Aberrant Phenotypes in Acute Myeloid Leukemia and Its Relationship with Prognosis and Survival: A Systematic Review and Meta-Analysis
a systematic review and meta-analysis
Background: The aim of this review was to evaluate the influence of aberrant phenotypes in prognosis and survival in acute myeloid leukemia (AML) patients by multiparametric flow cytometry.
Materials and Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a review of PubMed, Scopus, Science Direct and Web of Science was carried out through 1998 to 2016, conducted by two reviewers independently, evaluating titles, abstracts and full-texts of the selected studies.
Results: Ten studies were included on this review, in which the aberrant phenotype expression of 17 markers were detected in AML patients. From these, 11 aberrant phenotypes were associated with prognosis, which eight had shown negative impact on prognosis: CD7, CD56, CD15, CD2, CD3, CD90low, CD123high, CD117high, and three others were associated with good prognosis: CD19, CD98high and CD117+/CD15+. Meta-analysis showed that aberrant expression of CD56 as a poor prognostic marker with unfavorable outcomes is implicated in decreased overall survival in AML patients in 28 months (95% CI: 0.62 to 0.92).
Conclusion: This was observed when there was association between CD56 expression and other prognostic factors, influencing on patients’ management care and treatment.
2. Prada-Arismendy J, Arroyave J, Röthlisberger S. Molecular biomarkers in acute myeloid leukemia. Blood Rev. 2017; 31(1):63–76.
3. Khwaja A, Bjorkholm M, Gale RE, et al. Acute myeloid leukaemia. Nat Rev Dis Primers. 2016; 2:16010.
4. De Kouchkovsky I, Abdul-Hay M. Acute myeloid leukemia: a comprehensive review and 2016 update. Blood Cancer J. 2016; 6(7):e441.
5. Strickland SA, Mohan SR, Savona MR. Unfavorable-risk acute myeloid leukemia dissected. Curr Opin Hematol. 2016; 23(2):144–9.
6. Miller KD, Siegel RL, Lin CC, et al. Cancer treatment and survivorship statistics, 2016. CA Cancer J Clin. 2016; 66(4):271–89.
7. Rose-Inman H, Kuehl D. Acute leukemia. Emerg Med Clin North Am. 2014; 32(3):579–96.
8. Khakhlari N, Gogoi B, Barua A, et al. A Study of Aberrant Phenotypes in Acute Leukemia by Flowcytometry. Int J Med Res Prof. 2016; 2(4):50–53.
9. Chen X, Cherian S. Acute Myeloid Leukemia Immunophenotyping by Flow Cytometric Analysis. Clin Lab Med. 2017; 37(4):753–769.
10. Momani A, Abbasi N, Alsokhni H, et al. Aberrant Antigen Expression in Patients with Acute Leukemias; Experience of King Hussein Medical Center in Jordan. JRSM. 2016; 23(2):59–67.
11. Wertheim GBW. Molecular characterization and testing in acute myeloid leukemia. J Hematopathol. 2015; 8:177–89.
12. Hamad IN, Assad S, Rahman M, et al. Flow cytometric analysis: four-year experience in a Tertiary Care Centre of Pakistan. Cureus. 2016; 8(9):e764.
13. Finak G, Langweiler M, Jaimes M, et al. Standardizing flow cytometry immunophenotyping analysis from the human immunophenotyping consortium. Sci Rep. 2016; 6:20686
14. Parikh BP, Patel SP, Raiya BN, et al. Applicability of a single 5 color cytoplasmic markers tube as primary panel for immunophenotyping of acute leukemia: a Gujarat Cancer and Research Institute experience. Indian J Cancer. 2016; 53(3):349–352.
15. Rahman MM, Rahim R. Flow cytometric immunophenotyping of acute leukemia: the essential considerations. Pulse. 2016; 9:27–36.
16. Zeijlemaker W, Kelder A, Wouters R, et al. Absence of leukaemic CD34+ cells in acute myeloid leukaemia is of high prognostic value: a longstanding controversy deciphered. Br J Haematol. 2015; 171(2):227–238.
17. Moher D, Liberati A, Tetzlaff J, et al. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009; 6(7):e1000097
18. Bendall SC, Nolan GP, Roederer M, et al. A deep profiler’s guide to cytometry. Trends Immunol. 2012; 33(7):323–32.
19. Vandenbroucke JP, Von Elm E, Altman DG, et al. Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration. Epidemiology. 2007; 18(6):805–35.
20. Higgins JPT, Green S. Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0. [Updated March 2011]. The Cochrane Collaboration, 2011. Available at https://handbook-5-1.cochrane.org/.
21. R. Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, 2016. Available at https://www.R-project.org/.
22. Viechtbauer W. Conducting meta-analyses in R with the metafor package. J Stat Softw. 2010; 36(3):1–48.
23. Rausei-Mills V, Chang KL, Gaal KK, et al. Aberrant expression of CD7 in myeloblasts is highly associated with de novo acute myeloid leukemias with FLT3/ITD mutation. Am J Clin Pathol. 2008; 129(4):624–9.
24. Abdulateef NAB, Ismail MM, Aljedani H. Clinical significance of co-expression of aberrant antigens in acute leukemia: a retrospective cohort study in Makah Al Mukaramah, Saudi Arabia. Asia Pac J Cancer Prev. 2014;15(1): 221–7.
25. Bahia DM, Yamamoto M, Chauffaille M de L, et al. Aberrant phenotypes in acute myeloid leukemia: a high frequency and clinical significance. Haematologica. 2001;86(8):801–6.
26. Jahedi M, Shamsasenjan K, Sanaat Z, et al. Aberrant phenotype in Iranian patients with acute myeloid leukemia. Adv Pharm Bull. 2014; 4(1): 43–47.
27. Chen SW, Li CF, Chuang SS, et al. Aberrant co-expression of CD19 and CD56 as surrogate markers of
acute myeloid leukemias with t(8;21) in Taiwan. Int J Lab Hematol. 2008; 30(2):133–8.
28. Cui W, Zhang D, Cunningham MT, et al. Leukemia-associated aberrant immunophenotype in patients with acute myeloid leukemia: changes at refractory disease or first relapse and clinicopathological findings. Int J Lab Hematol. 2014; 36(6):636–49.
29. Iriyama N, Hatta Y, Takeuchi J, et al. CD56 expression is an independent prognostic factor for relapse in acute myeloid leukemia with t(8;21). Leuk Res. 2013; 37(9):1021–6.
30. Breccia M, Porpris MS, Minotti C, et al. Aberrant phenotypic expression of CD15 and CD56 identifies poor prognostic acute promyelocytic leukemia patients. Leuk Res. 2014; 38(2):194–7.
31. Chávez-Gonzáles A, Dorantes-Acosta E, Moreno-Lorenzana D, et al. Expression of CD90, CD96, CD117, and CD123 on different hematopoietic cell populations from pediatric patients with acute myeloid leukemia. Arch Med Res. 2014; 45(4):343–50.
32. Nikolova M, Guenova M, Taskov H, et al. Levels of expression of CAF(CD98) have prognostic significance in adult acute leukemia. Leuk Res. 1998; 22(1):39–47.
33. Tang J, Li J, Zhu X, et al. Novel CD7-specific nanobody-based immunotoxins potently enhanced apoptosis of CD7-positive malignant cells. Oncotarget. 2016; 7(23):34070–34083.
34. Gomes-Silva D, Srinivasan M, Sharma S, et al. CD7-edited T cells expressing a CD7-specific CAR for the therapy of T-cell malignancies. Blood. 2017; 130(3):285-296.
35. Feng Y, Wang Y, Zhu Z, et al. Differential killing of CD56-expressing cells by drug-conjugated human antibodies targeting membrane-distal and membrane-proximal non-overlapping epitopes. MAbs. 2016;8(4):799–810.
36. Van Acker HH, Capsomidis A, Smits EL, et al. CD56 in the Immune System: More Than a Marker for Cytotoxicity? Front Immunol. 2017; 8:892.
37. Wang X, Ji CG, Zhang JZH. Glycosylation Modulates Human CD2-CD58 Adhesion via Conformational Adjustment. J Phys Chem B. 2015;119(22):6493−501.
38. Birnbaum ME, Berry R, Hsiao YS, et al. Molecular architecture of the αβ T cell receptor–CD3 complex. PNAS. 2014;111(49):17576–17581.
39. Williams AF, Gagnon J. Neuronal Cell Thy-1 Glycoprotein: Homology with Immunoglobulin. Science. 1982;216(4547):696–703.
40. Wang K, Wei G, Liu D. CD19: a biomarker for B cell development, lymphoma diagnosis and therapy. Exp Hematol Oncol. 2012; 1(36):1-7.
41. Hoseini SS, Cheung NK. Acute myeloid leukemia targets for bispecific antibodies. Blood Cancer J. 2017; 7(2):e522.
42. Foster BM, Zaidi D, Young TR, et al. CD117/c-kit in Cancer Stem Cell-Mediated Progression and Therapeutic Resistance. Biomedicines. 2018; 6(1): 31.
43. Gadhoum SZ, Sackstein R. Lewis x/CD15 expression in human myeloid cell differentiation is regulated by sialidase activity. Nat Chem Biol. 2008; 4(12): 751–757.
44. Forsthuber TG, Cimbora DM, Ratchford JN, et al. B cell-based therapies in CNS autoimmunity: differentiating CD19 and CD20 as therapeutic targets. Ther Adv Neurol Disord. 2018; 11: 1756286418761697.
45. Hayes GM, Chinn L, Cantor JM, et al. Antitumor activity of an anti-CD98 antibody. Int J Cancer. Int J Cancer. 2015; 137(3):710-20
46. Karnell JL, Dimasi N, Karnell FG, et al. CD19 and CD32b Differentially Regulate Human B Cell Responsiveness. J Immunol. 2014; 192(4): 1480–1490.
47. Kumar A, Bhanja A, Bhattacharyya J, et al. Multiple roles of CD90 in cancer. Tumor Biol. 2016;37(9):11611–11622.
48. Shaikh MV, Kala M, Nivsarkara M. CD90 a potential cancer stem cell marker and a therapeutic target. Cancer Biomark. 2016; 16(3):301–7.
49. Testa U, Pelosi E, Frankel A. CD 123 is a membrane biomarker and a therapeutic target in hematologic malignancies. Biomark Res. 2014; 2(1):4.
50. Babaei MA, Kamalidehghan B, Saleem M, et al. Receptor tyrosine kinase (c-Kit) inhibitors: a potential therapeutic target in cancer cells. Drug Des Devel Ther 2016;10: 2443-59.
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