Growth factor signaling predicts therapy resistance mechanisms and defines neuroblastoma subtypes

Area of Science:

• Oncology
• Molecular Biology
• Cancer Genomics

Background:

• Neuroblastoma (NB) exhibits limited recurrent mutations, complicating targeted therapy development.
• Multikinase inhibitors show promise for high-risk NB but face resistance via alternative signaling pathways.

Purpose of the Study:

• Develop a predictive model for NB patient survival based on growth factor gene expression.
• Identify signaling pathways involved in therapy response and resistance in NB.
• Investigate therapeutic strategies combining growth factor pathway inhibitors with existing anti-NB drugs.

Main Methods:

• Developed a survival prediction model using expression data from 1189 NB tumors.
• Analyzed signaling pathways and gene sets in 60 NB patients to identify therapy response markers.
• Evaluated the in vitro effects of growth factors and kinase inhibitors on NB cells.
• Assessed the role of ERK activation in growth factor-mediated drug resistance.

Main Results:

• A novel model accurately predicts NB patient survival, distinguishing favorable from poor outcomes, independent of MYCN status.
• Upregulated EPO, NGF, and HGF signaling pathways correlate with poor response to therapy.
• EPO and NGF protect NB cells against multiple multikinase inhibitors by activating ERK.
• Combined ERK inhibition and dasatinib demonstrate synergistic NB cell death.

Conclusions:

• Growth factor signaling activity is crucial for NB outcome prediction and can inform personalized therapy regimens.
• Targeting growth factor pathways and ERK activation presents a viable strategy to enhance the efficacy of anti-NB therapies.
• Combining multikinase inhibitors with ERK inhibitors offers a synergistic approach to combat NB, particularly in resistant cases.