Proteogenomic Characterization of High-Grade Lung Neuroendocrine Carcinoma Deciphers Molecular Diversity and Potential Biomarkers of Different Histological Subtypes in Chinese Population

High-grade lung neuroendocrine carcinomas (Lu-NECs) are clinically refractory malignancies with poor prognosis and limited therapeutic advances. The biological and molecular features underlying the histological heterogeneity of Lu-NECs are not fully understood. In this study, we present a multi-omic...

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Bibliographic Details
Main Authors: Zicheng Zhang, Xi Wu, Siqi Bao, Xujie Sun, Fan Yang, Yibo Zhang, Zijian Yang, Liujin Zhang, Ruanqi Chen, Puyuan Xing, Junling Li, Meng Zhou, Lin Yang
Format: Article
Language:English
Published: American Association for the Advancement of Science (AAAS) 2025-01-01
Series:Research
Online Access:https://spj.science.org/doi/10.34133/research.0671
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Summary:High-grade lung neuroendocrine carcinomas (Lu-NECs) are clinically refractory malignancies with poor prognosis and limited therapeutic advances. The biological and molecular features underlying the histological heterogeneity of Lu-NECs are not fully understood. In this study, we present a multi-omics integration of whole-exome sequencing and deep proteomic profiling in 93 Chinese Lu-NECs to establish the first comprehensive proteogenomic atlas of this disease spectrum. Our analyses revealed a high degree of mutational concordance among the subtypes at the genomic level; however, distinct proteomic profiles enabled a clear differentiation of histological subtypes, unveiling subtype-specific molecular and biological features related to tumor metabolism, immunity, and proliferation. Furthermore, RB1 mutations confer divergent prognostic effects through subtype-specific cis- and trans-proteomic regulation. In addition, we identified potential protein biomarkers for histological subtype classification and risk stratification, which were validated by immunohistochemistry in an independent cohort. This study provides a valuable proteogenomic resource and insight into Lu-NEC heterogeneity.
ISSN:2639-5274