# Research Progress on Molecular Subtypes and Precision Therapy of Pulmonary Large Cell Neuroendocrine Carcinoma

**Authors:** Yuchao FENG, Xiaohong CAO

PMC · DOI: 10.3779/j.issn.1009-3419.2025.102.06 · Chinese Journal of Lung Cancer · 2025-03-21

## TL;DR

This review discusses the molecular subtypes and precision therapies for pulmonary large cell neuroendocrine carcinoma, highlighting recent advances in targeted and immune treatments.

## Contribution

The paper provides an updated overview of molecular classification and precision therapy strategies for LCNEC, emphasizing future directions toward personalized treatment.

## Key findings

- LCNEC molecular subtypes are defined by mutations in genes like RB1 and TP53, influencing survival and treatment response.
- Immune checkpoint inhibitors show promise in LCNEC but carry risks of overactive immune responses.
- Targeted therapies have identified multiple potential drug targets, though their effectiveness varies.

## Abstract

肺大细胞神经内分泌癌（large cell neuroendocrine carcinoma, LCNEC）是有独特特征的高级别神经内分泌肿瘤，其治疗多借鉴小细胞肺癌与非小细胞肺癌治疗方案。近年来其发病率呈上升趋势，其预后受个体、临床分期及治疗方式等多因素交互影响，异质性显著。在分子亚型的研究中依据RB1、TP53等关键基因突变划分出多个亚组，基因组亚型与生存率、化疗反应及精准治疗的疗效相关。靶向治疗挖掘出多个靶点，药物疗效不一。免疫治疗进展突出，免疫检查点抑制剂（immune checkpoint inhibitors, ICIs）单用或联合化放疗在不同分期均显成效，却存在过度增殖性疾病风险，精准预后标志物亟待挖掘。本综述针对LCNEC的分子亚型研究和靶向、免疫等精准治疗的最新研究进展进行综述，并指出未来LCNEC治疗将朝着精准化、个体化方向发展。

## Linked entities

- **Genes:** RB1 (RB transcriptional corepressor 1) [NCBI Gene 5925], TP53 (tumor protein p53) [NCBI Gene 7157]
- **Diseases:** large cell neuroendocrine carcinoma (MONDO:0005057), small cell lung cancer (MONDO:0008433), non-small cell lung cancer (MONDO:0005233)

## Full-text entities

- **Genes:** RB1 (RB transcriptional corepressor 1) [NCBI Gene 5925] {aka OSRC, PPP1R130, RB, p105-Rb, p110-RB1, pRb}, TP53 (tumor protein p53) [NCBI Gene 7157] {aka BCC7, BMFS5, LFS1, P53, TRP53}
- **Diseases:** neuroendocrine tumor (MESH:D018358), NSCLC (MESH:D002289), SCLC (MESH:D055752), LCNEC (MESH:D018287)

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/PMC11931233/full.md

## References

69 references — full list in the complete paper: https://tomesphere.com/paper/PMC11931233/full.md

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Source: https://tomesphere.com/paper/PMC11931233