Spatial transcriptomic analysis across histological subtypes reveals molecular heterogeneity and prognostic markers in early-stage lung adenocarcinoma.

BACKGROUND: The progression and prognosis of early-stage lung adenocarcinoma are closely associated with histologic subtypes, yet the presence of mixed histologic patterns often complicates prognostic assessment. Currently, the correlation between molecular and histologic features remains poorly understood. METHODS: Formalin-fixed paraffin-embedded (FFPE) samples were collected from patients with primary early-stage lung adenocarcinoma, encompassing three histologic subtypes: well-differentiated, moderately differentiated, and poorly differentiated. The GeoMx Digital Spatial Profiler platform was utilized to obtain spatial transcriptomic profiling. Regions of interest were carefully selected and further subdivided into three categories of areas of interest, specifically epithelial cell-enriched regions, macrophage-enriched regions, and other regions. Multiplex immunofluorescence (mIF) assays were employed to validate the obtained results. RESULTS: Distinct molecular characteristics were identified in tumor epithelial- and macrophage-enriched compartments spanning well-differentiated to poorly differentiated tumors. In poorly differentiated tumors, we observed enrichment of pathways related to humoral immune response, complement activation regulation, and extracellular matrix receptor interaction pathways, all of which are significantly associated with poorer prognosis. We integrated these pathways to develop a composite molecular signature that strongly correlate with adverse prognosis. CONCLUSIONS: Our results provide new insights into the link between molecular and histologic subtypes in mixed-type lung adenocarcinomas. Specifically, the identified molecular signatures offer potential biomarkers for predicting disease progression and prognosis, thus facilitating more precise and personalized therapeutic approaches. KEY POINTS: Poorly differentiated components in mixed-type early-stage lung adenocarcinoma (LUAD) are characterized by enrichment of humoral immune response, complementactivation regulation, and extracellular matrix receptor interaction pathways, which areassociated with worse prognosis. A composite molecular signature integrating the keypathways strongly correlates with adverse clinical outcomes, serving as apotential prognostic biomarker. Digital spatial transcriptomics reveals spatially resolvedmolecular heterogeneity in tumor epithelial- and macrophage-enrichedcompartments, bridging the gap between histologic subtypes and molecularmechanisms in LUAD.