Landscape of Cell States and Multicellular Ecotypes in Non-Small Cell Lung Cancer

Area of Science:

• Oncology
• Genomics
• Bioinformatics

Background:

• Non-small cell lung cancer (NSCLC) is the most common lung cancer type, posing a significant global health challenge.
• Understanding tumor microenvironment (TME) heterogeneity is crucial for predicting NSCLC progression and patient outcomes.

Purpose of the Study:

• To systematically characterize the TME landscape in NSCLC by defining distinct cell states and multicellular ecotypes.
• To validate the identified TME features across diverse transcriptomic datasets and assess their prognostic significance.

Main Methods:

• Utilized the EcoTyper framework to identify 34 transcriptionally defined cell states and 6 multicellular ecotypes within NSCLC.
• Validated findings across 11 bulk transcriptomic cohorts, one single-cell RNA sequencing cohort, and one spatial transcriptomics cohort.
• Performed prognostic analyses and transcriptional regulatory analysis to identify key gene regulators.

Main Results:

• Successfully delineated the NSCLC TME landscape, revealing significant cell states and ecotypes.
• Demonstrated strong reproducibility and robustness of the identified TME features across multiple independent cohorts.
• Identified significant associations between specific cell states/ecotypes and NSCLC patient survival outcomes.
• Highlighted SP8, MAZ, and FOS as potential regulators influencing NSCLC ecotype formation.

Conclusions:

• This study provides a comprehensive atlas of TME-associated cell states and ecotypes in NSCLC.
• The findings offer novel insights into NSCLC tumor heterogeneity.
• Results suggest potential for personalized prognostic assessment and therapeutic interventions based on TME profiling.