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Updated: Mar 8, 2026

Author Spotlight: Advancements in Molecular Biomarker Testing for Non-Squamous Non-Small Cell Lung Cancer
Published on: September 8, 2023
Heterogeneous associations between molecular subtypes of small cell lung cancer and survival prognosis: a systematic
Shumeng Li1, Hui Li1, Jinghong Wu2
1Department of Oncology, Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, 100010, China.
Background:
Small cell lung cancer (SCLC) is a heterogeneous disease with different pathogenic mechanisms. A range of molecular classification systems has been proposed based on the tumor's molecular characteristics. However, the relationship between these various molecular subtypes and survival prognosis remains unclear and has not been incorporated into clinical practice. Therefore, we conducted a systematic review of studies investigating the relationship between molecular subtypes of SCLC and patient survival prognosis.
Method:
A comprehensive search was conducted in the PubMed, Embase, Cochrane, and Web of Science databases, utilizing combinations of terms related to SCLC, molecular subtypes, and survival prognosis. Two independent reviewers were tasked with data extraction and quality assessment.
Results:
Following a comprehensive review of the pertinent literature, eight studies were included. Some methodological heterogeneity across these studies contributed to frequently inconsistent conclusions. Our findings tend to suggest that the inflammatory subtype (SCLC-I), which belongs to the non-neuroendocrine (non-NE) subtype, exhibits a survival advantage in most cases, while the ASCL1-dominant subtype (SCLC-A), which belongs to the NE subtype, shows a poorer survival prognosis, except in some exceptional cases.
Conclusions:
This is one of the first comprehensive systematic reviews to explore the relationship between molecular subtypes and survival prognosis in SCLC. Future high-quality studies employing standardized subtype definitions are warranted to validate these prognostic associations and enable definitive conclusions. Furthermore, emerging multi-omics and integrated spatial analyses have revealed novel subtypes and predictors, which are significantly associated with survival prognosis.
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