Supplemental_Material_for_Three-dimensional_Co-culture_by_Lu_et_al – Supplemental material for Three-Dimensional Leukemia Co-Culture System for In Vitro High-Content Metabolomics Screening

Supplemental material, Supplemental_Material_for_Three-dimensional_Co-culture_by_Lu_et_al for Three-Dimensional Leukemia Co-Culture System for In Vitro High-Content Metabolomics Screening by Xiyuan Lu, Alessia Lodi, Marina Konopleva and Stefano Tiziani in SLAS Discovery</p

Stable Isotope Dilution LC-HRMS Assay To Determine Free SN-38, Total SN-38, and SN-38G in a Tumor Xenograft Model after Intravenous Administration of Antibody–Drug Conjugate (Sacituzumab Govitecan)

Antibody–drug conjugates (ADCs) have gained significant interest over the past few years due to their targeted delivery, higher efficacy, decreased toxicity and improved therapeutic index over conventional anticancer therapies. Sacituzumab govitecan (SG) is an ADC composed of a Trop-2-targeted antibody conjugated to the cytotoxic payload SN-38. SG is currently being evaluated in clinical trials of several solid cancers. In this nonclinical study, we have developed a highly sensitive and selective approach to measure free and total SN-38 and its glucuronidation metabolite (SN-38G) using stable isotope dilution (SID) ultrahigh-performance liquid chromatography–high resolution mass spectrometry (UHPLC-HRMS). An efficient and fast hydrolysis procedure (2 h at 100 °C) was established to release SN-38, conjugated to the antibody by carbonate linkage. The assay involves the extraction of free SN-38, SN-38G by protein precipitation, and subsequent acid hydrolysis of the protein layer to release antibody-bound SN-38. The developed UHPLC-HRMS method resulted in good linearity (r2 ≥ 0.997), accuracy (RE ≤ ± 9.1%), precision (CVs ≤ 7.7%), and extraction recoveries (85.6–109.3%). The validated method was applied in the plasma and tumor of mice bearing human brain (U251) and breast (MDA-MB-468) tumor xenografts treated with a single dose (0.5 mg) of SG for 6 h. Results revealed the presence of trace level of SN-38G and free SN-38 in plasma, which suggests an improved therapeutic index of SG. The established method makes a significant contribution to the assessment of SG in different cancers

Additional file 1 of An IGF-1R-mTORC1-SRPK2 signaling Axis contributes to FASN regulation in breast cancer

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Additional file 2 of An IGF-1R-mTORC1-SRPK2 signaling Axis contributes to FASN regulation in breast cancer

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Additional file 3 of An IGF-1R-mTORC1-SRPK2 signaling Axis contributes to FASN regulation in breast cancer

Additional file 3

1H-MRS and GC-MS metabolic profiles of bone marrow and peripheral blood samples at the time of ALL diagnosis.

<p>Representative spectra of BM (blue line) and PB (red line) specimens. Spectra were acquired from (A) 1H-MRS analysis of filtered polar fractions, (B) 1H-MRS analysis of recovered whole lipid fractions, and (C) GC-MS analysis of FFA extracts. Metabolites with the greatest difference between BM and PB are labeled and include alanine (Ala), free cholesterol (CHOL), cholesterol esters (CHOLest), choline (Cho), formate (For), glucose (Glc), glutamate (Glu), glutamine (Gln), lactate (Lac), histidine (His), hypoxanthine (Hpx), palmitic acid, oleic acid, triacylglyceride (TAG), and uridine (Ur). Other abbreviations used are: (2HB), 2-hydroxybutyrate; (3HB), 3-hydroxybutyrate; (2Og), 2oxo-glutarate; (2Oic), 2oxo-isocaproate; (BAA), branched amino acids; (Car), carnitine; (Cho), choline; (CHOL), free cholesterol, (CHOLest), cholesterol esters; (For), formate; (Fum), fumarate; (Glyc), glycerol; (GPCho), glycero-3-phosphocholine; (Hpx), hypoxanthine; (Lac), lactate; (Niac), niacinamide; (Pglu), pyroglutamate; (Pyr), pyruvate; (Ur), uridine; (Pdx), pyridoxine; (TAG), triacylglyceride; (T-Chol), total cholesterol.</p

Multivariate analysis of peripheral blood polar fractions in response to drug therapy.

<p>Untargeted mPCA was performed on 1H-MRS spectra acquired on the polar fractions of PB (A, B). (A) mPCA scores plot shows a clear separation between PB samples collected on day 0 versus day 8 (49.63% on PC1), on day 0 versus day 29 (50.85% on PC1), and on day 8 versus day 29 (38.14% on PC1). (B) Loadings plot for the first principal components depicts the most relevant discriminatory metabolites for BM before therapy (negative loadings) and during or after therapy (positive loadings).</p

Network representation of correlations between metabolite pairs.

<p>Plots represent the largest connected component of the networks obtained with the ARACNE algorithm for B0-P0 (A) and B29-P29 (B). Blue nodes indicate metabolites relevant to lipid metabolism; green nodes indicate amino acids, including derivatives and analogues; red edges indicate anti-correlation; and light green edges indicate correlation. Shorter edges denote smaller p-values (higher R2). Note the presence of a community of lipid metabolites on the right side in (A) and the predominance of amino acids in (B). </p

Statistical analysis of pairwise correlations of amino acids, lipid metabolites, and other metabolites.

<p>Plots show the probability distribution function (PDF) of the p-values of edges in a relevance network of metabolites with strong correlation in B0-P0 (A) and B29-P29 (B). Edges are classified in three groups (lipid metabolism, amino acids, and others). Note the presence of the high peak at small p-values in the lipid metabolite distribution in (A) and in the amino acid (including derivatives and analogues) distribution in (B), indicating enriched correlation among lipid metabolites at day 0 and amino acids at day 29, respectively. </p

Targeted metabolic analysis of bone marrow and peripheral blood samples at diagnosis and after induction therapy.

<p>Shown are the mean fold differences in metabolite concentrations in BM and PB samples collected (A) at the time of diagnosis and (B) after induction therapy (mean ± SEM, n = 10 patients). Statistical significance was assessed based on absolute metabolite concentrations (SI, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0082859#pone.0082859.s001" target="_blank">Table S1</a>) using the nonparametric two-sided Wilcoxon Rank Sum Test (WRST) and p-values were corrected using false discovery rate (FDR). The bar plot is color coded according to p-values (pFDR < 10%). At day 0 (A), 22 metabolites were significantly different between BM and PB with pFDR <10%, 14 of which had pFDR <5%. In contrast, only 4 of 110 identified metabolites were found to be significantly different between BM and PB at day 29 (B). Both bar plots also show the differences in the ratios of glutamate to glutamine, aspartate to asparagine, choline to creatine, unsaturated to saturated fatty acids, and the sum of glutamine plus pyroglutamate.</p