Author
Raf Van de Plas
Other affiliations: Katholieke Universiteit Leuven, Vanderbilt University, Vanderbilt University Medical Center
Bio: Raf Van de Plas is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Mass spectrometry imaging & Medicine. The author has an hindex of 19, co-authored 38 publications receiving 1396 citations. Previous affiliations of Raf Van de Plas include Katholieke Universiteit Leuven & Vanderbilt University.
Papers
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TL;DR: The NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping.
Abstract: Author(s): Snyder, Michael P; Lin, Shin; Posgai, Amanda; Atkinson, Mark; Regev, Aviv; Rood, Jennifer; Rozenblatt-Rosen, Orit; Gaffney, Leslie; Hupalowska, Anna; Satija, Rahul; Gehlenborg, Nils; Shendure, Jay; Laskin, Julia; Harbury, Pehr; Nystrom, Nicholas A; Silverstein, Jonathan C; Bar-Joseph, Ziv; Zhang, Kun; Borner, Katy; Lin, Yiing; Conroy, Richard; Procaccini, Dena; Roy, Ananda L; Pillai, Ajay; Brown, Marishka; Galis, Zorina S; Cai, Long; Shendure, Jay; Trapnell, Cole; Lin, Shin; Jackson, Dana; Snyder, Michael P; Nolan, Garry; Greenleaf, William James; Lin, Yiing; Plevritis, Sylvia; Ahadi, Sara; Nevins, Stephanie A; Lee, Hayan; Schuerch, Christian Martijn; Black, Sarah; Venkataraaman, Vishal Gautham; Esplin, Ed; Horning, Aaron; Bahmani, Amir; Zhang, Kun; Sun, Xin; Jain, Sanjay; Hagood, James; Pryhuber, Gloria; Kharchenko, Peter; Atkinson, Mark; Bodenmiller, Bernd; Brusko, Todd; Clare-Salzler, Michael; Nick, Harry; Otto, Kevin; Posgai, Amanda; Wasserfall, Clive; Jorgensen, Marda; Brusko, Maigan; Maffioletti, Sergio; Caprioli, Richard M; Spraggins, Jeffrey M; Gutierrez, Danielle; Patterson, Nathan Heath; Neumann, Elizabeth K; Harris, Raymond; deCaestecker, Mark; Fogo, Agnes B; van de Plas, Raf; Lau, Ken; Cai, Long; Yuan, Guo-Cheng; Zhu, Qian; Dries, Ruben; Yin, Peng; Saka, Sinem K; Kishi, Jocelyn Y; Wang, Yu; Goldaracena, Isabel; Laskin, Julia; Ye, DongHye; Burnum-Johnson, Kristin E; Piehowski, Paul D | Abstract: Transformative technologies are enabling the construction of three dimensional (3D) maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible 3D molecular and cellular atlas of the human body, in health and various disease settings.
298 citations
TL;DR: This tutorial provides a concise overview of support vector machines and different closely related techniques for pattern classification, illustrated on three real-life applications in the field of metabolomics, genetics and proteomics.
273 citations
TL;DR: The potential of image fusion is demonstrated through 'sharpening' of IMS images, which uses microscopy measurements to predict ion distributions at a spatial resolution that exceeds that of measured ion images by ten times or more, and prediction of ion distributions in tissue areas that were not measured by IMS.
Abstract: We describe a predictive imaging modality created by 'fusing' two distinct technologies: imaging mass spectrometry (IMS) and microscopy. IMS-generated molecular maps, rich in chemical information but having coarse spatial resolution, are combined with optical microscopy maps, which have relatively low chemical specificity but high spatial information. The resulting images combine the advantages of both technologies, enabling prediction of a molecular distribution both at high spatial resolution and with high chemical specificity. Multivariate regression is used to model variables in one technology, using variables from the other technology. We demonstrate the potential of image fusion through several applications: (i) 'sharpening' of IMS images, which uses microscopy measurements to predict ion distributions at a spatial resolution that exceeds that of measured ion images by ten times or more; (ii) prediction of ion distributions in tissue areas that were not measured by IMS; and (iii) enrichment of biological signals and attenuation of instrumental artifacts, revealing insights not easily extracted from either microscopy or IMS individually.
229 citations
TL;DR: Using both shotgun and 2D‐imaging lipidomics analysis, a hitherto unrecognized alteration in phospholipid profiles in NSCLC is uncovered, which may have important biological implications and may have significant potential for biomarker development.
Abstract: Non-small cell lung cancer (NSCLC) is the leading cause of cancer death globally. To develop better diagnostics and more effective treatments, research in the past decades has focused on identification of molecular changes in the genome, transcriptome, proteome, and more recently also the metabolome. Phospholipids, which nevertheless play a central role in cell functioning, remain poorly explored. Here, using a mass spectrometry (MS)-based phospholipidomics approach, we profiled 179 phospholipid species in malignant and matched non-malignant lung tissue of 162 NSCLC patients (73 in a discovery cohort and 89 in a validation cohort). We identified 91 phospholipid species that were differentially expressed in cancer versus non-malignant tissues. Most prominent changes included a decrease in sphingomyelins (SMs) and an increase in specific phosphatidylinositols (PIs). Also a decrease in multiple phosphatidylserines (PSs) was observed, along with an increase in several phosphatidylethanolamine (PE) and phosphatidylcholine (PC) species, particularly those with 40 or 42 carbon atoms in both fatty acyl chains together. 2D-imaging MS of the most differentially expressed phospholipids confirmed their differential abundance in cancer cells. We identified lipid markers that can discriminate tumor versus normal tissue and different NSCLC subtypes with an AUC (area under the ROC curve) of 0.999 and 0.885, respectively. In conclusion, using both shotgun and 2D-imaging lipidomics analysis, we uncovered a hitherto unrecognized alteration in phospholipid profiles in NSCLC. These changes may have important biological implications and may have significant potential for biomarker development.
138 citations
TL;DR: It is shown that the MALDI timsTOF platform can maintain reasonable data acquisition rates while providing the specificity necessary to differentiate components in complex mixtures of lipid adducts, and provides a uniquely tunable platform to address many challenges associated with advanced molecular imaging applications.
Abstract: Imaging mass spectrometry (IMS) enables the spatially targeted molecular assessment of biological tissues at cellular resolutions. New developments and technologies are essential for uncovering the molecular drivers of native physiological function and disease. Instrumentation must maximize spatial resolution, throughput, sensitivity, and specificity, because tissue imaging experiments consist of thousands to millions of pixels. Here, we report the development and application of a matrix-assisted laser desorption/ionization (MALDI) trapped ion-mobility spectrometry (TIMS) imaging platform. This prototype MALDI timsTOF instrument is capable of 10 μm spatial resolutions and 20 pixels/s throughput molecular imaging. The MALDI source utilizes a Bruker SmartBeam 3-D laser system that can generate a square burn pattern of 2 pixels/s) while providing the specificity necessary to differentiate components in complex mixtures of lipid adducts. The combination of high-spatial-resolution and throughput imaging capabilities with high-performance TIMS separations provides a uniquely tunable platform to address many challenges associated with advanced molecular imaging applications.
124 citations
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01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.
10,141 citations
01 Aug 2000
TL;DR: Assessment of medical technology in the context of commercialization with Bioentrepreneur course, which addresses many issues unique to biomedical products.
Abstract: BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.
4,833 citations
01 Jan 1990
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.
2,933 citations
TL;DR: This Review explores how different aspects of FA synthesis promote tumorigenesis and tumour progression and strategies to target this pathway have not yet translated into clinical practice.
Abstract: Lipid metabolism, in particular the synthesis of fatty acids (FAs), is an essential cellular process that converts nutrients into metabolic intermediates for membrane biosynthesis, energy storage and the generation of signalling molecules. This Review explores how different aspects of FA synthesis promote tumorigenesis and tumour progression. FA synthesis has received substantial attention as a potential target for cancer therapy, but strategies to target this process have not yet translated into clinical practice. Furthermore, efforts to target this pathway must consider the influence of the tumour microenvironment.
885 citations