Evidence map›Paper›PMID 26937202›Full record

ArticleOncoTargets and therapy2016

Using the geometric mean fluorescence intensity index method to measure ZAP-70 expression in patients with chronic lymphocytic leukemia.

Yu-Jie Wu, Hui Wang, Jian-Hua Liang, Yi Miao, Lu Liu, Hai-Rong Qiu, Chun Qiao, Rong Wang, Jian-Yong Li

Abstract read
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Article in OncoTargets and therapy, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Yu-Jie WuDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.
Hui WangDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.
Jian-Hua LiangDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.
Yi MiaoDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.
Lu LiuDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.
Hai-Rong QiuDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.
Chun QiaoDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.
Rong WangDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.
Jian-Yong LiDepartment of Hematology, First Affiliated Hospital of Nanjing Medical University, Jiangsu Province Hospital, Nanjing, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Expression of ζ-chain-associated protein kinase 70 kDa (ZAP-70) in chronic lymphocytic leukemia (CLL) is associated with more aggressive disease and can help differentiate CLL from cases expressing mutated or unmutated immunoglobulin heavy chain variable region (IgHV) genes. However, standardizing ZAP-70 expression by flow cytometric analysis has proved unsatisfactory. The key point is that ZAP-70 is weakly expressed with a continuous expression pattern rather than a clear discrimination between positive and negative CLL cells, which means that the resulting judgment is subjective. Thus, in this study, we aimed at assessing the reliability and repeatability of ZAP-70 expression using the geometric mean fluorescence intensity (geo MFI) index method based on flow cytometry with 256-channel resolution in a series of 402 CLL patients and to compare ZAP-70 with other biological and clinical prognosticators. According to IgHV mutational status, we were able to confirm that the optimal cut-off point for the geo MFI index was 3.5 in the test set. In multivariate analyses that included the major clinical and biological prognostic markers for CLL, the prognostic impact of ZAP-70 expression appeared to have stronger discriminatory power when the geo MFI index method was applied. In addition, we found that ZAP-70-positive patients according to the geo MFI index method had shorter time to first treatment or overall survival (P=0.0002, P=0.0491). This is the first report showing that ZAP-70 expression can be evaluated by a new approach, the geo MFI index, which could be a useful prognostic method as it is more reliable, less subjective, and therefore better associated with improvement of CLL prognostication and prediction of clinical course.

Indexed as

chronic lymphocytic leukemiaflow cytometrygeometric mean fluorescence intensity indexprognosisZAP-70

Identifiers

PMID26937202
PMCPMC4762435

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