Adipose Stromal Cell-Derived Cancer-Associated Fibroblasts Suppress FGFR Inhibitor Efficacy.
Mikhail G KoloninDimitris AnastassiouPublished in: Cancer research (2024)
Cancer aggressiveness has been linked with obesity, and studies have shown that adipose tissue can enhance cancer progression. In this issue of Cancer Research, Hosni and colleagues discover a paracrine mechanism mediated by adipocyte precursor cells through which urothelial carcinomas become resistant to erdafitinib, a recently approved therapy inhibiting fibroblast growth factor receptors (FGFR). They identified neuregulin 1 (NRG1) secreted by adipocyte precursor cells as an activator of HER3 signaling that enables resistance. The NRG1-mediated FGFR inhibitor resistance was amenable to intervention with pertuzumab, an antibody blocking the NRG1/HER3 axis. To investigate the nature of the resistance-associated NRG1-expressing cells in human patients, the authors analyzed published single-cell RNA sequencing data and observed that such cells appear in a cluster assigned as inflammatory cancer-associated fibroblasts (iCAF). Notably, the gene signature corresponding to these CAFs is highly similar to that shared by adipose stromal cells (ASC) in fat tissue and fibro-adipogenic progenitors (FAP) in skeletal muscle of cancer-free individuals. Because fibroblasts with the ASC/FAP signature are enriched in various carcinomas, it is possible that the paracrine signaling conferred by NRG1 is a pan-cancer mechanism of FGFR inhibitor resistance and tumor aggressiveness. See related article by Hosni et al., p. 725.
Keyphrases
- adipose tissue
- papillary thyroid
- induced apoptosis
- insulin resistance
- skeletal muscle
- squamous cell
- cell cycle arrest
- randomized controlled trial
- type diabetes
- signaling pathway
- endothelial cells
- cell death
- metabolic syndrome
- stem cells
- lymph node metastasis
- gene expression
- high fat diet
- oxidative stress
- systematic review
- extracellular matrix
- deep learning
- nlrp inflammasome
- dna methylation
- high throughput
- patient reported outcomes
- transcription factor
- artificial intelligence
- urinary tract