H2020Индивидуална стипендия2017–2019

SAMNets · Investigation of adaptive design and rewiring of Survival-Apoptosis-Mitogenic (SAM) signalling transduction network

„Хоризонт 2020“ — Действия „Мария Склодовска-Кюри“

Период: 2017-05-01 → 2019-04-30
Финансиране от ЕС: 187 866 €
Участници: 1
Схема: MSCA-IF-EF-ST

Линиите свързват координатора с партньорите.

Накратко на български

Компютърни модели анализират как раковите клетки променят сигналите си, за да станат устойчиви на лекарства, например при лечението на меланом. Това помага за систематичния подбор на най-ефективни комбинации от инхибитори според мутациите на пациента.

Този кратък обзор е генериран от изкуствен интелект

Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.

Резултати накратко

Investigation of adaptive design and rewiring of Survival-Apoptosis-Mitogenic (SAM) signalling transduction network

Driver mutations in survival, apoptotic and mitogenic signalling pathways are found in majority of human cancers. Increasing hope rests on targeted cancer therapies with kinase inhibitors, which inhibit mutated or overexpressed signalling proteins. Unfortunately, innate or acquired resistance to kinase inhibitors in cancer remains a pressing problem. For example, although RAF inhibitors are known to be effective in treatment of metastatic melanoma with BRAFV600E mutation and wild-type RAS genes, resistance to RAF inhibitors inevitably occurs (>80% of responders) within 6-8 months. Multiple mechanisms can lead to resistance, such as oncogenic RAS mutations, upregulation of upstream receptors, RAF overexpression or amplification and BRAFV600E splice variants with the enhanced dimerization potential. This resistance cannot be overcome by existing RAF inhibitors. A way to overcome resistance to kinase inhibitors can be the use of inhibitor combinations, but it is unclear how the best combinations can be chosen. A plethora of confounding factors, including allosteric drug–kinase interactions, phosphorylation-induced conformational changes and kinase dimerization, multiple feedback loops and different cell mutational and expression profiles hamper the intuitive reasoning on the choice of optimal drug combinations. Understanding the drugs’ mode of action and the mode of their combined actions at the network level would enable a systematic and robust design of the best combinations. The overall objective of the project was developing data-driven computational models of signalling pathways beyond current state of the art to systematically and objectively identify best inhibitor combinations depending on mutational and expression background. The developed models revealed a new principle of kinase inhibition: inhibition of the same enzyme or closely related enzymes of the same family with two structurally different inhibitors that bind to both protomers in the asymmetric homo- and hetero dimers. The subsequent experiments on cancer cell lines corroborated model predictions.

Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз

Цел на проекта

Cell life is not the property of any single protein or gene; rather it emerges from concerted actions of multiple molecules in cellular networks. Current proposal is focused on Signal Transduction Networks (STN) connecting the environment to cell responses. A major challenge is to understand how STN integrate and process environmental signals in a robust and reliable way and how they “compute” cell fate decisions depending on genetic background. To answer this question, the study will be focused on three interconnecting STNs: the Survival (PI3K/PTEN/AKT), Apoptotic (RASSF1/MST/LATS) and Mitogenic (EGFR/RAS/RAF/MEK/ERK) pathways, the SAM network. In the scope of current proposal the methods of signalling network reconstruction will be improved and the SAM network topology will be reconstructed in the panel of cell lines. Based on available data and reconstructed network topology the mechanistic site-specific dynamic model of SAM network will be developed and validated. Model predictions of dependence of signalling outputs behaviour on different perturbations (like small molecule inhibitors and their combinations) and background (mutations and protein expression levels) will be validated. The signalling outputs will be experimentally correlated to the cell fate decisions.The developed models will relate mutational information to treatment responses in the context of different expression landscapes and they will explain and predict mechanisms of intrinsic and acquired drug resistances, which often cannot be picked up by only intuitive reasoning. During the project the applicant will get training in a range of modern computational modelling, biochemical and molecular biology techniques used to study intracellular signalling networks. As a result, he will acquire skills of efficient integration of wet and dry parts of systems biology which will uniquely qualify him in the field significantly enhancing his career prospects.

Оригинален текст от CORDIS (на английски).

Участници

UNIVERSITY COLLEGE DUBLIN, NATIONAL UNIVERSITY OF IRELAND, DUBLIN · DublinКоординаторИрландия