PO.BCS01.13 · 生物信息与计算

Subcellular 3D multi-omic models of CDH1-mutant diffuse gastric cancer improve recapitulation of tumor microenvironment structure and reveal precancer signature niches

海报缩略图:Subcellular 3D multi-omic models of CDH1-mutant diffuse gastric cancer improve recapitulation of tumor microenvironment structure and reveal precancer signature niches
编号 6890 展板 3 时间 4/22 09:00–12:00 区域 Section 4 主讲 Jean Clemenceau, BS
分会场 New Algorithms and Computational Methods
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作者与单位

Jean R. Clemenceau1, Yunhe Liu2, Idania Carolina Lubo Julio3, Soyoung Im4, Seock-Jin Chung1, Sam C. Wang5, Paul F. Mansfield6, Luisa Maren Solis Soto3, Linghua Wang2, Tae Hyun Hwang1

1Section of Surgical Research, Vanderbilt University Medical Center, Nashville, TN,2UT MD Anderson Cancer Center, Houston, TX,3Department of Translational Molecular Pathology, UT MD Anderson Cancer Center, Houston, TX,4Department of Pathology, The Catholic University of Korea St. Vincent's Hospital, Suwon, Korea, Republic of,5Department of Surgery, UT Southwestern Medical Center, Dallas, TX,6Department of Surgical Oncology, UT MD Anderson Cancer Center, Houston, TX

摘要 Abstract

Diffuse-type gastric adenocarcinoma (DGC) presents as the more invasive and aggressive gastric cancer subtype with poorer prognosis. Hereditary germline CDH1 mutations are known to drive DGC in 1-3% of cases in what is known as hereditary diffuse gastric cancer (HDGC). Despite the genomic characterization of HDGC, the mechanisms of onset are still poorly understood, given that evidence suggests it can bypass the classic cascade of gastric intestinal metaplasia (IM) to dysplasia to cancer. Additionally, HDGC presents a complex tumor microenvironment (TME) given by its highly infiltrative distribution with increased immune and stromal interactions, as well as IM and dysplastic marker gene expression. These factors present an opportunity to better understand the complex cellular dynamics to elucidate the etiology of this disease. New advances in spatial transcriptomics and fluorescence imaging have reduced per-sample costs of spatial biology assays, allowing the scale necessary for studying serial sections. HDGC samples were collected as formalin-fixed, paraffin embedded blocks. Samples were serially sectioned at 5µm thickness into G4x gel pads. Regions of interest (10mm x 10mm) were isolated from the gels pads and transferred to a G4x X2 spatial flow cell. Samples were processed using Singular Genomics G4x spatial multi-omic assay with a custom pre-gastric cancer panel consisting of 16 proteins, 341 transcripts, and fluorescent-based H&E images for every section of tissue. Data was processed following quality control, implementing cell type annotation, followed by registration of cell coordinates, incorporation of histopathological tissue annotations by a board-certified pathologist, and cell neighborhood analysis. Two models were produced with 7 and 9 serial sections (16 total) representing a tissue depth of 35 µm and 45 µm and populations of 1.6M and 3.4M cells, respectively. The models recapitulate 3D morphology of known tissue structures, such as non-neoplastic epithelial glands, vasculature, and tertiary lymphoid structures. We observed TFF2, a SPEM cell IM marker, expression in the tumor-adjacent gastric mucosa. We also found small clusters of TFF2+ cells within the superficial tumor-invasive area, only present in a few of the total tissue layers. We successfully built two 3D spatial multi-omic, subcellular resolution models for CDH1-mutant HDGC representing 35-45µm of tissue thickness that recapitulate the samples' histological structures. We show the spatial distribution of metaplastic markers expressed in tumor-adjacent epithelium. Our 3D models allowed for the identification of rare-cell events, such as small TFF2+ cell clusters within tumor-infiltrated tissue regions. These results show the promise that high-resolution 3D models present for improving our understanding of complex TMEs, such as HDGC.
利益披露 Disclosure
J. R. Clemenceau, None.. I. Lubo Julio, None.. S. Im, None.. S. Chung, None.. S. C. Wang, None.. P. F. Mansfield, None.. L. M. Solis Soto, None. T. Hwang, Kure.ai Therapeutics Other, Co-founder. Kure.s Other, Co-founder. IQVIA Other, Received consulting fees.

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