TMT-based comprehensive proteomic profiling identifies serum prognostic signatures of acute myeloid leukemia

Abstract: Acute myeloid leukemia (AML) is classified into favorable-risk, intermediate-risk, and poor-risk subtypes. This study aimed to compare the serum proteomic signatures of the three AML subtypes and identify prognostic biomarkers for AML. Serum samples from patients with favorable-risk (n = 14), intermediate-risk (n = 19), and poor-risk AMLs (n = 18) were used for the analysis of tandem mass tag (TMT) labeling-based quantitative proteomics. Comparative analysis was performed to identify differentially expressed proteins (DEPs) between groups. Prognostic proteins were screened using binary logistics regression analysis. TMT-MS/MS proteomics analysis identified 138 DEPs. Fumarate hydratase (FH), isocitrate dehydrogenase 2 (IDH2), and enolase 1 (ENO1) were significantly upregulated in poor-risk patients compared with favorable-risk patients. ELISA assay confirmed that patients with poor-risk AMLs had higher levels of IDH2, ENO1, and FH compared with intermediate-risk AML patients. Logistics analysis identified that proteins 3-hydroxyacyl-CoA dehydrogenase type-2 (HADH, odds ratio (OR) = 1.035, p = 0.010), glutamine synthetase (GLUL, OR = 1.022, p = 0.039), and lactotransferrin (LTF, OR = 1.1224, p = 0.016) were associated with poor prognosis, and proteins ENO1 (OR = 1.154, p = 0.053), FH (OR = 1.043, p = 0.059), and IDH2 (OR = 3.350, p = 0.055) were associated with AML prognosis. This study showed that AML patients had elevated levels of FH, IDH2, ENO1, LTF, and GLUL proteins and might be at high risk of poor prognosis.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
TMT-based comprehensive proteomic profiling identifies serum prognostic signatures of acute myeloid leukemia ; volume:18 ; number:1 ; year:2023 ; extent:12
Open medicine ; 18, Heft 1 (2023) (gesamt 12)

Creator
Zhang, Wei
Liu, Bei
Wu, Shiwen
Zhao, Li

DOI
10.1515/med-2022-0602
URN
urn:nbn:de:101:1-2023033114023588808729
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
14.08.2025, 10:48 AM CEST

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Associated

  • Zhang, Wei
  • Liu, Bei
  • Wu, Shiwen
  • Zhao, Li

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