References
1. Xu Y, McKenna RW, Karandikar NJ, Pildain AJ, Kroft SH. Flow
cytometric analysis of monocytes as a tool for distinguishing chronic
myelomonocytic leukemia from reactive monocytosis. Am J Clin
Pathol . Nov 2005;124(5):799-806. doi:10.1309/HRJ1-XKTD-77J1-UTFM
2. Talati C, Zhang L, Shaheen G, et al. Monocyte subset analysis
accurately distinguishes CMML from MDS and is associated with a
favorable MDS prognosis. Blood . Mar 30 2017;129(13):1881-1883.
doi:10.1182/blood-2016-12-753210
3. Selimoglu-Buet D, Wagner-Ballon O, Saada V, et al. Characteristic
repartition of monocyte subsets as a diagnostic signature of chronic
myelomonocytic leukemia. Blood . Jun 4 2015;125(23):3618-26.
doi:10.1182/blood-2015-01-620781
4. Picot T, Aanei CM, Flandrin Gresta P, et al. Evaluation by Flow
Cytometry of Mature Monocyte Subpopulations for the Diagnosis and
Follow-Up of Chronic Myelomonocytic Leukemia. Front Oncol .
2018;8:109. doi:10.3389/fonc.2018.00109
5. Hudson CA, Burack WR, Leary PC, Bennett JM. Clinical Utility of
Classical and Nonclassical Monocyte Percentage in the Diagnosis of
Chronic Myelomonocytic Leukemia. Am J Clin Pathol . Aug 30
2018;150(4):293-302. doi:10.1093/ajcp/aqy054
6. Passlick B, Flieger D, Ziegler-Heitbrock HW. Identification and
characterization of a novel monocyte subpopulation in human peripheral
blood. Blood . Nov 15 1989;74(7):2527-34.
7. Ziegler-Heitbrock L, Ancuta P, Crowe S, et al. Nomenclature of
monocytes and dendritic cells in blood. Blood . Oct 21
2010;116(16):e74-80. doi:10.1182/blood-2010-02-258558
8. Grage-Griebenow E, Zawatzky R, Kahlert H, Brade L, Flad H, Ernst M.
Identification of a novel dendritic cell-like subset of CD64(+) /
CD16(+) blood monocytes. Eur J Immunol . Jan 2001;31(1):48-56.
doi:10.1002/1521-4141(200101)31:1<48::aid-immu48>3.0.co;2-5
9. Patnaik MM, Timm MM, Vallapureddy R, et al. Flow cytometry based
monocyte subset analysis accurately distinguishes chronic myelomonocytic
leukemia from myeloproliferative neoplasms with associated monocytosis.Blood Cancer J . Jul 21 2017;7(7):e584. doi:10.1038/bcj.2017.66
10. Wong KL, Tai JJ, Wong WC, et al. Gene expression profiling reveals
the defining features of the classical, intermediate, and nonclassical
human monocyte subsets. Blood . Aug 4 2011;118(5):e16-31.
doi:10.1182/blood-2010-12-326355
11. Ozanska A, Szymczak D, Rybka J. Pattern of human monocyte
subpopulations in health and disease. Scand J Immunol . Apr 3
2020;doi:10.1111/sji.12883
12. Carstensen M, Christensen T, Stilund M, Moller HJ, Petersen EL,
Petersen T. Activated monocytes and markers of inflammation in newly
diagnosed multiple sclerosis. Immunol Cell Biol . Apr 6
2020;doi:10.1111/imcb.12337
13. Inoue S, Shibata T, Ravindranath Y, Gohle N. Clonal origin of
erythroid cells in juvenile chronic myelogenous leukemia. Blood .
Mar 1987;69(3):975-6.
14. Inoue S, Ravindranath Y, Thompson RI, Zuelzer WW, Ottenbreit MJ.
Cytogenetics of juvenile type chronic granulocytic leukemia.Cancer . May 1977;39(5):2017-24.
doi:10.1002/1097-0142(197705)39:5<2017::aid-cncr2820390518>3.0.co;2-z
15. Niemeyer CM, Flotho C. Juvenile myelomonocytic leukemia: who’s the
driver at the wheel? Blood . Mar 7 2019;133(10):1060-1070.
doi:10.1182/blood-2018-11-844688
16. Murakami N, Okuno Y, Yoshida K, et al. Integrated molecular
profiling of juvenile myelomonocytic leukemia. Blood . Apr 5
2018;131(14):1576-1586. doi:10.1182/blood-2017-07-798157