Format

Send to

Choose Destination
Pathologe. 2013 Nov;34 Suppl 2:201-9. doi: 10.1007/s00292-013-1824-8.

[Differential diagnosis of myeloproliferative neoplasms. Quantitative NF-E2 immunohistochemistry for differentiating between essential thrombocythemia and primary myelofibrosis].

[Article in German]

Author information

1
Institut für Pathologie, Universitätsklinikum Freiburg, Breisacher Str. 115a, 79106, Freiburg, Deutschland, Konrad.Aumann@uniklinik-freiburg.de.

Abstract

BACKGROUND:

Besides essential thrombocythemia (ET), polycythemia vera (PV) and primary myelofibrosis (PMF) the myeloproliferative neoplasms (MPN) defined by the World Health Organization (WHO) comprise the entity of unclassifiable MPNs (MPN, U). The exact differential diagnosis of the specific MPN entities can be challenging particularly at early stages of the diseases. So far, pathologists have had to rely only on histomorphological evaluation of bone marrow biopsies in combination with laboratory data because helpful ancillary tests are not yet available. Even molecular tests, such as JAK2 mutation analysis are not helpful particularly in the differential diagnosis of ET and PMF because both entities are associated with the V617F mutation in 50 % of the cases. Recently overexpression of the transcription factor NF-E2 in MPN was described.

MATERIALS AND METHODS:

A collective of samples consisting of 163 bone marrow biopsies including 139 MPN cases was stained immunohistochemically for NF-E2 and analyzed regarding the subcellular localization of NF-E2 in erythroid progenitor cells. The results were compared between the MPN entities as well as the controls and statistical analyses were conducted.

RESULTS AND DISCUSSION:

This study showed that NF-E2 immunohistochemistry and analysis of the proportion of nuclear positive erythroblasts of all erythroid precursor cells can help to distinguish between ET and PMF even in early stages of the diseases. An MPN, U case showing a proportion of more than 20 % nuclear positive erythroblasts can be classified as a PMF with 92 % accuracy.

PMID:
24196613
DOI:
10.1007/s00292-013-1824-8
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Springer
Loading ...
Support Center