Which STAT partners dominate cancer signaling networks?
An IID-based interactome shows STAT3 as the busiest hub, STAT1 as a frequent antagonist, and points to cytoplasmic nodes for JAK/STAT-targeted therapy ideas.
Source
JAK-STAT core cancer pathway: An integrative cancer interactome analysis
Study at a glance
- Design
- Computational / modelling — IID 2018 literature-curated STAT PPI interactomes filtered by disease/tissue expression context and visualized with NAViGaTOR
- N
- Network counts of STAT partners (e.g., STAT3 n=166 proteins) rather than a patient cohort N
- Population
- Curated human STAT protein–protein interactions across major cancer contexts
- Outcome
- Member-specific STAT interactomes and proposed targeting points in oncogenic JAK/STAT signaling
Structured fields used in claim comparison tables when every cited study has a complete layer.
What they did
Using IID 2018 PPIs (stringent multi-evidence + expression context), the authors built global and cancer-specific STAT interactomes and mapped them with NAViGaTOR, integrating literature on STAT-linked diseases.
What they found
STAT3 had the largest diversity (166 partners) vs STAT1 (81); STAT3/5 emerge as pleiotropic oncogenes while STAT1 often counters STAT3; EGFR/ESR1 interplay and cytoplasmic hubs inform targeting hypotheses.
The limits
What it doesn't show
Not a clinical drug trial; missing edges may reflect study bias, and network centrality ≠ proven drug efficacy.
Key terms
- JAK/STAT
- Janus kinase / signal transducer and activator of transcription pathway.
- Interactome
- Network map of protein–protein interactions for STAT family members.
- IID
- Integrated Interactions Database supplying curated, context-annotated PPIs.
- STAT3
- Often oncogenic STAT with the largest interaction diversity in this analysis.
- STAT1
- Frequently antagonistic to oncogenic STAT3 in the authors’ framing.
Flashcards
Research intelligence for this paper
See its role on concept claims, tensions it is part of, placement history, and related discoveries.
Quiz yourself
Best description of this study?
Common questions
Is this wet-lab binding for every edge?
No—it aggregates curated literature/database PPIs with expression filters.
Why STAT3 looks biggest?
Both biology and publication volume; authors note literature bias influences apparent degree.
Therapeutic takeaway?
Hitting central cytoplasmic communication hubs may limit pathway rerouting—hypothesis-generating.
Subject mapping?
Biology / cell-signaling (computational systems view of JAK/STAT).
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