Identification of DNA damage response genes as targets for personalized treatment of Glioblastoma through RNA interference screens

Doctoral thesis (2017)

Despite surgical resection and genotoxic treatment with ionizing radiation and the DNA alkylating agent temozolomide (TMZ), glioblastoma (GBM) remains one of the most lethal cancers, due in part to the ... [more ▼]

Despite surgical resection and genotoxic treatment with ionizing radiation and the DNA alkylating agent temozolomide (TMZ), glioblastoma (GBM) remains one of the most lethal cancers, due in part to the action of DNA repair factors that drive resistance and lead to tumor relapse. Important features of these mechanisms include the inherent redundancy and complexity of the many DNA repair pathways activated as part of the DNA damage response (DDR). One important DDR factor is encoded by the O-6-methylguanine-DNA methyltransferase (MGMT) gene whose epigenetic silencing is a strong predictive marker for favorable outcome in GBM patients treated with TMZ. However, even patients displaying MGMT promoter methylation succumb to tumor relapse, indicating that other DNA repair mechanisms promote resistance to the treatment. The main aim of this work was to identify essential DDR factors that support GBM cell survival under TMZ treatment in order to provide novel targets and thus, novel insights into drug combinations that could overcome GBM chemoresistance. The strategy to achieve this goal was to use well-characterized GBM cell lines in focused loss of function shRNA screens performed under different conditions. Indeed, screens were designed to uncover DDR genes that are essential for GBM cells i) under normal conditions, ii) under TMZ treatment, iii) and under TMZ treatment in MGMT negative contexts. Pooled shRNAs targeting more than 500 DDR genes were introduced into GBM cells reflecting two clinically-relevant GBM contexts: a MGMT-positive context using MGMT-expressing cells and a negative one, using cell lines in which MGMT was depleted hrough pharmacological inhibition or RNA interference. Potential DDR targets that could sensitize GBM cells to TMZ have been identified and some of them validated. Surprisingly, some of these targets are not only involved in pathways that are commonly known to drive TMZ resistance (i.e. Double strand break repair, Direct repair), but also in repair pathways such as transcription-coupled nucleotide excision repair (TC-NER) or the early steps of the Fanconi Anemia pathway (FA). While components of the early FA pathway might be attractive targets especially in MGMT-negative contexts, it may be interesting to target factors involved in the early steps of the TC-NER to sensitize MGMTpositive cells to TMZ. So in addition to its predictive and prognostic value, MGMT might be a relevant stratification marker to treat patients in a personalized way. Supporting this hypothesis, the screen analyses revealed that the curative inhibition of some genes in combination with TMZ treatment might turn to be deleterious depending on MGMT expression level. One of the promising target will be further investigated in vitro as well as in vivo to elucidate the molecular mechanisms by which this gene operates to confer cellular resistance to TMZ. This study opens up new horizons for combinatorial therapies and hopefully, will be used to improve therapeutical approaches, particularly for MGMT-positive GBM patients, who currently do not benefit at all from chemotherapy. [less ▲]

Identification of falsifications in survey data: results of explorative studies and further steps

Scientific Conference (2011, May)

Identification of human proteins that modify misfolding and proteotoxicity of pathogenic ataxin-1.

in PLoS genetics (2012), 8(8), 1002897

Proteins with long, pathogenic polyglutamine (polyQ) sequences have an enhanced propensity to spontaneously misfold and self-assemble into insoluble protein aggregates. Here, we have identified 21 human ... [more ▼]

Proteins with long, pathogenic polyglutamine (polyQ) sequences have an enhanced propensity to spontaneously misfold and self-assemble into insoluble protein aggregates. Here, we have identified 21 human proteins that influence polyQ-induced ataxin-1 misfolding and proteotoxicity in cell model systems. By analyzing the protein sequences of these modifiers, we discovered a recurrent presence of coiled-coil (CC) domains in ataxin-1 toxicity enhancers, while such domains were not present in suppressors. This suggests that CC domains contribute to the aggregation- and toxicity-promoting effects of modifiers in mammalian cells. We found that the ataxin-1-interacting protein MED15, computationally predicted to possess an N-terminal CC domain, enhances spontaneous ataxin-1 aggregation in cell-based assays, while no such effect was observed with the truncated protein MED15ΔCC, lacking such a domain. Studies with recombinant proteins confirmed these results and demonstrated that the N-terminal CC domain of MED15 (MED15CC) per se is sufficient to promote spontaneous ataxin-1 aggregation in vitro. Moreover, we observed that a hybrid Pum1 protein harboring the MED15CC domain promotes ataxin-1 aggregation in cell model systems. In strong contrast, wild-type Pum1 lacking a CC domain did not stimulate ataxin-1 polymerization. These results suggest that proteins with CC domains are potent enhancers of polyQ-mediated protein misfolding and aggregation in vitro and in vivo. [less ▲]

Identification of large-scale genomic variation in cancer genomes using in silico reference models

in Nucleic Acids Research (2015)

Identifying large-scale structural variation in cancer genomes continues to be a challenge to researchers. Current methods rely on genome alignments based on a reference that can be a poor fit to highly ... [more ▼]

Identifying large-scale structural variation in cancer genomes continues to be a challenge to researchers. Current methods rely on genome alignments based on a reference that can be a poor fit to highly variant and complex tumor genomes. To address this challenge we developed a method that uses available breakpoint information to generate models of structural variations. We use these models as references to align previously unmapped and discordant reads from a genome. By using these models to align unmapped reads, we show that our method can help to identify large-scale variations that have been previously missed. [less ▲]

The Identification of Math and Reading Difficulties in a Multilingual Educational Setting

Scientific Conference (2020, January 24)

Identification of New IkappaBalpha Complexes by an Iterative Experimental and Mathematical Modeling Approach.

in PLoS computational biology (2014), 10(3), 1003528

The transcription factor nuclear factor kappa-B (NFkappaB) is a key regulator of pro-inflammatory and pro-proliferative processes. Accordingly, uncontrolled NFkappaB activity may contribute to the ... [more ▼]

The transcription factor nuclear factor kappa-B (NFkappaB) is a key regulator of pro-inflammatory and pro-proliferative processes. Accordingly, uncontrolled NFkappaB activity may contribute to the development of severe diseases when the regulatory system is impaired. Since NFkappaB can be triggered by a huge variety of inflammatory, pro-and anti-apoptotic stimuli, its activation underlies a complex and tightly regulated signaling network that also includes multi-layered negative feedback mechanisms. Detailed understanding of this complex signaling network is mandatory to identify sensitive parameters that may serve as targets for therapeutic interventions. While many details about canonical and non-canonical NFkappaB activation have been investigated, less is known about cellular IkappaBalpha pools that may tune the cellular NFkappaB levels. IkappaBalpha has so far exclusively been described to exist in two different forms within the cell: stably bound to NFkappaB or, very transiently, as unbound protein. We created a detailed mathematical model to quantitatively capture and analyze the time-resolved network behavior. By iterative refinement with numerous biological experiments, we yielded a highly identifiable model with superior predictive power which led to the hypothesis of an NFkappaB-lacking IkappaBalpha complex that contains stabilizing IKK subunits. We provide evidence that other but canonical pathways exist that may affect the cellular IkappaBalpha status. This additional IkappaBalpha:IKKgamma complex revealed may serve as storage for the inhibitor to antagonize undesired NFkappaB activation under physiological and pathophysiological conditions. [less ▲]

Identification of novel inhibitors of dietary lipid absorption using zebrafish.

in PloS one (2010), 5(8), 12386

Pharmacological inhibition of dietary lipid absorption induces favorable changes in serum lipoprotein levels in patients that are at risk for cardiovascular disease and is considered an adjuvant or ... [more ▼]

Pharmacological inhibition of dietary lipid absorption induces favorable changes in serum lipoprotein levels in patients that are at risk for cardiovascular disease and is considered an adjuvant or alternative treatment with HMG-CoA reductase inhibitors (statins). Here we demonstrate the feasibility of identifying novel inhibitors of intestinal lipid absorption using the zebrafish system. A pilot screen of an unbiased chemical library identified novel compounds that inhibited processing of fluorescent lipid analogues in live zebrafish larvae. Secondary assays identified those compounds suitable for testing in mammals and provided insight into mechanism of action, which for several compounds could be distinguished from ezetimibe, a drug used to inhibit cholesterol absorption in humans that broadly inhibited lipid absorption in zebrafish larvae. These findings support the utility of zebrafish screening assays to identify novel compounds that target complex physiological processes. [less ▲]

Identification of optimal process parameters in selective laser sintering

Scientific Conference (2019)

Selective Laser Sintering (SLS) is an efficient method for manufacturing complex geometries with high strength and durability. The SLS process subjects a powder bed to thermal cycles allowing theparticles ... [more ▼]

Selective Laser Sintering (SLS) is an efficient method for manufacturing complex geometries with high strength and durability. The SLS process subjects a powder bed to thermal cycles allowing theparticles to coalesce into a solid part without being completely melted. The thermal cycles along withthe thermo-mechanical properties of the powder dictate the properties of the manufactured part.Choosing optimal parameters that lead to functional parts with the desired stiffness, density andstrength requires extensive testing. Microscales models such that Molecular dynamics and DiscreteParticles offer great flexibilities and capacity to reproduce the SLS process from the physical point ofview [1].This study presents a multi-physical model based on the Extended Discrete Element Method forsimulating the thermodynamics and thermo-mechanics that take place in the SLS process as well asthe microstructure evolution of the part. A thermo-viscoelastic constitutive model for discreteparticles is coupled with heat transfer, sintering and fracture to predict.A genetic algorithm is employed to identify optimal process parameters, namely laser power,scanning speed, preheating temperature and layer thickness in an automated iterative process. Theseparameters are identified so that the density and strength of the cooled part meet the target values. [less ▲]

Identification of pathogenic variant enriched regions across genes and gene families

E-print/Working paper (2019)

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene family members, and genetic variants within these regions are potentially more likely to ... [more ▼]

Missense variant interpretation is challenging. Essential regions for protein function are conserved among gene family members, and genetic variants within these regions are potentially more likely to confer risk to disease. Here, we generated 2,871 gene family protein sequence alignments involving 9,990 genes and performed missense variant burden analyses to identify novel essential protein regions. We mapped 2,219,811 variants from the general population into these alignments and compared their distribution with 65,034 missense variants from patients. With this gene family approach, we identified 398 regions enriched for patient variants spanning 33,887 amino acids in 1,058 genes. As a comparison, testing the same genes individually we identified less patient variant enriched regions involving only 2,167 amino acids and 180 genes. Next, we selected de novo variants from 6,753 patients with neurodevelopmental disorders and 1,911 unaffected siblings, and observed a 5.56-fold enrichment of patient variants in our identified regions (95% C.I. =2.76-Inf, p-value = 6.66×10−8). Using an independent ClinVar variant set, we found missense variants inside the identified regions are 111-fold more likely to be classified as pathogenic in comparison to benign classification (OR = 111.48, 95% C.I = 68.09-195.58, p-value < 2.2e−16). All patient variant enriched regions identified (PERs) are available online through a user-friendly platform for interactive data mining, visualization and download at http://per.broadinstitute.org. In summary, our gene family burden analysis approach identified novel patient variant enriched regions in protein sequences. This annotation can empower variant interpretation. [less ▲]

Identification of predictors of emergent literacy

in The 16th European Conference on Developmental Psychology (2013, September)

Two studies examined the predictive value of a range of variables associated with young children on their later literacy. Study 1 involved children age 5 to 7 from Serbia (N = 159); Study 2 engaged ... [more ▼]

Two studies examined the predictive value of a range of variables associated with young children on their later literacy. Study 1 involved children age 5 to 7 from Serbia (N = 159); Study 2 engaged children age 4 to 6 from Luxembourg (N = 174). Children in Study 1 were assessed on entry to school, aged 5, and again at age 7. Children in Study 2 were assessed once, in preschool. In Study 1, multilevel models indicated that a baseline assessment administrated in school language at the age of 5, in particular with respect to their competence in mathematics, were the most significant predictors of children’s emergent literacy at the age of 7 after controlling for age, gender, vocabulary, and phonological awareness. In Study 2, gender, vocabulary, phonological awareness, and competence in mathematics at the age of 5 were significant predictors of emergent literacy at the same age, after controlling for age, test administered in school language, and behavior. The level of parental education in Study 1 and the children’s behavior in both studies proved not to be significant. Both studies have important educational implications, suggesting that practitioners should assess language-minority children at the start of school in their mother tongue and act upon the outcomes of those assessments to avoid later literacy problems. [less ▲]