Abstract
Tertiary Lymphoid Structures (TLSs) are organized aggregates of immune cells that form in non-lymphoid tissues under chronic inflammation, including cancer. In most cases, TLS presence in tumors correlates with improved clinical outcomes, underscoring their prognostic and predictive value. However, standardizing TLS assessment remains challenging due to their complex cellular composition, multi-lobular structures, and highly variable appearances within tissue sections. Current TLS assessment methods rely largely on manual identification of these structures, which is inefficient for large datasets and introduces significant variability and potential bias. In this pilot study, we therefore applied a novel digital approach to characterize TLSs in whole-slide images of colorectal cancer tissue sections stained with multiplexed immunofluorescence. This approach enabled comprehensive identification of major lymphocyte subsets within TLSs across entire tissue sections and facilitated assessment of their proliferative activity. Compared to traditional methods that require manual counting and phenotyping of individual TLSs, the whole-slide approach proved far simpler and efficiently distinguished patients with strikingly different levels of immune activity within their TLSs. Notably, we observed strong correlations between the proliferation of B-cells within TLSs and that of T-cell subsets. We also present an automated computational pipeline for TLS identification in whole-slide images, providing a fast, unbiased alternative to manual boundary delineation. Overall, our findings demonstrate that whole-section digital quantification of immune cell activity within TLSs offers substantial advantages over traditional methods. This approach has the potential to accelerate immuno-oncology research by enabling robust correlations between TLS states and clinical outcomes. Ultimately, automated TLS analysis could pave the way for standardized clinical tests, maximizing the value of these structures as potential biomarkers and therapeutic targets.
Poster presentation.