A recent study has unveiled key molecular insights that could transform the treatment landscape for lung neuroendocrine tumors (NETs). The Neuroendocrine Tumor Research Foundation provided the funding for the research, which focused on gene expression and regulation that drive the growth of lung neuroendocrine tumors.
Yotam Drier, PhD, of the Hebrew University of Jerusalem, and his colleagues identified three distinct subtypes of lung NETs—proneural, luminal-like, and HNF+—each with unique regulatory elements and molecular drivers. Their findings were published Oct. 3 in the journal Proceedings of the National Academy of Sciences.
One of the most promising findings from the study centers on the HNF+ subtype, which is driven by FGFR signaling. Researchers found that tumors in this category may respond to FGFR inhibitors, a class of drugs already known to target similar pathways in other cancers. This opens the door to personalized treatment approaches, offering hope for improved outcomes in patients whose tumors exhibit this molecular signature.
In addition, the investigators identified two biomarkers associated with the subtypes that could pave the way for more precise diagnostic tools. These biomarkers may enable clinicians to easily classify tumors into one of the three subtypes in a clinical setting, potentially leading to more targeted and effective treatments for those living with lung NETs.
“Lung neuroendocrine tumors display remarkable clinical heterogeneity, making the treatment of these patients challenging,” said Dr. Drier. “We mapped gene expression and the regulatory elements that control it in 23 tumors resected from patients, and our findings revealed three major subtypes. In particular, we identified that FGFRs, which are known receptors of growth signals, are highly activated in one of the subtypes. Drugs targeting this receptor can indeed inhibit tumor growth, suggesting a new therapeutic strategy for these patients.”
The study’s use of enhancer and gene expression profiling allowed Dr. Drier and his colleagues to uncover the complex regulatory networks that drive lung NETs, providing a more nuanced understanding of these tumors than traditional histopathological classifications. This research highlights the diversity and heterogeneity of lung NETs, emphasizing the importance of gene regulation in tumor behavior.