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A systems thinking driven approach to investigate the contribution of metabolic derangements due to aminoacid deprivation in driving genomic instability in mantle cell lymphoma

Classification: 
national research
Programme: 
Other funding Opportunities
Call: 
Gilead Sciences s.r.l. Fellowship Program 2019
Main ERC field: 
Life Sciences
Unict role: 
Beneficiary
Duration (months): 
12
Start date: 
Friday, October 25, 2019
End date: 
Saturday, January 25, 2020
Total cost: 
€ 124.055,00
Unict cost: 
€ 25.000,00
Coordinator: 
Università degli Studi di Catania
Principal investigator in Unict: 
Francesco Di Raimondo
University department involved: 
Department of General Surgery and Medical-Surgical Specialties

Abstract

Non-Hodgkin’s lymphomas are neoplasms derived from lymphoid cells at various stages of development 1 and they represent the sixth most frequently occurring cancer 2. Mantle cell lymphoma (MCL), characterized by the deregulation of Cyclin D1 (CCND1) due to presence of the t(11;14)(11q13;11q32) chromosomal translocation, is one of the most common lymphoma subtypes, accounting for 5-10% of all non-Hodgkin’s lymphomas.

Despite recent advances, including the introduction of novel non chemotherapeutic agents7,19,20, long term disease control continues to be a challenge with a median survival of 5 to 7 years. Indeed, after an initial response to chemotherapy, neoplastic cells remain residually in the marrow and digestive tract, making MCL prone to recur leading to short survival prognosis.

The main genetic feature of MCL is the t(11;14)(q13;q32) chromosomal translocation with the deregulated ectopic expression of CCND1 due to the juxtaposition of its gene in proximity to IGHV@ region3. Moreover, MCL is one of the B-cell malignancies with the highest degree of genomic instability, and a large number of secondary chromosomal alterations have been described, including losses, gains, and amplifications of chromosomal regions that contain genes involved in cell-cycle regulation, DNA damage response pathways, signal transduction, and apoptosis. In most of MCL patients uniparental disomy (or loss of heterozygosity, LOH) has been described, contributing to the inactivation of tumor suppressor genes5-7. The PI3K/AKT/mTOR pathway, constitutively activated in MCL, has been targeted for the development of different drugs21-23. However, the pattern of somatic mutations determining an activation of the canonical or of the non-canonical NFKB pathway would affect the response to the targeted approach based on bortezomib, and especially to the BTK-inhibitor ibrutinib8.

Our and other groups are investigating if the characteristic re-emergence of MCL is generated from cross-talk between stromal and lymphoma cells the tumor-immune microenvironment (TIME)24,25; however, the underlying mechanisms are poorly understood and not extensively explored25.

Conventional wisdom ascribes metabolic reprogramming in cancer to meeting increased demands for intermediates to support rapid proliferation. Prior models have proposed benefits toward cell survival, immortality, and stress resistance, although the recent discovery of oncometabolites has shifted attention to chromatin targets affecting gene expression. Disrupting cancer metabolism revealed roles for both glycolysis and glutaminolysis in promoting double-strand breaks repair and preventing accelerated senescence after irradiation in a breast cancer model 26, an unexplored field in the research of MCL biology. Moreover, cell fitness depend on tonic BCR signaling 27 converging on metabolic rewiring, even if formally shown only in Burkitt lymphoma28.

Thus, taking advantage of computer modelling and in vitro experiments, we propone to investigate the metabolic rewiring occurring under prolonged aminoacid starvation (limiting the model to those amino-acids relevant for the immune-suppressive milieu in the microenvironment: glutamine, arginine and tryptophan) and the related, if any, quantity and quality of genomic aberrancies in MCL cell lines previously characterized and available in our laboratory.

The primary end-point of the current project proposal is to identify genomic lesions occurring in MCL cell lines upon long-term arginine and tryptophan starvation, to predict if external sources availability can affect genome stability (including frequency of new LOH).

The secondary endpoint is to characterize the main molecular machinery (including metabolites, transcripts, lncRNA, miRNA) mediating the adaptive metabolic response able to sustain DNA damage and genomic instability. In order to limit the number of testable candidates in vitro, we will take advantage of a new computational-based simulator we are testing in other similar projects ongoing in the lab.

In brief, we will compute MCL changes upon aminoacid starvation as the behavior of a dynamic complex system, featuring all the necessary interacting components, whose aggregate activity exhibits self-organization under selective pressures (adaptive responses to microenvironment changes), being at the same time highly sensitive to initial conditions (e.g., concentration of extracellular metabolites). In systems theory, the complex behavior of a dynamic system is described in terms underlying accessible patterns, hierarchical feedback loops, self-organization, as well as sensitive dependence on external parameters. A dynamic complex system behaves and reacts to changes in ways that are based on the complexity of the internal structure and patterns, often counter-intuitive and virtually unpredictable. For example, small changes in some parameters gives rise to a change in the behavior in different system parts, due to the capability of the feedback network to “propagate” in a non-linear way the modification, in so addressing an overall systemic re-arrangement. Thus, we propose to first build-up a systemic diagram of MCL environment, based on the energy system language and its development using the concept of EMERGY (from EMbodied enERGY) (19-21). This novel approach has the purpose to develop a computational simulator (22,23) of the different environment scenarios (e.g. single aminoacid deprivation, tryptophan and arginine total or partial deprivation) for different internal and external initial conditions (e.g., modifying fluxes of primary sources, or coefficient of equations describing processes occurring in the cells).

Candidate genes belonging to the selected pathways identified by the computational simulator will be validate through functional experiments of gene silencing/enhancement to assess their contribution to the cellular response to tryptophan or arginine starvation.