Molecular characterization of large cell neuroendocrine carcinoma of the lung by multilayered omics analysis
Year: 2026
Type: article
Study design: Observational Study
Abstract: Large cell neuroendocrine carcinoma (LCNEC) is a rare type of lung cancer with a very poor prognosis, and its underlying molecular features remain elusive. Here, multi-omics analysis of 27 LCNEC cases along with seven small cell lung carcinomas is performed. The genomic and epigenomic alterations as well as the correlation of the genomic mutations with the pathological subtypes are characterized, which are not always consistent. Spatial omics analyses are also conducted, and most of the cases are successfully grouped into a high ASCL1 neuroendocrine (NE) subtype and high ASCL2 or YAP1 non-NE subtypes; however, an ambiguous state is observed for some specimens, which shows the simultaneous expression of NE and non-NE lineage markers. The findings of this study indicate that LCNEC may transit toward the NE or non-NE directions. By controlling the transcriptional regulatory networks of such elasticity, a new approach may be contemplated to overcome the pleiotropic therapeutic responses of LCNEC. Large cell neuroendocrine carcinoma (LCNEC) is an aggressive lung cancer whose biological diversity remains poorly understood. Here, the authors combine genomic, epigenomic and spatial transcriptomic analyses to show that LCNEC cells can shift between neuroendocrine and non-neuroendocrine states, identifying intermediate cell states and immune microenvironment features that may influence prognosis and treatment responses.
Source: Nature Communications
Authors: Megumi Tateishi, Yoshiki Otsuka, Ryota Matsuoka, Kei Asayama, Junko Zenkoh, Tomoki Nakagawa, Yoshihiko Murata, Naohiro Kobayashi, Yukio Sato, Nobuyuki Hizawa, Hiroyoshi Tsubochi, Shunsuke Endo, Koichi Hagiwara, Toshiro Niki, Noriyoshi Fukushima, Kentaro Inamura, Akinori Kanai, Yutaka Suzuki, Daisuke Matsubara, Ayako Suzuki
Language: English
Topic: Lung Cancer Research Studies
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $6,990
OpenAlex ID: W7223082476
