An organoid library unveils subtype-specific IGF-1 dependency via a YAP-AP1 axis in human small cell lung cancer

Takahiro Fukushima1, Kazuhiro Togasaki2,3,4, Junko Hamamoto1

  • 1Division of Pulmonary Medicine, Department of Medicine, Keio University, School of Medicine, Tokyo, Japan.

Nature Cancer
|April 30, 2025
PubMed

Insights

Researchers developed 40 small cell lung cancer (SCLC) organoid models. Targeting insulin-like growth factor-1 (IGF-1) and YAP1 pathways suppressed non-neuroendocrine SCLC growth, offering new therapeutic avenues.

Area of Science:

  • Oncology
  • Molecular Biology
  • Genetics

Background:

  • Small cell lung cancer (SCLC) presents limited therapeutic options despite molecular subtype classification.
  • Subtype-specific treatments for SCLC remain largely undeveloped.
  • Patient-derived organoids offer a promising model for studying cancer heterogeneity.

Purpose of the Study:

  • To establish and characterize patient-derived SCLC organoid lines.
  • To identify molecular drivers and dependencies of different SCLC subtypes.
  • To explore targeted therapeutic strategies for non-neuroendocrine SCLC.

Main Methods:

  • Generation of 40 patient-derived SCLC organoid lines.
  • Transcriptome profiling to classify SCLC subtypes.
  • In vitro validation of therapeutic targets (IGF-1, YAP1, AP1).
  • Genetic manipulation of human alveolar cells to validate subtype-phenotype connections.

Main Results:

  • SCLC organoids classified into neuroendocrine (NE) and non-NE subtypes.
  • Non-NE SCLC characterized by YAP1 or POU2F3 expression and dependency on IGF-1 signaling.
  • Targeting IGF-1, YAP1, and AP1 pathways inhibited non-NE SCLC organoid growth.
  • TP53/RB1 alterations in alveolar cells induced airway epithelium-like fate and IGF-1 dependency.

Conclusions:

  • The established SCLC organoid library is a valuable resource for SCLC research.
  • Non-NE SCLC subtypes exhibit specific dependencies that can be therapeutically targeted.
  • Understanding SCLC subtype biology can reshape drug discovery and lead to novel therapies.