Subtopic Deep Dive

FGF Signaling in Cancer
Research Guide

What is FGF Signaling in Cancer?

FGF Signaling in Cancer examines dysregulated fibroblast growth factor (FGF) pathways driving tumor progression, angiogenesis, and metastasis in oncology.

Dysregulated FGF signaling promotes cancer through aberrant activation of FGFR tyrosine kinases, enhancing cell proliferation and vascularization (Turner and Grose, 2010, 2620 citations). Key FGF ligands interact with specific FGFRs to transduce signals via pathways like MAPK and PI3K (Ornitz and Itoh, 2015, 1995 citations; Eswarakumar et al., 2005, 1905 citations). Over 10 highly cited papers detail receptor specificity and therapeutic targeting.

15
Curated Papers
3
Key Challenges

Why It Matters

FGF signaling inhibition offers targeted therapies for cancers with FGFR amplifications, such as bladder and lung tumors, improving patient outcomes (Turner and Grose, 2010). Fibroblast-FGF interactions in tumor microenvironments drive fibrosis and angiogenesis, relevant for drug development (Kendall and Feghali-Bostwick, 2014). Ornitz and Itoh (2015) highlight FGFR inhibitors in clinical trials, reducing tumor growth in preclinical models.

Key Research Challenges

FGFR Isoform Specificity

FGFs bind FGFRs with varying affinities across 18 ligands and 4 receptors, complicating selective inhibition (Ornitz et al., 1996, 1889 citations). Alternative splicing generates IIIb/IIIc isoforms with tissue-specific expression, challenging broad-spectrum inhibitors (Ornitz and Itoh, 2015). Therapeutic design must avoid off-target effects on normal development.

Resistance to Inhibitors

Cancers develop resistance to FGFR tyrosine kinase inhibitors via pathway crosstalk and mutations (Turner and Grose, 2010). Fibroblast-derived FGFs in stroma sustain signaling post-inhibition (Powers et al., 2000, 1323 citations). Combination therapies are needed to overcome adaptive responses.

Tumor Microenvironment Role

FGF signaling from cancer-associated fibroblasts promotes ECM remodeling and immune evasion (Kendall and Feghali-Bostwick, 2014, 1026 citations). Angiogenesis driven by FGF2-FGFR1 axis resists anti-VEGF therapies. Dissecting paracrine vs. autocrine effects remains difficult.

Essential Papers

1.

Fibroblast growth factor signalling: from development to cancer

Nicholas C. Turner, Richard Grose · 2010 · Nature reviews. Cancer · 2.6K citations

2.

Role of platelet-derived growth factors in physiology and medicine

Johanna Andræ, R Gallini, Christer Betsholtz · 2008 · Genes & Development · 2.4K citations

Platelet-derived growth factors (PDGFs) and their receptors (PDGFRs) have served as prototypes for growth factor and receptor tyrosine kinase function for more than 25 years. Studies of PDGFs and P...

3.

FGF-21 as a novel metabolic regulator

Alexei Kharitonenkov, Tatiyana L. Shiyanova, Anja Köester et al. · 2005 · Journal of Clinical Investigation · 2.1K citations

Diabetes mellitus is a major health concern, affecting more than 5% of the population. Here we describe a potential novel therapeutic agent for this disease, FGF-21, which was discovered to be a po...

4.

The Fibroblast Growth Factor signaling pathway

David M. Ornitz, Nobuyuki Itoh · 2015 · Wiley Interdisciplinary Reviews Developmental Biology · 2.0K citations

The signaling component of the mammalian Fibroblast Growth Factor ( FGF ) family is comprised of eighteen secreted proteins that interact with four signaling tyrosine kinase FGF receptors ( FGFRs )...

5.

Fibroblast growth factors.

David M. Ornitz, Nobuyuki Itoh · 2001 · Genome Biology · 1.9K citations

6.

Cellular signaling by fibroblast growth factor receptors

Veraragavan P. Eswarakumar, Irit Lax, Joseph Schlessinger · 2005 · Cytokine & Growth Factor Reviews · 1.9K citations

7.

Receptor Specificity of the Fibroblast Growth Factor Family

David M. Ornitz, Jian Xu, Jennifer S. Colvin et al. · 1996 · Journal of Biological Chemistry · 1.9K citations

Fibroblast growth factors (FGFs) are essential molecules for mammalian development. The nine known FGF ligands and the four signaling FGF receptors (and their alternatively spliced variants) are ex...

Reading Guide

Foundational Papers

Start with Turner and Grose (2010) for cancer-specific overview (2620 citations), then Ornitz and Itoh (2001) for FGF family basics (1950 citations), and Eswarakumar et al. (2005) for receptor signaling (1905 citations).

Recent Advances

Ornitz and Itoh (2015) updates pathway mechanisms (1995 citations); Kendall and Feghali-Bostwick (2014) covers fibroblast roles in fibrosis-cancer (1026 citations).

Core Methods

FGFR binding specificity assays (Ornitz et al., 1996); tyrosine kinase signaling via MAPK/STAT (Eswarakumar et al., 2005); inhibitor screens and genetic models (Turner and Grose, 2010).

How PapersFlow Helps You Research FGF Signaling in Cancer

Discover & Search

Research Agent uses searchPapers('FGF signaling cancer FGFR inhibitors') to retrieve Turner and Grose (2010), then citationGraph reveals 2620 downstream papers on clinical trials, while findSimilarPapers expands to Ornitz and Itoh (2015) for pathway details.

Analyze & Verify

Analysis Agent applies readPaperContent on Turner and Grose (2010) to extract FGFR mutation data, verifyResponse with CoVe cross-checks claims against Ornitz et al. (1996), and runPythonAnalysis plots citation trends or FGFR binding affinities using pandas for statistical verification; GRADE grading scores evidence strength for therapeutic claims.

Synthesize & Write

Synthesis Agent detects gaps in resistance mechanisms from Turner and Grose (2010) vs. Powers et al. (2000), flags contradictions in pathway models; Writing Agent uses latexEditText for manuscript sections, latexSyncCitations integrates 10+ references, latexCompile generates PDF, and exportMermaid diagrams FGFR signaling cascades.

Use Cases

"Analyze FGFR1 expression data from FGF-cancer papers using Python."

Research Agent → searchPapers → Analysis Agent → runPythonAnalysis (pandas/matplotlib on extracted expression datasets from Ornitz and Itoh 2015) → researcher gets publication-ready survival correlation plots.

"Write LaTeX review on FGF inhibitors in bladder cancer."

Synthesis Agent → gap detection → Writing Agent → latexEditText + latexSyncCitations (Turner 2010 et al.) + latexCompile → researcher gets compiled PDF with figures and 20 citations.

"Find GitHub code for FGFR signaling simulations."

Research Agent → paperExtractUrls (Eswarakumar 2005) → paperFindGithubRepo → githubRepoInspect → researcher gets runnable Python models for MAPK pathway simulations.

Automated Workflows

Deep Research workflow conducts systematic review: searchPapers → citationGraph (Turner 2010 hub) → DeepScan 7-steps → structured report on 50+ FGF-cancer papers with GRADE scores. Theorizer generates hypotheses on FGFR-IIIc resistance from Powers et al. (2000) via contradiction flagging and pathway synthesis. DeepScan verifies inhibitor efficacy claims with CoVe across Ornitz papers.

Frequently Asked Questions

What defines FGF signaling in cancer?

Dysregulated FGF-FGFR interactions drive oncogenesis via MAPK/PI3K activation, as detailed in Turner and Grose (2010).

What are key methods for studying FGF pathways?

Receptor binding assays, tyrosine kinase inhibitor screens, and genetic knockout models assess specificity (Ornitz et al., 1996; Eswarakumar et al., 2005).

What are landmark papers?

Turner and Grose (2010, 2620 citations) reviews cancer roles; Ornitz and Itoh (2015, 1995 citations) details signaling components.

What open problems exist?

Overcoming inhibitor resistance and targeting stroma FGF sources without toxicity (Turner and Grose, 2010; Kendall and Feghali-Bostwick, 2014).

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