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The emergence of spatial profiling technologies in recent years has accelerated opportunities to profile in detail the molecular attributes of a wide range of tissue pathologies using archival specimens. However, tissue treatment for fixation and storage does not always support generation of high-quality genomic data. The purpose of this study was to investigate the impacts of Proteinase K (ProtK) treatment, as a way to increase target transcript exposure, on downstream sequencing data quality metrics for spatial transcriptomic data using formalin-fixed, paraffin-embedded samples. In a series of four independent assessments using different tissue types (nasal mucosa, tonsil, pancreas), varying concentrations of ProtK (ranging from 0.1 to 1 µg/mL) were used as part of the sample processing workflow to generate transcriptomic data using the Nanostring GeoMx DSP and Illumina NextSeq 2000 platforms. Use of higher concentrations of ProtK was generally found to increase total reads (2-4-fold). However, negative probe counts also tended to be increased (2-12-fold), resulting in reductions in the signal-to-noise ratio (10-70% lower) and the number of genes detected above background (50-80% lower). These effects were not seen in all tissues and impacts of tissue handling and processing, beyond ProtK treatment, on data quality metrics, also require consideration. Regardless, these observations highlight the need for careful consideration of a range of sample processing factors and benefits that may be achieved through the optimisation of sample processing workflows for specific tissues as a way to maximise the generation of quality data using spatial transcriptomic approaches.

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The discovery of biomarkers, essential for successful drug development, is often hindered by the limited availability of tissue samples, typically obtained through core needle biopsies. Standard 'omics platforms can consume significant amounts of tissue, forcing scientist to trade off spatial context for high-plex assays, such as genome-wide assays. While bulk gene expression approaches and standard single-cell transcriptomics have been valuable in defining various molecular and cellular mechanisms, they do not retain spatial context. As such, they have limited power in resolving tissue heterogeneity and cell-cell interactions. Current spatial transcriptomics platforms offer limited transcriptome coverage and have low throughput, restricting the number of samples that can be analyzed daily or even weekly. While the Digital Spatial Profiling (DSP) method does not provide single-cell resolution, it presents a significant advancement by enabling scalable whole transcriptome and ultrahigh-plex protein analysis from distinct tissue compartments and structures using a single tissue slide. These capabilities overcome significant constraints in biomarker analysis in solid tissue specimens. These advancements in tissue profiling play a crucial role in deepening our understanding of disease biology and in identifying potential therapeutic targets and biomarkers. To enhance the use of spatial biology tools in drug discovery and development, the DSP Scientific Consortium has created best practices guidelines. These guidelines, built on digital spatial profiling data and expertise, offer a practical framework for designing spatial studies and using current and future spatial biology platforms. The aim is to improve tissue analysis in all research areas supporting drug discovery and development.

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Alpha-smooth muscle actin (α-SMA) expression in the stroma is linked to the presence of cancer-associated fibroblasts and is known to correlate with worse outcomes in various tumors. In this study, using a GeoMx digital spatial profiling approach, we characterized the gene expression of the tumor and α-SMA-expressing stromal cell compartments in pancreatic neuroendocrine tumors (PanNETs). The profiling was performed on tissues from eight retrospective cases (three grade 1, four grade 2, and one grade 3). Selected regions of interest were segmented geometrically based on tissue morphology and fluorescent signals from synaptophysin and α-SMA markers. The α-SMA-expressing stromal-cell-associated genes were involved in pathways of extracellular matrix modification, whereas, in tumor cells, the gene expression profiles were associated with pathways involved in cell proliferation. The comparison of gene expression profiles across all three PanNET grades revealed that the differences between grades are not only present at the level of the tumor but also in the α-SMA-expressing stromal cells. Furthermore, the tumor cells from regions with a rich presence of adjacent α-SMA-expressing stromal cells revealed an upregulation of matrix metalloproteinase-9 (MMP9) expression in grade 3 tumors. This study provides an in-depth characterization of gene expression profiles in α-SMA-expressing stromal and tumor cells, and outlines potential crosstalk mechanisms.

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Objectives: Non-small-cell lung carcinoma (NSCLC) is the most prevalent and lethal form of lung cancer. The need for biomarker-informed stratification of targeted therapies has underpinned the need to uncover the underlying properties of the tumor microenvironment (TME) through high-plex quantitative assays. Methods: In this study, we profiled resected NSCLC tissues from 102 patients by targeted spatial proteomics of 78 proteins across tumor, immune activation, immune cell typing, immune-oncology, drug targets, cell death and PI3K/AKT modules to identify the tumor and stromal signatures associated with overall survival (OS). Results: Survival analysis revealed that stromal CD56 (HR = 0.384, P = 0.06) and tumoral TIM3 (HR = 0.703, P = 0.05) were associated with better survival in univariate Cox models. In contrast, after adjusting for stage, BCLXL (HR = 2.093, P = 0.02) and cleaved caspase 9 (HR = 1.575, P = 0.1) negatively influenced survival. Delta testing indicated the protective effect of TIM-3 (HR = 0.614, P = 0.04) on OS. In multivariate analysis, CD56 (HR = 0.172, P = 0.001) was associated with better survival in the stroma, while B7.H3 (HR = 1.72, P = 0.008) was linked to poorer survival in the tumor. Conclusions: Deciphering the TME using high-plex spatially resolved methods is giving us new insights into compartmentalised tumor and stromal protein signatures associated with clinical endpoints in NSCLC.

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Gastric poorly cohesive carcinoma (PCC) manifests with a diffuse pattern and diverse tumor cell morphologies, often indicating a more unfavorable prognosis. Recent consensus has reclassified PCC based on the proportion of signet-ring cells (SRCs) in tumors for research purposes. The two most distinct subtypes, poorly cohesive carcinoma not otherwise specified (PCC-NOS) and signet-ring cell carcinoma (SRCC), are characterized by less than 10% and more than 90% SRCs, respectively. However, research comparing the clinicopathological and transcriptomic differences between these subtypes remains limited. In this study, we conducted a comparative analysis of clinicopathological features in 55 advanced-stage PCCs, consisting of 43 PCC-NOS and 12 SRCC cases. Subsequently, 12 PCC-NOS and 5 SRCC cases were randomly selected for initial cancer-related gene expression profiling and pathway enrichment analysis using the GeoMx digital spatial profiler, followed by validation in a separate validation group comprising 16 PCC-NOS and 6 SRCC cases. These transcriptomic findings were then correlated with tumor morphology and clinicopathological data. PCC-NOS cases exhibited larger tumor size, a higher prevalence of pathological N3 disease, and a worse 1-year progression-free survival rate compared to SRCC cases. Clustering of PCC-NOS and SRCC was successfully achieved using the GeoMx Cancer Transcriptome Atlas. Among all studied genes, only MMP7 showed differential expression, with its overexpression significantly associated with the PCC-NOS subtype, increased perineural invasion, and earlier disease progression. Pathway analysis revealed significantly enriched pathways in PCC-NOS related to vesicle-mediated transport, adaptive immune systems, oncogenic signaling, and extracellular matrix organization, while SRCC displayed significant enrichment in pathways associated with respiratory electron transport and the cell cycle. In conclusion, this study compares and correlates clinicopathological features and transcriptomic data between PCC-NOS and SRCC at advanced stages, employing the latest consensus classification and a novel platform for analysis.

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INTRODUCTION: The colorectal serrated pathway involves precursor lesions known as sessile serrated lesions (SSL) and traditional serrated adenomas (TSA). Mutations in BRAF or KRAS are crucial early events in this pathway. Additional genetic and epigenetic changes contribute to the progression of these lesions into high-grade lesions and, eventually, invasive carcinoma. METHODS: We employed digital spatial profiling to investigate the transcriptional changes associated with SSL and TSA. The genes identified are confirmed by immunohistochemical (IHC) staining. Colorectal cancer (CRC) cell lines with CEACAM6 overexpression and knockdown were established to study the roles of CEACAM6 on tumorigenesis of CRC. RESULTS: Ten genes were upregulated in SSL and TSA, and seven were upregulated in both types of lesions. IHC staining confirmed overexpression of CEACAM6, LCN2, KRT19, and lysozyme in SSL and TSA. CEACAM6 expression is an early event in the serrated pathway but a late event in the conventional pathway. Using cell line models, we confirmed that CEACAM6 promotes CRC cells' proliferation, migration, and invasion abilities. CONCLUSION: These results highlight that the transcriptional changes in the early stages of tumorigenesis exhibit relative uniformity. Identifying these early events may hold significant promise in elucidating the mechanisms behind tumor initiation.

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Small cell lung cancer (SCLC) is a highly aggressive malignancy characterized by rapid growth and early metastasis and is susceptible to treatment resistance and recurrence. Understanding the intra-tumoral spatial heterogeneity in SCLC is crucial for improving patient outcomes and clinically relevant subtyping. In this study, a spatial whole transcriptome-wide analysis of 25 SCLC patients at sub-histological resolution using GeoMx Digital Spatial Profiling technology is performed. This analysis deciphered intra-tumoral multi-regional heterogeneity, characterized by distinct molecular profiles, biological functions, immune features, and molecular subtypes within spatially localized histological regions. Connections between different transcript-defined intra-tumoral phenotypes and their impact on patient survival and therapeutic response are also established. Finally, a gene signature, termed ITHtyper, based on the prevalence of intra-tumoral heterogeneity levels, which enables patient risk stratification from bulk RNA-seq profiles is identified. The prognostic value of ITHtyper is rigorously validated in independent multicenter patient cohorts. This study introduces a preliminary tumor-centric, regionally targeted spatial transcriptome resource that sheds light on previously unexplored intra-tumoral spatial heterogeneity in SCLC. These findings hold promise to improve tumor reclassification and facilitate the development of personalized treatments for SCLC patients.

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As around 25% to 30% of classical Hodgkin lymphoma (cHL) patients with advanced stages do not respond to standard therapies, the tumor microenvironment of cHL is one avenue that may be explored with the aim of improving risk stratification. CD4+ T cells are thought to be one of the main cell types in the tumor microenvironment. However, few immune signatures have been studied, and many of these lack related spatial data. Thus, our aim is to spatially resolve the CD4+ T cell subtypes that influence cHL outcome, depicting new immune signatures or transcriptional patterns that are in crosstalk with the tumor cells. This study was conducted using the NanoString GeoMx digital spatial profiling technology, based on the selection of distinct functional areas of patients' tissues followed by gene-expression profiling. The goals were to assess the differences in CD4+ T cell populations between tumor-rich and immune-predominant areas defined by different CD30 and PD-L1 expression levels and seek correlations with clinical metadata. Our results depict a complex map of CD4+ T cells with different functions and differentiation states that are enriched at distinct locations, the flux of cytokines and chemokines that could be related to these, and the specific relationships with the clinical outcome.

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Mucinous colorectal cancer (CRC) is a common histological subtype of colorectal adenocarcinoma, associated with a poor response to chemoradiotherapy. The commensal facultative anaerobes fusobacteria, have been associated with poor prognosis specifically in mesenchymal CRC. Interestingly, fusobacterial infection is especially prevalent in mucinous CRC. The objective of this study was therefore to increase our understanding of beneficial and detrimental effects of fusobacterial infection, by contrasting host cell signaling and immune responses in areas of high vs. low infection, using mucinous rectal cancer as a clinically relevant example. We employed spatial transcriptomic profiling of 106 regions of interest from 8 mucinous rectal cancer samples to study gene expression in the epithelial and immune segments across regions of high versus low fusobacterial infection. Fusobacteria high regions were associated with increased oxidative stress, DNA damage, and P53 signaling. Meanwhile regions of low fusobacterial prevalence were characterized by elevated JAK-STAT, Il-17, Il-1, chemokine and TNF signaling. Immune masks within fusobacterial high regions were characterized by elevated proportions of cytotoxic (CD8+) T cells (p = 0.037), natural killer (NK) cells (p < 0.001), B-cells (p < 0.001), and gamma delta T cells (p = 0.003). Meanwhile, fusobacteria low regions were associated with significantly greater M2 macrophage (p < 0.001), fibroblast (p < 0.001), pericyte (p = 0.002), and endothelial (p < 0.001) counts.

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Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal human malignancies. Tissue microarrays (TMA) are an established method of high throughput biomarker interrogation in tissues but may not capture histological features of cancer with potential biological relevance. Topographic TMAs (T-TMAs) representing pathophysiological hallmarks of cancer were constructed from representative, retrospective PDAC diagnostic material, including 72 individual core tissue samples. The T-TMA was interrogated with tissue hybridization-based experiments to confirm the accuracy of the topographic sampling, expression of pro-tumourigenic and immune mediators of cancer, totalling more than 750 individual biomarker analyses. A custom designed Next Generation Sequencing (NGS) panel and a spatial distribution-specific transcriptomic evaluation were also employed. The morphological choice of the pathophysiological hallmarks of cancer was confirmed by protein-specific expression. Quantitative analysis identified topography-specific patterns of expression in the IDO/TGF-ß axis; with a heterogeneous relationship of inflammation and desmoplasia across hallmark areas and a general but variable protein and gene expression of c-MET. NGS results highlighted underlying genetic heterogeneity within samples, which may have a confounding influence on the expression of a particular biomarker. T-TMAs, integrated with quantitative biomarker digital scoring, are useful tools to identify hallmark specific expression of biomarkers in pancreatic cancer.

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The disease-specific accumulation of pathological proteins has long been the major focus of research in neurodegenerative diseases (ND), including Alzheimer's disease (AD) and related dementias (RD), but the recent identification of a multitude of genetic risk factors for ND in immune-associated genes highlights the importance of immune processes in disease pathogenesis and progression. Studies in animal models have characterized the local immune response to disease-specific proteins in AD and ADRD, but due to the complexity of disease processes and the co-existence of multiple protein pathologies in human donor brains, the precise role of immune processes in ND is far from understood. To better characterize the interplay between different extracellular and intracellular protein pathologies and the brain's intrinsic immune system in ND, we set out to comprehensively profile the local immune response in postmortem brain samples of individuals with "pure" beta-Amyloid and tau pathology (AD), "pure" α-Synuclein pathology in Lewy body diseases (LBD), as well as cases with Alzheimer's disease neuropathological changes (ADNC) and Lewy body pathology (MIX). Combining immunohistochemical profiling of microglia and digital image analysis, along with deep immunophenotyping using gene expression profiling on the NanoString nCounter® platform and digital spatial profiling on the NanoString GeoMx® platform we identified a robust immune activation signature in AD brain samples. This signature is maintained in persons with mixed pathologies, irrespective of co-existence of AD pathology and Lewy body (LB) pathology, while LBD brain samples with "pure" LB pathology exhibit an attenuated and distinct immune signature. Our studies highlight disease- and brain region-specific immune response profiles to intracellular and extracellular protein pathologies and further underscore the complexity of neuroimmune interactions in ND.

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BACKGROUND: SARS-CoV-2 infection during pregnancy is associated with an increased risk for stillbirth, preeclampsia, and preterm birth. However, this does not seem to be caused by intrauterine fetal infection because vertical transmission is rarely reported. There is a paucity of data regarding the associated placental SARS-CoV-2 histopathology and their relationship with the timing and severity of infection. OBJECTIVE: This study aimed to determine if maternal SARS-CoV-2 infection was associated with specific patterns of placental injury and if these findings differed by gestational age at time of infection or disease severity. STUDY DESIGN: A retrospective cohort study was performed at the University of California San Diego between March 2020 and February 2021. Placentas from pregnancies with a positive SARS-CoV-2 test were matched with 2 sets of controls; 1 set was time-matched by delivery date and sent to pathology for routine clinical indications, and the other was chosen from a cohort of placentas previously collected for research purposes without clinical indications for pathologic examination before the SARS-CoV-2 outbreak. Placental pathologic lesions were defined based on standard criteria and included maternal and fetal vascular malperfusion and acute and chronic inflammatory lesions. A bivariate analysis was performed using the independent Student t test and Pearson chi-square test. A logistic regression was used to control for relevant covariates. Regions of SARS-CoV-2-associated villitis were further investigated using protein-based digital spatial profiling assays on the GeoMx platform, validated by immunohistochemistry, and compared with cases of infectious villitis and villitis of unknown etiology. Differential expression analysis was performed to identify protein expression differences between these groups of villitis. RESULTS: We included 272 SARS-CoV-2 positive cases, 272 time-matched controls, and 272 historic controls. The mean age of SARS-CoV-2 affected subjects was 30.1±5.5 years and the majority were Hispanic (53.7%) and parous (65.7%). SARS-CoV-2 placentas demonstrated a higher frequency of the 4 major patterns of placental injury (all P<.001) than the historic controls. SARS-CoV-2 placentas also showed a higher frequency of chronic villitis and severe chronic villitis (P=.03 for both) than the time-matched controls, which remained significant after controlling for gestational age at delivery (adjusted odds ratio, 1.52; 95% confidence interval, 1.01-2.28; adjusted odds ratio, 2.12; 95% confidence interval, 1.16-3.88, respectively). Digital spatial profiling revealed that programmed death-ligand 1 was increased in villitis-positive regions of the SARS-CoV-2 (logFC, 0.47; adjusted P value =.002) and villitis of unknown etiology (logFC, 0.58; adjusted P value =.003) cases, but it was conversely decreased in villitis-positive regions of the infectious villitis group (log FC, -1.40; adjusted P value <.001). CONCLUSION: Chronic villitis seems to be the most specific histopathologic finding associated with SARS-CoV-2 maternal infection. Chronic villitis involves damage to the vasculosyncytial membrane of the chorionic villi, which are involved in gas and nutrient exchange, suggesting potential mechanisms of placental (and perhaps neonatal) injury, even in the absence of vertical transmission. Surprisingly, changes in protein expression in SARS-CoV-2-associated villitis seem to be more similar to villitis of unknown etiology than to infectious villitis.

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Acute Pancreatitis (AP) is associated with high mortality and current treatment options are limited to supportive care. We found that blockade of activin A (activin) in mice improves outcomes in two murine models of AP. To test the hypothesis that activin is produced early in response to pancreatitis and is maintained throughout disease progression to stimulate immune cells, we first performed digital spatial profiling (DSP) of human chronic pancreatitis (CP) patient tissue. Then, transwell migration assays using RAW264.7 mouse macrophages and qPCR analysis of "neutrophil-like" HL-60 cells were used for functional correlation. Immunofluorescence and western blots on cerulein-induced pancreatitis samples from pancreatic acinar cell-specific Kras knock-in (Ptf1aCreER™; LSL-KrasG12D) and functional WT Ptf1aCreER™ mouse lines mimicking AP and CP to allow for in vivo confirmation. Our data suggest activin promotes neutrophil and macrophage activation both in situ and in vitro, while pancreatic activin production is increased as early as 1 h in response to pancreatitis and is maintained throughout CP in vivo. Taken together, activin is produced early in response to pancreatitis and is maintained throughout disease progression to promote neutrophil and macrophage activation.

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Objectives: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus infection in pregnancy is associated with higher incidence of placental dysfunction, referred to by a few studies as a 'preeclampsia-like syndrome'. However, the mechanisms underpinning SARS-CoV-2-induced placental malfunction are still unclear. Here, we investigated whether the transcriptional architecture of the placenta is altered in response to SARS-CoV-2 infection. Methods: We utilised whole-transcriptome, digital spatial profiling, to examine gene expression patterns in placental tissues from participants who contracted SARS-CoV-2 in the third trimester of their pregnancy (n = 7) and those collected prior to the start of the coronavirus disease 2019 (COVID-19) pandemic (n = 9). Results: Through comprehensive spatial transcriptomic analyses of the trophoblast and villous core stromal cell subpopulations in the placenta, we identified SARS-CoV-2 to promote signatures associated with hypoxia and placental dysfunction. Notably, genes associated with vasodilation (NOS3), oxidative stress (GDF15, CRH) and preeclampsia (FLT1, EGFR, KISS1, PAPPA2) were enriched with SARS-CoV-2. Pathways related to increased nutrient uptake, vascular tension, hypertension and inflammation were also enriched in SARS-CoV-2 samples compared to uninfected controls. Conclusions: Our findings demonstrate the utility of spatially resolved transcriptomic analysis in defining the underlying pathogenic mechanisms of SARS-CoV-2 in pregnancy, particularly its role in placental dysfunction. Furthermore, this study highlights the significance of digital spatial profiling in mapping the intricate crosstalk between trophoblasts and villous core stromal cells, thus shedding light on pathways associated with placental dysfunction in pregnancies with SARS-CoV-2 infection.

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Background: Clear-cell renal cell carcinoma (ccRCC) is the most common and aggressive form of renal cancer and a paradigm of inter- and intratumor heterogeneity. We carried out an exploratory digital spatial profiling of the tumor interior and periphery of two ccRCC tumor specimens and mapped spatially the molecular and cellular composition of their tumor microenvironment and ecosystem. Materials and methods: Digital spatial profiling of the whole transcriptome of 19 regions of interest (ROIs) was carried out from two selected highly immunogenic stage pT3a/grade 3 (G3) and stage pT3a/grade 4 (G4) ccRCC. A total of 9-10 ROIs were selected from distinct areas from each tumor, including tumor interior and tumor periphery, and differences in gene expression were analyzed by RNA sequencing, pathway enrichment analysis, and cell deconvolution. Results: The distinct areas from the two locally advanced tumors displayed unique gene expression spatial patterns defining distinct biological pathways. Dimensional reduction analysis showed that the G3 ccRCC, compared to the G4 ccRCC, correlated with more variability between regions from the tumor interior and tumor periphery. Cell deconvolution analysis illustrated higher abundance of immune cells, including macrophages, myeloid dendritic cells, and CD4 T cells, and lower abundance of regulatory T cells in the tumor periphery compared to the tumor interior. Conclusions: Transcriptome spatial profiling revealed high inter- and intratumor heterogeneity in the analyzed tumors and provided information with potential clinical utility. This included the finding of less intratumor heterogeneity and more tumor-infiltrated T cells in the ccRCC tumor specimen with a higher grade.

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Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are heterogeneous malignancies that arise from complex cellular interactions within the tissue microenvironment. Here, we sought to decipher tumor-derived signals from the surrounding microenvironment by applying digital spatial profiling (DSP) to hormone-secreting and non-functional GEP-NETs. By combining this approach with in vitro studies of human-derived organoids, we demonstrated the convergence of cell autonomous immune and pro-inflammatory proteins that suggests their role in neuroendocrine differentiation and tumorigenesis. DSP was used to evaluate the expression of 40 neural- and immune-related proteins in surgically resected duodenal and pancreatic NETs (n = 20) primarily consisting of gastrinomas (18/20). A total of 279 regions of interest were examined between tumors, adjacent normal and abnormal-appearing epithelium, and the surrounding stroma. The results were stratified by tissue type and multiple endocrine neoplasia I (MEN1) status, whereas protein expression was validated by immunohistochemistry (IHC). A tumor immune cell autonomous inflammatory signature was further evaluated by IHC and RNAscope, while functional pro-inflammatory signaling was confirmed using patient-derived duodenal organoids. Gastrin-secreting and non-functional pancreatic NETs showed a higher abundance of immune cell markers and immune infiltrate compared with duodenal gastrinomas. Compared with non-MEN1 tumors, MEN1 gastrinomas and preneoplastic lesions showed strong immune exclusion and upregulated expression of neuropathological proteins. Despite a paucity of immune cells, duodenal gastrinomas expressed the pro-inflammatory and pro-neural factor IL-17B. Treatment of human duodenal organoids with IL-17B activated NF-κB and STAT3 signaling and induced the expression of neuroendocrine markers. In conclusion, multiplexed spatial protein analysis identified tissue-specific neuro-immune signatures in GEP-NETs. Duodenal gastrinomas are characterized by an immunologically cold microenvironment that permits cellular reprogramming and neoplastic transformation of the preneoplastic epithelium. Moreover, duodenal gastrinomas cell autonomously express immune and pro-inflammatory factors, including tumor-derived IL-17B, that stimulate the neuroendocrine phenotype. © 2024 The Pathological Society of Great Britain and Ireland.

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BACKGROUND: Platinum-based neoadjuvant chemotherapy (NAC) is standard for patients with muscle-invasive bladder cancer (MIBC). Pathologic response (complete: ypT0N0 and partial:

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BACKGROUND: The majority of pancreatic ductal adenocarcinoma (PDAC) patients experience disease progression while on treatment with gemcitabine and nanoparticle albumin-bound (nab)-paclitaxel (GemPac) necessitating the need for a more effective treatment strategy for this refractory disease. Previously, we have demonstrated that nuclear exporter protein exportin 1 (XPO1) is a valid therapeutic target in PDAC, and the selective inhibitor of nuclear export selinexor (Sel) synergistically enhances the efficacy of GemPac in pancreatic cancer cells, spheroids and patient-derived tumours, and had promising activity in a phase I study. METHODS: Here, we investigated the impact of selinexor-gemcitabine-nab-paclitaxel (Sel-GemPac) combination on LSL-KrasG12D/+ ; LSL-Trp53R172H/+ ; Pdx1-Cre (KPC) mouse model utilising digital spatial profiling (DSP) and single nuclear RNA sequencing (snRNAseq). RESULTS: Sel-GemPac synergistically inhibited the growth of the KPC tumour-derived cell line. The Sel-GemPac combination reduced the 2D colony formation and 3D spheroid formation. In the KPC mouse model, at a sub-maximum tolerated dose (sub-MTD) , Sel-GemPac enhanced the survival of treated mice compared to controls (p < .05). Immunohistochemical analysis of residual KPC tumours showed re-organisation of tumour stromal architecture, suppression of proliferation and nuclear retention of tumour suppressors, such as Forkhead Box O3a (FOXO3a). DSP revealed the downregulation of tumour promoting genes such as chitinase-like protein 3 (CHIL3/CHI3L3/YM1) and multiple pathways including phosphatidylinositol 3'-kinase-Akt (PI3K-AKT) signalling. The snRNAseq demonstrated a significant loss of cellular clusters in the Sel-GemPac-treated mice tumours including the CD44+ stem cell population. CONCLUSION: Taken together, these results demonstrate that the Sel-GemPac treatment caused broad perturbation of PDAC-supporting signalling networks in the KPC mouse model. HIGHLIGHTS: The majority of pancreatic ductal adenocarcinoma (PDAC) patients experience disease progression while on treatment with gemcitabine and nanoparticle albumin-bound (nab)-paclitaxel (GemPac). Exporter protein exportin 1 (XPO1) inhibitor selinexor (Sel) with GemPac synergistically inhibited the growth of LSL-KrasG12D/+; LSL-Trp53R172H/+; Pdx1-Cre (KPC) mouse derived cell line and enhanced the survival of mice. Digital spatial profiling shows that Sel-GemPac causes broad perturbation of PDAC-supporting signalling in the KPC model.

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Although anti-programmed death-1 (PD-1) antibody therapy improves the prognosis in patients with head and neck squamous cell carcinoma (HNSCC), some patients exhibit disease progression even after showing a good response to the treatment initially because of acquired resistance. Here, we aimed to reveal the dynamic changes in the tumor and tumor microenvironment (TME) in a 77-year-old man diagnosed with oral squamous cell carcinoma who developed acquired resistance after the administration of nivolumab using spatial transcriptomics. The results showed that, before immunotherapy, the activated pathways in the tumor area were mainly related to the cancer immune system, including antigen processing cross-presentation, interferon-gamma signaling, and the innate immune system. After immunotherapy, the activated pathways were mainly related to epigenetic modification, including RMTs methylate histone arginine and HDAC deacetylates histones. Before immunotherapy, the activated pathways in the TME were mainly related to the metabolism of proteins, including SRP-dependent co-translational protein targeting the membrane. After immunotherapy, the activated pathways in the TME were related to sensory perception and signal transduction. Our study revealed that epigenetic-modification-related pathways were mainly activated after establishing acquired resistance, suggesting that epigenetic modification in the tumor may prevent cancer immune system activation via the anti-PD-1 antibody.

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BACKGROUND: Biopsies obtained from primary oesophageal squamous cell carcinoma (ESCC) guide diagnosis and treatment. However, spatial intra-tumoral heterogeneity (ITH) influences biopsy-derived information and patient responsiveness to therapy. Here, we aimed to elucidate the spatial ITH of ESCC and matched lymph node metastasis (LNmet ). METHODS: Primary tumour superficial (PTsup ), deep (PTdeep ) and LNmet subregions of patients with locally advanced resectable ESCC were evaluated using whole-exome sequencing (WES), whole-transcriptome sequencing and spatially resolved digital spatial profiling (DSP). To validate the findings, immunohistochemistry was conducted and a single-cell transcriptomic dataset was analysed. RESULTS: WES revealed 15.72%, 5.02% and 32.00% unique mutations in PTsup , PTdeep and LNmet , respectively. Copy number alterations and phylogenetic trees showed spatial ITH among subregions both within and among patients. Driver mutations had a mixed intra-tumoral clonal status among subregions. Transcriptome data showed distinct differentially expressed genes among subregions. LNmet exhibited elevated expression of immunomodulatory genes and enriched immune cells, particularly when compared with PTsup (all P < .05). DSP revealed orthogonal support of bulk transcriptome results, with differences in protein and immune cell abundance between subregions in a spatial context. The integrative analysis of multi-omics data revealed complex heterogeneity in mRNA/protein levels and immune cell abundance within each subregion. CONCLUSIONS: This study comprehensively characterised spatial ITH in ESCC, and the findings highlight the clinical significance of unbiased molecular classification based on multi-omics data and their potential to improve the understanding and management of ESCC. The current practices for tissue sampling are insufficient for guiding precision medicine for ESCC, and routine profiling of PTdeep and/or LNmet should be systematically performed to obtain a more comprehensive understanding of ESCC and better inform treatment decisions.

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