Date & Time: Wednesday, May 25th, 11am-12pm ET
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Join us for a TTC-hosted webinar and hear from NCI’s Dr. Peng Jiang about a new Cytokine Signaling Analyzer called “CytoSig.” This novel software-based platform provides both a database of target genes modulated by cytokines and a predictive model of cytokine signaling cascades from transcriptomic profiles. CytoSig covers 20,591 curated human cytokine, chemokine, and growth factor response experiments, and can reliably predict the activity of 43 cytokines in both tissues and single cells based on the transcriptional effect of cytokine target genes. CytoSig therefore provides a significantly more comprehensive analysis of cytokine signaling than the currently used Interferome and GSEA databases.
Technology Overview
Cytokines are a broad category of intercellular signaling proteins that are critical for intercellular communication in human health and disease. Current methods for systematic profiling of cytokine signaling activities are challenging due to: (i) cytokines’ short half-lives; (ii) pleiotropic functions; and (iii) cytokine activity redundancy within specific cellular contexts. Additionally, existing cytokine signaling target databases only cover a small fraction of cytokines, leaving most cytokine-induced target changes unexplored.
CytoSig solves these challenges with its significantly larger database content coverage and uses transcriptome data to model cytokine signaling activity and regulatory cascades in human inflammatory processes. CytoSig couples large-scale automatic data processing with natural language processing functions to assist expert metadata annotations with RNA-sequencing (RNA-seq) and MicroArray big-data analysis. CytoSig is therefore, an excellent tool for leveraging big-data resources in public domains to predict clinical outcomes of anticancer therapies that inhibit cytokine signaling. The NCI is seeking parties interested in licensing and/or co-development of this technology.
The NCI is seeking parties interested in licensing and/or co-development of this technology.
Technology Competitive Advantages
- Integrative framework leveraging public domain big-data resources to identify therapeutic targets
- Larger, more comprehensive cytokine coverage compared to existing databases
- Predictions have better associations with clinical outcomes compared to other methods, and therefore can better inform decisions about anti-cytokine therapies in treating inflammatory diseases
- Not affected by absence of cytokine-producing cells or zero-read counts for ligand or receptor genes in single-cell transcriptomics analysis
Why attend?
- Assess co-development and/or licensing interest in this technology
- Interact with the inventor, ask questions, and provide feedback
- Learn how to partner with the NCI
Who Should Attend?
- Business development professionals
- Drug development professionals
- Biotech/pharma/academia researchers
- Investors and entrepreneurs
About the Presenter
Peng Jiang, Ph.D.
Stadtman Investigator
NCI Center for Cancer Research, Cancer Data Science Laboratory
Interested in learning more?
Register for the webinar
Contact us NCITechTransfer@mail.nih.gov