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- Berglund, U. W., et al.
(author)
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Validation and development of MTH1 inhibitors for treatment of cancer
- 2016
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In: Annals of Oncology. - : Elsevier BV. - 0923-7534 .- 1569-8041. ; 27:12, s. 2275-2283
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Journal article (peer-reviewed)abstract
- Background: Previously, we showed cancer cells rely on the MTH1 protein to prevent incorporation of otherwise deadly oxidised nucleotides into DNA and we developed MTH1 inhibitors which selectively kill cancer cells. Recently, several new and potent inhibitors of MTH1 were demonstrated to be non-toxic to cancer cells, challenging the utility of MTH1 inhibition as a target for cancer treatment. Material and methods: Human cancer cell lines were exposed in vitro to MTH1 inhibitors or depleted of MTH1 by siRNA or shRNA. 8-oxodG was measured by immunostaining and modified comet assay. Thermal Proteome profiling, proteomics, cellular thermal shift assays, kinase and CEREP panel were used for target engagement, mode of action and selectivity investigations of MTH1 inhibitors. Effect of MTH1 inhibition on tumour growth was explored in BRAF V600E-mutated malignant melanoma patient derived xenograft and human colon cancer SW480 and HCT116 xenograft models. Results: Here, we demonstrate that recently described MTH1 inhibitors, which fail to kill cancer cells, also fail to introduce the toxic oxidized nucleotides into DNA. We also describe a new MTH1 inhibitor TH1579, (Karonudib), an analogue of TH588, which is a potent, selective MTH1 inhibitor with good oral availability and demonstrates excellent pharmacokinetic and anti-cancer properties in vivo. Conclusion: We demonstrate that in order to kill cancer cells MTH1 inhibitors must also introduce oxidized nucleotides into DNA. Furthermore, we describe TH1579 as a best-in-class MTH1 inhibitor, which we expect to be useful in order to further validate the MTH1 inhibitor concept.
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- Nutter, S., et al.
(author)
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Changing the global obesity narrative to recognize and reduce weight stigma: A position statement from the World Obesity Federation
- 2023
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In: Obesity Reviews. - 1467-7881. ; 25:1
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Journal article (peer-reviewed)abstract
- Weight stigma, defined as pervasive misconceptions and stereotypes associated with higher body weight, is both a social determinant of health and a human rights issue. It is imperative to consider how weight stigma may be impeding health promotion efforts on a global scale. The World Obesity Federation (WOF) convened a global working group of practitioners, researchers, policymakers, youth advocates, and individuals with lived experience of obesity to consider the ways that global obesity narratives may contribute to weight stigma. Specifically, the working group focused on how overall obesity narratives, food and physical activity narratives, and scientific and public-facing language may contribute to weight stigma. The impact of weight stigma across the lifespan was also considered. Taking a global perspective, nine recommendations resulted from this work for global health research and health promotion efforts that can help to reduce harmful obesity narratives, both inside and outside health contexts.
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- Bulten, W, et al.
(author)
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Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
- 2022
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In: Nature medicine. - : Springer Science and Business Media LLC. - 1546-170X .- 1078-8956. ; 28:21, s. 154-
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Journal article (peer-reviewed)abstract
- Artificial intelligence (AI) has shown promise for diagnosing prostate cancer in biopsies. However, results have been limited to individual studies, lacking validation in multinational settings. Competitions have been shown to be accelerators for medical imaging innovations, but their impact is hindered by lack of reproducibility and independent validation. With this in mind, we organized the PANDA challenge—the largest histopathology competition to date, joined by 1,290 developers—to catalyze development of reproducible AI algorithms for Gleason grading using 10,616 digitized prostate biopsies. We validated that a diverse set of submitted algorithms reached pathologist-level performance on independent cross-continental cohorts, fully blinded to the algorithm developers. On United States and European external validation sets, the algorithms achieved agreements of 0.862 (quadratically weighted κ, 95% confidence interval (CI), 0.840–0.884) and 0.868 (95% CI, 0.835–0.900) with expert uropathologists. Successful generalization across different patient populations, laboratories and reference standards, achieved by a variety of algorithmic approaches, warrants evaluating AI-based Gleason grading in prospective clinical trials.
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