Abstract B032: Spatial study of tertiary lymphoid structures in lung adenocarcinoma using 3D lightsheet whole-organ Imaging and machine learning-based quantification
Authors: Jeevanandam Advait , Connolly Kelli , Joshi Nikhil 
Published: November 2024

Abstract
Lung Adenocarcinoma (LUAD) leads in cancer deaths worldwide. Immune Checkpoint blockade (ICB) therapy has improved patient survival of some subtypes (like Kras oncogene-driven; loss of tumor-suppressor p53– “KP”), but not others (Kras oncogene-driven; loss of LKB1– “KL”). Some studies suggest the poorly inflamed KL tumor environment reduces T cell infiltration. However, the impact of other immune mechanisms/cell types on overall ICB-responsiveness remains understudied. Tertiary lymphoid structures (TLSs) are T/B cell aggregates organized by various cell types that form within inflamed non-lymphoid organs. Recent studies have strongly correlated tumor-associated TLSs (TA-TLSs) with positive clinical outcomes and are predictive of patient responders to immunotherapy in many solid tumor types. Thus, understanding the mechanistic factors that sustain mature TA-TLSs will provide more clarity on what molecularly entails an optimal immune response within an ICB-treated patient. To that end, a major advancement has been our knowledge of TA-TLS phenotypic markers driven through developments in multiplex immunofluorescence imaging of 2D tissue sections. However, tissue sectioning destroys the organ architecture, providing limited spatial information over a small field of view. Therefore, non-destructive 3D fluorescent imaging of whole organs, and lightsheet fluorescence microscopy (LSFM) can provide a novel and broader global view of multicellular structures, like TA-TLSs within the whole organ. By using the Blaze ultramicroscope, we imaged whole lung lobes from our novel autochthonous neoantigen-induced lung adenocarcinoma cancer models of KP and KL mice based on our previously published immunogenic KP x NINJA (inversion-induced joined neoantigen) model, which relies on Cre- recombinase activity dependent activation of KrasLox-Stop-Lox (LSL)G12D and deletion of p53fl/fl. Then, doxycycline and tamoxifen administration lead to lung-specific promoter [club cell secretory protein (CCSP)-rtTA] dependent expression of NINJA. We have also developed novel image segmentation methods using machine learning tools in Imaris 10.2 to identify tumors and immune cell clusters, enabling the quantification of the distance and volume of observable tumors and TLSs in the entire organ, which to our knowledge has not been previously attempted. Using this novel imaging and quantification pipeline, we recently discovered that while KP-NINJA lungs produce many TA-TLSs, the KL tumors (compared to KP) lack organized TA-TLSs, and that intriguingly, B-cells are sparsely sequestered near the main bronchus, away from tumors, resembling small bronchi-associated lymphoid structures (BALTs) that typically form in inflamed lungs. We are concurrently doing 2D multiplex cyclic-immunofluorescence imaging to characterize the variety of other cell types present in TLSs of KP-NINJA vs KL-NINJA and more closely understand the molecular cues sustaining TA-TLSs, providing clarity on what entails an “optimal” immune response within an ICB-treated patient.
Citation Format: Advait Jeevanandam, Kelli Connolly, Nikhil Joshi. Spatial study of tertiary lymphoid structures in lung adenocarcinoma using 3D lightsheet whole-organ Imaging and machine learning-based quantification [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B032.