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Yapp, C.

Publications and source records attributed to Yapp, C..

27 records · Page 2Linked to original sources

The spatial landscape of progression and immunoediting in primary melanoma at single cell resolution

Cutaneous melanoma is a highly immunogenic malignancy, surgically curable at early stages, but life- threatening when metastatic. Here we integrate high-plex imaging, 3D high-resolution microscopy, and spatially-resolved micro-region transcriptomics to study immune evasion and immunoediting in primary melanoma. We find that recurrent cellular neighborhoods involving tumor, immune, and stromal cells change significantly along a progression axis involving precursor states, melanoma in situ, and invasive tumor. Hallmarks of immunosuppression are already detectable in precursor regions. When tumors become locally invasive, a consolidated and spatially restricted suppressive environment forms along the tumor-stromal boundary. This environment is established by cytokine gradients that promote expression of MHC-II and IDO1, and by PD1-PDL1 mediated cell contacts involving macrophages, dendritic cells, and T cells. A few millimeters away, cytotoxic T cells synapse with melanoma cells in fields of tumor regression. Thus, invasion and immunoediting can co-exist within a few millimeters of each other in a single specimen. STATEMENT OF SIGNIFICANCEThe reorganization of the tumor ecosystem in primary melanoma is an excellent setting in which to study immunoediting and immune evasion. Guided by classical histopathology, spatial profiling of proteins and mRNA reveals recurrent morphological and molecular features of tumor evolution that involve localized paracrine cytokine signaling and direct cell-cell contact.

cancer biology↗

UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues

Newly developed technologies have made it feasible to routinely collect highly multiplexed (20-60 channel) images at subcellular resolution from human tissues for research and diagnostic purposes. Extracting single cell data from such images requires efficient and accurate image segmentation, a challenging problem that has recently benefited from the use of deep learning. In this paper, we demonstrate two approaches to improving tissue segmentation that are applicable to multiple deep learning frameworks. The first uses "real augmentations" that comprise defocused and saturated image data collected on the same instruments as the actual data; using real augmentation improves model accuracy to a significantly greater degree than computational augmentation (Gaussian blurring). The second involves imaging the nuclear envelope to better identify nuclear outlines. The two approaches cumulatively and substantially improve segmentation on a wide range of tissue types and provide a set of improved segmentation models. We speculate that the use of real augmentations may have applications in image processing outside of microscopy.

bioinformatics↗

Multiplexed 3D atlas of state transitions and immune interactions in colorectal cancer

Advanced solid cancers are complex assemblies of tumor, immune, and stromal cells characterized by high intratumoral variation. We use highly multiplexed tissue imaging, 3D reconstruction, spatial statistics, and machine learning to identify cell types and states underlying morphological features of known diagnostic and prognostic significance in colorectal cancer. Quantitation of these features in high-plex marker space reveals recurrent transitions from one tumor morphology to the next, some of which are coincident with long-range gradients in the expression of oncogenes and epigenetic regulators. At the tumor invasive margin, where tumor, normal, and immune cells compete, T-cell suppression involves multiple cell types and 3D imaging shows that seemingly localized 2D features such as tertiary lymphoid structures are commonly interconnected and have graded molecular properties. Thus, while cancer genetics emphasizes the importance of discrete changes in tumor state, whole-specimen imaging reveals large-scale morphological and molecular gradients analogous to those in developing tissues.

cancer biology↗

MCMICRO: A scalable, modular image-processing pipeline for multiplexed tissue imaging

Highly multiplexed tissue imaging makes molecular analysis of single cells possible in a preserved spatial context. However, reproducible analysis of the underlying data poses a substantial computational challenge. Here we describe a modular and open-source computational pipeline (MCMICRO) for performing the sequential steps needed to transform large, multi-channel whole slide images into single-cell data. We demonstrate use of MCMICRO on images of different tissues and tumors acquired using multiple imaging platforms, thereby providing a solid foundation for the continued development of tissue imaging software.

bioinformatics↗

Age-dependent regulation of SARS-CoV-2 cell entry genes and cell death programs correlates with COVID-19 disease severity

Angiotensin-converting enzyme 2 (ACE2) maintains cardiovascular and renal homeostasis but also serves as the entry receptor for the novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), the causal agent of novel coronavirus disease 2019 (COVID-19)1. COVID-19 disease severity, while highly variable, is typically lower in pediatric patients than adults (particularly the elderly), but increased rates of hospitalizations requiring intensive care are observed in infants than in older children. The reasons for these differences are unknown. To detect potential age-based correlates of disease severity, we measured ACE2 protein expression at the single cell level in human lung tissue specimens from over 100 donors from [~]4 months to 75 years of age. We found that expression of ACE2 in distal lung epithelial cells generally increases with advancing age but exhibits extreme intra- and inter-individual heterogeneity. Notably, we also detected ACE2 expression on neonatal airway epithelial cells and within the lung parenchyma. Similar patterns were found at the transcript level: ACE2 mRNA is expressed in the lung and trachea shortly after birth, downregulated during childhood, and again expressed at high levels in late adulthood in alveolar epithelial cells. Furthermore, we find that apoptosis, which is a natural host defense system against viral infection, is also dynamically regulated during lung maturation, resulting in periods of heightened apoptotic priming and dependence on pro-survival BCL-2 family proteins including MCL-1. Infection of human lung cells with SARS-CoV-2 triggers an unfolded protein stress response and upregulation of the endogenous MCL-1 inhibitor Noxa; in juveniles, MCL-1 inhibition is sufficient to trigger apoptosis in lung epithelial cells - this may limit virion production and inflammatory signaling. Overall, we identify strong and distinct correlates of COVID-19 disease severity across lifespan and advance our understanding of the regulation of ACE2 and cell death programs in the mammalian lung. Furthermore, our work provides the framework for potential translation of apoptosis modulating drugs as novel treatments for COVID-19.

cell biology↗

Highly multiplexed immunofluorescence images and single-cell data of immune markers in tonsil and lung cancer

In this data descriptor, we document a dataset of multiplexed immunofluorescence images and derived single-cell measurements of immune lineage and other markers in formaldehyde-fixed and paraffin-embedded (FFPE) human tonsil and lung cancer tissue. We used tissue cyclic immunofluorescence (t-CyCIF) to generate fluorescence images which we artifact corrected using the BaSiC tool, stitched and registered using the ASHLAR algorithm, and segmented using ilastik software and MATLAB. We extracted single-cell features from these images using HistoCAT software. The resulting dataset can be visualized using image browsers and analyzed using high-dimensional, single-cell methods. This dataset is a valuable resource for biological discovery of the immune system in normal and diseased states as well as for the development of multiplexed image analysis and viewing tools.\n\nMETADATA SUMMARY\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@6edf3eorg.highwire.dtl.DTLVardef@1026e07org.highwire.dtl.DTLVardef@85a7baorg.highwire.dtl.DTLVardef@c6d7e5org.highwire.dtl.DTLVardef@87fccf_HPS_FORMAT_FIGEXP M_TBL C_TBL

cancer biology↗

Combined inhibition of mTOR and PIKKs exploits replicative and checkpoint vulnerabilities to induce death of PI3K-activated triple-negative breast cancer cells

SUMMARY SUMMARY HIGHLIGHTS INTRODUCTION RESULTS DISCUSSION FUNDING AUTHOR CONTRIBUTIONS STAR METHODS Cell lines METHOD DETAILS Western blotting Evaluation of drug sensitivity Immunofluorescence microscopy Primary antibodies and dilutions Single-stranded DNA ssDNA and... Live cell microscopy Extraction of polar metabolites Metabolomics profiling by... Isobolograms and analysis of... Cell cycle model and... QUANTIFICATION AND STATISTICAL... Viable cell counts ...

cancer biology↗

Highly multiplexed in situ protein imaging with signal amplification by Immuno-SABER

Probing the molecular organization of tissues requires in situ analysis by microscopy. However current limitations in multiplexing, sensitivity, and throughput collectively constitute a major barrier for comprehensive single-cell profiling of proteins. Here, we report Immunostaining with Signal Amplification By Exchange Reaction (Immuno-SABER), a rapid, highly multiplexed signal amplification method that simultaneously tackles these key challenges. Immuno-SABER utilizes DNA-barcoded antibodies and provides a method for highly multiplexed signal amplification via modular orthogonal DNA concatemers generated by Primer Exchange Reaction. This approach offers the capability to preprogram and control the amplification level independently for multiple targets without in situ enzymatic reactions, and the intrinsic scalability to rapidly amplify and image a large number of protein targets. We validated our approach in diverse sample types including cultured cells, cryosections, FFPE sections, and whole mount tissues. We demonstrated independently tunable 5-180-fold amplification for multiple targets, covering the full signal range conventionally achieved by secondary antibodies to tyramide signal amplification, as well as simultaneous signal amplification for 10 different proteins using standard equipment and workflow. We further combined Immuno-SABER with Expansion Microscopy to enable rapid and highly multiplexed super-resolution tissue imaging. Overall, Immuno-SABER presents an effective and accessible platform for rapid, multiplexed imaging of proteins across scales with high sensitivity.

cell biology↗

Super-resolution microscopy of the β-carboxysome reveals a homogenous matrix

Carbon fixation in cyanobacteria makes a major contribution to the global carbon cycle. The cyanobacterial carboxysome is a proteinaceous microcompartment that protects and concentrates the carbon-fixing enzyme RuBisCO in a paracrystalline lattice, making it possible for these organisms to fix CO2 from the atmosphere. The protein responsible for the organization of this lattice in beta-type carboxysomes of the freshwater cyanobacterium Synechococcus elongatus, CcmM, occurs in two isoforms thought to localize differentially within the carboxysome matrix. Here we use widefield timelapse and 3D-structured illumination microscopy (3D-SIM) to study the recruitment and localization of these two isoforms. We demonstrate that this super-resolution technique is capable of successfully resolving the outer protein shell of the carboxysome from its internal cargo. We develop an automated analysis pipeline to analyze and quantify 3D-SIM images and generate a population level description of carboxysome shell protein, RuBisCO, and CcmM isoform localization. We find that both CcmM isoforms colocalize in space and time, prompting a revised model of the internal arrangement of the beta carboxysome.

cell biology↗