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NMR spectroscopy based metabolic profiling of drug induced changes in vitro can discriminate between pharmacological classes
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för medicinska vetenskaper, Cancerfarmakologi och beräkningsmedicin.
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för läkemedelskemi, Avdelningen för analytisk farmaceutisk kemi.
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för läkemedelskemi, Avdelningen för analytisk farmaceutisk kemi.
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Farmaceutiska fakulteten, Institutionen för läkemedelskemi, Avdelningen för analytisk farmaceutisk kemi.
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2014 (Engelska)Ingår i: Journal of chemical information and modeling, ISSN 1549-9596, Vol. 54, nr 11, s. 3251-3258Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Drug induced changes in mammalian cell line models have already been extensively profiled at the systemic mRNA level and subsequently used to suggest mechanisms of action for new substances as well as to support drug repurposing, i.e. identifying new potential indications for drugs already licensed for other pharmacotherapy settings. The seminal work in this field, which includes a large database and computational algorithms for pattern matching, is known as the “Connectivity Map” (CMap). The potential of similar exercises at the metabolite level is, however, still largely unexplored. Only recently the first high throughput metabolomic assay pilot study was published, involving screening of metabolic response to a set of 56 kinase inhibitors in a 96-well format. Here we report results from a separately developed metabolic profiling assay, which leverages 1H NMR spectroscopy to the quantification of metabolic changes in the HCT116 colorectal cancer cell line, in response to each of 26 compounds. These agents are distributed across 12 different pharmacological classes covering a broad spectrum of bioactivity. Differential metabolic profiles, inferred from multivariate spectral analysis of 18 spectral bins, allowed clustering of most tested drugs according to their respective pharmacological class. A more advanced supervised analysis, involving one multivariate scattering matrix per pharmacological class and using only 3 spectral bins (three metabolites), showed even more distinct pharmacology-related cluster formations. In conclusion, this kind of relatively fast and inexpensive profiling seems to provide a promising alternative to that afforded by mRNA expression analysis, which is relatively slow and costly. As also indicated by the present pilot study, the resulting metabolic profiles do not seem to provide as information rich signatures as those obtained using systemic mRNA profiling, but the methodology holds strong promise for significant refinement.

Ort, förlag, år, upplaga, sidor
2014. Vol. 54, nr 11, s. 3251-3258
Nationell ämneskategori
Cancer och onkologi
Identifikatorer
URN: urn:nbn:se:uu:diva-234564DOI: 10.1021/ci500502fISI: 000345551000021PubMedID: 25321343OAI: oai:DiVA.org:uu-234564DiVA, id: diva2:757068
Tillgänglig från: 2014-10-21 Skapad: 2014-10-21 Senast uppdaterad: 2015-02-03Bibliografiskt granskad
Ingår i avhandling
1. Towards High-Throughput Phenotypic and Systemic Profiling of in vitro Growing Cell Populations using Label-Free Microscopy and Spectroscopy: Applications in Cancer Pharmacology
Öppna denna publikation i ny flik eller fönster >>Towards High-Throughput Phenotypic and Systemic Profiling of in vitro Growing Cell Populations using Label-Free Microscopy and Spectroscopy: Applications in Cancer Pharmacology
2014 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

Modern techniques like automated microscopy and spectroscopy now make it possible to study quantitatively, across multiple phenotypic and molecular parameters, how cell populations are affected by different treatments and/or environmental disturbances. As the technology development at the instrument level often is ahead of the data analytical tools and the scientific questions, there is a large and growing need for computational algorithms enabling desired data analysis. These algorithms must have capacity to extract and process quantitative dynamic information about how the cell population is affected by different stimuli with the final goal to transform this information into development of new powerful therapeutic strategies. In particular, there is a great need for automated systems that can facilitate the analysis of massive data streams for label-free methods such as phase contrast microscopy (PCM) imaging and spectroscopy (NMR). Therefore, in this thesis, algorithms for quantitative high-throughput phenotypic and systemic profiling of in vitro growing cell populations via label-free microscopy and spectroscopy are developed and evaluated. First a two-dimensional filter approach for high-throughput screening for drugs inducing autophagy and apoptosis from phase contrast time-lapse microscopy images is studied. Then new methods and applications are presented for label-free extraction and comparison of time-evolving morphological features in phase-contrast time-lapse microscopy images recorded from in vitro growing cell populations. Finally, the use of dynamic morphology and NMR/MS spectra for implementation of a reference database of drug induced changes, analogous to the outstanding mRNA gene expression based Connectivity Map database, is explored. In conclusion, relatively simple computational methods are useful for extraction of very valuable biological and pharmacological information from time-lapse microscopy images and NMR spectroscopy data offering great potential for biomedical applications in general and cancer pharmacology in particular.

Ort, förlag, år, upplaga, sidor
Uppsala: Acta Universitatis Upsaliensis, 2014. s. 50
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1045
Nyckelord
label free vesicle detector, high-throughput, phase contrast microscopy, Library of Pharmacologically Active Compounds, High Content Screening, fluorometric microculture cytotoxicity assay, nuclear magnetic resonance, mass spectrometry
Nationell ämneskategori
Medicin och hälsovetenskap
Identifikatorer
urn:nbn:se:uu:diva-234565 (URN)978-91-554-9082-9 (ISBN)
Disputation
2014-11-25, Robergsalen, entrance 40, 4th floor, Akademiska Sjukhuset, Uppsala, 09:30 (Engelska)
Opponent
Handledare
Tillgänglig från: 2014-11-04 Skapad: 2014-10-21 Senast uppdaterad: 2015-02-03

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Aftab, ObaidEngskog, MikaelHaglöf, JakobElmsjö, AlbertArvidsson, TorbjörnPettersson, CurtHammerling, UlfGustafsson, Mats

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Aftab, ObaidEngskog, MikaelHaglöf, JakobElmsjö, AlbertArvidsson, TorbjörnPettersson, CurtHammerling, UlfGustafsson, Mats
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