Journal: Analytical Chemistry

Article Title: Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning

doi: 10.1021/acs.analchem.9b00026

Figure Lengend Snippet: Figure 2. MS and optical images of spheroid slices. (A) A common ion [PC(34:1) + H]+ (m/z 760.5964) illustrating shapes of MS images of spheroid slices in the control and drug treatment groups. (B) Optical images of the corresponding spheroid slices. (C) MS images of [Irinotecan + H]+ (m/z 587.2923) in drug treated spheroids. The heterogeneous cell microenvironment inside spheroids can affect the cell metabolic pathways and result in metabolites changes in different regions. To illustrate the heterogeneity of spatial distribution of molecules in spheroids, we constructed the MS images of a number of representative lipids (e.g., PC, phosphatidylethanolamine (PE), and phosphatidylglycerol (PG)) that are more abundant in the outer regions (Figure 3A). In addition, we investigated the influence of anticancer drug

Article Snippet: Chemicals and materials Chemicals used in the experiments include reagents, such as methanol, water, agarose (Sigma-Aldrich, St. Louis, MO, USA), and anticancer drug Irinotecan (Thermo Scientific, Ward Hill, MA, USA).

Techniques: Control, Construct

Journal: Analytical Chemistry

Article Title: Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning

doi: 10.1021/acs.analchem.9b00026

Figure Lengend Snippet: Figure 5. MSI data analysis using ML methods for an Irinotecan treated spheroid (5 µM, 1 h). (A) Classification of MSI data obtained from unsupervised ML (CLARA). (B) Three clustered MSI data from CLARA analysis were color-coded to reconstruct their spatial distributions representing the inner region (yellow), the outer region (green), and the background (purple), respectively. (C) The selection of the training data for supervised ML (Random Forest) was based on MCR-ALS results. (D) Color-coded spatial distributions obtained from Random Forest are similar to CLARA results shown in 5B. Because training data selection may affect the prediction accuracy of supervised ML, we compared the performance of MCR-ALS with the other two common methods: k-means and hierarchical clustering. Our results indicate the training data selection based on three different methods (i.e., MCR-ALS, k- means, and hierarchical clustering) resulted in very similar prediction of MSI data (Figure S12). Changes of metabolites inside spheroids induced by Irinotecan treatment Anticancer drug treatment can change the microenvironment of cells, affect metabolomic pathways, and result in changes of metabolites. To obtain metabolites altered by Irinotecan inside spheroids, we generated two averaged mass spectra

Article Snippet: Chemicals and materials Chemicals used in the experiments include reagents, such as methanol, water, agarose (Sigma-Aldrich, St. Louis, MO, USA), and anticancer drug Irinotecan (Thermo Scientific, Ward Hill, MA, USA).

Techniques: Selection, Generated

Journal: Analytical Chemistry

Article Title: Anticancer Drug Affects Metabolomic Profiles in Multicellular Spheroids: Studies Using Mass Spectrometry Imaging Combined with Machine Learning

doi: 10.1021/acs.analchem.9b00026

Figure Lengend Snippet: Figure 4. Results of MCR-ALS analysis of MSI data obtained from Irinotecan treated spheroid (5 µM, 1 h). (A) The spatial distribution patterns and the corresponding ions of (A) component 1 (outer region of spheroid), (B) component 2 (inner region of spheroid), and (C) component 3 (background).

Article Snippet: Chemicals and materials Chemicals used in the experiments include reagents, such as methanol, water, agarose (Sigma-Aldrich, St. Louis, MO, USA), and anticancer drug Irinotecan (Thermo Scientific, Ward Hill, MA, USA).

Techniques: