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Volume 18, Issue 1 (March-2026 2026)
Iranian Journal of Blood and Cancer 2026, 18(1): 40-48 |
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Saeedi N, Khalili Tanha G, Judaki A A, Nazari E. Extracellular Immune Signatures as Prognostic Biomarkers and Liquid-Biopsy Candidates in AML. Iranian Journal of Blood and Cancer 2026; 18 (1) :40-48
URL: http://ijbc.ir/article-1-1831-en.html
URL: http://ijbc.ir/article-1-1831-en.html
1- Student Research Committee, Islamic Azad University, Mashhad Branch, Mashhad, Iran.
2- Department of Medical Genetics and Molecular Medicine, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
3- Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. & Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
2- Department of Medical Genetics and Molecular Medicine, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
3- Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran. & Department of Health Information Technology and Management, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abstract: (686 Views)
Background: Acute myeloid leukemia (AML) has poor long-term survival, necessitating robust prognostic biomarkers. While conventional markers focus on cytogenetics and mutations, immune-extracellular genes suitable for liquid biopsy remain understudied.
Methods: RNA-sequencing data from 200 AML patients were analyzed from The Cancer Genome Atlas (TCGA). Univariate Cox regression identified survival-associated genes. Gene Ontology enrichment analysis selected immune and extracellular genes, with Kaplan-Meier analysis validating prognostic significance. REACTOME pathway enrichment revealed biological mechanisms. External validation used GEPIA2.
Results: Cox regression identified 201 survival-associated genes (p<0.05): 149 favorable prognosis (HR<1) and 52 poor prognosis (HR>1). Gene Ontology enrichment revealed 29 immune-associated and 9 extracellular genes, with 5 overlapping candidates. Kaplan-Meier analysis confirmed four genes; EPHA10, CD160, BTN2A2, and KLRK1 as significant protective prognostic markers (p<0.05, HR<1). REACTOME analysis highlighted immune signaling pathways including adaptive immune response, natural killer cell-mediated cytotoxicity, and cell surface interactions. External validation demonstrated differential expression in AML versus normal tissues.
Conclusion: This study identified EPHA10, CD160, BTN2A2, and KLRK1 as novel immune-extracellular prognostic biomarkers in AML. These genes represent promising candidates for liquid biopsy applications and personalized immunotherapy strategies, offering new perspectives for monitoring immune surveillance and overcoming AML immune evasion.
Methods: RNA-sequencing data from 200 AML patients were analyzed from The Cancer Genome Atlas (TCGA). Univariate Cox regression identified survival-associated genes. Gene Ontology enrichment analysis selected immune and extracellular genes, with Kaplan-Meier analysis validating prognostic significance. REACTOME pathway enrichment revealed biological mechanisms. External validation used GEPIA2.
Results: Cox regression identified 201 survival-associated genes (p<0.05): 149 favorable prognosis (HR<1) and 52 poor prognosis (HR>1). Gene Ontology enrichment revealed 29 immune-associated and 9 extracellular genes, with 5 overlapping candidates. Kaplan-Meier analysis confirmed four genes; EPHA10, CD160, BTN2A2, and KLRK1 as significant protective prognostic markers (p<0.05, HR<1). REACTOME analysis highlighted immune signaling pathways including adaptive immune response, natural killer cell-mediated cytotoxicity, and cell surface interactions. External validation demonstrated differential expression in AML versus normal tissues.
Conclusion: This study identified EPHA10, CD160, BTN2A2, and KLRK1 as novel immune-extracellular prognostic biomarkers in AML. These genes represent promising candidates for liquid biopsy applications and personalized immunotherapy strategies, offering new perspectives for monitoring immune surveillance and overcoming AML immune evasion.
Keywords: Acute myeloid leukemia, Biomarkers, Immune microenvironment, Extracellular genes, Prognosis, TCGA
: Original Article |
Subject:
AI in Medicine
Received: 2025/11/9 | Accepted: 2026/03/7 | Published: 2026/03/31
Received: 2025/11/9 | Accepted: 2026/03/7 | Published: 2026/03/31
References
1. Siegel, R.L., K.D. Miller, and A. Jemal, Cancer statistics, 2020. CA Cancer J Clin, 2020. 70(1): p. 7-30. [DOI:10.3322/caac.21590]
2. Shallis, R.M., et al., Epidemiology of acute myeloid leukemia: Recent progress and enduring challenges. Blood Rev, 2019. 36: p. 70-87. [DOI:10.1016/j.blre.2019.04.005]
3. Xia, C., et al., Cancer statistics in China and United States, 2022: profiles, trends, and determinants. Chin Med J (Engl), 2022. 135(5): p. 584-590. [DOI:10.1097/CM9.0000000000002108]
4. Döhner, H., et al., Diagnosis and management of AML in adults: 2017 ELN recommendations from an international expert panel. Blood, 2017. 129(4): p. 424-447. [DOI:10.1182/blood-2016-08-733196]
5. Sabattini, E., et al., WHO classification of tumours of haematopoietic and lymphoid tissues in 2008: an overview. Pathologica, 2010. 102(3): p. 83-7.
6. Yohe, S., Molecular Genetic Markers in Acute Myeloid Leukemia. J Clin Med, 2015. 4(3): p. 460-78. [DOI:10.3390/jcm4030460]
7. Chen, Y., X. Qiu, and R. Liu, Comprehensive characterization of immunogenic cell death in acute myeloid leukemia revealing the association with prognosis and tumor immune microenvironment. BMC Medical Genomics, 2024. 17(1): p. 107. [DOI:10.1186/s12920-024-01876-w]
8. Hu, X., et al., Exploring prognostic genes in the immune microenvironment of acute myeloid leukemia via weighted gene co-expression network analysis. Medicine, 2025. 104(42): p. e44062. [DOI:10.1097/MD.0000000000044062]
9. Liu, M., et al., Immunosuppressive cells in acute myeloid leukemia: mechanisms and therapeutic target. Frontiers in Immunology, 2025. 16: p. 1627161. [DOI:10.3389/fimmu.2025.1627161]
10. Tettamanti, S., et al., Catch me if you can: how AML and its niche escape immunotherapy. Leukemia, 2022. 36(1): p. 13-22. [DOI:10.1038/s41375-021-01350-x]
11. Koedijk, J.B., et al., A multidimensional analysis reveals distinct immune phenotypes and the composition of immune aggregates in pediatric acute myeloid leukemia. Leukemia, 2024. 38(11): p. 2332-2343. [DOI:10.1038/s41375-024-02381-w]
12. Mumme, H.L., et al., Identification of leukemia-enriched signature through the development of a comprehensive pediatric single-cell atlas. Nature Communications, 2025. 16(1): p. 4114. [DOI:10.1038/s41467-025-59362-5]
13. Tosato, G., Ephrin ligands and Eph receptors contribution to hematopoiesis. Cell Mol Life Sci, 2017. 74(18): p. 3377-3394. [DOI:10.1007/s00018-017-2566-1]
14. Darling, T. and T. Lamb, Emerging roles for Eph receptors and ephrin ligands in immunity. Front Immunol 10: 1473. 2019. [DOI:10.3389/fimmu.2019.01473]
15. Koshikawa, N., et al., Specific detection of soluble EphA2 fragments in blood as a new biomarker for pancreatic cancer. Cell Death & Disease, 2017. 8(10): p. e3134-e3134. [DOI:10.1038/cddis.2017.545]
16. Brenner, A.K., T.H. Andersson Tvedt, and Ø. Bruserud, The Complexity of Targeting PI3K-Akt-mTOR Signalling in Human Acute Myeloid Leukaemia: The Importance of Leukemic Cell Heterogeneity, Neighbouring Mesenchymal Stem Cells and Immunocompetent Cells. Molecules, 2016. 21(11). [DOI:10.3390/molecules21111512]
17. Wang, A., et al., Comprehensive analysis of Epha10 as a predictor of clinical prognosis and immune checkpoint therapy efficacy in non-small cell lung cancer. Sci Rep, 2024. 14(1): p. 19623. [DOI:10.1038/s41598-024-70466-8]
18. Cha, J.H., et al., Ephrin receptor A10 monoclonal antibodies and the derived chimeric antigen receptor T cells exert an antitumor response in mouse models of triple-negative breast cancer. J Biol Chem, 2022. 298(4): p. 101817. [DOI:10.1016/j.jbc.2022.101817]
19. Li, Y., et al., Isoform expression patterns of EPHA10 protein mediate breast cancer progression by regulating the E-Cadherin and β-catenin complex. Oncotarget, 2017. 8(18): p. 30344-30356. [DOI:10.18632/oncotarget.15910]
20. Kojima, R., et al., Molecular basis for herpesvirus entry mediator recognition by the human immune inhibitory receptor CD160 and its relationship to the cosignaling molecules BTLA and LIGHT. J Mol Biol, 2011. 413(4): p. 762-72. [DOI:10.1016/j.jmb.2011.09.018]
21. Tan, C.L., et al., CD160 Stimulates CD8(+) T Cell Responses and Is Required for Optimal Protective Immunity to Listeria monocytogenes. Immunohorizons, 2018. 2(7): p. 238-250. [DOI:10.4049/immunohorizons.1800039]
22. Crinier, A., et al., Reply to 'Comment to: Single-cell profiling reveals the trajectories of natural killer cell differentiation in bone marrow and a stress signature induced by acute myeloid leukemia'. Cell Mol Immunol, 2021. 18(5): p. 1350-1352.
https://doi.org/10.1038/s41423-021-00678-9 [DOI:10.1038/s41423-020-00574-8]
23. Pan, Y., et al., Immunotherapy-relevance of a candidate prognostic score for Acute Myeloid Leukemia. Heliyon, 2024. 10(11): p. e32154. [DOI:10.1016/j.heliyon.2024.e32154]
24. Farren, T.W., et al., Minimal residual disease detection with tumor-specific CD160 correlates with event-free survival in chronic lymphocytic leukemia. Blood Cancer J, 2015. 5(1): p. e273. [DOI:10.1038/bcj.2014.92]
25. Crinier, A., et al., Single-cell profiling reveals the trajectories of natural killer cell differentiation in bone marrow and a stress signature induced by acute myeloid leukemia. Cell Mol Immunol, 2021. 18(5): p. 1290-1304.
https://doi.org/10.1038/s41423-021-00678-9 [DOI:10.1038/s41423-020-00574-8]
26. Sarter, K., et al., Btn2a2, a T cell immunomodulatory molecule coregulated with MHC class II genes. Journal of Experimental Medicine, 2016. 213(2): p. 177-187. [DOI:10.1084/jem.20150435]
27. Ammann, J.U., A. Cooke, and J. Trowsdale, Butyrophilin Btn2a2 inhibits TCR activation and phosphatidylinositol 3-kinase/Akt pathway signaling and induces Foxp3 expression in T lymphocytes. J Immunol, 2013. 190(10): p. 5030-6. [DOI:10.4049/jimmunol.1203325]
28. Sarter, K., et al., Btn2a2, a T cell immunomodulatory molecule coregulated with MHC class II genes. J Exp Med, 2016. 213(2): p. 177-87. [DOI:10.1084/jem.20150435]
29. Wang, H., et al., BTN2A2, a new biomarker and therapeutic target for glioma. Aging (Albany NY), 2023. 15(20): p. 10996-11011. [DOI:10.18632/aging.205039]
30. Xiao, L., et al., An antibody targeting an immune checkpoint molecule BTN2A2 enhances anti-tumor immunity. Neoplasia, 2025. 65: p. 101161. [DOI:10.1016/j.neo.2025.101161]
31. Mastaglio, S., et al., Natural killer receptor ligand expression on acute myeloid leukemia impacts survival and relapse after chemotherapy. Blood Adv, 2018. 2(4): p. 335-346. [DOI:10.1182/bloodadvances.2017015230]
32. Bandyopadhyay, S.K., et al., KDM6A Modulates Anti-Tumor Immune Response By Integrating Immunogenic Cell Death in Human Acute Myeloid Leukemia. Blood, 2023. 142: p. 2753. [DOI:10.1182/blood-2023-178210]
33. Truxova, I., et al., Calreticulin exposure on malignant blasts correlates with improved natural killer cell-mediated cytotoxicity in acute myeloid leukemia patients. Haematologica, 2020. 105(7): p. 1868-1878. [DOI:10.3324/haematol.2019.223933]
34. Hussein, B.A., et al., Impact of NK Cell Activating Receptor Gene Variants on Receptor Expression and Outcome of Immunotherapy in Acute Myeloid Leukemia. Front Immunol, 2021. 12: p. 796072. [DOI:10.3389/fimmu.2021.796072]
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