ReviewMolecular cancer research : MCR2024
Small Cell Lung Cancer Neuronal Features and Their Implications for Tumor Progression, Metastasis, and Therapy.
Review in Molecular cancer research : MCR, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Role of neuron-specific SWI/SNF complex subunit BAF53B: from neuron to small cell lung carcinoma.Human cell · 2026Article
- Central nervous system and cancer: mechanistic insights and therapeutic opportunities CNS and cancer: a review.Medical oncology (Northwood, London, England) · 2026Review
- The neuronal network of small cell lung cancer: a narrative review of the role of the nervous system in the pathogenesis and progression.Translational lung cancer research · 2026Review
- Neuro-immune crosstalk in lung cancer brain metastasis: mechanisms, therapeutic targets, and translational opportunities.Medical oncology (Northwood, London, England) · 2026Review
- Refractory hyponatremia in small cell lung cancer: a case report and literature review.Frontiers in endocrinology · 2026Review
- The Five-Decade Journey of Small Cell Lung Cancer.Cancer communications (London, England) · 2026Review
- Neural regulation of lung cancer: from mechanisms to clinical implications.European journal of medical research · 2025Review
- Wired for growth: neuron-tumour signalling in the lung and brain increases growth of a hard-to-treat cancer.Nature · 2025Article
- [Crosstalk between Tumor Cells and Neural Signals in Neuroendocrine Carcinoma Metastasis: Communication Hijacking Based Perspective].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025Review
- Metastatic organotropism in small cell lung cancer.bioRxiv : the preprint server for biology · 2025Article
- Peripheral Facial Palsy in Small Cell Lung Cancer with Mastoid Metastasis.European journal of case reports in internal medicine · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Small cell lung cancer (SCLC) is an epithelial neuroendocrine form of lung cancer for which survival rates remain dismal and new therapeutic approaches are greatly needed. Key biological features of SCLC tumors include fast growth and widespread metastasis, as well as rapid resistance to treatment. Similar to pulmonary neuroendocrine cells, SCLC cells have traits of both hormone-producing cells and neurons. In this study, we specifically discuss the neuronal features of SCLC. We consider how neuronal G protein-coupled receptors and other neuronal molecules on the surface of SCLC cells can contribute to the growth of SCLC tumors and serve as therapeutic targets in SCLC. We also review recent evidence for the role of neuronal programs expressed by SCLC cells in the fast proliferation, migration, and metastasis of these cells. We further highlight how these neuronal programs may be particularly relevant for the development of brain metastases and how they can assist SCLC cells to functionally interact with neurons and astrocytes. A greater understanding of the molecular and cellular neuronal features of SCLC is likely to uncover new vulnerabilities in SCLC cells, which may help develop novel therapeutic approaches. More generally, the epithelial-to-neuronal transition observed during tumor progression in SCLC and other cancer types can contribute significantly to tumor development and response to therapy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.