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- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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- Niemi, MEK, et al.
(author)
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- 2021
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swepub:Mat__t
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- Menden, MP, et al.
(author)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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In: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Journal article (peer-reviewed)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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- Kuiper, Babette I., et al.
(author)
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Pan-European survey on current treatment strategies in patients with upfront resectable colorectal liver metastases
- 2024
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In: HPB. - : ELSEVIER SCI LTD. - 1365-182X .- 1477-2574. ; 26:5, s. 639-647
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Journal article (peer-reviewed)abstract
- Background: There is a lack of consensus on the definition of upfront resectability and use of perioperative systemic therapy for colorectal liver metastases (CRLM). This survey aimed to summarize the current treatment strategies for upfront resectable CRLM throughout Europe. Methods: A survey was sent to all members of the European-African Hepato-Pancreato-Biliary Association to gain insight into the current views on resectability and the use of systemic therapy for upfront Results: The survey was completed by 87 surgeons from 24 countries. The resectability of CRLM is mostly based on the volume of the future liver remnant, while considering tumor biology. Thermal ablation was considered as an acceptable adjunct to resection in parenchymal-sparing CRLM surgery by 77 % of the respondents. A total of 40.2 % of the respondents preferred standard perioperative systemic Conclusion: Among the participating European hepato-pancreato-biliary surgeons, there is a high degree of consensus on the definition of CRLM resectability. However, there is much variety in the use of adjunctive thermal ablation. Major variations persist in the use of perioperative systemic therapy in cases of upfront resectable CRLM, stressing the need for further evidence and a consensus.
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- van der Hage, J., et al.
(author)
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The ESSO core curriculum committee update on surgical oncology
- 2021
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In: Ejso. - : Elsevier BV. - 0748-7983. ; 47:11
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Journal article (peer-reviewed)abstract
- Introduction: Surgical oncology is a defined specialty within the European Board of Surgery within the European Union of Medical Specialists (UEMS). Variation in training and specialization still occurs across Europe. There is a need to align the core knowledge needed to fulfil the criteria across subspecialities in surgical oncology. Material and methods: The core curriculum, established in 2013, was developed with contributions from expert advisors from within the European Society of Surgical Oncology (ESSO), European Society for Radiotherapy and Oncology (ESTRO) and European Society of Medical Oncology (ESMO) and related subspeciality experts. Results: The current version reiterates and updates the core curriculum structure needed for current and future candidates who plans to train for and eventually sit the European fellowship exam for the European Board of Surgery in Surgical Oncology. The content included is not intended to be exhaustive but, rather to give the candidate an idea of expectations and areas for in depth study, in addition to the practical requirements. The five elements included are: Basic principles of oncology; Disease site specific oncology; Generic clinical skills; Training recommendations, and, lastly; Eligibility for the EBSQ exam in Surgical Oncology. Conclusions: As evidence-based care for cancer patients evolves through research into basic science, translational research and clinical trials, the core curriculum will evolve, mature and adapt to deliver continual improvements in cancer outcomes for patients. (c) 2021 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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- Ostaszewski, Marek, et al.
(author)
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COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms
- 2021
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In: Molecular Systems Biology. - : John Wiley & Sons. - 1744-4292 .- 1744-4292. ; 17:10
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Journal article (peer-reviewed)abstract
- We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.
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