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Label free high throughput screening for apoptosis inducing chemicals using time-lapse microscopy signal processing
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
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2014 (English)In: Apoptosis (London), ISSN 1360-8185, E-ISSN 1573-675X, Vol. 19, no 9, p. 1411-1418Article in journal (Refereed) Published
Abstract [en]

Label free time-lapse microscopy has opened a new avenue to the study of time evolving events in living cells. When combined with automated image analysis it provides a powerful tool that enables automated large-scale spatiotemporal quantification at the cell population level. Very few attempts, however, have been reported regarding the design of image analysis algorithms dedicated to the detection of apoptotic cells in such time-lapse microscopy images. In particular, none of the reported attempts is based on sufficiently fast signal processing algorithms to enable large-scale detection of apoptosis within hours/days without access to high-end computers. Here we show that it is indeed possible to successfully detect chemically induced apoptosis by applying a two-dimensional linear matched filter tailored to the detection of objects with the typical features of an apoptotic cell in phase-contrast images. First a set of recorded computational detections of apoptosis was validated by comparison with apoptosis specific caspase activity readouts obtained via a fluorescence based assay. Then a large screen encompassing 2,866 drug like compounds was performed using the human colorectal carcinoma cell line HCT116. In addition to many well known inducers (positive controls) the screening resulted in the detection of two compounds here reported for the first time to induce apoptosis.

Place, publisher, year, edition, pages
2014. Vol. 19, no 9, p. 1411-1418
Keywords [en]
Apoptosis, high throughput screening, cancer
National Category
Cancer and Oncology
Research subject
Bioinformatics
Identifiers
URN: urn:nbn:se:uu:diva-229069DOI: 10.1007/s10495-014-1009-9ISI: 000340518000010OAI: oai:DiVA.org:uu-229069DiVA, id: diva2:735520
Funder
Swedish Society for Medical Research (SSMF)Available from: 2014-07-29 Created: 2014-07-29 Last updated: 2018-01-09Bibliographically approved
In thesis
1. Towards High-Throughput Phenotypic and Systemic Profiling of in vitro Growing Cell Populations using Label-Free Microscopy and Spectroscopy: Applications in Cancer Pharmacology
Open this publication in new window or tab >>Towards High-Throughput Phenotypic and Systemic Profiling of in vitro Growing Cell Populations using Label-Free Microscopy and Spectroscopy: Applications in Cancer Pharmacology
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
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.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2014. p. 50
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1045
Keywords
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
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-234565 (URN)978-91-554-9082-9 (ISBN)
Public defence
2014-11-25, Robergsalen, entrance 40, 4th floor, Akademiska Sjukhuset, Uppsala, 09:30 (English)
Opponent
Supervisors
Available from: 2014-11-04 Created: 2014-10-21 Last updated: 2015-02-03
2. Drug Repositioning for Cancer Treatment: Novel Candidate Identification Strategies
Open this publication in new window or tab >>Drug Repositioning for Cancer Treatment: Novel Candidate Identification Strategies
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Regardless of the enormous investments in cancer research and drug development, the proportion of approved drugs in oncology is low compared to other indications, and new avenues are needed. One attractive approach in this regard is drug repositioning where new uses outside the scope of the original medical indications for existing drugs are identified. It offers the advantages of reduced development risks, time and cost over de novo drug discovery pathways.

The main focus of this thesis was to explore and employ different strategies to identify repurposable drug candidates for treatment of cancer. Aiming for this, in the first project we followed a bioinformatics approach to evaluate PDE3A as a drug target and biomarker. We showed that subgroups of tumors, within many different cancer types, overexpress PDE3A (mRNA and protein) and that PDE3A can predict sensitivity to the clinically tested phosphodiesterase inhibitors zardaverine and quazinone (Paper I). In the second project, a novel automated image based microscopy assay was developed and used for detection of apoptotic cells. In a screen the method was successfully used to identify apoptosis inducing compounds. Two of these apoptosis inducers were found to have repurposing potential (Paper II). Moreover, high-throughput combination screening was performed using different cell models. In paper III, monolayer cell cultures were used as cell model to search for combination partners for the anti-parasitic compound mebendazole (a repurposing candidate). As a result, the antipsychotic drug thioridazine was found to have synergistic effect when combined with mebendazol. Finally, a novel drug-combination platform for three-dimensional cell culture based screening, in 384 well formats, was developed. This assay was used to search for combination partners to the anti-parasitic compound nitazoxanide (a repurposing candidate), which was previously reported to specifically target quiescent cancer cells. The screen identified the antifungal agent ketoconazole as selectively toxic to hypoxic and nutrient deprived cancer cells when combined with nitazoxanide (Paper IV). Thus, we have developed/explored several methodological approaches and identified drugs that potentially can be repurposed for treatment of cancer. 

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 40
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1416
Keywords
cancer treatment, drug repositioning, Phosphodiesterase 3A (PDE3A), apoptosis, combination screening
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-338327 (URN)978-91-513-0203-4 (ISBN)
Public defence
2018-02-28, Rosénsalen, Akademiska sjukhuset, ing 95/96 nbv, Uppsala, 09:00 (English)
Opponent
Supervisors
Available from: 2018-02-05 Created: 2018-01-09 Last updated: 2018-04-04

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Publisher's full texthttp://link.springer.com/article/10.1007%2Fs10495-014-1009-9

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Aftab, ObaidNazir, MadihaFryknäs, MårtenHammerling, UlfLarsson, RolfGustafsson, Mats G

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