Investigating Translation and Metabolism in mTORC2-driven Cancer

Projektinformationen

TransMetTOR

ID Finanzhilfevereinbarung: 101029147

DOI

10.3030/101029147

Projekt abgeschlossen

EK-Unterschriftsdatum 4 März 2021

Startdatum 1 April 2021

Enddatum 31 März 2023

Finanziert unter

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Gesamtkosten

€ 166 320,00

EU-Beitrag

€ 166 320,00

Koordiniert durch

UNIVERSITE DE LIEGE
Belgium

Periodic Reporting for period 1 - TransMetTOR (Investigating Translation and Metabolism in mTORC2-driven Cancer)

Berichtszeitraum: 2021-04-01 bis 2023-03-31

Zusammenfassung vom Kontext und den Gesamtzielen des Projekts

The identification of the genetic mutations responsible for the formation of cancers has paved the way for the development of new drugs which specifically attack cancer cells, resulting in significant improvement in patient outcome. However, tumor development also involves a series of non-genetic mechanisms that allow cancer cells to adapt to their environment and escape therapies. For instance, the regulations of cellular metabolism and protein synthesis appear to be central mechanisms allowing adaptation and reprogramming of cancer cells during tumor development. In this project, we propose to study the mechanisms underlying the reprogramming of cellular metabolism by protein synthesis in the context of lung cancer. Lung cancer is the leading cause of cancer death worldwide and therefore represents a major health concern. Moreover, lung tumors are very heterogeneous and characterized by a multitude of genetic alterations, which renders them resistant to current chemo-, radio- and immunotherapies. Thus, the long-term goal of the proposed project is to characterize the molecular mechanisms that link mRNA translation to the regulation of cancer metabolism in order to identify molecular targets and metabolic vulnerabilities which can be used for the development of new effective treatments. To achieve this goal, we will generate and characterize novel preclinical models of lung cancer. Results obtained from these models will then be validated using human patient material. Ultimately, by deeply characterizing clinically relevant models of lung cancer, this project will provide a better understanding of the complex regulatory mechanisms that support lung cancer development and progression, and will highlight new therapeutic strategies for the treatment of lung cancer.

Arbeit, die ab Beginn des Projekts bis zum Ende des durch den Bericht erfassten Berichtszeitraums geleistet wurde, und die wichtigsten bis dahin erzielten Ergebnisse

By analysing large cohorts of lung cancer patients, we have demonstrated the clinical relevance of targeting the mTORC2 signalling pathway in lung cancer. We have then generated a set of innovative mouse models that recapitulate genetic alterations that are frequently observed in lung cancer patients. Finally, we have performed in-depth characterisation of these models and have highlighted a series of vulnerabilities, as well as potential molecular targets, that are associated with aggressive lung tumors. We are currently evaluating the therapeutic potential of inhibiting specific metabolic pathways to impair the growth of these aggressive lung tumors.

Over the last two years, the results from the TransMetTor project have been presented in national and international meetings, under the form of oral and poster communications. In addition to basic scientists, these results have attracted the interest of clinicians and have led to the generation of long-term collaborations that will be crucial to further translate these findings into clinics.

Fortschritte, die über den aktuellen Stand der Technik hinausgehen und voraussichtliche potenzielle Auswirkungen (einschließlich der bis dato erzielten sozioökonomischen Auswirkungen und weiter gefassten gesellschaftlichen Auswirkungen des Projekts)

Unbiased analysis of our unique set of novel lung cancer mouse models have identified molecular targets as well as specific, targetable, metabolic features that are associated with a particular subtype of aggressive lung cancer. Moreover, this cancer-associated metabolic rewiring correlated with specific changes in the immune landscape of these lung tumors, suggesting that they might respond to particular immunotherapy treatments. Thus, in addition to increasing our basic knowledge of cancer biology, the results from the TransMetTOR project have the potential to be exploited for the development of future anticancer therapies.

Workflow of the TransMetTOR project