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Over the past three-decades, Janus kinase (Jak) and signal transducer and activator of transcription (STAT) signaling has emerged as a paradigm to understand the involvement of signal transduction in development and disease pathology. At the molecular level, cytokines and interleukins steer Jak/STAT signaling to transcriptional regulation of target genes, which are involved in cell differentiation, migration, and proliferation. Jak/STAT signaling is involved in various types of blood cell disorders and cancers in humans, and its activation is associated with carcinomas that are more invasive or likely to become metastatic. Despite immense information regarding Jak/STAT regulation, the signaling network has numerous missing links, which is slowing the progress towards developing drug therapies. In mammals, many components act in this cascade, with substantial cross-talk with other signaling pathways. In Drosophila, there are fewer pathway components, which has enabled significant discoveries regarding well-conserved regulatory mechanisms. Work across species illustrates the relevance of these regulators in humans. In this review, we showcase fundamental Jak/STAT regulation mechanisms in blood cells, stem cells, and cell motility. We examine the functional relevance of key conserved regulators from Drosophila to human cancer stem cells and metastasis. Finally, we spotlight less characterized regulators of Drosophila Jak/STAT signaling, which stand as promising candidates to be investigated in cancer biology. These comparisons illustrate the value of using Drosophila as a model for uncovering the roles of Jak/STAT signaling and the molecular means by which the pathway is controlled.
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Applying molecular communication theory to estimate information loss in cell signal transduction: an approach based on cancer transcriptomics
Signal transduction pathways are chemical communication channels embedded in biological cells, and they propagate information from the environment to regulate cell growth and proliferation, among other cell's behaviors. Disruptions in the normal functionalities of these channels, mostly resulting from mutations in the underlying genetic code, can be leading causes of diseases, such as cancer. Motivated by the increasing availability of public data on genetic code expression in cell tissue samples, i.e., transcriptomics, and the emerging field of molecular communication, a novel data-driven approach based on experimental data mining and communication theory is proposed in this paper. This approach is an alternative to existing computational models of these pathways in the context of cancer, which often appear to oversimplify the complexity of the underlying mechanisms. In contrast, a computational methodology is here derived to estimate the difference in information propagation performance of signal transduction pathways in healthy and diseased cells, solely based on transcriptomic data. This methodology is built upon a molecular communication abstraction of information flow through the pathway and its correlation with the expression of the underlying DNA genes. Numerical results are presented for a case study based on the JAK-STAT pathway in kidney cancer, and correlated with the occurrence of pathway gene mutations in the available data.
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- Award ID(s):
- 1816969
- PAR ID:
- 10117228
- Date Published:
- Journal Name:
- NANOCOM '18 Proceedings of the 5th ACM International Conference on Nanoscale Computing and Communication
- Page Range / eLocation ID:
- 16
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3233188.3233202
