The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1.

Lineage plasticity is a recognized hallmark of cancer progression that can shape therapy outcomes. The underlying cellular and molecular mechanisms mediating lineage plasticity remain poorly understood. Here, we describe a versatile in vivo platform to identify and interrogate the molecular determinants of neuroendocrine lineage transformation at different stages of prostate cancer progression. Adenocarcinomas reliably develop following orthotopic transplantation of primary mouse prostate organoids acutely engineered with human-relevant driver alterations (e.g., Rb1-/-; Trp53-/-; cMyc+ or Pten-/-; Trp53-/-; cMyc+), but only those with Rb1 deletion progress to ASCL1+ neuroendocrine prostate cancer (NEPC), a highly aggressive, androgen receptor signaling inhibitor (ARSI)-resistant tumor. Importantly, we show this lineage transition requires a native in vivo microenvironment not replicated by conventional organoid culture. By integrating multiplexed immunofluorescence, spatial transcriptomics and PrismSpot to identify cell type-specific spatial gene modules, we reveal that ASCL1+ cells arise from KRT8+ luminal epithelial cells that progressively acquire transcriptional heterogeneity, producing large ASCL1+;KRT8- NEPC clusters. Ascl1 loss in established NEPC results in transient tumor regression followed by recurrence; however, Ascl1 deletion prior to transplantation completely abrogates lineage plasticity, yielding adenocarcinomas with elevated AR expression and marked sensitivity to castration. The dynamic feature of this model reveals the importance of timing of therapies focused on lineage plasticity and offers a platform for identification of additional lineage plasticity drivers.

Multiresolution nondestructive 3D pathology of whole lymph nodes for breast cancer staging.

SIGNIFICANCE: For breast cancer patients, the extent of regional lymph node (LN) metastasis influences the decision to remove all axillary LNs. Metastases are currently identified and classified with visual analysis of a few thin tissue sections with conventional histology that may underrepresent the extent of metastases. AIM: We sought to enable nondestructive three-dimensional (3D) pathology of human axillary LNs and to develop a practical workflow for LN staging with our method. We also sought to evaluate whether 3D pathology improves staging accuracy in comparison to two-dimensional (2D) histology. APPROACH: We developed a method to fluorescently stain and optically clear LN specimens for comprehensive imaging with multiresolution open-top light-sheet microscopy. We present an efficient imaging and data-processing workflow for rapid evaluation of H&E-like datasets in 3D, with low-resolution screening to identify potential metastases followed by high-resolution localized imaging to confirm malignancy. RESULTS: We simulate LN staging with 3D and 2D pathology datasets from 10 metastatic nodes, showing that 2D pathology consistently underestimates metastasis size, including instances in which 3D pathology would lead to upstaging of the metastasis with important implications on clinical treatment. CONCLUSIONS: Our 3D pathology method may improve clinical management for breast cancer patients by improving staging accuracy of LN metastases.

Fluorescent labeling of abundant reactive entities (FLARE) for cleared-tissue and super-resolution microscopy.

Fluorescence microscopy is a vital tool in biomedical research but faces considerable challenges in achieving uniform or bright labeling. For instance, fluorescent proteins are limited to model organisms, and antibody conjugates can be inconsistent and difficult to use with thick specimens. To partly address these challenges, we developed a labeling protocol that can rapidly visualize many well-contrasted key features and landmarks on biological specimens in both thin and thick tissues or cultured cells. This approach uses established reactive fluorophores to label a variety of biological specimens for cleared-tissue microscopy or expansion super-resolution microscopy and is termed FLARE (fluorescent labeling of abundant reactive entities). These fluorophores target chemical groups and reveal their distribution on the specimens; amine-reactive fluorophores such as hydroxysuccinimidyl esters target accessible amines on proteins, while hydrazide fluorophores target oxidized carbohydrates. The resulting stains provide signals analogous to traditional general histology stains such as H&E or periodic acid-Schiff but use fluorescent probes that are compatible with volumetric imaging. In general, the stains for FLARE are performed in the order of carbohydrates, amine and DNA, and the incubation time for the stains varies from 1 h to 1 d depending on the combination of stains and the type and thickness of the biological specimens. FLARE is powerful, robust and easy to implement in laboratories that already routinely do fluorescence microscopy.

Prostate Cancer Risk Stratification via Nondestructive 3D Pathology with Deep Learning-Assisted Gland Analysis.

Prostate cancer treatment planning is largely dependent upon examination of core-needle biopsies. The microscopic architecture of the prostate glands forms the basis for prognostic grading by pathologists. Interpretation of these convoluted three-dimensional (3D) glandular structures via visual inspection of a limited number of two-dimensional (2D) histology sections is often unreliable, which contributes to the under- and overtreatment of patients. To improve risk assessment and treatment decisions, we have developed a workflow for nondestructive 3D pathology and computational analysis of whole prostate biopsies labeled with a rapid and inexpensive fluorescent analogue of standard hematoxylin and eosin (H&E) staining. This analysis is based on interpretable glandular features and is facilitated by the development of image translation-assisted segmentation in 3D (ITAS3D). ITAS3D is a generalizable deep learning-based strategy that enables tissue microstructures to be volumetrically segmented in an annotation-free and objective (biomarker-based) manner without requiring immunolabeling. As a preliminary demonstration of the translational value of a computational 3D versus a computational 2D pathology approach, we imaged 300 ex vivo biopsies extracted from 50 archived radical prostatectomy specimens, of which, 118 biopsies contained cancer. The 3D glandular features in cancer biopsies were superior to corresponding 2D features for risk stratification of patients with low- to intermediate-risk prostate cancer based on their clinical biochemical recurrence outcomes. The results of this study support the use of computational 3D pathology for guiding the clinical management of prostate cancer. SIGNIFICANCE: An end-to-end pipeline for deep learning-assisted computational 3D histology analysis of whole prostate biopsies shows that nondestructive 3D pathology has the potential to enable superior prognostic stratification of patients with prostate cancer.

Feature-rich covalent stains for super-resolution and cleared tissue fluorescence microscopy.

Fluorescence microscopy is a workhorse tool in biomedical imaging but often poses substantial challenges to practitioners in achieving bright or uniform labeling. In addition, while antibodies are effective specific labels, their reproducibility is often inconsistent, and they are difficult to use when staining thick specimens. We report the use of conventional, commercially available fluorescent dyes for rapid and intense covalent labeling of proteins and carbohydrates in super-resolution (expansion) microscopy and cleared tissue microscopy. This approach, which we refer to as Fluorescent Labeling of Abundant Reactive Entities (FLARE), produces simple and robust stains that are modern equivalents of classic small-molecule histology stains. It efficiently reveals a wealth of key landmarks in cells and tissues under different fixation or sample processing conditions and is compatible with immunolabeling of proteins and in situ hybridization labeling of nucleic acids.

Multi-immersion open-top light-sheet microscope for high-throughput imaging of cleared tissues.

Recent advances in optical clearing and light-sheet microscopy have provided unprecedented access to structural and molecular information from intact tissues. However, current light-sheet microscopes have imposed constraints on the size, shape, number of specimens, and compatibility with various clearing protocols. Here we present a multi-immersion open-top light-sheet microscope that enables simple mounting of multiple specimens processed with a variety of clearing protocols, which will facilitate wide adoption by preclinical researchers and clinical laboratories. In particular, the open-top geometry provides unsurpassed versatility to interface with a wide range of accessory technologies in the future.

Rapid pathology of lumpectomy margins with open-top light-sheet (OTLS) microscopy.

Open-top light-sheet microscopy is a technique that can potentially enable rapid ex vivo inspection of large tissue surfaces and volumes. Here, we have optimized an open-top light-sheet (OTLS) microscope and image-processing workflow for the comprehensive examination of surgical margin surfaces, and have also developed a novel fluorescent analog of H&E staining that is robust for staining fresh unfixed tissues. Our tissue-staining method can be achieved within 2.5 minutes followed by OTLS microscopy of lumpectomy surfaces at a rate of up to 1.5 cm2/minute. An image atlas is presented to show that OTLS image quality surpasses that of intraoperative frozen sectioning and can approximate that of gold-standard H&E histology of formalin-fixed paraffin-embedded (FFPE) tissues. Qualitative evidence indicates that these intraoperative methods do not interfere with downstream post-operative H&E histology and immunohistochemistry. These results should facilitate the translation of OTLS microscopy for intraoperative guidance of lumpectomy and other surgical oncology procedures.

Volumetric, Nanoscale Optical Imaging of Mouse and Human Kidney via Expansion Microscopy.

Although light microscopy is a powerful tool for the assessment of kidney physiology and pathology, it has traditionally been unable to resolve structures separated by less than the ~250 nm diffraction limit of visible light. Here, we report on the optimization, validation, and application of a recently developed super-resolution fluorescence microscopy method, called expansion microscopy (ExM), for volumetric interrogation of mouse and human kidney tissue with 70-75 nm lateral and ~250 nm axial spatial resolution. Using ExM with a standard confocal microscope, we resolve fine details of structures that have traditionally required visualization by electron microscopy, including podocyte foot processes, the glomerular basement membrane, and the cytoskeleton. This inexpensive and accessible approach to volumetric, nanoscale imaging enables visualization of fine structural details of kidney tissues that were previously difficult or impossible to measure by conventional methodologies.