Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

KiRNet: Integrated, kinase-centered network model for investigating kinase-driven phenotypes

ABSTRACT: The ever-increasing size and scale of biological information have created a need for systems-level tools that synthesize large quantities of dispersed and distinct data and inform decision- and hypothesis-making processes in basic and translational sciences. To address this need, we have created KiRNet, an kinase-centered method designed to integrate results of functional screens with interactome or other protein-protein interaction data, as well as additional molecular data to generate functional network-level models. These network models can be further optimized and refined to identify small, differentially regulated subnetworks, even in the absence of large-scale datasets. As a proof of concept, we applied KiRNet to liver cancer cells driven by Fzd2, a gene known to cause epithelial-mesenchymal transition and cancer metastasis and identified a subnetwork of 166 proteins that regulate this cell state. The KiRNet derived information can be used to formulate high-value predictions for future testing and thus accelerate basic and translational discoveries.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Taran S. Gujral

PROVIDER: MSV000086446 | MassIVE | Thu Nov 12 10:37:00 GMT 2020

REPOSITORIES: MassIVE

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

An Integrated Approach to Reconstructing Genome-scale Transcriptional Regulatory Networks [ChIP-Seq]

Project description:By integrating sequence information from closely related bacteria with a compendium of high-throughput gene expression datasets, a large-scale transcriptional regulatory networks was constructed for Rhodobacter sphaeroides. Predictions from this network were validated in part using genome-wide analysis for 3 transcription factors (PpsR, RSP_0489 and RSP_3341). Genome-wide protein-DNA interaction analysis of 3 transcription factors predicted to be involved in photosynthesis (PpsR), carbon metabolism (RSP_0489) and iron homeostasis (RSP_3341) were used to validate predictions from a large-scale reconstruction of R. sphaeroides transcriptional regulatory network.

2014-07-01 | E-GEOD-58648 | biostudies-arrayexpress

Expression profiling of archival tissues for long-term health studies

Project description:Over 20 million archival tissue samples are stored annually in the United States as formalin-fixed, paraffin-embedded (FFPE) tissue blocks, but only recently has whole-genome expression profiling from these samples become technically feasible. Here, we introduce novel general methods for assessing, summarizing, and visualizing expression data quality from archival samples. We validated these methods in technical study of 144 clinical breast cancer and autopsy samples and in an overview of all current publicly available FFPE whole-genome expression data. We additionally performed a case study incorporating over 1,000 colorectal cancer (CRC) samples collected from patients across the United States over a period of more than 25 years, integrating clinicopathological information, tumor molecular data, and archival tissue gene expression on an unparalleled scale. Both large-scale clinical studies presented a much greater range of data quality than previous smaller studies, emphasizing the need for rigorous quality control in translational applications of archival tissue gene expression profiling. This series includes 1,003 FFPE-preserved CRC tumors, assayed by Illumina HumanRef-v3 WG-DASL microarray.

2012-10-02 | E-GEOD-32651 | biostudies-arrayexpress

Novel mouse cell lines and in vivo models for human high-grade neuroendocrine lung carcinoma SCLC and LCNEC

Project description:There is a clear need to expand the toolkit of adequate mouse models and cell lines available for preclinical studies of high-grade neuroendocrine lung carcinoma (Small Cell Lung Carcinoma, SCLC and Large Cell Neuroendocrine Carcinoma, LCNEC), two highly aggressive tumor types with dismal prognosis and few therapeutic options. Actually, paucity is extreme in the case of LCNEC. Given the lack of murine cell lines and transplant models of LCNEC the need is imperative/unmet. In this study, we have generated and examined new models of LCNEC and SCLC transplantable cell lines derived from our previously developed primary mouse LCNEC and SCLC tumors. RNA-seq analysis demonstrated that our cell lines and syngeneic tumors maintained the transcriptome program from the original transgenic primary tumor, and display strong similarities to human SCLC or LCNEC. Importantly, the SCLC transplanted cell lines show the ability of metastasize, mimicking this characteristic of the human condition. In summary, we have generated mouse cell line tools that allow further basic and translational research, as well as preclinical testing of new treatment strategies for SCLC and LCNEC, as they retain important features of their human counterparts and address the lack of LCNEC disease models.

2023-10-29 | GSE242422 | GEO

An Integrated Approach to Reconstructing Genome-scale Transcriptional Regulatory Networks [ChIP-Seq]

2014-07-01 | GSE58648 | GEO

Expression profiling of archival tissues for long-term health studies

2012-10-02 | GSE32651 | GEO

Enterococcus faecalis V583 - data analysis

Project description:Genome-scale models represent the link between an organism's genetic information and experimentally observable biological phenotypes. They facilitate metabolic engineering and the discovery of network properties such as the identification of novel drug targets. Most commonly, metabolite consumption data is used to limit the solution space, sometimes in combination with gene expression data. However, information about gene expression only poorly correlates with the abundance of the respective proteins within the cell. As such, we developed a method to map and integrate the whole-cell proteome into genome-scale models on the example of lactic acid bacteria (LAB). To the best of our knowledge, this work represents the first effort to integrate proteome data into genome-scale models on such a scale .

2016-12-06 | PXD002869 | Pride

Enterococcus faecalis V583, Part 1

2016-12-06 | PXD001576 | Pride

Project description:Hoverfly pollination network created using DNA metabarcoding

| PRJNA437768 | ENA

Mediator Kinase Inhibition Impedes Transcriptional Plasticity and Prevents Resistance to ERK/MAPK-Targeted Therapy in KRAS-Mutant Cancers

Project description:Acquired resistance remains a major challenge for therapies targeting oncogene activated pathways. KRAS is the most frequently mutated oncogene in human cancers, yet strategies targeting its downstream signaling kinases have failed to produce durable treatment responses. Here, we developed multiple models of acquired resistance to dual-mechanism ERK/MAPK inhibitors across KRAS-mutant pancreatic, colorectal, and lung cancers, and then probed the long-term events enabling survival against this class of drugs. These studies revealed that resistance emerges secondary to large-scale transcriptional adaptations that are diverse and tumor-specific. Transcriptional reprogramming extends beyond the well-established early response, and instead represents a dynamic, evolved population-level process that is refined to attain a stably resistant phenotype. Mechanistic and translational studies reveal that resistance to dual-mechanism ERK/MAPK inhibition is broadly susceptible to manipulation of the epigenetic machinery, and that Mediator kinase, in particular, can be co-targeted at a bottleneck point to prevent diverse, tumor-specific resistance programs.

2024-05-15 | GSE237177 | GEO

Mediator Kinase Inhibition Impedes Transcriptional Plasticity and Prevents Resistance to Sustained MAPK-Targeted Therapy in KRAS-Mutant Cancers

Project description:Acquired resistance remains a major challenge for therapies targeting oncogene activated pathways. KRAS, for example, is the most frequently mutated oncogene in human cancers, yet strategies targeting its downstream signaling kinases have failed to produce durable treatment responses. Here, we developed multiple models of acquired resistance to second-generation MAPK inhibitors across KRAS-mutant pancreatic, colorectal, and lung cancers, then probed the long-term events enabling survival against this class of drugs. These studies revealed that resistance emerges secondary to large-scale transcriptional adaptations that are diverse and tumor-specific. Transcriptional reprogramming extends beyond the well-established early response, and instead represents a dynamic, evolved process that is refined to attain a stably resistant phenotype. Mechanistic and translational studies reveal that resistance to sustained MAPK inhibition is broadly susceptible to manipulation of the epigenetic machinery, and that Mediator kinase, in particular, can be co-targeted at a bottleneck point to prevent diverse, tumor-specific resistance programs.

2024-06-26 | GSE234378 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data