High‐Resolution 3D Printing of Pancreatic Ductal Microanatomy Enabled by Serial Histology

Kiemen, Ashley L.; Forjaz, André; Sousa, Ricardo; Han, Kyu Sang; Hruban, Ralph H.; Wood, Laura D.; Wu, PeiHsun; Wirtz, Denis

doi:10.1002/admt.202301837

Cited by 3 publications

(1 citation statement)

References 21 publications

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“…CODA is a workflow for quantitative 3D mapping of tissues using serially sectioned, hematoxylin and eosin (H&E) stained and digitized microscope slides that has been used extensively to study the 3D microanatomy, transcriptomic signatures, and 3D genetic heterogeneity of PanINs at single-cell resolution. 11,18,[24][25][26][27][28][29] As with existing serial sectioning workflows [30][31][32][33][34][35][36][37] , CODA is compatible with integration of multiple histological stains for study of structures that are difficult to detect using H&E alone. [36][37][38][39] Here, through extension of CODA to analyze immunohistochemically (IHC) stained serial histological images, we explore at cellular resolution the spatial landscape of immune infiltration in large 3D pancreas tissues containing PanINs.…”

Section: Introductionmentioning

confidence: 99%

3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure

Kiemen,

Almagro-Pérez,

Matos

et al. 2024

Preprint

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SUMMARYPancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer for which few effective therapies exist. Immunotherapies specifically are ineffective in pancreatic cancer, in part due to its unique stromal and immune microenvironment. Pancreatic intraepithelial neoplasia, or PanIN, is the main precursor lesion to PDAC. Recently it was discovered that PanINs are remarkably abundant in the grossly normal pancreas, suggesting that the vast majority will never progress to cancer. Here, through construction of 48 samples of cm3-sized human pancreas tissue, we profiled the immune microenvironment of 1,476 PanINs in 3D and at single-cell resolution to better understand the early evolution of the pancreatic tumor microenvironment and to determine how inflammation may play a role in cancer progression.We found that bulk pancreatic inflammation strongly correlates to PanIN cell fraction. We found that the immune response around PanINs is highly heterogeneous, with distinct immune hotspots and cold spots that appear and disappear in a span of tens of microns. Immune hotspots generally mark locations of higher grade of dysplasia or locations near acinar atrophy. The immune composition at these hotspots is dominated by naïve, cytotoxic, and regulatory T cells, cancer associated fibroblasts, and tumor associated macrophages, with little similarity to the immune composition around less-inflamed PanINs. By mapping FOXP3+ cells in 3D, we found that regulatory T cells are present at higher density in larger PanIN lesions compared to smaller PanINs, suggesting that the early initiation of PanINs may not exhibit an immunosuppressive response.This analysis demonstrates that while PanINs are common in the pancreases of most individuals, inflammation may play a pivotal role, both at the bulk and the microscopic scale, in demarcating regions of significance in cancer progression.

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Section: Introductionmentioning

confidence: 99%

3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure

Kiemen,

Almagro-Pérez,

Matos

et al. 2024

Preprint

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PanIN or IPMN? Redefining Lesion Size in 3 Dimensions

Kiemen,

Dequiedt,

Shen

et al. 2024

American Journal of Surgical Pathology

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Pancreatic ductal adenocarcinoma (PDAC) develops from 2 known precursor lesions: a majority (∼85%) develops from pancreatic intraepithelial neoplasia (PanIN), and a minority develops from intraductal papillary mucinous neoplasms (IPMNs). Clinical classification of PanIN and IPMN relies on a combination of low-resolution, 3-dimensional (D) imaging (computed tomography, CT), and high-resolution, 2D imaging (histology). The definitions of PanIN and IPMN currently rely heavily on size. IPMNs are defined as macroscopic: generally >1.0 cm and visible in CT, and PanINs are defined as microscopic: generally <0.5 cm and not identifiable in CT. As 2D evaluation fails to take into account 3D structures, we hypothesized that this classification would fail in evaluation of high-resolution, 3D images. To characterize the size and prevalence of PanINs in 3D, 47 thick slabs of pancreas were harvested from grossly normal areas of pancreatic resections, excluding samples from individuals with a diagnosis of an IPMN. All patients but one underwent preoperative CT scans. Through construction of cellular resolution 3D maps, we identified >1400 ductal precursor lesions that met the 2D histologic size criteria of PanINs. We show that, when 3D space is considered, 25 of these lesions can be digitally sectioned to meet the 2D histologic size criterion of IPMN. Re-evaluation of the preoperative CT images of individuals found to possess these large precursor lesions showed that nearly half are visible on imaging. These findings demonstrate that the clinical classification of PanIN and IPMN fails in evaluation of high-resolution, 3D images, emphasizing the need for re-evaluation of classification guidelines that place significant weight on 2D assessment of 3D structures.

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qMAP enabled microanatomical mapping of human skin aging

Han,

Sander,

Kumer

et al. 2024

Preprint

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Skin is the most visible indicator of aging, in part because it is the largest organ exposed to the outer environment. It is well recognized that age-related cumulative damage to our skin tissue degrades its structural integrity, yet how age affects the skin at the micro-anatomical and cellular scales is poorly understood. Here, we develop an Automated detection of Skin Cellular features and Microanatomy (AutoSCM) to characterize the microanatomical tissue and cellular features that change in the skin with age. We automatically label twelve distinct skin tissue components and nuclei contours on whole slide images from skin histological sections stained by hematoxylin and eosin (H&E). Then, we extract 914 objective structural features, from which we determine 108 are significantly affected by age and 806 are not. In addition to identifying decreases in epidermal and dermal thickness and hair follicle appendage density with age, we identify four previously unknown biomarkers of human aging in skin including: increased interstitial space, reduced sebaceous gland size, hair loss in back skin, and progressive horizontal alignment of the extracellular matrix and stromal cells. We further find major sex-based differences in aging skin, including increased stromal cell density by 28%, fibroblast density by 24%, epidermal thickness by 15%, and decreased epidermal cell density by 21%, sweat gland size by 23%, and 28% less content of arrector pili muscles in female compared to male. This rigorously curated and segmented atlas of normal skin microarchitecture constitutes important reference maps for future studies in age-associated diseases of the skin.

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High‐Resolution 3D Printing of Pancreatic Ductal Microanatomy Enabled by Serial Histology

Cited by 3 publications

References 21 publications

3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure

3D histology reveals that immune response to pancreatic precancers is heterogeneous and depends on global pancreas structure

PanIN or IPMN? Redefining Lesion Size in 3 Dimensions

qMAP enabled microanatomical mapping of human skin aging

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