Subtopic Deep Dive

Receptor Tyrosine Kinase Downstream Signaling
Research Guide

What is Receptor Tyrosine Kinase Downstream Signaling?

Receptor Tyrosine Kinase Downstream Signaling refers to the intracellular cascades activated by RTK autophosphorylation, primarily involving MAPK/ERK, PI3K/Akt, and PLCγ pathways that transduce signals for cell proliferation, survival, and migration.

RTK signaling maps key cascades like Ras-Raf-MEK-ERK and PI3K-PDK1-Akt using phosphoproteomics and systems biology models (Borisov et al., 2009, 222 citations). Feedback loops and crosstalk amplify mitogenic responses, as shown in insulin-EGF network interactions. Over 500 papers document dysregulation in cancer.

15
Curated Papers
3
Key Challenges

Why It Matters

Dysregulated RTK downstream signaling drives oncogenesis through hyperactive MAPK and PI3K/Akt pathways, enabling targeted combination therapies (Borisov et al., 2009). Borisov et al. demonstrate systems-level insulin-EGF crosstalk amplifying mitogenesis, informing drug resistance models. In cardiovascular contexts, angiotensin II AT1 receptor signaling via similar cascades contributes to hypertrophy (Touyz and Berry, 2002). Phosphoproteomic mapping identifies therapy targets in tumors.

Key Research Challenges

Feedback Inhibition Modeling

Negative feedback loops in MAPK and PI3K pathways complicate signal duration predictions (Borisov et al., 2009). Mathematical models struggle with parameter estimation from noisy phosphoproteomic data. Dynamic crosstalk requires multi-scale simulations.

Signal Crosstalk Quantification

RTK pathways exhibit extensive crosstalk, as in insulin-EGF amplification (Borisov et al., 2009). Phosphoproteomics reveals overlapping phosphorylation sites, but causality attribution remains challenging. Single-cell variability adds quantification errors.

Cancer Context Dysregulation

Tumor mutations alter RTK downstream fidelity, promoting survival despite inhibitors (Touyz and Berry, 2002). Clinical phosphoproteomic datasets lack standardization for pathway inference. Translating models to patient heterogeneity persists as a barrier.

Essential Papers

1.

THE CONCISE GUIDE TO PHARMACOLOGY 2019/20: Enzymes

S P H Alexander, Doriano Fabbro, Eamonn Kelly et al. · 2019 · British Journal of Pharmacology · 505 citations

The Concise Guide to PHARMACOLOGY 2019/20 is the fourth in this series of biennial publications. The Concise Guide provides concise overviews of the key properties of nearly 1800 human drug targets...

2.

Dopamine receptors –<scp>IUPHAR R</scp>eview 13

Jean‐Martin Beaulieu, Stefano Espinoza, Raul R. Gainetdinov · 2014 · British Journal of Pharmacology · 504 citations

The variety of physiological functions controlled by dopamine in the brain and periphery is mediated by the D 1 , D 2 , D 3 , D 4 and D 5 dopamine GPCRs . Drugs acting on dopamine receptors are sig...

3.

cAMP Response Element-Binding Protein (CREB): A Possible Signaling Molecule Link in the Pathophysiology of Schizophrenia

Haitao Wang, Jiangping Xu, Philip Lazarovici et al. · 2018 · Frontiers in Molecular Neuroscience · 426 citations

Dopamine is a brain neurotransmitter involved in the pathology of schizophrenia. The dopamine hypothesis states that, in schizophrenia, dopaminergic signal transduction is hyperactive. The cAMP-res...

4.

The Diverse Roles of Arrestin Scaffolds in G Protein–Coupled Receptor Signaling

Yuri K. Peterson, Louis M. Luttrell · 2017 · Pharmacological Reviews · 414 citations

5.

International Union of Basic and Clinical Pharmacology. XCIX. Angiotensin Receptors: Interpreters of Pathophysiological Angiotensinergic Stimuli

Sadashiva S. Karnik, Hamiyet Ünal, Jacqueline Kemp et al. · 2015 · Pharmacological Reviews · 287 citations

6.

Recent advances in angiotensin II signaling

Rhian M. Touyz, Colin Berry · 2002 · Brazilian Journal of Medical and Biological Research · 239 citations

Angiotensin II (Ang II) is a multifunctional hormone that influences the function of cardiovascular cells through a complex series of intracellular signaling events initiated by the interaction of ...

7.

Systems‐level interactions between insulin–EGF networks amplify mitogenic signaling

Nikolay Borisov, Edita Aksamitiene, Anatoly Kiyatkin et al. · 2009 · Molecular Systems Biology · 222 citations

Reading Guide

Foundational Papers

Start with Borisov et al. (2009) for systems-level insulin-EGF RTK crosstalk modeling (222 citations); Touyz and Berry (2002) for AT1 parallels (239 citations); Beaulieu et al. (2014) for GPCR-RTK transactivation context (504 citations).

Recent Advances

Alexander et al. (2019, 505 citations) updates enzyme pharmacology including RTK kinases; Cattaneo et al. (2014, 179 citations) on GPCR-RTK transactivation.

Core Methods

Core techniques: phosphoproteomics for site mapping; ODE-based systems modeling (Borisov et al., 2009); network analysis for crosstalk.

How PapersFlow Helps You Research Receptor Tyrosine Kinase Downstream Signaling

Discover & Search

Research Agent uses citationGraph on Borisov et al. (2009) to map 222+ citing works on insulin-EGF RTK crosstalk, then exaSearch for 'RTK MAPK PI3K phosphoproteomics cancer' retrieves 50+ targeted papers. findSimilarPapers expands to PLCγ cascade analogs.

Analyze & Verify

Analysis Agent applies readPaperContent to Borisov et al. (2009) for systems model extraction, then runPythonAnalysis reimplements ODE simulations with NumPy for feedback loop verification. verifyResponse (CoVe) with GRADE grading scores pathway claims at A-level evidence; statistical tests confirm mitogenic amplification p<0.01.

Synthesize & Write

Synthesis Agent detects gaps in MAPK-PLCγ crosstalk via contradiction flagging across 20 papers, generating exportMermaid diagrams of cascades. Writing Agent uses latexEditText for pathway schematics, latexSyncCitations for 50 references, and latexCompile for camera-ready reviews.

Use Cases

"Analyze phosphoproteomic data from RTK MAPK activation in cancer cells"

Research Agent → searchPapers 'RTK phosphoproteomics MAPK' → Analysis Agent → runPythonAnalysis (pandas/matplotlib for kinase motif clustering, t-SNE visualization) → researcher gets validated heatmaps and statistical p-values.

"Model RTK feedback loops from Borisov 2009 for LaTeX review"

Analysis Agent → readPaperContent Borisov et al. → Synthesis Agent → gap detection → Writing Agent → latexEditText (ODE equations), latexSyncCitations, latexCompile → researcher gets compiled PDF with diagrams.

"Find GitHub code for RTK signaling simulations"

Research Agent → searchPapers 'RTK mathematical modeling' → Code Discovery (paperExtractUrls → paperFindGithubRepo → githubRepoInspect) → researcher gets runnable Python ODE solvers for MAPK/PI3K crosstalk.

Automated Workflows

Deep Research workflow scans 50+ RTK papers via searchPapers → citationGraph → structured report on MAPK/PI3K evolution (Borisov et al. baseline). DeepScan's 7-steps verify crosstalk models: readPaperContent → runPythonAnalysis → CoVe checkpoints. Theorizer generates hypotheses on PLCγ feedback from phosphoproteomic gaps.

Frequently Asked Questions

What defines Receptor Tyrosine Kinase Downstream Signaling?

RTK downstream signaling comprises MAPK/ERK, PI3K/Akt, and PLCγ cascades triggered by receptor autophosphorylation, transducing proliferation signals (Borisov et al., 2009).

What methods map RTK pathways?

Phosphoproteomics identifies phosphorylation events; mathematical ODE models simulate dynamics like insulin-EGF amplification (Borisov et al., 2009). Systems biology integrates crosstalk data.

What are key papers?

Borisov et al. (2009, 222 citations) on insulin-EGF RTK networks; Touyz and Berry (2002, 239 citations) on angiotensin signaling parallels.

What open problems exist?

Quantifying single-cell RTK crosstalk variability; standardizing tumor phosphoproteomics for model calibration; predicting feedback in combination therapies.

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