Multiomic characterization of small cell lung cancer: Real-world insights into therapeutic opportunities.
[BACKGROUND] The dominant expression of lineage-related transcription factors (TFs)-ASCL1, NEUROD1, POU2F3, and, controversially, YAP1-has enabled the classification of small cell lung cancer (SCLC) i
- 표본수 (n) 944
APA
Puri S, Elliott A, et al. (2026). Multiomic characterization of small cell lung cancer: Real-world insights into therapeutic opportunities.. Cancer, 132(5), e70284. https://doi.org/10.1002/cncr.70284
MLA
Puri S, et al.. "Multiomic characterization of small cell lung cancer: Real-world insights into therapeutic opportunities.." Cancer, vol. 132, no. 5, 2026, pp. e70284.
PMID
41761743
Abstract
[BACKGROUND] The dominant expression of lineage-related transcription factors (TFs)-ASCL1, NEUROD1, POU2F3, and, controversially, YAP1-has enabled the classification of small cell lung cancer (SCLC) into distinct subtypes (SCLC-A/N/P/Y, respectively). Emerging evidence suggests that a T cell-inflamed phenotype characterizes an SCLC subset. A large-scale multiomic analysis of samples from real-world patients with SCLC was conducted to examine the expression of clinically relevant biomarkers across SCLC subtypes.
[METHODS] Comprehensive molecular profiling of patient samples (N = 944) was performed via next-generation DNA sequencing (592-gene panel or whole exome), RNA sequencing (whole transcriptome), and immunohistochemistry. Tumors were stratified on the basis of the dominant expression of an individual TF (SCLC-A/N/Y/P subtypes), coexpression of multiple TFs (mixed), or low expression of all four TFs (TF-) for characterization of immune-related gene signatures (T-cell inflamed, natural killer cell, and Stimulator of Interferon Genes pathway) and clinically relevant target genes.
[RESULTS] The cohort was composed of 25.6% SCLC-A, 10.2% SCLC-N, 12.5% SCLC-Y, 4.3% SCLC-P, 19.5% SCLC TF-, and 27.9% mixed subtypes. The SCLC-Y subtype exhibited the highest expression of immune-related gene signatures, with comparable expression observed in mixed samples expressing YAP1. Additionally, expression of clinically relevant target genes found in SCLC-A (DLL3, SEZ6, and BCL2) and SCLC-N (SSTR2) was increased in mixed samples expressing ASCL1 and NEUROD1. The TF- subtype was not associated with increased immune-related signatures or other target genes.
[CONCLUSIONS] This large-scale multiomic analysis revealed significant associations between SCLC subtypes and specific immune signatures and comutations. These findings provide insights into the molecular heterogeneity of SCLC, and highlight potential biomarkers for targeted therapies.
[METHODS] Comprehensive molecular profiling of patient samples (N = 944) was performed via next-generation DNA sequencing (592-gene panel or whole exome), RNA sequencing (whole transcriptome), and immunohistochemistry. Tumors were stratified on the basis of the dominant expression of an individual TF (SCLC-A/N/Y/P subtypes), coexpression of multiple TFs (mixed), or low expression of all four TFs (TF-) for characterization of immune-related gene signatures (T-cell inflamed, natural killer cell, and Stimulator of Interferon Genes pathway) and clinically relevant target genes.
[RESULTS] The cohort was composed of 25.6% SCLC-A, 10.2% SCLC-N, 12.5% SCLC-Y, 4.3% SCLC-P, 19.5% SCLC TF-, and 27.9% mixed subtypes. The SCLC-Y subtype exhibited the highest expression of immune-related gene signatures, with comparable expression observed in mixed samples expressing YAP1. Additionally, expression of clinically relevant target genes found in SCLC-A (DLL3, SEZ6, and BCL2) and SCLC-N (SSTR2) was increased in mixed samples expressing ASCL1 and NEUROD1. The TF- subtype was not associated with increased immune-related signatures or other target genes.
[CONCLUSIONS] This large-scale multiomic analysis revealed significant associations between SCLC subtypes and specific immune signatures and comutations. These findings provide insights into the molecular heterogeneity of SCLC, and highlight potential biomarkers for targeted therapies.
MeSH Terms
Humans; Small Cell Lung Carcinoma; Lung Neoplasms; Biomarkers, Tumor; Male; Female; Transcription Factors; Gene Expression Profiling; Middle Aged; Basic Helix-Loop-Helix Proteins; Gene Expression Regulation, Neoplastic; Aged; Transcriptome; High-Throughput Nucleotide Sequencing; YAP-Signaling Proteins