A novel systems biology approach to evaluate mouse models of late-onset Alzheimer’s disease
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PROVIDER: PRJNA593734 | ENA |
REPOSITORIES: ENA
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Project description:Background: Late-onset Alzheimer’s disease (LOAD) is the most common form of dementia worldwide. To date, animal models of Alzheimer’s have focused on rare familial mutations, due to a lack of frank neuropathology from models based on common disease genes. Recent multi-cohort studies of postmortem human brain transcriptomes have identified a set of 30 gene co-expression modules associated with LOAD, providing a molecular catalog of relevant endophenotypes. Results: This resource enables precise gene-based alignment between new animal models and human molecular signatures of disease. Here, we describe a new resource to efficiently screen mouse models for LOAD relevance. A new NanoString nCounter® Mouse AD panel was designed to correlate key human disease processes and pathways with mRNA from mouse brains. Analysis of three mouse models based on LOAD genetics, carrying APOE4 and TREM2*R47H alleles and the 5xFAD mouse, a widely used amyloid pathology model, demonstrated overlaps with distinct human AD modules that, in turn, are functionally enriched in key disease-associated pathways. Comprehensive comparison with full transcriptome data from same-sample RNA-Seq shows strong correlation between gene expression changes independent of experimental platform. Conclusions: Taken together, we show that the nCounter Mouse AD panel offers a rapid, cost-effective and highly reproducible approach to assess disease relevance of potential LOAD mouse models
2020-02-03 | GSE141509 | GEO
Project description: Not available
| S-EPMC7656729 | biostudies-literature
Project description:Systems biology of prostate cancer
| PRJEB34826 | ENA
Project description:Background Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models. Results mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a “shortest path” algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including “Cytoskeleton remodeling/TGF/WNT”, “Cytoskeleton remodeling/Cytoskeleton remodeling”, and “Cell adhesion/Chemokines and adhesion”. Of these, the “Cytoskeleton remodeling/TGF/WNT” was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the “Cytoskeleton remodeling/TGF/WNT” pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform. Conclusions In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS.
2012-04-25 | GSE37552 | GEO
Project description:Background Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models. Results mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a “shortest path” algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including “Cytoskeleton remodeling/TGF/WNT”, “Cytoskeleton remodeling/Cytoskeleton remodeling”, and “Cell adhesion/Chemokines and adhesion”. Of these, the “Cytoskeleton remodeling/TGF/WNT” was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the “Cytoskeleton remodeling/TGF/WNT” pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform. Conclusions In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS. In this study we analyzed two human metastatic OS cell lines and their parental non-metastatic lines. The two human metastatic OS cell line models were HOS/143B and SaOS-2/LM7. The HOS cell line, originally known as M.T. and later as TE-85, was derived from an OS of a 13 year-old girl. The 143B metastatic subline was generated from HOS by a Ki-RAS oncogene transformation [Rhim, J.S., et al., Characterization of human cells transformed in vitro by N-methyl-N'-nitro-N-nitrosoguanidine. Int J Cancer, 1977. 19(4): p. 505-10.]. The SaOS-2 cell was derived from an OS of an 11 year-old girl, and its metastatic subline LM7, was developed by multiple in vivo selection of SaOS-2 cells in mice with pulmonary metastases [Jia, S.F., L.L. Worth, and E.S. Kleinerman, A nude mouse model of human osteosarcoma lung metastases for evaluating new therapeutic strategies. Clin Exp Metastasis, 1999. 17(6): p. 501-6.]. No replicates were included.
2012-04-24 | E-GEOD-37552 | biostudies-arrayexpress
Project description: Not available
| S-EPMC3677161 | biostudies-literature
Project description: Not available
| S-EPMC4027758 | biostudies-other
Project description:Yeast Saccharomyces cerevisiae is a powerful model system for systems-wide biology screens and large-scale proteomics methods. The proteomics community has achieved nearly complete coverage for this organism owing to advances in mass spectrometry. However, it remains challenging to scale the technology for rapid and high-throughput analysis of the yeast proteome to investigate biological pathways on a global scale. Here we describe a systems biology approach employing plate-based sample preparation and rapid, single-run data independent mass spectrometry analysis (DIA). Our approach is straightforward, easy to implement and enables quantitative profiling and comparisons of hundreds of largely covered yeast proteomes in only a few days. We evaluate its capability by characterizing changes in the yeast proteome in response to a variety of stresses commonly used in yeast research, identify distinct responses to each stress, and provide a comprehensive resource of these responses. Using our facile, rapid and robust methodology, we observe many previously characterized stress responses, including carbon source dependent regulation of the GID E3 ligase, an important regulator of cellular metabolism during the switch between gluconeogenic and glycolytic growth conditions. Furthermore, we applied our methodology to search for new regulatory targets of the GID ligase during a metabolic switch. We are able to pinpoint effects of a single deletion or point mutation in the GID complex on the global proteome, and thereby identify and validate novel targets of the GID E3 ligase. Moreover, our approach allowed the identification of targets from multiple cellular pathways that display distinct patterns of regulation.
2020-11-26 | PXD021559 | Pride
Project description:Non-familial Alzheimer’s disease (AD) occurring before 65 years of age is commonly referred to as early-onset Alzheimer’s disease (EOAD) and constitutes ~5-6% of all Alzheimer’s disease (AD) cases. While EOAD exhibits the same clinicopathological changes such as amyloid plaques, neurofibrillary tangles (NFTs), brain atrophy, and cognitive decline as observed in the more prevalent late-onset AD (LOAD), EOAD patients tend to have more severe cognitive deficits, including visuospatial, language, and motor dysfunction. Patient-derived induced pluripotent stem cells (iPSCs) have been used to model and study penetrative, familial AD (FAD) mutations in APP, PSEN1, and PSEN2, but have been seldom used for sporadic forms of AD that display more heterogeneous disease manifestation. In this study, we sought to characterize iPSC-derived neurons from EOAD patients via RNA-sequencing. A modest difference in expression profiles between EOAD patients and non-demented control subjects resulted in a limited number of differentially expressed genes (DEGs). Based on this analysis, we provide evidence that iPSC-derived neuron model systems, likely due to the loss of EOAD-associated epigenetic signatures during the iPSC reprogramming, are not an ideal model system to study sporadic AD.
2023-11-21 | GSE231341 | GEO
Project description: Not available
| S-EPMC5568992 | biostudies-literature