2019; 38:193. 10.1186/s13046-019-1192-1
    1. Birkbak NJ, Kochupurakkal B, Izarzugaza JM, Eklund AC, Li Y, Liu J, Szallasi Z, Matulonis UA, Richardson AL, Iglehart JD, Wang ZC. Tumor mutation burden forecasts outcome in ovarian cancer with BRCA1 or BRCA2 mutations. PLoS One. 2013; 8:e80023. 10.1371/journal.pone.0080023
    1. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio SA, Behjati S, Biankin AV, Bignell GR, Bolli N, Borg A, Børresen-Dale AL, Boyault S, Burkhardt B, Butler AP, et al., and Australian Pancreatic Cancer Genome Initiative, and ICGC Breast Cancer Consortium, and ICGC MMML-Seq Consortium, and ICGC PedBrain. Signatures of mutational processes in human cancer. Nature. 2013; 500:415–21. 10.1038/nature12477
    1. Aggen DH, Drake CG. Biomarkers for immunotherapy in bladder cancer: a moving target. J Immunother Cancer. 2017; 5:94. 10.1186/s40425-017-0299-1
    1. Zuazo M, Arasanz H, Fernández-Hinojal G, García-Granda MJ, Gato M, Bocanegra A, Martínez M, Hernández B, Teijeira L, Morilla I, Lecumberri MJ, Fernández de Lascoiti A, Vera R, et al.. Functional systemic CD4 immunity is required for clinical responses to PD-L1/PD-1 blockade therapy. EMBO Mol Med. 2019; 11:e10293. 10.15252/emmm.201910293
    1. Hsu J, Hodgins JJ, Marathe M, Nicolai CJ, Bourgeois-Daigneault MC, Trevino TN, Azimi CS, Scheer AK, Randolph HE, Thompson TW, Zhang L, Iannello A, Mathur N, et al.. Contribution of NK cells to immunotherapy mediated by PD-1/PD-L1 blockade. J Clin Invest. 2018; 128:4654–68. 10.1172/JCI99317
    1. Iyer NG, Ozdag H, Caldas C. p300/CBP and cancer. Oncogene. 2004; 23:4225–31. 10.1038/sj.onc.1207118
    1. Bemanian V, Noone JC, Sauer T, Touma J, Vetvik K, Søderberg-Naucler C, Lindstrøm JC, Bukholm IR, Kristensen VN, Geisler J. Somatic EP300-G211S mutations are associated with overall somatic mutational patterns and breast cancer specific survival in triple-negative breast cancer. Breast Cancer Res Treat. 2018; 172:339–51. 10.1007/s10549-018-4927-3
    1. Saloura V, Izumchenko E, Zuo Z, Bao R, Korzinkin M, Ozerov I, Zhavoronkov A, Sidransky D, Bedi A, Hoque MO, Koeppen H, Keck MK, Khattri A, et al.. Immune profiles in primary squamous cell carcinoma of the head and neck. Oral Oncol. 2019; 96:77–88. 10.1016/j.oraloncology.2019.06.032
    1. McGranahan N, Furness AJ, Rosenthal R, Ramskov S, Lyngaa R, Saini SK, Jamal-Hanjani M, Wilson GA, Birkbak NJ, Hiley CT, Watkins TB, Shafi S, Murugaesu N, et al.. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science. 2016; 351:1463–69. 10.1126/science.aaf1490
    1. van Loosdregt J, Vercoulen Y, Guichelaar T, Gent YY, Beekman JM, van Beekum O, Brenkman AB, Hijnen DJ, Mutis T, Kalkhoven E, Prakken BJ, Coffer PJ. Regulation of Treg functionality by acetylation-mediated Foxp3 protein stabilization. Blood. 2010; 115:965–74. 10.1182/blood-2009-02-207118
    1. Sakaguchi S, Ono M, Setoguchi R, Yagi H, Hori S, Fehervari Z, Shimizu J, Takahashi T, Nomura T. Foxp3+ CD25+ CD4+ natural regulatory T cells in dominant self-tolerance and autoimmune disease. Immunol Rev. 2006; 212:8–27. 10.1111/j.0105-2896.2006.00427.x
    1. West NR, Kost SE, Martin SD, Milne K, Deleeuw RJ, Nelson BH, Watson PH. Tumour-infiltrating FOXP3(+) lymphocytes are associated with cytotoxic immune responses and good clinical outcome in oestrogen receptor-negative breast cancer. Br J Cancer. 2013; 108:155–62. 10.1038/bjc.2012.524
    1. Zhu G, Pei L, Yin H, Lin F, Li X, Zhu X, He W, Gou X. Profiles of tumor-infiltrating immune cells in renal cell carcinoma and their clinical implications. Oncol Lett. 2019; 18:5235–42. 10.3892/ol.2019.10896
    1. Marshall EA, Ng KW, Kung SH, Conway EM, Martinez VD, Halvorsen EC, Rowbotham DA, Vucic EA, Plumb AW, Becker-Santos DD, Enfield KS, Kennett JY, Bennewith KL, et al.. Emerging roles of T helper 17 and regulatory T cells in lung cancer progression and metastasis. Mol Cancer. 2016; 15:67. 10.1186/s12943-016-0551-1
    1. Ghosh S, Taylor A, Chin M, Huang HR, Conery AR, Mertz JA, Salmeron A, Dakle PJ, Mele D, Cote A, Jayaram H, Setser JW, Poy F, et al.. Regulatory T Cell Modulation by CBP/EP300 Bromodomain Inhibition. J Biol Chem. 2016; 291:13014–27. 10.1074/jbc.M115.708560
    1. Liu Y, Wang L, Predina J, Han R, Beier UH, Wang LC, Kapoor V, Bhatti TR, Akimova T, Singhal S, Brindle PK, Cole PA, Albelda SM, Hancock WW. Inhibition of p300 impairs Foxp3⁺ T regulatory cell function and promotes antitumor immunity. Nat Med. 2013; 19:1173–77. 10.1038/nm.3286
    1. Vahidi Y, Faghih Z, Talei AR, Doroudchi M, Ghaderi A. Memory CD4+ T cell subsets in tumor draining lymph nodes of breast cancer patients: A focus on T stem cell memory cells. Cell Oncol (Dordr). 2018; 41:1–11. 10.1007/s13402-017-0352-6
    1. Hotta K, Sho M, Fujimoto K, Shimada K, Yamato I, Anai S, Konishi N, Hirao Y, Nonomura K, Nakajima Y. Prognostic significance of CD45RO+ memory T cells in renal cell carcinoma. Br J Cancer. 2011; 105:1191–96. 10.1038/bjc.2011.368
    1. Bryceson YT, March ME, Ljunggren HG, Long EO. Synergy among receptors on resting NK cells for the activation of natural cytotoxicity and cytokine secretion. Blood. 2006; 107:159–66. 10.1182/blood-2005-04-1351
    1. Dianat-Moghadam H, Rokni M, Marofi F, Panahi Y, Yousefi M. Natural killer cell-based immunotherapy: from transplantation toward targeting cancer stem cells. J Cell Physiol. 2018; 234:259–73. 10.1002/jcp.26878
    1. Chalmers ZR, Connelly CF, Fabrizio D, Gay L, Ali SM, Ennis R, Schrock A, Campbell B, Shlien A, Chmielecki J, Huang F, He Y, Sun J, et al.. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017; 9:34. 10.1186/s13073-017-0424-2
    1. Mayakonda A, Lin DC, Assenov Y, Plass C, Koeffler HP. Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res. 2018; 28:1747–56. 10.1101/gr.239244.118
    1. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA. 2005; 102:15545–50. 10.1073/pnas.0506580102
    1. Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, Hoang CD, Diehn M, Alizadeh AA. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015; 12:453–57. 10.1038/nmeth.3337

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren