Vaccination generates functional progenitor tumor-specific CD8 T cells and long-term tumor control.

BACKGROUND: Immune checkpoint blockade (ICB) therapies are an important treatment for patients with advanced cancers; however, only a subset of patients with certain types of cancer achieve durable remission. Cancer vaccines are an attractive strategy to boost patient immune responses, but less is known about whether and how immunization can induce long-term tumor immune reprogramming and arrest cancer progression. We developed a clinically relevant genetic cancer mouse model in which hepatocytes sporadically undergo oncogenic transformation. We compared how tumor-specific CD8 T cells (TST) differentiated in mice with early sporadic lesions as compared with late lesions and tested how immunotherapeutic strategies, including vaccination and ICB, impact TST function and liver cancer progression. METHODS: Mice with a germline floxed allele of the SV40 large T antigen (TAG) undergo spontaneous recombination and activation of the TAG oncogene, leading to rare early cancerous TAG-expressing lesions that inevitably progress to established liver cancer. We assessed the immunophenotype (CD44, PD1, TCF1, and TOX expression) and function (TNFα and IFNγ cytokine production) of tumor/TAG-specific CD8 T cells in mice with early and late liver lesions by flow cytometry. We vaccinated mice, either alone or in combination with ICB, to test whether these immunotherapeutic interventions could stop liver cancer progression and improve survival. RESULTS: In mice with early lesions, a subset of TST were PD1+ TCF1+ TOX- and could produce IFNγ while TST present in mice with late liver cancers were PD1+ TCF1lo/- TOX+ and unable to make effector cytokines. Strikingly, vaccination with attenuated TAG epitope-expressing Listeria monocytogenes (LMTAG) blocked liver cancer development and led to a population of TST that were PD1-heterogeneous, TCF1+ TOX- and polyfunctional cytokine producers. Vaccine-elicited TCF1+TST could self-renew and differentiate, establishing them as progenitor TST. In contrast, ICB administration did not slow cancer progression or improve LMTAG vaccine efficacy. CONCLUSION: Vaccination, but not ICB, generated a population of functional progenitor TST and halted cancer progression in a clinically relevant model of sporadic liver cancer. In patients with early cancers or at high risk of cancer recurrence, immunization may be the most effective strategy.

Alterations in cellular metabolic pathway and epithelial cell maturation induced by MYO5B defects are partially reversible by LPAR5 activation.

Functional loss of the motor protein, Myosin Vb (MYO5B), induces various defects in intestinal epithelial function and causes a congenital diarrheal disorder, microvillus inclusion disease (MVID). Utilizing the MVID model mice, Vil1-CreERT2;Myo5bflox/flox (MYO5B∆IEC) and Vil1-CreERT2;Myo5bflox/G519R (MYO5B(G519R)), we previously reported that functional MYO5B loss disrupts progenitor cell differentiation and enterocyte maturation that result in villus blunting and deadly malabsorption symptoms. In this study, we determined that both absence and a point mutation of MYO5B impair lipid metabolism and alter mitochondrial structure, which may underlie the progenitor cell malfunction observed in MVID intestine. Along with a decrease in fatty acid oxidation, the lipogenesis pathway was enhanced in the MYO5B∆IEC small intestine. Consistent with these observations in vivo, RNA-sequencing of enteroids generated from the two MVID mouse strains showed similar downregulation of energy metabolic enzymes, including mitochondrial oxidative phosphorylation genes. In our previous studies, lysophosphatidic acid (LPA) signaling ameliorates epithelial cell defects in MYO5B∆IEC tissues and enteroids. The present study demonstrated that the highly soluble LPAR5-preferred agonist, Compound-1, improved sodium transporter localization and absorptive function, and tuft cell differentiation in patient-modeled MVID animals that carry independent mutations in MYO5B. Body weight loss in male MYO5B(G519R) mice was ameliorated by Compound-1. These observations suggest that Compound-1 treatment has a trophic effect on intestine with MYO5B functional loss through epithelial cell-autonomous pathways that can accelerate the differentiation of progenitor cells and the maturation of enterocytes. Targeting LPAR5 may represent an effective therapeutic approach for treatment of MVID symptoms induced by different point mutations in MYO5B.

Disruption of mitochondrial electron transport impairs urinary concentration via AMPK-dependent suppression of aquaporin-2.

Urinary concentration is an energy-dependent process that minimizes body water loss by increasing aquaporin-2 (AQP2) expression in collecting duct (CD) principal cells. To investigate the role of mitochondrial (mt) ATP production in renal water clearance, we disrupted mt electron transport in CD cells by targeting ubiquinone (Q) binding protein QPC (UQCRQ), a subunit of mt complex III essential for oxidative phosphorylation. QPC-deficient mice produced less concentrated urine than controls, both at baseline and after type 2 vasopressin receptor stimulation with desmopressin. Impaired urinary concentration in QPC-deficient mice was associated with reduced total AQP2 protein levels in CD tubules, while AQP2 phosphorylation and membrane trafficking remained unaffected. In cultured inner medullary CD cells treated with mt complex III inhibitor antimycin A, the reduction in AQP2 abundance was associated with activation of 5' adenosine monophosphate-activated protein kinase (AMPK) and was reversed by treatment with AMPK inhibitor SBI-0206965. In summary, our studies demonstrated that the physiological regulation of AQP2 abundance in principal CD cells was dependent on mt electron transport. Furthermore, our data suggested that oxidative phosphorylation in CD cells was dispensable for maintaining water homeostasis under baseline conditions, but necessary for maximal stimulation of AQP2 expression and urinary concentration.

Acute tuft cell ablation induces malabsorption and alterations in secretory and immune cell lineages in small intestine.

Background & Aims: Intestinal tuft cells have recently been the interest of studies in several human gastrointestinal diseases. However, the impact of tuft cell deletion on intestinal physiological functions are not fully understood. This study investigated the effects of acute tuft cell loss on nutrient absorption and cell lineage differentiation. Methods: Tuft cell deletion was induced in DCLK1-IRES-GFP-CreERT2/+;Rosa-DTA (DCLK1-DTA) mice by a single tamoxifen injection concomitant with littermate controls. Intestinal tissues were analyzed two-, four-, or seven-days post tamoxifen injection. Results: DCLK1-DTA mice showed significantly shortened small intestinal length and body weight loss on day 4. Impaired activities of Na + -dependent glucose transporter 1 (SGLT1) and cystic fibrosis transmembrane regulator (CFTR) were observed in Ussing chamber experiments. Tissue immunostaining revealed a transient deletion of intestinal and biliary tuft cells, which was maximal on day 4 and recovered by day 7. On day 4 post tamoxifen, cholecystokinin (CCK)+ enteroendocrine cell numbers were increased particularly in the ileum. Correlated with the tuft cell reduction, the frequency of mislocalized Paneth cells, which were co-labeled by Paneth and goblet cell markers, was increased in the villus regions. In the lamina propria, fewer mast cells and leukocytes were found in the day 4 DCLK1-DTA mice than in controls. Conclusion: Ablation of intestinal tuft cells may induce nutrient malabsorption through alterations in epithelial cell proliferation and differentiation along with changes in mucosal defense response. These observations elucidate a new role for tuft cells in regulating intestinal absorption and mucosal regeneration.

Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based Signatures.

Crohn's disease (CD) is a chronic and relapsing inflammatory condition that affects segments of the gastrointestinal tract. CD activity is determined by histological findings, particularly the density of neutrophils observed on Hematoxylin and Eosin stains (H&E) imaging. However, understanding the broader morphometry and local cell arrangement beyond cell counting and tissue morphology remains challenging. To address this, we characterize six distinct cell types from H&E images and develop a novel approach for the local spatial signature of each cell. Specifically, we create a 10-cell neighborhood matrix, representing neighboring cell arrangements for each individual cell. Utilizing t-SNE for non-linear spatial projection in scatter-plot and Kernel Density Estimation contour-plot formats, our study examines patterns of differences in the cellular environment associated with the odds ratio of spatial patterns between active CD and control groups. This analysis is based on data collected at the two research institutes. The findings reveal heterogeneous nearest-neighbor patterns, signifying distinct tendencies of cell clustering, with a particular focus on the rectum region. These variations underscore the impact of data heterogeneity on cell spatial arrangements in CD patients. Moreover, the spatial distribution disparities between the two research sites highlight the significance of collaborative efforts among healthcare organizations. All research analysis pipeline tools are available at https://github.com/MASILab/cellNN.

Nucleus subtype classification using inter-modality learning.

Understanding the way cells communicate, co-locate, and interrelate is essential to understanding human physiology. Hematoxylin and eosin (H&E) staining is ubiquitously available both for clinical studies and research. The Colon Nucleus Identification and Classification (CoNIC) Challenge has recently innovated on robust artificial intelligence labeling of six cell types on H&E stains of the colon. However, this is a very small fraction of the number of potential cell classification types. Specifically, the CoNIC Challenge is unable to classify epithelial subtypes (progenitor, endocrine, goblet), lymphocyte subtypes (B, helper T, cytotoxic T), or connective subtypes (fibroblasts, stromal). In this paper, we propose to use inter-modality learning to label previously un-labelable cell types on virtual H&E. We leveraged multiplexed immunofluorescence (MxIF) histology imaging to identify 14 subclasses of cell types. We performed style transfer to synthesize virtual H&E from MxIF and transferred the higher density labels from MxIF to these virtual H&E images. We then evaluated the efficacy of learning in this approach. We identified helper T and progenitor nuclei with positive predictive values of 0.34 ± 0.15 (prevalence 0.03 ± 0.01) and 0.47 ± 0.1 (prevalence 0.07 ± 0.02) respectively on virtual H&E. This approach represents a promising step towards automating annotation in digital pathology.

Altered cellular metabolic pathway and epithelial cell maturation induced by MYO5B defects are partially reversible by LPAR5 activation.

Functional loss of the motor protein, Myosin Vb (MYO5B), induces various defects in intestinal epithelial function and causes a congenital diarrheal disorder, microvillus inclusion disease (MVID). Utilizing the MVID model mice, Vil1-Cre ERT2 ;Myo5b flox/flox (MYO5BΔIEC) and Vil1-Cre ERT2 ;Myo5b flox/G519R (MYO5B(G519R)), we previously reported that functional MYO5B loss disrupts progenitor cell differentiation and enterocyte maturation that result in villus blunting and deadly malabsorption symptoms. In this study, we determined that both absence and a point mutation of MYO5B impair lipid metabolism and alter mitochondrial structure, which may underlie the progenitor cell malfunction observed in MVID intestine. Along with a decrease in fatty acid oxidation, the lipogenesis pathway was enhanced in the MYO5BΔIEC small intestine. Consistent with these observations in vivo , RNA-sequencing of enteroids generated from two MVID mouse strains showed similar downregulation of energy metabolic enzymes, including mitochondrial oxidative phosphorylation genes. In our previous studies, lysophosphatidic acid (LPA) signaling ameliorates epithelial cell defects in MYO5BΔIEC tissues and enteroids. The present study demonstrates that the highly soluble LPAR5-preferred agonist, Compound-1, improved sodium transporter localization and absorptive function, and tuft cell differentiation in patient-modeled MVID animals that carry independent mutations in MYO5B. Body weight loss in male MYO5B(G519R) mice was ameliorated by Compound-1. These observations suggest that Compound-1 treatment has a trophic effect on intestine with MYO5B functional loss through epithelial cell-autonomous pathways that may improve the differentiation of progenitor cells and the maturation of enterocytes. Targeting LPAR5 may represent an effective therapeutic approach for treatment of MVID symptoms induced by different point mutations in MYO5B. NEW & NOTEWOTHY: This study demonstrates the importance of MYO5B for cellular lipid metabolism and mitochondria in intestinal epithelial cells, a previously unexplored function of MYO5B. Alterations in cellular metabolism may underlie the progenitor cell malfunction observed in microvillus inclusion disease (MVID). To examine the therapeutic potential of progenitor-targeted treatments, the effects of LPAR5-preferred agonist, Compound-1, was investigated utilizing several MVID model mice and enteroids. Our observations suggests that Compound-1 may provide a therapeutic approach for treating MVID.

Identification and multimodal characterization of a specialized epithelial cell type associated with Crohn's disease.

Crohn's disease (CD) is a complex chronic inflammatory disorder with both gastrointestinal and extra-intestinal manifestations associated immune dysregulation. Analyzing 202,359 cells from 170 specimens across 83 patients, we identify a distinct epithelial cell type in both terminal ileum and ascending colon (hereon as 'LND') with high expression of LCN2, NOS2, and DUOX2 and genes related to antimicrobial response and immunoregulation. LND cells, confirmed by in-situ RNA and protein imaging, are rare in non-IBD controls but expand in active CD, and actively interact with immune cells and specifically express IBD/CD susceptibility genes, suggesting a possible function in CD immunopathogenesis. Furthermore, we discover early and late LND subpopulations with different origins and developmental potential. A higher ratio of late-to-early LND cells correlates with better response to anti-TNF treatment. Our findings thus suggest a potential pathogenic role for LND cells in both Crohn's ileitis and colitis.

Alleviating tiling effect by random walk sliding window in high-resolution histological whole slide image synthesis.

Multiplex immunofluorescence (MxIF) is an advanced molecular imaging technique that can simultaneously provide biologists with multiple (i.e., more than 20) molecular markers on a single histological tissue section. Unfortunately, due to imaging restrictions, the more routinely used hematoxylin and eosin (H&E) stain is typically unavailable with MxIF on the same tissue section. As biological H&E staining is not feasible, previous efforts have been made to obtain H&E whole slide image (WSI) from MxIF via deep learning empowered virtual staining. However, the tiling effect is a long-lasting problem in high-resolution WSI-wise synthesis. The MxIF to H&E synthesis is no exception. Limited by computational resources, the cross-stain image synthesis is typically performed at the patch-level. Thus, discontinuous intensities might be visually identified along with the patch boundaries assembling all individual patches back to a WSI. In this work, we propose a deep learning based unpaired high-resolution image synthesis method to obtain virtual H&E WSIs from MxIF WSIs (each with 27 markers/stains) with reduced tiling effects. Briefly, we first extend the CycleGAN framework by adding simultaneous nuclei and mucin segmentation supervision as spatial constraints. Then, we introduce a random walk sliding window shifting strategy during the optimized inference stage, to alleviate the tiling effects. The validation results show that our spatially constrained synthesis method achieves a 56% performance gain for the downstream cell segmentation task. The proposed inference method reduces the tiling effects by using 50% fewer computation resources without compromising performance. The proposed random sliding window inference method is a plug-and-play module, which can be generalized for other high-resolution WSI image synthesis applications. The source code with our proposed model are available at https://github.com/MASILab/RandomWalkSlidingWindow.git.

GammaGateR: semi-automated marker gating for single-cell multiplexed imaging.

MOTIVATION: Multiplexed immunofluorescence (mIF) is an emerging assay for multichannel protein imaging that can decipher cell-level spatial features in tissues. However, existing automated cell phenotyping methods, such as clustering, face challenges in achieving consistency across experiments and often require subjective evaluation. As a result, mIF analyses often revert to marker gating based on manual thresholding of raw imaging data. RESULTS: To address the need for an evaluable semi-automated algorithm, we developed GammaGateR, an R package for interactive marker gating designed specifically for segmented cell-level data from mIF images. Based on a novel closed-form gamma mixture model, GammaGateR provides estimates of marker-positive cell proportions and soft clustering of marker-positive cells. The model incorporates user-specified constraints that provide a consistent but slide-specific model fit. We compared GammaGateR against the newest unsupervised approach for annotating mIF data, employing two colon datasets and one ovarian cancer dataset for the evaluation. We showed that GammaGateR produces highly similar results to a silver standard established through manual annotation. Furthermore, we demonstrated its effectiveness in identifying biological signals, achieved by mapping known spatial interactions between CD68 and MUC5AC cells in the colon and by accurately predicting survival in ovarian cancer patients using the phenotype probabilities as input for machine learning methods. GammaGateR is a highly efficient tool that can improve the replicability of marker gating results, while reducing the time of manual segmentation. AVAILABILITY AND IMPLEMENTATION: The R package is available at https://github.com/JiangmeiRubyXiong/GammaGateR.

Cross-scale multi-instance learning for pathological image diagnosis.

Analyzing high resolution whole slide images (WSIs) with regard to information across multiple scales poses a significant challenge in digital pathology. Multi-instance learning (MIL) is a common solution for working with high resolution images by classifying bags of objects (i.e. sets of smaller image patches). However, such processing is typically performed at a single scale (e.g., 20× magnification) of WSIs, disregarding the vital inter-scale information that is key to diagnoses by human pathologists. In this study, we propose a novel cross-scale MIL algorithm to explicitly aggregate inter-scale relationships into a single MIL network for pathological image diagnosis. The contribution of this paper is three-fold: (1) A novel cross-scale MIL (CS-MIL) algorithm that integrates the multi-scale information and the inter-scale relationships is proposed; (2) A toy dataset with scale-specific morphological features is created and released to examine and visualize differential cross-scale attention; (3) Superior performance on both in-house and public datasets is demonstrated by our simple cross-scale MIL strategy. The official implementation is publicly available at https://github.com/hrlblab/CS-MIL.

Inhibition of autocrine HGF maturation overcomes cetuximab resistance in colorectal cancer.

Although amplifications and mutations in receptor tyrosine kinases (RTKs) act as bona fide oncogenes, in most cancers, RTKs maintain moderate expression and remain wild-type. Consequently, cognate ligands control many facets of tumorigenesis, including resistance to anti-RTK therapies. Herein, we show that the ligands for the RTKs MET and RON, HGF and HGFL, respectively, are synthesized as inactive precursors that are activated by cellular proteases. Our newly generated HGF/HGFL protease inhibitors could overcome both de novo and acquired cetuximab resistance in colorectal cancer (CRC). Conversely, HGF overexpression was necessary and sufficient to induce cetuximab resistance and loss of polarity. Moreover, HGF-induced cetuximab resistance could be overcome by the downstream MET inhibitor, crizotinib, and upstream protease inhibitors. Additionally, HAI-1, an endogenous inhibitor of HGF proteases, (i) was downregulated in CRC, (ii) exhibited increased genomic methylation that correlated with poor prognosis, (iii) HAI-1 expression correlated with cetuximab response in a panel of cancer cell lines, and (iv) exogenous addition of recombinant HAI-1 overcame cetuximab resistance in CC-HGF cells. Thus, we describe a targetable, autocrine HAI-1/Protease/HGF/MET axis in cetuximab resistance in CRC.

Coronavirus M Protein Trafficking in Epithelial Cells Utilizes a Myosin Vb Splice Variant and Rab10.

The membrane (M) glycoprotein of coronaviruses (CoVs) serves as the nidus for virion assembly. Using a yeast two-hybrid screen, we identified the interaction of the cytosolic tail of Murine Hepatitis Virus (MHV-CoV) M protein with Myosin Vb (MYO5B), specifically with the alternative splice variant of cellular MYO5B including exon D (MYO5B+D), which mediates interaction with Rab10. When co-expressed in human lung epithelial A549 and canine kidney epithelial MDCK cells, MYO5B+D co-localized with the MHV-CoV M protein, as well as with the M proteins from Porcine Epidemic Diarrhea Virus (PEDV-CoV), Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome 2 (SARS-CoV-2). Co-expressed M proteins and MYO5B+D co-localized with endogenous Rab10 and Rab11a. We identified point mutations in MHV-CoV M that blocked the interaction with MYO5B+D in yeast 2-hybrid assays. One of these point mutations (E121K) was previously shown to block MHV-CoV virion assembly and its interaction with MYO5B+D. The E to K mutation at homologous positions in PEDV-CoV, MERS-CoV and SARS-CoV-2 M proteins also blocked colocalization with MYO5B+D. The knockdown of Rab10 blocked the co-localization of M proteins with MYO5B+D and was rescued by re-expression of CFP-Rab10. Our results suggest that CoV M proteins traffic through Rab10-containing systems, in association with MYO5B+D.

Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors.

Colorectal cancer exhibits dynamic cellular and genetic heterogeneity during progression from precursor lesions toward malignancy. Analysis of spatial multi-omic data from 31 human colorectal specimens enabled phylogeographic mapping of tumor evolution that revealed individualized progression trajectories and accompanying microenvironmental and clonal alterations. Phylogeographic mapping ordered genetic events, classified tumors by their evolutionary dynamics, and placed clonal regions along global pseudotemporal progression trajectories encompassing the chromosomal instability (CIN+) and hypermutated (HM) pathways. Integrated single-cell and spatial transcriptomic data revealed recurring epithelial programs and infiltrating immune states along progression pseudotime. We discovered an immune exclusion signature (IEX), consisting of extracellular matrix regulators DDR1, TGFBI, PAK4, and DPEP1, that charts with CIN+ tumor progression, is associated with reduced cytotoxic cell infiltration, and shows prognostic value in independent cohorts. This spatial multi-omic atlas provides insights into colorectal tumor-microenvironment co-evolution, serving as a resource for stratification and targeted treatments.

Topological-Preserving Membrane Skeleton Segmentation in Multiplex Immunofluorescence Imaging.

Multiplex immunofluorescence (MxIF) is an emerging imaging technology whose downstream molecular analytics highly rely upon the effectiveness of cell segmentation. In practice, multiple membrane markers (e.g., NaKATPase, PanCK and ß-catenin) are employed to stain membranes for different cell types, so as to achieve a more comprehensive cell segmentation since no single marker fits all cell types. However, prevalent watershed-based image processing might yield inferior capability for modeling complicated relationships between markers. For example, some markers can be misleading due to questionable stain quality. In this paper, we propose a deep learning based membrane segmentation method to aggregate complementary information that is uniquely provided by large scale MxIF markers. We aim to segment tubular membrane structure in MxIF data using global (membrane markers z-stack projection image) and local (separate individual markers) information to maximize topology preservation with deep learning. Specifically, we investigate the feasibility of four SOTA 2D deep networks and four volumetric-based loss functions. We conducted a comprehensive ablation study to assess the sensitivity of the proposed method with various combinations of input channels. Beyond using adjusted rand index (ARI) as the evaluation metric, which was inspired by the clDice, we propose a novel volumetric metric that is specific for skeletal structure, denoted as clDiceSKEL. In total, 80 membrane MxIF images were manually traced for 5-fold cross-validation. Our model outperforms the baseline with a 20.2% and 41.3% increase in clDiceSKEL and ARI performance, which is significant (p<0.05) using the Wilcoxon signed rank test. Our work explores a promising direction for advancing MxIF imaging cell segmentation with deep learning membrane segmentation. Tools are available at https://github.com/MASILab/MxIF_Membrane_Segmentation.

GammaGateR: semi-automated marker gating for single-cell multiplexed imaging.

Motivation: Multiplexed immunofluorescence (mIF) is an emerging assay for multichannel protein imaging that can decipher cell-level spatial features in tissues. However, existing automated cell phenotyping methods, such as clustering, face challenges in achieving consistency across experiments and often require subjective evaluation. As a result, mIF analyses often revert to marker gating based on manual thresholding of raw imaging data. Results: To address the need for an evaluable semi-automated algorithm, we developed GammaGateR, an R package for interactive marker gating designed specifically for segmented cell-level data from mIF images. Based on a novel closed-form gamma mixture model, GammaGateR provides estimates of marker-positive cell proportions and soft clustering of marker-positive cells. The model incorporates user-specified constraints that provide a consistent but slide-specific model fit. We compared GammaGateR against the newest unsupervised approach for annotating mIF data, employing two colon datasets and one ovarian cancer dataset for the evaluation. We showed that GammaGateR produces highly similar results to a silver standard established through manual annotation. Furthermore, we demonstrated its effectiveness in identifying biological signals, achieved by mapping known spatial interactions between CD68 and MUC5AC cells in the colon and by accurately predicting survival in ovarian cancer patients using the phenotype probabilities as input for machine learning methods. GammaGateR is a highly efficient tool that can improve the replicability of marker gating results, while reducing the time of manual segmentation. Availability and Implementation: The R package is available at https://github.com/JiangmeiRubyXiong/GammaGateR.

A Specialized Epithelial Cell Type Regulating Mucosal Immunity and Driving Human Crohn's Disease.

Crohn's disease (CD) is a complex chronic inflammatory disorder that may affect any part of gastrointestinal tract with extra-intestinal manifestations and associated immune dysregulation. To characterize heterogeneity in CD, we profiled single-cell transcriptomics of 170 samples from 65 CD patients and 18 non-inflammatory bowel disease (IBD) controls in both the terminal ileum (TI) and ascending colon (AC). Analysis of 202,359 cells identified a novel epithelial cell type in both TI and AC, featuring high expression of LCN2, NOS2, and DUOX2, and thus is named LND. LND cells, confirmed by high-resolution in-situ RNA imaging, were rarely found in non-IBD controls, but expanded significantly in active CD. Compared to other epithelial cells, genes defining LND cells were enriched in antimicrobial response and immunoregulation. Moreover, multiplexed protein imaging demonstrated that LND cell abundance was associated with immune infiltration. Cross-talk between LND and immune cells was explored by ligand-receptor interactions and further evidenced by their spatial colocalization. LND cells showed significant enrichment of expression specificity of IBD/CD susceptibility genes, revealing its role in immunopathogenesis of CD. Investigating lineage relationships of epithelial cells detected two LND cell subpopulations with different origins and developmental potential, early and late LND. The ratio of the late to early LND cells was related to anti-TNF response. These findings emphasize the pathogenic role of the specialized LND cell type in both Crohn's ileitis and Crohn's colitis and identify novel biomarkers associated with disease activity and treatment response.

Patient-derived enteroids provide a platform for the development of therapeutic approaches in microvillus inclusion disease.

Microvillus inclusion disease (MVID), caused by loss-of-function mutations in the motor protein myosin Vb (MYO5B), is a severe infantile disease characterized by diarrhea, malabsorption, and acid/base instability, requiring intensive parenteral support for nutritional and fluid management. Human patient-derived enteroids represent a model for investigation of monogenic epithelial disorders but are a rare resource from MVID patients. We developed human enteroids with different loss-of function MYO5B variants and showed that they recapitulated the structural changes found in native MVID enterocytes. Multiplex immunofluorescence imaging of patient duodenal tissues revealed patient-specific changes in localization of brush border transporters. Functional analysis of electrolyte transport revealed profound loss of Na+/H+ exchange (NHE) activity in MVID patient enteroids with near-normal chloride secretion. The chloride channel-blocking antidiarrheal drug crofelemer dose-dependently inhibited agonist-mediated fluid secretion. MVID enteroids exhibited altered differentiation and maturation versus healthy enteroids. γ-Secretase inhibition with DAPT recovered apical brush border structure and functional Na+/H+ exchange activity in MVID enteroids. Transcriptomic analysis revealed potential pathways involved in the rescue of MVID cells including serum/glucocorticoid-regulated kinase 2 (SGK2) and NHE regulatory factor 3 (NHERF3). These results demonstrate the utility of patient-derived enteroids for developing therapeutic approaches to MVID.

Predicting Crohn's disease severity in the colon using mixed cell nucleus density from pseudo labels.

Crohn's disease (CD) is a debilitating inflammatory bowel disease with no known cure. Computational analysis of hematoxylin and eosin (H&E) stained colon biopsy whole slide images (WSIs) from CD patients provides the opportunity to discover unknown and complex relationships between tissue cellular features and disease severity. While there have been works using cell nuclei-derived features for predicting slide-level traits, this has not been performed on CD H&E WSIs for classifying normal tissue from CD patients vs active CD and assessing slide label-predictive performance while using both separate and combined information from pseudo-segmentation labels of nuclei from neutrophils, eosinophils, epithelial cells, lymphocytes, plasma cells, and connective cells. We used 413 WSIs of CD patient biopsies and calculated normalized histograms of nucleus density for the six cell classes for each WSI. We used a support vector machine to classify the truncated singular value decomposition representations of the normalized histograms as normal or active CD with four-fold cross-validation in rounds where nucleus types were first compared individually, the best was selected, and further types were added each round. We found that neutrophils were the most predictive individual nucleus type, with an AUC of 0.92 ± 0.0003 on the withheld test set. Adding information improved cross-validation performance for the first two rounds and on the withheld test set for the first three rounds, though performance metrics did not increase substantially beyond when neutrophils were used alone.

Influence of Cell-type Ratio on Spatially Resolved Single-cell Transcriptomes using the Tangram Algorithm: Based on Implementation on Single-Cell and MxIF Data.

The Tangram algorithm is a benchmarking method of aligning single-cell (sc/snRNA-seq) data to various forms of spatial data collected from the same region. With this data alignment, the annotation of the single-cell data can be projected to spatial data. However, the cell composition (cell-type ratio) of the single-cell data and spatial data might be different because of heterogeneous cell distribution. Whether the Tangram algorithm can be adapted when the two data have different cell-type ratios has not been discussed in previous works. In our practical application that maps the cell-type classification results of single-cell data to the Multiplex immunofluorescence (MxIF) spatial data, cell-type ratios were different, though they were sampled from adjacent areas. In this work, both simulation and empirical validation were conducted to quantitatively explore the impact of the mismatched cell-type ratio on the Tangram mapping in different situations. Results show that the cell-type difference has a negative influence on classification accuracy.