A public data-based molecular classification of small cell lung cancer by neuroactive signaling networks unveils distinct microenvironment landscapes and immunotherapy-related prognostic biomarkers.

ABSTRACT:

Background

Small cell lung cancer (SCLC) represents an aggressive malignancy characterized by marked heterogeneity and neuroendocrine differentiation. Despite its clinical significance, the functional landscape of neuroendocrine function, while neuroactive-signaling-related genes (NRGs) in SCLC pathogenesis remains poorly characterized. Therefore, the aim of this study is to classify SCLC based on neuroactive signaling networks and to analyze the characteristics of these classifications in relation to the immune microenvironment.

Methods

Through integrated analysis of bulk transcriptomic profiling from 79 primary SCLC tumors and single-cell transcriptomic profiling from 11 SCLC tumors, we employed a consensus clustering algorithm to deconvolute transcriptional programs under

SUBMITTER: Zhou W 

PROVIDER: S-EPMC12683401 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature