Molecular Cancer | Multi-omics analysis reveals heterogeneity of disease subtypes and potential biomarkers in small cell lung cancer

This study reveals the heterogeneity of small cell lung cancer (SCLC) subtypes and their spatial relationships with the immune microenvironment through multi-omics and spatial immune analyses. It identifies that MHC-I expression levels are closely related to the spatial distribution of immune cell infiltration, providing potential biomarkers for predicting the efficacy of immune checkpoint therapies. Meanwhile, high DLL3 expression correlates with neuroendocrine phenotypes and an immune-cold microenvironment, suggesting its potential as a therapeutic target.

 

Literature Overview

This article, 'Multi-omic profiling provides insights into the heterogeneity, microenvironmental features, and biomarker landscape of small-cell lung cancer,' published in the journal Molecular Cancer, reviews and summarizes the molecular subtype heterogeneity, immune microenvironment characteristics, and potential biomarkers of small-cell lung cancer (SCLC), with particular emphasis on the association between expression patterns of MHC-I and DLL3 and immune cell infiltration and treatment responses.

Background Knowledge

SCLC accounts for approximately 15% of all lung cancer cases and is characterized by aggressive and rapid growth, with most patients presenting at advanced stages at diagnosis. Although the combination of immune checkpoint inhibitors and chemotherapy has significantly prolonged survival in some patients, the overall response rate remains low, highlighting the need for more precise biomarkers to guide therapy. Recently, SCLC has been classified into several molecular subtypes, including SCLC-A, SCLC-N, SCLC-P, and SCLC-I, which differ in gene expression, immune microenvironment, and response to treatment. For instance, the SCLC-I subtype exhibits higher antigen presentation and T-cell infiltration, suggesting a potential sensitivity to immunotherapy. DLL3, an inhibitory ligand of the Notch signaling pathway, is highly expressed in SCLC and its expression is associated with poor immune infiltration. By integrating multi-omics analyses with immunohistochemistry (IHC), RNA sequencing, methylomics, and multiplex immunofluorescence techniques, this study systematically deciphers the molecular features of SCLC and their spatial relationship with the immune microenvironment, offering new insights for personalized therapeutic strategies.

 

 

Research Methods and Experiments

The research team conducted multi-omics analyses on 159 untreated small-cell lung cancer patient samples, including genomic, transcriptomic, proteomic, and methylomic data. These analyses were complemented with immunohistochemistry (IHC) and multiplex immunofluorescence (mIF) techniques to assess the spatial characteristics of the tumor microenvironment. MHC-I and DLL3 expression levels were quantified using H-score and TC-score. Additionally, flow cytometry, protein expression analysis, and survival analysis (Kaplan-Meier method) were employed to evaluate the relationships between immune cell infiltration, antigen presentation capacity, and patient prognosis.

Key Conclusions and Perspectives

• Small cell lung cancer demonstrates significant heterogeneity, with approximately 15% sample discordance between RNAseq and IHC subtyping, suggesting that IHC alone may underestimate the complexity of subtypes
• High MHC-I expression predominantly occurs in non-neuroendocrine subtypes (SCLC-P and SCLC-ANP-negative), and correlates with increased CD8+ T-cell density and an immune-hot microenvironment, indicating its potential as a biomarker for immune therapy response
• High DLL3 expression is associated with neuroendocrine subtypes (SCLC-A and SCLC-N), which exhibit reduced immune cell infiltration, suggesting they represent immune-cold tumors suitable for DLL3-targeted T-cell engaging therapies
• Methylomic analysis identifies four methylation clusters that may improve subtype prediction and longitudinal monitoring
• Proteomic analysis reveals upregulation of antigen-presentation-related proteins (e.g., B2M, TAP1, TAP2) and immunoproteasome subunits (e.g., PSMB8, PSMB9) in MHC-I-high expressing samples, indicating a link between MHC-I expression and immune activation

Research Significance and Prospects

This study provides systematic multi-omics data support for molecular subtyping and immunotherapeutic strategies in small-cell lung cancer, emphasizing the value of MHC-I and DLL3 as potential biomarkers and therapeutic targets. Future research may further explore the predictive roles of these biomarkers in combination immunotherapy strategies and develop more accurate therapeutic subtyping systems using spatial omics technologies. Additionally, combination strategies involving DLL3-targeted T-cell engagers and immunotherapies targeting MHC-I-high tumors warrant further investigation to improve therapeutic outcomes.

 

 

Conclusion

In summary, this study comprehensively elucidates the heterogeneity of small-cell lung cancer and its relationship with the immune microenvironment by integrating genomic, transcriptomic, proteomic, and immunohistochemical data. High MHC-I expression correlates with non-neuroendocrine subtypes and an immune-hot microenvironment, whereas high DLL3 expression associates with immune-cold microenvironments and neuroendocrine phenotypes. These findings provide a new dimension for molecular subtyping of small-cell lung cancer and potential biomarkers for personalized immunotherapy. Future studies may focus on the dynamic changes of these biomarkers in treatment response and further optimize therapeutic strategies by incorporating spatial immune analysis, advancing precision medicine in this disease.

 

Mingchao Xie, Miljenka Vuko, Shashank Saran, Lauren A Byers, and Giulia Fabbri. Multi-omic profiling provides insights into the heterogeneity, microenvironmental features, and biomarker landscape of small-cell lung cancer. Molecular Cancer.