Abstract 2680: Volumetric analysis of spatial tumor phylogeny enabled by 3D pathology-guided macrodissection (3DPM)

Abstract Current methods for studying tumor phylogeny primarily rely on manual macrodissection or laser capture microdissection of tumor regions identified in thin 2D histology sections. With the emergence of non-destructive 3D pathology workflows, the study of 3D spatial tumor phylogeny is proposed, whereby distinct tumor regions may be macrodissected based on 3D pathology datasets for downstream DNA sequencing and clonal reconstruction. The tumor phylogenetic tree can then be mapped into 3D space using the spatial locations of different subclones, providing an improved understanding of the spatial spread of tumors along their evolutionary paths. To implement the concept of 3D spatial tumor phylogeny, we are developing a 3D pathology-guided macrodissection (3DPM) system as an alternative to current techniques that are limited to thin 2D tissue sections. In our workflow, tissues stained with H&E-analog fluorescence dyes are first imaged using an open-top light sheet (OTLS) microscope. Based on 3D pathology datasets digitally false colored to mimic the appearance of H&E staining, regions of interest with distinct tumor morphologies are annotated by pathologists. The tissue specimen along with the digital annotations are then transferred to a co-registered 3D macrodissection system, which is based on a portable desktop five-axis CNC milling machine. For each volume of interest, the unwanted background tissue is first milled away from the top, followed by detachment of the volume through angled cuts. The toolpath is optimized to maximize the purity and volume of the dissected tissue. Large FFPE tissue slices from archived prostatectomies (centimeter-scale lateral dimensions and millimeter-scale axial dimensions) are being used for proof-of-concept demonstrations. First, we aim to show that the 3D macrodissection method can achieve high tumor purity comparable to laser capture microdissection, despite the increased challenge of dissecting 3D contours vs. 2D tissue regions. Second, we anticipate that more distinct subclones can be identified in each tumor region due to improved sampling of volumetric tissue regions with distinct morphologies (e.g. different Gleason patterns and sub-variants) in comparison to 2D thin-section dissection methods. Finally, given that prostate cancer is known to be multifocal and exhibits complex clonal expansion within the primary tumor, we aim to elucidate whether these multiclonal expansions are spatially separated, intermixed, or vary between cases using reconstructed 3D spatial phylogenetic trees. In summary, 3DPM aims to deepen our understanding of prostate cancer evolution and to enable many new directions in tumor phylogenetics research. Citation Format: Huai-Ching Hsieh, Qinghua Han, Gan Gao, David Brenes, Elena Baraznenok, Robert Serafin, Kevin W. Bishop, Eric Q. Konnick, Colin Pritchard, Sandy Figiel, Freddie C. Hamdy, Ian G. Mills, Lawrence D. True, Michael C. Haffner, Srinivasa R. Rao, Dan J. Woodcock, Jonathan T.C. Liu. Volumetric analysis of spatial tumor phylogeny enabled by 3D pathology-guided macrodissection (3DPM) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2680.