Abstract
Background: Response to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer is highly variable, and predictive biomarkers are lacking. While immune infiltration influences treatment response, the spatial organisation and functional state of immune cells within the tumour microenvironment remain poorly understood.
Methods: re-treatment rectal cancer biopsies from patients treated with nCRT (n = 20; 12 complete responders, 4 intermediate responders, 4 non-responders) were analysed using NanoString GeoMx digital spatial proteomics. Regions of interest (ROIs) were selected based on immune architecture, including tertiary lymphoid structures (TLSs) and tumour regions without TLSs, and segmented into CD19⁺, CD3⁺, PanCK⁺, and full ROIs. Protein expression across immune, checkpoint, cell death, and innate immune pathways was quantified. Unsupervised clustering and differential expression analyses used linear mixed-effects models accounting for repeated measures.
Results: Spatial proteomic profiling revealed distinct immune patterns associated with response to nCRT. Complete responders formed discrete clusters across multiple ROI types and exhibited reduced expression of immune checkpoint proteins (PD-1, PD-L1, CTLA-4) alongside increased expression of cell death-associated proteins, including cleaved caspase-9. TLSs were more frequently observed in complete responders and displayed response-associated protein signatures. In tumour regions lacking TLSs, complete responders showed reduced ARG1, CTLA-4, and CD68 expression, with increased STING expression, consistent with a less immunosuppressive and more innate immune-activated tumour microenvironment.
Conclusions: Distinct spatial immune architectures characterise response to nCRT in rectal cancer. Complete response is associated with reduced immune suppression, enhanced apoptotic signalling, and spatially organised immune features, including TLSs and STING activation in non-TLS tumour regions. These findings support spatial proteomic biomarkers as tools for predicting treatment response and guiding precision therapy in rectal cancer.