A novel gene prognostic signature lymphocyte cytosolic protein 2 regulates melanoma progression by activating tumor-infiltrating CD8+ T-cells through the interferon regulatory factor 5 signaling pathway

Cutaneous malignant melanoma is the most lethal skin cancer. The advent of immunotherapy has revolutionized the status of clinical therapies of melanoma, which brought new hope to these patients. However, only a small proportion of patients are responders. Therefore, the identification of novel prognostic and immune-related biomarkers is crucial to guide the development of melanoma clinical treatments. Herein, RNA-seq data of the cutaneous melanoma from public database were used for identifying prognostic gene signatures, and we found that lymphocyte cytosolic protein 2 (LCP2) was highly expressed in melanoma patient, which was associated with better prognosis for melanoma. Kyoto Encyclopedia of Genes and Genomes and gene ontology analyses demonstrated that the differentially expressed genes are significantly involved in lysosome, B-cell receptor signaling pathways, Fc epsilon RI signaling pathway, and T-cell receptor signaling pathway, indicating that these signaling pathways play important roles in melanoma. LCP2 expression was positively correlated with CD8+ T-cell and the overall survival of melanoma patients, and this positive correlation was directly confirmed by fluorescence-activated cell sorting experiment. The in vivo experiment showed that LCP2 knockdown significantly promoted the melanoma progression and decreased interferon regulatory factor 5 (IRF5) expression. In conclusion, we identified that LCP2 is a possible prognostic gene signature for progression-free survival of melanoma patients and regulates melanoma progression by activating tumor-infiltrating CD8+ T-cells through the IRF5 signaling pathway, indicating that LCP2 could serve as a prognostic biomarker and therapeutic target in immunotherapy.
Torre LA, Bray F, Siegel RL, et al., 2015, Global cancer statistics, 2012. CA Cancer J Clin, 65(2): 87–108. https://doi.org/10.3322/caac.21262
Schadendorf D, Fisher DE, Garbe C, et al., 2015, Melanoma. Nat Rev Dis Primers, 1: 15003. https://doi.org/10.1038/nrdp.2015.3
Luke JJ, Flaherty KT, Ribas A, et al., 2017, Targeted agents and immunotherapies: Optimizing outcomes in melanoma. Nat Rev Clin Oncol, 14(8): 463. https://doi.org/10.1038/nrclinonc.2017.43
Redman JM, Gibney GT, Atkins MB, 2016, Advances in immunotherapy for melanoma. BMC Med, 14(1): 20. https://doi.org/10.1186/s12916-016-0571-0
D’Arcangelo D, Giampietri C, Muscio M, et al., 2018, WIPI1, BAG1, and PEX3 autophagy-related genes are relevant melanoma markers. Oxidat Med Cell Longev, 2018: 1471682. https://doi.org/10.1155/2018/1471682
Gerami P, Cook RW, Wilkinson J, et al., 2015, Development of a prognostic genetic signature to predict the metastatic risk associated with cutaneous melanoma. Clin Cancer Res, 21(1): 175–183. https://doi.org/10.1158/1078-0432.CCR-13-3316
Zhao Y, Schaafsma E, Gorlov IP, et al., 2018, A leukocyte infiltration score defined by a gene signature predicts melanoma patient prognosis. Mol Cancer Res, 17(1): 109filtra. https://doi.org/10.1158/1541-7786.MCR-18-0173
Clements JL, Ross-Barta SE, Tygrett LT, et al., 1998, SLP-76 expression is restricted to hemopoietic cells of monocyte, granulocyte, and T lymphocyte lineage and is regulated during T cell maturation and activation. J Immunol, 161: 3880–3889.
Jumaa H, Wollscheid B, Mitterer M, et al., 1999, Abnormal development and function of B lymphocytes in mice deficient for the signalling adaptor protein SLP-65. Immunity, 11: 547–554. https://doi.org/10.1016/s1074-7613(00)80130-2
Zhang J, Wang L, Xu X, et al., 2020, Transcriptome-based network analysis unveils eight immune-related genes as molecular signatures in the immunomodulatory subtype of triple negative breast cancer. Front Oncol, 10: 1787. https://doi.org/10.3389/fonc.2020.01787
Huo Y, Zhang K, Han S, et al., 2021, Lymphocyte cytosolic protein 2 is a novel prognostic marker in lung adenocarcinoma. J Int Med Res, 49(11): 3000605211059681. https://doi.org/10.1177/03000605211059681
Wang Z, Peng M, 2021, A novel prognostic biomarker LCP2 correlates with metastatic melanoma-infiltrating CD8 T cells. Sci Rep, 11(1): 9164. https://doi.org/10.1038/s41598-021-88676-9
Koretzky GA, Abtahian F, Silverman MA, 2006, SLP76 and SLP65: Complex regulation of signalling in lymphocytes and beyond. Nat Rev Immunol, 6(1): 67–78. https://doi.org/10.1038/nri1750
Navas VH, Cuche C, Alcover A, et al., 2017, Serine phosphorylation of SLP76 is dispensable for T cell development but modulates helper T cell function. PLoS One, 12(1): e0170396. https://doi.org/10.1371/journal.pone.0170396
Sommers CL, Menon RK, Grinberg A, et al., 2001, Knock-in mutation of the distal four tyrosines of linker for activation of T cells blocks murine T cell development. J Exp Med, 194(2): 135–142. https://doi.org/10.1084/jem.194.2.135
Maltzman JS, Kovoor L, Clements JL, et al., 2005, Conditional deletion reveals a cell-autonomous requirement of SLP-76 for thymocyte selection. J Exp Med, 202(7): 893–900. https://doi.org/10.1084/jem.20051128
Siggs OM, Miosge LA, Daley SR, et al., 2015, Quantitative reduction of the TCR adapter protein SLP-76 unbalances immunity and immune regulation. J Immunol, 194(6): 2587–2595. https://doi.org/10.4049/jimmunol.1400326
Fabregat A, Jupe S, Matthews L, et al., 2017, The reactome pathway knowledgebase. Nucleic Acids Res, 46(D1): D649–D655. https://doi.org/10.1093/nar/gkx1132
Hastie T, Tibshirani R, Narasimhan B, et al., 2016, Impute: Imputation for microarray data. Oral History Rev, 2016.
Benjamini Y, Hochberg Y, 1995, Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc Ser B Methodol, 57(1): 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x
Tang Z, Li C, Kang B, et al., 2017, GEPIA: A web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Res, 45(W1): W98–W102. https://doi.org/10.1093/nar/gkx247
Yu G, Wang LG, Han Y, et al., 2012, clusterProfiler: An R package for comparing biological themes among gene clusters. OMICS, 16(5): 284–287. https://doi.org/10.1089/omi.2011.0118
Friedman J, Hastie T, Tibshirani R, 2009, Glmnet: Lasso and Elastic-net Regularized Generalized Linear Models. R Package Version, 1(4).
Newman AM, Liu CL, Green MR, et al., 2015, Robust enumeration of cell subsets from tissue expression profiles. Nat Methods, 12(5): 453–457. https://doi.org/10.1038/nmeth.3337
Balatoni T, Mohos A, Papp E, et al., 2018, Tumor-infiltrating immune cells as potential biomarkers predicting response to treatment and survival in patients with metastatic melanoma receiving ipilimumab therapy. Cancer Immunol Immunother, 67(1): 141–151. https://doi.org/10.1007/s00262-017-2072-1
Liu D, 2019, CAR-T “the living drugs”, immune checkpoint inhibitors, and precision medicine: A new era of cancer therapy. J Hematol Oncol, 12(1): 113. https://doi.org/10.1186/s13045-019-0819-1
Dabrosin N, Juul KS, Georgsen JB, et al., 2019, Innate immune cell infiltration in melanoma metastases affects survival and is associated with BRAFV600E mutation status. Melanoma Res, 29(1): 30–37. https://doi.org/10.1097/CMR.0000000000000515
Fu X, Yin M, 2022, Monocytes in tumor: The perspectives of single-cell analysis. Tumor Discov, 1(1): 4. https://doi.org/10.36922/td.v1i1.4
Honda K, Taniguchi T, 2006, IRFs: Master regulators of signalling by Toll-like receptors and cytosolic pattern-recognition receptors. Nat Rev Immunol, 6(9): 644–658. https://doi.org/10.1038/nri1900
Honda K, Takaoka A, Taniguchi T, 2006, Type I interferon [corrected] gene induction by the interferon regulatory factor family of transcription factors. Immunity, 25(3): 349–360. https://doi.org/10.1016/j.immuni.2006.08.009
Tamura T, Yanai H, Savitsky D, et al., 2008, The IRF family transcription factors in immunity and oncogenesis. Annu Rev Immunol, 26: 535–584. https://doi.org/10.1146/annurev.immunol.26.021607.090400
Lohoff M, Mak TW, 2005, Roles of interferon-regulatory factors in T-helper-cell differentiation. Nat Rev Immunol, 5(2): 125–135. https://doi.org/10.1038/nri1552
Battistini A, 2009, Interferon regulatory factors in hematopoietic cell differentiation and immune regulation. J Interferon Cytokine Res, 29(12): 765–780. https://doi.org/10.1089/jir.2009.0030
Zhao GN, Jiang DS, Li H, 2015, Interferon regulatory factors: At the crossroads of immunity, metabolism, and disease. Biochim Biophys Acta Mol Basis Dis, 1852(2): 365–378. https://doi.org/10.1016/j.bbadis.2014.04.030
Barnes BJ, Kellum MJ, Field AE, et al., 2002, Multiple regulatory domains of IRF-5 control activation, cellular localization, and induction of chemokines that mediate recruitment of T lymphocytes. Mol Cell Biol, 22(16): 5721–5740. https://doi.org/1128/MCB.22.16.5721-5740.2002
Kaur A, Lee LH, Chow SC, et al., 2018, IRF5-mediated immune responses and its implications in immunological disorders. Int Rev Immunol, 37(5): 229–248. https://doi.org/10.1080/08830185.2018.146962
Pimenta EM, De S, Weiss R, et al., 2015, IRF5 is a novel regulator of CXCL13 expression in breast cancer that regulates CXCR5(+) B-and T-cell trafficking to tumor conditioned media. Immunol Cell Biol, 93(5): 486–499. https://doi.org/10.1038/icb.2014.110
Takaoka A, Yanai H, Kondo S, et al., 2005, Integral role of IRF-5 in the gene induction programme activated by Toll-like receptors. Nature, 434(7030): 243–249. https://doi.org/10.1038/nature03308