Stroma AReactive Invasion Front Areas (SARIFA) proves prognostic relevance in gastric carcinoma and is based on a tumor-adipocyte interaction indicating an altered immune response.

BACKGROUND: Recently, we presented Stroma AReactive Invasion Front Areas (SARIFA) as a new histomorphologic negative prognostic biomarker in gastric cancer. It is defined as direct contact between tumor cells and fat cells. The aim of this study was to further elucidate the underlying genomic, transcriptional, and immunological mechanisms of the SARIFA phenomenon. METHODS: To address these questions, SARIFA was classified on H&E-stained tissue sections of three cohorts: an external cohort (n = 489, prognostic validation), the TCGA-STAD cohort (n = 194, genomic and transcriptomic analysis), and a local cohort (n = 60, digital spatial profiling (whole transcriptome) and double RNA in situ hybridization/immunostaining of cytokines). RESULTS: SARIFA status proved to be an independent negative prognostic factor for overall survival in an external cohort of gastric carcinomas. In TCGA-STAD cohort, SARIFA is not driven by distinct genomic alterations, whereas the gene expression analyses showed an upregulation of FABP4 in SARIFA-positive tumors. In addition, the transcriptional regulations of white adipocyte differentiation, triglyceride metabolism, and catabolism were upregulated in pathway analyses. In the DSP analysis of SARIFA-positive tumors, FABP4 and the transcriptional regulation of white adipocyte differentiation were upregulated in macrophages. Additionally, a significantly lower expression of the cytokines IL6 and TNFα was observed at the invasion front. CONCLUSIONS: SARIFA proves to be a strong negative prognostic biomarker in advanced gastric cancer, implicating an interaction of tumor cells with tumor-promoting adipocytes with crucial changes in tumor cell metabolism. SARIFA is not driven by tumor genetics but is very likely driven by an altered immune response as a causative mechanism.

Spiny projection neurons exhibit transcriptional signatures within subregions of the dorsal striatum.

The dorsal striatum is organized into functional territories defined by corticostriatal inputs onto both direct and indirect spiny projection neurons (SPNs), the major cell types within the striatum. In addition to circuit connectivity, striatal domains are likely defined by the spatially determined transcriptomes of SPNs themselves. To identify cell-type-specific spatiomolecular signatures of direct and indirect SPNs within dorsomedial, dorsolateral, and ventrolateral dorsal striatum, we used RNA profiling in situ hybridization with probes to >98% of protein coding genes. We demonstrate that the molecular identity of SPNs is mediated by hundreds of differentially expressed genes across territories of the striatum, revealing extraordinary heterogeneity in the expression of genes that mediate synaptic function in both direct and indirect SPNs. This deep insight into the complex spatiomolecular organization of the striatum provides a foundation for understanding both normal striatal function and for dissecting region-specific dysfunction in disorders of the striatum.

SARS-CoV-2 infection produces chronic pulmonary epithelial and immune cell dysfunction with fibrosis in mice.

A subset of individuals who recover from coronavirus disease 2019 (COVID-19) develop post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (PASC), but the mechanistic basis of PASC-associated lung abnormalities suffers from a lack of longitudinal tissue samples. The mouse-adapted SARS-CoV-2 strain MA10 produces an acute respiratory distress syndrome in mice similar to humans. To investigate PASC pathogenesis, studies of MA10-infected mice were extended from acute to clinical recovery phases. At 15 to 120 days after virus clearance, pulmonary histologic findings included subpleural lesions composed of collagen, proliferative fibroblasts, and chronic inflammation, including tertiary lymphoid structures. Longitudinal spatial transcriptional profiling identified global reparative and fibrotic pathways dysregulated in diseased regions, similar to human COVID-19. Populations of alveolar intermediate cells, coupled with focal up-regulation of profibrotic markers, were identified in persistently diseased regions. Early intervention with antiviral EIDD-2801 reduced chronic disease, and early antifibrotic agent (nintedanib) intervention modified early disease severity. This murine model provides opportunities to identify pathways associated with persistent SARS-CoV-2 pulmonary disease and test countermeasures to ameliorate PASC.

A model of persistent post SARS-CoV-2 induced lung disease for target identification and testing of therapeutic strategies.

COVID-19 survivors develop post-acute sequelae of SARS-CoV-2 (PASC), but the mechanistic basis of PASC-associated lung abnormalities suffers from a lack of longitudinal samples. Mouse-adapted SARS-CoV-2 MA10 produces an acute respiratory distress syndrome (ARDS) in mice similar to humans. To investigate PASC pathogenesis, studies of MA10-infected mice were extended from acute disease through clinical recovery. At 15-120 days post-virus clearance, histologic evaluation identified subpleural lesions containing collagen, proliferative fibroblasts, and chronic inflammation with tertiary lymphoid structures. Longitudinal spatial transcriptional profiling identified global reparative and fibrotic pathways dysregulated in diseased regions, similar to human COVID-19. Populations of alveolar intermediate cells, coupled with focal upregulation of pro-fibrotic markers, were identified in persistently diseased regions. Early intervention with antiviral EIDD-2801 reduced chronic disease, and early anti-fibrotic agent (nintedanib) intervention modified early disease severity. This murine model provides opportunities to identify pathways associated with persistent SARS-CoV-2 pulmonary disease and test countermeasures to ameliorate PASC.

Differential protein expression in the hippocampi of resilient individuals identified by digital spatial profiling.

Clinical symptoms correlate with underlying neurodegenerative changes in the vast majority of people. However, an intriguing group of individuals demonstrate neuropathologic changes consistent with Alzheimer disease (AD) yet remain cognitively normal (termed "resilient"). Previous studies have reported less overall neuronal loss, less gliosis, and fewer comorbidities in these individuals. Herein, NanoString GeoMx™ Digital Spatial Profiler (DSP) technology was utilized to investigate protein expression differences comparing individuals with dementia and AD neuropathologic change to resilient individuals. DSP allows for spatial analysis of protein expression in multiple regions of interest (ROIs) on formalin-fixed paraffin-embedded sections. ROIs in this analysis were hippocampal neurofibrillary tangle (NFT)-bearing neurons, non-NFT-bearing neurons, and their immediate neuronal microenvironments. Analyses of 86 proteins associated with CNS cell-typing or known neurodegenerative changes in 168 ROIs from 14 individuals identified 11 proteins displaying differential expression in NFT-bearing neurons of the resilient when compared to the demented (including APP, IDH1, CD68, GFAP, SYP and Histone H3). In addition, IDH1, CD68, and SYP were differentially expressed in the environment of NFT-bearing neurons when comparing resilient to demented. IDH1 (which is upregulated under energetic and oxidative stress) and PINK1 (which is upregulated in response to mitochondrial dysfunction and oxidative stress) both displayed lower expression in the environment of NFT-bearing neurons in the resilient. Therefore, the resilient display less evidence of energetic and oxidative stress. Synaptophysin (SYP) was increased in the resilient, which likely indicates better maintenance of synapses and synaptic connections. Furthermore, neurofilament light chain (NEFL) and ubiquitin c-terminal hydrolase (Park5) were higher in the resilient in the environment of NFTs. These differences all suggest healthier intact axons, dendrites and synapses in the resilient. In conclusion, resilient individuals display protein expression patterns suggestive of an environment containing less energetic and oxidative stress, which in turn results in maintenance of neurons and their synaptic connections.

Stroma AReactive Invasion Front Areas (SARIFA) - a new prognostic biomarker in gastric cancer related to tumor-promoting adipocytes.

Compared to other malignancies, there is a lack of easy-to-evaluate biomarkers for gastric cancer, which is associated with an adverse clinical outcome in many cases. Here, we present Stroma AReactive Invasion Front Areas (SARIFA) as a new histological prognostic marker. We defined SARIFA as the direct contact between a cluster of tumor glands/cells comprising at least five tumor cells and inconspicuous surrounding adipose tissue at the invasion front. A total of 480 adenocarcinomas of the stomach and the gastroesophageal junction from two different collections were classified according to SARIFA. To understand the potential underlying mechanisms, a transcriptome analysis was conducted using digital spatial profiling (DSP). It was found that 20% of the tumors were SARIFA-positive. Kappa values between the three pathologists were good in both collections: 0.74 and 0.78. Patients who presented SARIFA-positive tumors had a significantly lower overall survival in Collections A (median: 20.0 versus 44.0 months; p = 0.014, n = 160) and B (median: 15.0 versus 41.0 months; p < 0.0001, n = 320). SARIFA positivity emerged as a negative independent prognostic factor for overall survival (HR 1.638, 95% CI 1.153-2.326, p = 0.006). Using DSP, the most upregulated genes in SARIFA-positive cases were those associated with triglyceride catabolism and endogenous sterols. COL15A1, FABP2, and FABP4 were differentially expressed in positive cases. At the protein level, the expression of proteins related to lipid metabolism was confirmed. SARIFA combines low inter-observer variability, minimal effort, and high prognostic relevance, and is therefore an extremely promising biomarker related to tumor-promoting adipocytes in gastric cancer. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd. on behalf of The Pathological Society of Great Britain and Ireland.

Clustering the autisms using glutamate synapse protein interaction networks from cortical and hippocampal tissue of seven mouse models.

Background: Autism spectrum disorders (ASDs) are a heterogeneous group of behaviorally defined disorders and are associated with hundreds of rare genetic mutations and several environmental risk factors. Mouse models of specific risk factors have been successful in identifying molecular mechanisms associated with a given factor. However, comparisons among different models to elucidate underlying common pathways or to define clusters of biologically relevant disease subtypes have been complicated by different methodological approaches or different brain regions examined by the labs that developed each model. Here, we use a novel proteomic technique, quantitative multiplex co-immunoprecipitation or QMI, to make a series of identical measurements of a synaptic protein interaction network in seven different animal models. We aim to identify molecular disruptions that are common to multiple models. Methods: QMI was performed on 92 hippocampal and cortical samples taken from seven mouse models of ASD: Shank3B, Shank3Δex4-9, Ube3a2xTG, TSC2, FMR1, and CNTNAP2 mutants, as well as E12.5 VPA (maternal valproic acid injection on day 12.5 post-conception). The QMI panel targeted a network of 16 interacting, ASD-linked, synaptic proteins, probing 240 potential co-associations. A custom non-parametric statistical test was used to call significant differences between ASD models and littermate controls, and Hierarchical Clustering by Principal Components was used to cluster the models using mean log2 fold change values. Results: Each model displayed a unique set of disrupted interactions, but some interactions were disrupted in multiple models. These tended to be interactions that are known to change with synaptic activity. Clustering revealed potential relationships among models and suggested deficits in AKT signaling in Ube3a2xTG mice, which were confirmed by phospho-western blots. Conclusions: These data highlight the great heterogeneity among models, but suggest that high-dimensional measures of a synaptic protein network may allow differentiation of subtypes of ASD with shared molecular pathology.

Synaptic activity induces input-specific rearrangements in a targeted synaptic protein interaction network.

Cells utilize dynamic, network-level rearrangements in highly interconnected protein interaction networks to transmit and integrate information from distinct signaling inputs. Despite the importance of protein interaction network dynamics, the organizational logic underlying information flow through these networks is not well understood. Previously, we developed the quantitative multiplex co-immunoprecipitation platform, which allows for the simultaneous and quantitative measurement of the amount of co-association between large numbers of proteins in shared complexes. Here, we adapt quantitative multiplex co-immunoprecipitation to define the activity-dependent dynamics of an 18-member protein interaction network in order to better understand the underlying principles governing glutamatergic signal transduction. We first establish that immunoprecipitation detected by flow cytometry can detect activity-dependent changes in two known protein-protein interactions (Homer1-mGluR5 and PSD-95-SynGAP). We next demonstrate that neuronal stimulation elicits a coordinated change in our targeted protein interaction network, characterized by the initial dissociation of Homer1 and SynGAP-containing complexes followed by increased associations among glutamate receptors and PSD-95. Finally, we show that stimulation of distinct glutamate receptor types results in different modular sets of protein interaction network rearrangements, and that cells activate both modules in order to integrate complex inputs. This analysis demonstrates that cells respond to distinct types of glutamatergic input by modulating different combinations of protein co-associations among a targeted network of proteins. Our data support a model of synaptic plasticity in which synaptic stimulation elicits dissociation of pre-existing multiprotein complexes, opening binding slots in scaffold proteins and allowing for the recruitment of additional glutamatergic receptors. Open Science: This manuscript was awarded with the Open Materials Badge. For more information see: https://cos.io/our-services/open-science-badges/.