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1.
Mol Syst Biol ; 19(11): e11510, 2023 Nov 09.
Artigo em Inglês | MEDLINE | ID: mdl-37735975

RESUMO

For a short period during early development of mammalian embryos, both X chromosomes in females are active, before dosage compensation is ensured through X-chromosome inactivation. In female mouse embryonic stem cells (mESCs), which carry two active X chromosomes, increased X-dosage affects cell signaling and impairs differentiation. The underlying mechanisms, however, remain poorly understood. To dissect X-dosage effects on the signaling network in mESCs, we combine systematic perturbation experiments with mathematical modeling. We quantify the response to a variety of inhibitors and growth factors for cells with one (XO) or two X chromosomes (XX). We then build models of the signaling networks in XX and XO cells through a semi-quantitative modeling approach based on modular response analysis. We identify a novel negative feedback in the PI3K/AKT pathway through GSK3. Moreover, the presence of a single active X makes mESCs more sensitive to the differentiation-promoting Activin A signal and leads to a stronger RAF1-mediated negative feedback in the FGF-triggered MAPK pathway. The differential response to these differentiation-promoting pathways can explain the impaired differentiation propensity of female mESCs.


Assuntos
Células-Tronco Embrionárias , Células-Tronco Embrionárias Murinas , Feminino , Animais , Masculino , Camundongos , Células-Tronco Embrionárias Murinas/metabolismo , Células-Tronco Embrionárias/metabolismo , Caracteres Sexuais , Quinase 3 da Glicogênio Sintase , Fosfatidilinositol 3-Quinases/metabolismo , Transdução de Sinais , Diferenciação Celular/genética , Mamíferos
2.
Mol Cancer ; 21(1): 126, 2022 06 10.
Artigo em Inglês | MEDLINE | ID: mdl-35689207

RESUMO

BACKGROUND: Development of resistance to targeted therapies has tempered initial optimism that precision oncology would improve poor outcomes for cancer patients. Resistance mechanisms, however, can also confer new resistance-specific vulnerabilities, termed collateral sensitivities. Here we investigated anaplastic lymphoma kinase (ALK) inhibitor resistance in neuroblastoma, a childhood cancer frequently affected by activating ALK alterations. METHODS: Genome-wide forward genetic CRISPR-Cas9 based screens were performed to identify genes associated with ALK inhibitor resistance in neuroblastoma cell lines. Furthermore, the neuroblastoma cell line NBLW-R was rendered resistant by continuous exposure to ALK inhibitors. Genes identified to be associated with ALK inhibitor resistance were further investigated by generating suitable cell line models. In addition, tumor and liquid biopsy samples of four patients with ALK-mutated neuroblastomas before ALK inhibitor treatment and during tumor progression under treatment were genomically profiled. RESULTS: Both genome-wide CRISPR-Cas9-based screens and preclinical spontaneous ALKi resistance models identified NF1 loss and activating NRASQ61K mutations to confer resistance to chemically diverse ALKi. Moreover, human neuroblastomas recurrently developed de novo loss of NF1 and activating RAS mutations after ALKi treatment, leading to therapy resistance. Pathway-specific perturbations confirmed that NF1 loss and activating RAS mutations lead to RAS-MAPK signaling even in the presence of ALKi. Intriguingly, NF1 loss rendered neuroblastoma cells hypersensitive to MEK inhibition. CONCLUSIONS: Our results provide a clinically relevant mechanistic model of ALKi resistance in neuroblastoma and highlight new clinically actionable collateral sensitivities in resistant cells.


Assuntos
Neuroblastoma , Medicina de Precisão , Quinase do Linfoma Anaplásico/genética , Linhagem Celular Tumoral , Criança , Humanos , Mutação , Neuroblastoma/tratamento farmacológico , Neuroblastoma/genética , Neuroblastoma/patologia , Inibidores de Proteínas Quinases/farmacologia , Inibidores de Proteínas Quinases/uso terapêutico , Transdução de Sinais
3.
PLoS Comput Biol ; 17(11): e1009515, 2021 11.
Artigo em Inglês | MEDLINE | ID: mdl-34735429

RESUMO

Very high risk neuroblastoma is characterised by increased MAPK signalling, and targeting MAPK signalling is a promising therapeutic strategy. We used a deeply characterised panel of neuroblastoma cell lines and found that the sensitivity to MEK inhibitors varied drastically between these cell lines. By generating quantitative perturbation data and mathematical modelling, we determined potential resistance mechanisms. We found that negative feedbacks within MAPK signalling and via the IGF receptor mediate re-activation of MAPK signalling upon treatment in resistant cell lines. By using cell-line specific models, we predict that combinations of MEK inhibitors with RAF or IGFR inhibitors can overcome resistance, and tested these predictions experimentally. In addition, phospho-proteomic profiling confirmed the cell-specific feedback effects and synergy of MEK and IGFR targeted treatment. Our study shows that a quantitative understanding of signalling and feedback mechanisms facilitated by models can help to develop and optimise therapeutic strategies. Our findings should be considered for the planning of future clinical trials introducing MEKi in the treatment of neuroblastoma.


Assuntos
Retroalimentação , Modelos Biológicos , Neuroblastoma/metabolismo , Transdução de Sinais , Linhagem Celular Tumoral , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Ensaios de Seleção de Medicamentos Antitumorais , Humanos , Sistema de Sinalização das MAP Quinases , Neuroblastoma/tratamento farmacológico , Inibidores de Proteínas Quinases/farmacologia , Receptor IGF Tipo 1/metabolismo , Receptor IGF Tipo 2/metabolismo
4.
Bioinformatics ; 34(23): 4079-4086, 2018 12 01.
Artigo em Inglês | MEDLINE | ID: mdl-29931053

RESUMO

Motivation: Intracellular signalling is realized by complex signalling networks, which are almost impossible to understand without network models, especially if feedbacks are involved. Modular Response Analysis (MRA) is a convenient modelling method to study signalling networks in various contexts. Results: We developed the software package STASNet (STeady-STate Analysis of Signalling Networks) that provides an augmented and extended version of MRA suited to model signalling networks from incomplete perturbation schemes and multi-perturbation data. Using data from the Dialogue on Reverse Engineering Assessment and Methods challenge, we show that predictions from STASNet models are among the top-performing methods. We applied the method to study the effect of SHP2, a protein that has been implicated in resistance to targeted therapy in colon cancer, using a novel dataset from the colon cancer cell line Widr and a SHP2-depleted derivative. We find that SHP2 is required for mitogen-activated protein kinase signalling, whereas AKT signalling only partially depends on SHP2. Availability and implementation: An R-package is available at https://github.com/molsysbio/STASNet. Supplementary information: Supplementary data are available at Bioinformatics online.


Assuntos
Transdução de Sinais , Software , Linhagem Celular Tumoral , Neoplasias do Colo , Biologia Computacional , Humanos , Proteína Tirosina Fosfatase não Receptora Tipo 11/genética
5.
Biochem Biophys Res Commun ; 464(2): 386-91, 2015 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-26086105

RESUMO

Signaling pathways implicated in cancer create a complex network with numerous regulatory loops and redundant pathways. This complexity explains frequent failure of one-drug-one-target paradigm of treatment, resulting in drug resistance in patients. To overcome the robustness of cell signaling network, cancer treatment should be extended to a combination therapy approach. Integrating and analyzing patient high-throughput data together with the information about biological signaling machinery may help deciphering molecular patterns specific to each patient and finding the best combinations of candidates for therapeutic targeting. We review state of the art in the field of targeted cancer medicine from the computational systems biology perspective. We summarize major signaling network resources and describe their characteristics with respect to applicability for drug response prediction and intervention targets suggestion. Thus discuss methods for prediction of drug sensitivity and intervention combinations using signaling networks together with high-throughput data. Gradual integration of these approaches into clinical routine will improve prediction of response to standard treatments and adjustment of intervention schemes.


Assuntos
Antineoplásicos/uso terapêutico , Neoplasias/tratamento farmacológico , Resistencia a Medicamentos Antineoplásicos , Humanos , Modelos Teóricos , Neoplasias/metabolismo , Transdução de Sinais
6.
Mol Biol Cell ; 30(9): 1108-1117, 2019 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-30785867

RESUMO

HRAS, NRAS, and KRAS isoforms are almost identical proteins that are ubiquitously expressed and activate a common set of effectors. In vivo studies have revealed that they are not biologically redundant; however, the isoform specificity of Ras signaling remains poorly understood. Using a novel panel of isogenic SW48 cell lines endogenously expressing wild-type or G12V-mutated activated Ras isoforms, we have performed a detailed characterization of endogenous isoform-specific mutant Ras signaling. We find that despite displaying significant Ras activation, the downstream outputs of oncogenic Ras mutants are minimal in the absence of growth factor inputs. The lack of mutant KRAS-induced effector activation observed in SW48 cells appears to be representative of a broad panel of colon cancer cell lines harboring mutant KRAS. For MAP kinase pathway activation in KRAS-mutant cells, the requirement for coincident growth factor stimulation occurs at an early point in the Raf activation cycle. Finally, we find that Ras isoform-specific signaling was highly context dependent and did not conform to the dogma derived from ectopic expression studies.


Assuntos
Proteínas ras/genética , Proteínas ras/metabolismo , Linhagem Celular Tumoral , Transformação Celular Neoplásica/genética , Genes ras , Humanos , Peptídeos e Proteínas de Sinalização Intercelular/metabolismo , Mutação , Isoformas de Proteínas , Transdução de Sinais/fisiologia
7.
Database (Oxford) ; 2017(1)2017 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-28415074

RESUMO

Human diseases such as cancer are routinely characterized by high-throughput molecular technologies, and multi-level omics data are accumulated in public databases at increasing rate. Retrieval and visualization of these data in the context of molecular network maps can provide insights into the pattern of regulation of molecular functions reflected by an omics profile. In order to make this task easy, we developed NaviCom, a Python package and web platform for visualization of multi-level omics data on top of biological network maps. NaviCom is bridging the gap between cBioPortal, the most used resource of large-scale cancer omics data and NaviCell, a data visualization web service that contains several molecular network map collections. NaviCom proposes several standardized modes of data display on top of molecular network maps, allowing addressing specific biological questions. We illustrate how users can easily create interactive network-based cancer molecular portraits via NaviCom web interface using the maps of Atlas of Cancer Signalling Network (ACSN) and other maps. Analysis of these molecular portraits can help in formulating a scientific hypothesis on the molecular mechanisms deregulated in the studied disease. Database URL: NaviCom is available at https://navicom.curie.fr.


Assuntos
Internet , Neoplasias/metabolismo , Biologia Computacional , Humanos
8.
Cancer Res ; 77(12): 3364-3375, 2017 06 15.
Artigo em Inglês | MEDLINE | ID: mdl-28381545

RESUMO

Genomic features are used as biomarkers of sensitivity to kinase inhibitors used widely to treat human cancer, but effective patient stratification based on these principles remains limited in impact. Insofar as kinase inhibitors interfere with signaling dynamics, and, in turn, signaling dynamics affects inhibitor responses, we investigated associations in this study between cell-specific dynamic signaling pathways and drug sensitivity. Specifically, we measured 14 phosphoproteins under 43 different perturbed conditions (combinations of 5 stimuli and 7 inhibitors) in 14 colorectal cancer cell lines, building cell line-specific dynamic logic models of underlying signaling networks. Model parameters representing pathway dynamics were used as features to predict sensitivity to a panel of 27 drugs. Specific parameters of signaling dynamics correlated strongly with drug sensitivity for 14 of the drugs, 9 of which had no genomic biomarker. Following one of these associations, we validated a drug combination predicted to overcome resistance to MEK inhibitors by coblockade of GSK3, which was not found based on associations with genomic data. These results suggest that to better understand the cancer resistance and move toward personalized medicine, it is essential to consider signaling network dynamics that cannot be inferred from static genotypes. Cancer Res; 77(12); 3364-75. ©2017 AACR.


Assuntos
Antineoplásicos/farmacologia , Biomarcadores Tumorais/metabolismo , Neoplasias Colorretais/patologia , Resistencia a Medicamentos Antineoplásicos/efeitos dos fármacos , Transdução de Sinais/efeitos dos fármacos , Linhagem Celular Tumoral , Humanos , Modelos Estatísticos , Inibidores de Proteínas Quinases/farmacologia
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