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Drug Repositioning for Cancer Treatment: Novel Candidate Identification Strategies
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Sciences, Cancer Pharmacology and Computational Medicine.
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 [en]
cancer treatment, drug repositioning, Phosphodiesterase 3A (PDE3A), apoptosis, combination screening
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-338327ISBN: 978-91-513-0203-4 (print)OAI: oai:DiVA.org:uu-338327DiVA, id: diva2:1172325
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
List of papers
1. Label free high throughput screening for apoptosis inducing chemicals using time-lapse microscopy signal processing
Open this publication in new window or tab >>Label free high throughput screening for apoptosis inducing chemicals using time-lapse microscopy signal processing
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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.

Keywords
Apoptosis, high throughput screening, cancer
National Category
Cancer and Oncology
Research subject
Bioinformatics
Identifiers
urn:nbn:se:uu:diva-229069 (URN)10.1007/s10495-014-1009-9 (DOI)000340518000010 ()
Funder
Swedish Society for Medical Research (SSMF)
Available from: 2014-07-29 Created: 2014-07-29 Last updated: 2018-01-09Bibliographically approved
2. Drug combination screening for mebendazole for the treatment of colorectal cancer
Open this publication in new window or tab >>Drug combination screening for mebendazole for the treatment of colorectal cancer
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(English)Manuscript (preprint) (Other academic)
National Category
Medical and Health Sciences
Research subject
Clinical Pharmacology
Identifiers
urn:nbn:se:uu:diva-336682 (URN)
Available from: 2017-12-15 Created: 2017-12-15 Last updated: 2018-01-09
3. Drug combination screening in multicellular tumor spheroids identifies synthetic lethalities in quiescent cancer cells
Open this publication in new window or tab >>Drug combination screening in multicellular tumor spheroids identifies synthetic lethalities in quiescent cancer cells
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(English)Manuscript (preprint) (Other academic)
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:uu:diva-336689 (URN)
Available from: 2017-12-15 Created: 2017-12-15 Last updated: 2018-01-09
4. Targeting tumor cells based on Phosphodiesterase 3A expression
Open this publication in new window or tab >>Targeting tumor cells based on Phosphodiesterase 3A expression
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2017 (English)In: Experimental Cell Research, ISSN 0014-4827, E-ISSN 1090-2422, Vol. 361, no 2, p. 308-315Article in journal (Refereed) Published
Abstract [en]

We and others have previously reported a correlation between high phosphodiesterase 3 A (PDE3A) expression and selective sensitivity to phosphodiesterase (PDE) inhibitors. This indicates that PDE3A could serve both as a drug target and a biomarker of sensitivity to PDE3 inhibition. In this report, we explored publicly available mRNA gene expression data to identify cell lines with different PDE3A expression. Cell lines with high PDE3A expression showed marked in vitro sensitivity to PDE inhibitors zardaverine and quazinone, when compared with those having low PDE3A expression. Immunofluorescence and immunohistochemical stainings were in agreement with PDE3A mRNA expression, providing suitable alternatives for biomarker analysis of clinical tissue specimens. Moreover, we here demonstrate that tumor cells from patients with ovarian carcinoma show great variability in PDE3A protein expression and that level of PDE3A expression is correlated with sensitivity to PDE inhibition. Finally, we demonstrate that PDE3A is highly expressed in subsets of patient tumor cell samples from different solid cancer diagnoses and expressed at exceptional levels in gastrointestinal stromal tumor (GIST) specimens. Importantly, vulnerability to PDE3 inhibitors has recently been associated with co-expression of PDE3A and Schlafen family member 12 (SLFN12). We here demonstrate that high expression of PDE3A in clinical specimens, at least on the mRNA level, seems to be frequently associated with high SLFIV12 expression. In conclusion, PDE3A seems to be both a promising biomarker and drug target for individualized drug treatment of various cancers.

Keywords
Repositioning, Cancer, Therapy, PDE3A, Biomarker
National Category
Cancer and Oncology Cell Biology
Identifiers
urn:nbn:se:uu:diva-339786 (URN)10.1016/j.yexcr.2017.10.032 (DOI)000417774300013 ()29107068 (PubMedID)
Funder
Swedish Cancer Society, 2016/335Swedish Research Council, 2016-01112
Available from: 2018-02-16 Created: 2018-02-16 Last updated: 2018-04-04Bibliographically approved

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