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Metabolomics analysis identifies lysine and taurine as candidate prognostic biomarkers for AML-M2 patients

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Abstract

There is an ongoing search for potential biomarkers for acute myeloid leukemia (AML) patients using metabolic analysis. However, only few studies to date have focused on bone marrow samples or a specific subtype of AML. In the present study, we used gas chromatography time-of-flight mass spectrometry of plasma and bone marrow supernatants to compare the metabolic characteristics of patients with AML with maturation (AML-M2). This approach identified significantly altered metabolites. We next performed pathway analysis and determined relative mRNA expression by qRT-PCR. Our results show that lysine, methionine and serine were significantly decreased in AML-M2 patients compared with healthy control. Moreover, plasma abundance of lysine was negatively associated with patients’ risk stratification. Taurine had higher plasma abundance in AML-M2 patients and plasma level of taurine was positively related with AML-M2 risk status, while the expression level of taurine transporter showed a negative correlation. Receiver operating characteristic curve analysis showed these four metabolites had high diagnostic value with lysine showing the highest sensitivity and specificity. These results suggest that plasma abundances of lysine and taurine may serve as potential metabolic biomarkers for the prognosis of patients with AML-M2.

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (31371399).

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Authors and Affiliations

  1. Phase I Clinical Trials Unit, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Zhongshan Road 321#, Gulou district, Nanjing, 210008, China

    Xuan Zhou, Meihong Zheng, Qien Wang, Bei Cao & Juan Li

  2. Key Laboratory of Drug Metabolism and Pharmacokinetics, China Pharmaceutical University, 24 Tongjia Avenue, Gulou District, Nanjing, 210008, China

    Jiye Aa

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  1. Xuan Zhou
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12185_2020_2836_MOESM1_ESM.tif

Supplementary Figure 1: Typical GC/TOFMS total ion current (TIC) chromatograms of samples in AML-M2 patients and healthy donors. The red line represents control group while the black line represents patients group. (TIF 56 kb)

12185_2020_2836_MOESM2_ESM.tif

Supplementary Figure 2: Heat maps of the global metabolome for samples from AML patients and controls. (A) Plasma. (B) Bone marrow. (TIF 5104 kb)

12185_2020_2836_MOESM3_ESM.tif

Supplementary Figure 3: Kaplan‐Meier survival analysis of AML-M2 patients based on the abundance of (A) lysine, (B) methionine and (C) serine. (TIF 330 kb)

12185_2020_2836_MOESM4_ESM.tif

Supplementary Figure 4: Pathway analysis of significantly differential metabolites between patients and controls. (A) Plasma. (B) Bone marrow (TIF 2508 kb)

12185_2020_2836_MOESM5_ESM.tif

Supplementary Figure 5: Oncomine data-mining analysis of SLC6A6 in cancer. (A) Down-regulation of SLC6A6 was found in leukemia and lymphoma. (B) In Haferlach Leukemia’s dataset, the level of SLC6A6 mRNA was decreased in acute myeloid leukemia with all four probes (205920_at, 205921_s_at, 211030_s_at, 228754_at). The p-values were 0.002, 0.057, 0.007, and 1.99E-5, separately (TIF 2367 kb)

Supplementary Table 1: Primer sequences used for qRT-PCR (DOCX 14 kb)

Supplementary Table 2: Metabolites with significantly differential abundance in plasma samples (DOCX 17 kb)

Supplementary Table 3: Metabolites with significantly differential abundance in bone marrow samples (DOCX 17 kb)

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Zhou, X., Zheng, M., Wang, Q. et al. Metabolomics analysis identifies lysine and taurine as candidate prognostic biomarkers for AML-M2 patients. Int J Hematol 111, 761–770 (2020). https://doi.org/10.1007/s12185-020-02836-7

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