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Original Research

Immune-focused multi-omics analysis of prostate cancer: leukocyte Ig-Like receptors are associated with disease progression

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Article: 1851950 | Received 23 Apr 2020, Accepted 11 Nov 2020, Published online: 01 Dec 2020

References

  • Comiskey MC, Dallos MC, Drake CG. Immunotherapy in prostate cancer: teaching an old dog new tricks. Curr Oncol Rep. 2018;20:75. doi: 10.1007/s11912-018-0712-z.
  • Bilusic M, Madan RA, Gulley JL. Immunotherapy of prostate cancer: facts and hopes. Clin Cancer Res Off J Am Assoc Cancer Res. 2017;23:6764–11. doi:10.1158/1078-0432.CCR-17-0019.
  • Scheid E, Major P, Bergeron A, Finn OJ, Salter RD, Eady R, Yassine-Diab B, Favre D, Peretz Y, Landry C, et al. Tn-MUC1 DC vaccination of rhesus macaques and a phase I/II trial in patients with nonmetastatic castrate-resistant prostate cancer. Cancer Immunol Res. 2016;4:881–892. doi:10.1158/2326-6066.CIR-15-0189.
  • Wei SC, Duffy CR, Allison JP. Fundamental mechanisms of immune checkpoint blockade therapy. Cancer Discov. 2018;8:1069–1086. doi:10.1158/2159-8290.CD-18-0367.
  • Dempke WCM, Fenchel K, Uciechowski P, Dale SP. Second- and third-generation drugs for immuno-oncology treatment-The more the better? Eur J Cancer Oxf Engl 1990. 2017;74:55–72. doi: 10.1016/j.ejca.2017.01.001.
  • Marin-Acevedo JA, Dholaria B, Soyano AE, Knutson KL, Chumsri S, Lou Y. Next generation of immune checkpoint therapy in cancer: new developments and challenges. J Hematol Oncol J Hematol Oncol. 2018;11:39. doi:10.1186/s13045-018-0582-8.
  • Longo V, Brunetti O, Azzariti A, Galetta D, Nardulli P, Leonetti F, Silvestris N. Strategies to improve cancer immune checkpoint inhibitors efficacy, other than abscopal effect: a systematic review. Cancers. 2019;11(4):539. doi:10.3390/cancers11040539.
  • Kwon ED, Drake CG, Scher HI, Fizazi K, Bossi A, van den Eertwegh AJ, Krainer M, Houede N, Santos R, Mahammedi H, et al. Ipilimumab versus placebo after radiotherapy in patients with metastatic castration-resistant prostate cancer that had progressed after docetaxel chemotherapy (CA184-043): a multicentre, randomised, double-blind, phase 3 trial. Lancet Oncol. 2014;15:700–712. doi:10.1016/S1470-2045(14)70189-5.
  • Beer TM, Kwon ED, Drake CG, Fizazi K, Logothetis C, Gravis G, Ganju V, Polikoff J, Saad F, Humanski P, et al. Randomized, double-blind, phase III trial of ipilimumab versus placebo in asymptomatic or minimally symptomatic patients with metastatic chemotherapy-naive castration-resistant prostate cancer. J Clin Oncol Off J Am Soc Clin Oncol. 2017;Jan;35(1):40–47. doi:10.1200/JCO.2016.69.1584.
  • Jafari S, Molavi O, Kahroba H, Hejazi MS, Maleki-Dizaji N, Barghi S, Kiaie SH, Jadidi-Niaragh F. Clinical application of immune checkpoints in targeted immunotherapy of prostate cancer. Cell Mol Life Sci CMLS. 2020 Oct;77(19):3693-3710. doi: 10.1007/s00018-020-03459-1.
  • Markowski MC, Shenderov E, Eisenberger MA, Kachhap S, Pardoll DM, Denmeade SR, Antonarakis ES. Extreme responses to immune checkpoint blockade following bipolar androgen therapy and enzalutamide in patients with metastatic castration resistant prostate cancer. The Prostate. 2020;80(5):407–411. doi:10.1002/pros.23955.
  • Isaacsson Velho P, Antonarakis ES. PD-1/PD-L1 pathway inhibitors in advanced prostate cancer. Expert Rev Clin Pharmacol. 2018;11:475–486. doi:10.1080/17512433.2018.1464388.
  • Hudson LE, Allen RL. Leukocyte Ig-like receptors - a model for MHC class i disease associations. Front Immunol. 2016;7:281. doi: 10.3389/fimmu.2016.00281.
  • Naji A, Menier C, Maki G, Carosella ED, Rouas-Freiss N. Neoplastic B-cell growth is impaired by HLA-G/ILT2 interaction. Leukemia. 2012;26:1889–1892. doi:10.1038/leu.2012.62.
  • Brown D, Trowsdale J, Allen R. The LILR family: modulators of innate and adaptive immune pathways in health and disease. Tissue Antigens. 2004;64:215–225. doi: 10.1111/j.0001-2815.2004.00290.x.
  • Abeshouse A, Ahn J, Akbani R, Ally A, Amin S, Andry C, Annala M, Aprikian A, Armenia J, Arora A, et al. The molecular taxonomy of primary prostate cancer. Cell. 2015;163(4):1011–1025. doi:10.1016/j.cell.2015.10.025.
  • Barkal AA, Weiskopf K, Kao KS, Gordon SR, Rosental B, Yiu YY, George BM, Markovic M, Ring NG, Tsai JM, et al. Engagement of MHC class I by the inhibitory receptor LILRB1 suppresses macrophages and is a target of cancer immunotherapy. Nat Immunol. 2018;19:76–84. doi:10.1038/s41590-017-0004-z.
  • Zhao J, Zhong S, Niu X, Jiang J, Zhang R, Li Q. The MHC class I-LILRB1 signalling axis as a promising target in cancer therapy. Scand J Immunol. 2019;90:e12804. doi:10.1111/sji.12804.
  • Long Q, Xu J, Osunkoya AO, Sannigrahi S, Johnson BA, Zhou W, Gillespie T, Park JY, Nam RK, Sugar L, et al. Global transcriptome analysis of formalin-fixed prostate cancer specimens identifies biomarkers of disease recurrence. Cancer Res. 2014;74(12):3228–3237. doi:10.1158/0008-5472.CAN-13-2699.
  • Wyatt AW, Mo F, Wang K, McConeghy B, Brahmbhatt S, Jong L, Mitchell DM, Johnston RL, Haegert A, Li E, et al. Heterogeneity in the inter-tumor transcriptome of high risk prostate cancer. Genome Biol. 2014;15(8):426. doi:10.1186/s13059-014-0426-y.
  • Chen S, Huang V, Xu X, Livingstone J, Soares F, Jeon J, Zeng Y, Hua JT, Petricca J, Guo H, et al. Widespread and functional RNA circularization in localized prostate cancer. Cell. 2019;176(4):831–843.e22. doi:10.1016/j.cell.2019.01.025.
  • Bryant G, Wang L, Mulholland DJ. Overcoming oncogenic mediated tumor immunity in prostate cancer. Int J Mol Sci. 2017;18(7):1542. doi:10.3390/ijms18071542.
  • Rohart F, Gautier B, Singh A, Cao K-A, Schneidman D. L. mixOmics: an R package for ‘omics feature selection and multiple data integration. PLOS Comput Biol. 2017;13:e1005752. doi:10.1371/journal.pcbi.1005752.
  • Ivarsson MA, Michaëlsson J, Fauriat C. Activating killer cell Ig-like receptors in health and disease. Front Immunol. 2014;5:184. doi: 10.3389/fimmu.2014.00184.
  • Shimura S, Yang G, Ebara S, Wheeler TM, Frolov A, Thompson TC. Reduced infiltration of tumor-associated macrophages in human prostate cancer: association with cancer progression. Cancer Res. 2000;60:5857–5861.
  • Erlandsson A, Carlsson J, Lundholm M, Fält A, Andersson S-O, Andrén O, Davidsson S. M2 macrophages and regulatory T cells in lethal prostate cancer. The Prostate. 2019;79(4):363–369. doi:10.1002/pros.23742.
  • Carosella ED, Ploussard G, LeMaoult J, Desgrandchamps F, Systematic A. Review of immunotherapy in urologic cancer: evolving roles for targeting of CTLA-4, PD-1/PD-L1, and HLA-G. Eur Urol. 2015;68:267–279. doi:10.1016/j.eururo.2015.02.032.
  • Hayat SMG, Bianconi V, Pirro M, Jaafari MR, Hatamipour M, Sahebkar A. CD47: role in the immune system and application to cancer therapy. Cell Oncol Dordr. 2019;43:19-30. doi:10.1007/s13402-019-00469-5.
  • Sikic BI, Lakhani N, Patnaik A, Shah SA, Chandana SR, Rasco D, Colevas AD, O’Rourke T, Narayanan S, Papadopoulos K, et al. First-in-human, first-in-class phase i trial of the anti-CD47 antibody Hu5F9-G4 in patients with advanced cancers. J Clin Oncol Off J Am Soc Clin Oncol. 2019;37:946–953. doi:10.1200/JCO.18.02018.
  • Andrews S. 2010. FastQC: a quality control tool for high throughput sequence data. Available online at:http://www.bioinformatics.babraham.ac.uk/projects/fastqc
  • Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–2120. doi:10.1093/bioinformatics/btu170.
  • Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol. 2016;34:525–527. doi:10.1038/nbt.3519.
  • Soneson C, Love MI, Robinson MD. Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences. F1000Research. 2015;4:1521. doi:10.12688/f1000research.7563.1.
  • Smedley D, Haider S, Durinck S, Pandini L, Provero P, Allen J, Arnaiz O, Awedh MH, Baldock R, Barbiera G, et al. The BioMart community portal: an innovative alternative to large, centralized data repositories. Nucleic Acids Res. 2015;43(W1):W589–W598. doi:10.1093/nar/gkv350.
  • Kinsella RJ, Kähäri A, Haider S, Zamora J, Proctor G, Spudich G, Almeida-King J, Staines D, Derwent P, Kerhornou A, et al. Ensembl BioMarts: a hub for data retrieval across taxonomic space. Database (Oxford). 2011 Jul 23;2011:bar030. doi: 10.1093/database/bar030.
  • Risso D, Ngai J, Speed TP, Dudoit S. Normalization of RNA-seq data using factor analysis of control genes or samples. Nat Biotechnol. 2014;32:896–902. doi:10.1038/nbt.2931.
  • Gagnon-Bartsch JA, Speed TP. Using control genes to correct for unwanted variation in microarray data. Biostatistics. 2012;13:539–552. doi:10.1093/biostatistics/kxr034.
  • Vajda A, Marignol L, Barrett C, Madden SF, Lynch TH, Hollywood D, Perry AS. Gene expression analysis in prostate cancer: the importance of the endogenous control. The Prostate. 2013;73:382–390. doi:10.1002/pros.22578.
  • Chua SL, See Too WC, Khoo BY, Few LL. UBC and YWHAZ as suitable reference genes for accurate normalisation of gene expression using MCF7, HCT116 and HepG2 cell lines. Cytotechnology. 2011;63:645–654. doi:10.1007/s10616-011-9383-4.
  • de Kok JB, Roelofs RW, Giesendorf BA, Pennings JL, Waas ET, Feuth T, Swinkels DW, Span PN. Normalization of gene expression measurements in tumor tissues: comparison of 13 endogenous control genes. Lab Invest. 2005;85:154–159. doi:10.1038/labinvest.3700208.
  • Ohl F, Jung M, Xu C, Stephan C, Rabien A, Burkhardt M, Nitsche A, Kristiansen G, Loening SA, Radonić A, et al. Gene expression studies in prostate cancer tissue: which reference gene should be selected for normalization? J Mol Med. 2005;83:1014–1024. doi:10.1007/s00109-005-0703-z.
  • Dweep H, Gretz N. miRWalk2.0: a comprehensive atlas of microRNA-target interactions. Nat Methods. 2015;12: 697–697. doi:10.1038/nmeth.3485.
  • Seshan VE, Olshen A DNAcopy: DNA copy number data analysis. (Bioconductor version: Release (3.10), 2020). doi:10.18129/B9.bioc.DNAcopy.
  • Yu G, Wang L-G, He Q-Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics. 2015;31:2382–2383. doi:10.1093/bioinformatics/btv145.
  • Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST, et al. The variant call format and VCFtools. Bioinformatics. 2011;27:2156–2158. doi:10.1093/bioinformatics/btr330.
  • Angelova M, Charoentong P, Hackl H, Fischer ML, Snajder R, Krogsdam AM, Waldner MJ, Bindea G, Mlecnik B, Galon J, et al. Characterization of the immunophenotypes and antigenomes of colorectal cancers reveals distinct tumor escape mechanisms and novel targets for immunotherapy. Genome Biol. 2015;16(1). doi:10.1186/s13059-015-0620-6.
  • Rohart F, Eslami A, Matigian N, Bougeard S, Lê Cao K-A. MINT: a multivariate integrative method to identify reproducible molecular signatures across independent experiments and platforms. BMC Bioinform. 2017;18:128. doi: 10.1186/s12859-017-1553-8.
  • Budczies J, Klauschen F, Sinn BV, Győrffy B, Schmitt WD, Darb-Esfahani S, Denkert C. Cutoff finder: a comprehensive and straightforward web application enabling rapid biomarker cutoff optimization. PLoS ONE. 2012;7(12):e51862. doi:10.1371/journal.pone.0051862.