Spatial Transcriptomics Analysis: Maternal Obesity Impairs Myogenic Cell Migration and Differentiation during Embryonic Limb Development.

Limb muscle is responsible for physical activities and myogenic cell migration during embryogenesis is indispensable for limb muscle formation. Maternal obesity (MO) impairs prenatal skeletal muscle development, but the effects of MO on myogenic cell migration remain to be examined. C57BL/6 mice embryos were collected at E13.5. The GeoMx DSP platform was used to customize five regions along myogenic cell migration routes (myotome, dorsal/ventral limb, limb stroma, limb tip), and data were analyzed by GeomxTools 3.6.0. A total of 2224 genes were down-regulated in the MO group. The GO enrichment analysis showed that MO inhibited migration-related biological processes. The signaling pathways guiding myogenic migration such as hepatocyte growth factor signaling, fibroblast growth factor signaling, Wnt signaling and GTPase signaling were down-regulated in the MO E13.5 limb tip. Correspondingly, the expression levels of genes involved in myogenic cell migration, such as Pax3, Gab1, Pxn, Tln2 and Arpc, were decreased in the MO group, especially in the dorsal and ventral sides of the limb. Additionally, myogenic differentiation-related genes were down-regulated in the MO limb. MO impedes myogenic cell migration and differentiation in the embryonic limb, providing an explanation for the impairment of fetal muscle development and offspring muscle function due to MO.

A best practices framework for spatial biology studies in drug discovery and development: enabling successful cohort studies using digital spatial profiling.

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.

How spatial omics approaches can be used to map the biological impacts of stress in psychiatric disorders: a perspective, overview and technical guide.

Exposure to significant levels of stress and trauma throughout life is a leading risk factor for the development of major psychiatric disorders. Despite this, we do not have a comprehensive understanding of the mechanisms that explain how stress raises psychiatric disorder risk. Stress in humans is complex and produces variable molecular outcomes depending on the stress type, timing, and duration. Deciphering how stress increases disorder risk has consequently been challenging to address with the traditional single-target experimental approaches primarily utilized to date. Importantly, the molecular processes that occur following stress are not fully understood but are needed to find novel treatment targets. Sequencing-based omics technologies, allowing for an unbiased investigation of physiological changes induced by stress, are rapidly accelerating our knowledge of the molecular sequelae of stress at a single-cell resolution. Spatial multi-omics technologies are now also emerging, allowing for simultaneous analysis of functional molecular layers, from epigenome to proteome, with anatomical context. The technology has immense potential to transform our understanding of how disorders develop, which we believe will significantly propel our understanding of how specific risk factors, such as stress, contribute to disease course. Here, we provide our perspective of how we believe these technologies will transform our understanding of the neurobiology of stress, and also provided a technical guide to assist molecular psychiatry and stress researchers who wish to implement spatial omics approaches in their own research. Finally, we identify potential future directions using multi-omics technology in stress research.

Method for high-plex analysis of immune cells in human skin using the GeoMx system.

Specific T cell populations in the skin have been demonstrated as important disease drivers in several dermatoses. Due to the unique skin architecture, these cells are not grouped together in structures but dispersedly spread out throughout the epidermis. Following tissue disruption and isolation, only about 10% of skin T cells are recovered and any in vitro expansion may alter their bona fide phenotype. The Nanostring GeoMx system was developed to address cellular phenotype and protein expression in a tissue spatial context. To do so, regions of interest (ROI) must exceed a certain area threshold (usually 100 µm in diameter) to generate a sufficient signal-to-noise ratio. Here, we present an approach that allows for the pooling of numerous smaller ROIs within the skin, enabling T cell and melanocyte phenotyping. Skin samples from healthy individuals and vitiligo patients were analysed using the GeoMx system and several immune profiling panels. A sufficient signal-to-noise ratio was achieved by pooling smaller ROIs and analysing them as a single group. While this prevents spatial analysis, this method allows for detailed analysis of cells as a population in the context of their physiological environment, making it possible to investigate in situ phenotype of rare cells in different tissue compartments.

A spatial proteomic study of platinum refractory HGSOC implicates dual AKT and WNT activity linked to an immunosuppressive tumor microenvironment.

OBJECTIVE: Advanced-stage high-grade serous ovarian cancer (HGSOC) remains a deadly gynecologic malignancy with high rates of disease recurrence and limited, effective therapeutic options for patients. There is a significant need to better stratify HGSOC patients into platinum refractory (PRF) vs. sensitive (PS) cohorts at baseline to improve therapeutic responses and survival outcomes for PRF HGSOC. METHODS: We performed NanoString for GeoMx Digital Spatial Profile (G-DSP) multiplex protein analysis on PRF and PS tissue microarrays (TMAs) to study the bidirectional communication of cancer cells with immune cells in the tumor microenvironment (TME) of HGSOC. We demonstrate robust stratification of PRF and PS tumors at baseline using multiplex spatial proteomic biomarkers with implications for tailoring subsequent therapy. RESULTS: PS patients had elevated apoptotic and anti-tumor immune profiles, while PRF patients had dual AKT1 and WNT signaling with immunosuppressive profiles. We found that dual activity of AKT1 and WNT signaling supported the exclusion of immune cells, specifically tumor infiltrating lymphocytes (TILs), from the TME in PRF tumors, and this was not observed in PS tumors. The exclusion of immune cells from the TME of PRF tumors corresponded to abnormal endothelial cell structure in tumors with dual AKT1 and WNT signaling activity. CONCLUSIONS: We believe our findings provide improved understanding of tumor-immune crosstalk in HGSOC TME highlighting the importance of the relationship between AKT and WNT pathways, immune cell function, and platinum response in HGSOC.

Mapping Cellular Interactions from Spatially Resolved Transcriptomics Data.

Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently, through the introduction of spatially resolved transcriptomics technologies (SRTs), especially those that achieve single cell resolution. However, significant challenges remain to analyze such highly complex data properly. Here, we introduce a Bayesian multi-instance learning framework, spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight spacia's power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates, and most importantly the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of spacia for all three commercialized single cell resolution ST technologies: MERSCOPE/Vizgen, CosMx/Nanostring, and Xenium/10X. Spacia unveiled how endothelial cells, fibroblasts and B cells in the tumor microenvironment contribute to Epithelial-Mesenchymal Transition and lineage plasticity in prostate cancer cells. We deployed spacia in a set of pan-cancer datasets and showed that B cells also participate in PDL1/PD1 signaling in tumors. We demonstrated that a CD8+ T cell/PDL1 effectiveness signature derived from spacia analyses is associated with patient survival and response to immune checkpoint inhibitor treatments in 3,354 patients. We revealed differential spatial interaction patterns between γδ T cells and liver hepatocytes in healthy and cancerous contexts. Overall, spacia represents a notable step in advancing quantitative theories of cellular communications.

Spatial Relationships in the Tumor Microenvironment Demonstrate Association with Pathologic Response to Neoadjuvant Chemoimmunotherapy in Muscle-invasive Bladder Cancer.

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

Bexmarilimab-induced macrophage activation leads to treatment benefit in solid tumors: The phase I/II first-in-human MATINS trial.

Macrophage Clever-1 contributes to impaired antigen presentation and suppression of anti-tumor immunity. This first-in-human trial investigates the safety and tolerability of Clever-1 blockade with bexmarilimab in patients with treatment-refractory solid tumors and assesses preliminary anti-tumor efficacy, pharmacodynamics, and immunologic correlates. Bexmarilimab shows no dose-limiting toxicities in part I (n = 30) and no additional safety signals in part II (n = 108). Disease control (DC) rates of 25%-40% are observed in cutaneous melanoma, gastric, hepatocellular, estrogen receptor-positive breast, and biliary tract cancers. DC associates with improved survival in a landmark analysis and correlates with high pre-treatment intratumoral Clever-1 positivity and increasing on-treatment serum interferon γ (IFNγ) levels. Spatial transcriptomics profiling of DC and non-DC tumors demonstrates bexmarilimab-induced macrophage activation and stimulation of IFNγ and T cell receptor signaling selectively in DC patients. These data suggest that bexmarilimab therapy is well tolerated and show that macrophage targeting can promote immune activation and tumor control in late-stage cancer.

Spatial determination and prognostic impact of the fibroblast transcriptome in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma has a poor clinical outcome and responses to immunotherapy are suboptimal. Stromal fibroblasts are a dominant but heterogenous population within the tumor microenvironment and therapeutic targeting of stromal subsets may have therapeutic utility. Here, we combine spatial transcriptomics and scRNA-Seq datasets to define the transcriptome of tumor-proximal and tumor-distal cancer-associated fibroblasts (CAFs) and link this to clinical outcome. Tumor-proximal fibroblasts comprise large populations of myofibroblasts, strongly expressed podoplanin, and were enriched for Wnt ligand signaling. In contrast, inflammatory CAFs were dominant within tumor-distal subsets and expressed complement components and the Wnt-inhibitor SFRP2. Poor clinical outcome was correlated with elevated HIF-1α and podoplanin expression whilst expression of inflammatory and complement genes was predictive of extended survival. These findings demonstrate the extreme transcriptional heterogeneity of CAFs and its determination by apposition to tumor. Selective targeting of tumor-proximal subsets, potentially combined with HIF-1α inhibition and immune stimulation, may offer a multi-modal therapeutic approach for this disease.

Pancreatic cancer is one of the deadliest and most difficult cancers to treat. It responds poorly to immunotherapy for instance, despite this approach often succeeding in enlisting immune cells to fight tumours in other organs. This may be due, in part, to a type of cell called fibroblasts. Not only do these wrap pancreatic tumours in a dense, protective layer, they also foster complex relationships with the cancerous cells: some fibroblasts may fuel tumour growth, while other may help to contain its spread. These different roles may be linked to spatial location, with fibroblasts adopting different profiles depending on their proximity with cancer calls. For example, certain fibroblasts close to the tumour resemble the myofibroblasts present in healing wounds, while those at the periphery show signs of being involved in inflammation. Being able to specifically eliminate pro-cancer fibroblasts requires a better understanding of the factors that shape the role of these cells, and how to identify them. To examine this problem, Croft et al. relied on tumour samples obtained from pancreatic cancer patients. They mapped out the location of individual fibroblasts in the vicinity of the tumour and analysed their gene activity. These experiments helped to reveal the characteristics of different populations of fibroblasts. For example, they showed that the myofibroblast-like cells closest to the tumour exhibited signs of oxygen deprivation; they also produced podoplanin, a protein known to promote cancer progression. In contrast, cells further from the cancer produced more immune-related proteins. Combining these data with information obtained from patients' clinical records, Croft et al. found that samples from individuals with worse survival outcomes often featured higher levels of podoplanin and hypoxia. Inflammatory markers, however, were more likely to be present in individuals with good outcomes. Overall, these findings could help to develop ways to selectively target fibroblasts that support the growth of pancreatic cancer. Weakening these cells could in turn make the tumour accessible to immune cells, and more vulnerable to immunotherapies.

Spatial transcriptomics: Technologies, applications and experimental considerations.

The diverse cell types of an organ have a highly structured organization to enable their efficient and correct function. To fully appreciate gene functions in a given cell type, one needs to understand how much, when and where the gene is expressed. Classic bulk RNA sequencing and popular single cell sequencing destroy cell structural organization and fail to provide spatial information. However, the spatial location of gene expression or of the cell in a complex tissue provides key clues to comprehend how the neighboring genes or cells cross talk, transduce signals and work together as a team to complete the job. The functional requirement for the spatial content has been a driving force for rapid development of the spatial transcriptomics technologies in the past few years. Here, we present an overview of current spatial technologies with a special focus on the commercially available or currently being commercialized technologies, highlight their applications by category and discuss experimental considerations for a first spatial experiment.

A maladaptive pleural environment suppresses preexisting anti-tumor activity of pleural infiltrating T cells.

Introduction: Treatment options for patients with malignant pleural effusions (MPE) are limited due, at least in part, to the unique environment of the pleural space, which drives an aggressive tumor state and governs the behavior of infiltrating immune cells. Modulation of the pleural environment may be a necessary step toward the development of effective treatments. We examine immune checkpoint molecule (ICM) expression on pleural T cells, the secretomes of pleural fluid, pleural infiltrating T cells (PIT), and ability to activate PIT ex vivo. Methods: ICM expression was determined on freshly drained and in vitro activated PIT from breast, lung and renal cell cancer. Secretomics (63 analytes) of activated PIT, primary tumor cultures and MPE fluid was determined using Luminex technology. Complementary digital spatial proteomic profiling (42 analytes) of CD45+ MPE cells was done using the Nanostring GeoMx platform. Cytolytic activity was measured against autologous tumor targets. Results: ICM expression was low on freshy isolated PIT; regulatory T cells (T-reg) were not detectable by GeoMx. In vitro activated PIT coexpressed PD-1, LAG-3 and TIGIT but were highly cytotoxic against autologous tumor and uniquely secreted cytokines and chemokines in the > 100 pM range. These included CCL4, CCL3, granzyme B, IL-13, TNFα, IL-2 IFNγ, GM-CSF, and perforin. Activated PIT also secreted high levels of IL-6, IL-8 and sIL-6Rα, which contribute to polarization of the pleural environment toward wound healing and the epithelial to mesenchymal transition. Addition of IL-6Rα antagonist to cultures reversed tumor EMT but did not alter PIT activation, cytokine secretion or cytotoxicity. Discussion: Despite the negative environment, immune effector cells are plentiful, persist in MPE in a quiescent state, and are easily activated and expanded in culture. Low expression of ICM on native PIT may explain reported lack of responsiveness to immune checkpoint blockade. The potent cytotoxic activity of activated PIT and a proof-of-concept clinical scale GMP-expansion experiment support their promise as a cellular therapeutic. We expect that a successful approach will require combining cellular therapy with pleural conditioning using immune checkpoint blockers together with inhibitors of upstream master cytokines such as the IL-6/IL-6R axis.

Nodal reactive proliferation of monocytoid B-cells may represent atypical memory B-cells.

BACKGROUND: Reactive lymphadenopathies such as toxoplasmosis and cytomegalovirus lymphadenitis are associated with monocytoid cell proliferation. Monocytoid cells are B-lymphocytes with an undetermined subset. METHODS: Using digital spatial profiling whole transcriptome analyses, this study compared monocytoid and control B-cells. The B-cell subset of monocytoid cells was assigned according to gene expression profiles. RESULTS: This study identified 466 differentially expressed genes between monocytoid and control B-cells. The cellular deconvolution algorithm identified monocytoid cells as memory B-cells instead of as naïve B-cells. A comparison of the upregulated genes revealed that atypical memory B-cells had the largest number of genes overlapping with monocytoid cells compared with other memory B-cell subsets. Atypical memory B-cell markers, namely TBX21 (T-bet), FCRL4 (IRTA1), and ITGAX (CD11c), were all upregulated in monocytoid cells. Similar to atypical memory B-cells, monocytoid cells exhibited (1) upregulated transcription factors (TBX21, TOX), (2) upregulated genes associated with B-cell inhibition (FCRL5, FCRL4) and downregulated genes associated with B-cell activation (PIK3CG, NFKB1A, CD40), (3) downregulated cell cycle-related genes (CDK6, MYC), and (4) downregulated cytokine receptors (IL4R). This study also analyzed the expression of monocytoid cell signature genes in various memory B-cell subsets. Atypical memory B-cells exhibited a gene expression pattern similar to that of monocytoid cells, but other memory B-cell subsets did not. Furthermore, monocytoid cells and marginal zone lymphomas differed in gene expression profiles. CONCLUSION: Spatial transcriptomic analyses indicated that monocytoid cells may be atypical memory B-cells.

Mapping the Immune Cell Microenvironment with Spatial Profiling in Muscle Tissue Injected with the Venom of Daboia russelii.

Pathological and inflammatory events in muscle after the injection of snake venoms vary in different regions of the affected tissue and at different time intervals. In order to study such heterogeneity in the immune cell microenvironment, a murine model of muscle necrosis based on the injection of the venom of Daboia russelii was used. Histological and immunohistochemical methods were utilized to identify areas in muscle tissue with a different extent of muscle cell damage, based on the presence of hypercontracted muscle cells, a landmark of necrosis, and on the immunostaining for desmin. A gradient of inflammatory cells (neutrophils and macrophages) was observed from heavily necrotic areas to less damaged and non-necrotic areas. GeoMx® Digital Spatial Profiler (NanoString, Seattle, WA, USA) was used for assessing the presence of markers of various immune cells by comparing high-desmin (nondamaged) and low-desmin (damaged) regions of muscle. Markers of monocytes, macrophages, M2 macrophages, dendritic cells, neutrophils, leukocyte adhesion and migration markers, and hematopoietic precursor cells showed higher levels in low-desmin regions, especially in samples collected 24 hr after venom injection, whereas several markers of lymphocytes did not. Moreover, apoptosis (BAD) and extracellular matrix (fibronectin) markers were also increased in low-desmin regions. Our findings reveal a hitherto-unknown picture of immune cell microheterogeneity in venom-injected muscle which greatly depends on the extent of muscle cell damage and the time lapse after venom injection.

Quantitative RNA assessment and long-term stability in the FFPE tumor samples using Digital Spatial Profiler.

Background: Long-term storage of tissue slides has been reported to induce reduced biomarker (e.g. proteins and messenger RNA) detection. This study aimed to evaluate the impact of long-term storage time (0, 16, 24 and 36 weeks) and treatment conditions (non-paraffin and paraffin dipping) at 4°C on RNA quality in formalin-fixed and paraffin-embedded (FFPE) tissue sections. Materials and methods: NanoString GeoMx Digital Spatial Profiling (DSP), a novel platform that allows spatial profiling, was used to profile RNA in human bladder cancer FFPE tissue sections. Results: We observed excellent consistency of quantitative DSP RNA counts of all targets between two different treatment conditions (R > 0.97, Pearson correlation) at each time point and among all four different storage time points (R > 0.96, Pearson correlation) within each treatment condition. No significant difference was observed in the percentage of target genes with sufficient signal across two different treatment conditions at any time point (0 week, P = 0.96; 16 weeks, P = 0.76; 24 weeks, P = 0.96; 36 weeks, P = 0.76, Kolmogorov-Smirnov test) and across all four different storage time points (P > 0.05, Kolmogorov-Smirnov test) in either treatment condition. Conclusion: Although both treatment conditions provided similar results in terms of count reproducibility and signal preservation, we recommend paraffin dipping to generate reproducible RNA results and optimize sample storage. Technology behind the NanoString GeoMx DSP platform shows a robust and reproducible RNA signal from multiple targets in the FFPE tissue sections stored at 4°C for at least up to 36 weeks.

PFKFB3 overexpression in monocytes of patients with colon but not rectal cancer programs pro-tumor macrophages and is indicative for higher risk of tumor relapse.

Introduction: Circulating monocytes are main source for tumor-associated macrophages (TAMs) that control tumor growth, angiogenesis, metastasis and therapy resistance. We raised the questions how monocyte programming is affected by growing tumors localized in colon and rectal sections, and how treatment onsets affect monocyte programming in the circulation. Methods: Patients with rectal cancer and colon cancer were enrolled in the study. Peripheral blood monocytes were characterized by phenotypic analysis using flow cytometry, by transcriptomic analysis using RNA sequencing and by gene expression analysis using real-time RT-PCR. Phenotypic analysis was performed with IF/confocal microscopy. Spatial transcriptomic analysis was applied using GeoMX DSP-NGS. Results: In patients with rectal cancer, increased amount of CCR2+ monocytes was indicative for the absence of both lymphatic and hematogenous metastasis. In contrast, in patients with colon cancer CD163+ monocytes were indicative for LN metastasis. NGS analysis identified tumor-specific transcriptional programming of monocytes in all CRC patients compared to healthy individuals. The key transcriptional difference between monocytes of patients with colon and rectal cancer was increased expression of PFKFB3, activator of glycolysis that is currently considered as therapy target for major solid cancers. PFKFB3-expressing monocyte-derived macrophages massively infiltrated tumor in colon. Nanostring technology identified correlation of PFKFB3 with amount and tumor-promoting properties of TAMs in colon but not in rectal cancer. PFKFB3 was indicative for tumor relapse specifically in colon cancer. Discussion: Our findings provide essential argument towards CRC definition to cover two clinically distinct cancers - colon cancer and rectal cancer, that differentially interact with innate immunity.

Spatial molecular profiling of a central nervous system low-grade diffusely infiltrative tumour with INI1 deficiency featuring a high-grade atypical teratoid/rhabdoid tumour component.

We performed spatial epigenetic and transcriptomic analyses of a highly unusual low-grade diffusely infiltrative tumour with INI1 deficiency (CNS LGDIT-INI1), which harboured a high-grade component corresponding to an atypical teratoid/rhabdoid tumour (AT/RT). Methylation profiles of both low-grade and high-grade components yielded high similarity with AT/RTs of the MYC subgroup, whereas RNA expression analyses revealed increased translational activity and MYC pathway activation in the high-grade component. Close follow-up of patients harbouring CNS LGDIT-INI1 is warranted.

Best Practices for Spatial Profiling for Breast Cancer Research with the GeoMx® Digital Spatial Profiler.

Breast cancer is a heterogenous disease with variability in tumor cells and in the surrounding tumor microenvironment (TME). Understanding the molecular diversity in breast cancer is critical for improving prediction of therapeutic response and prognostication. High-plex spatial profiling of tumors enables characterization of heterogeneity in the breast TME, which can holistically illuminate the biology of tumor growth, dissemination and, ultimately, response to therapy. The GeoMx Digital Spatial Profiler (DSP) enables researchers to spatially resolve and quantify proteins and RNA transcripts from tissue sections. The platform is compatible with both formalin-fixed paraffin-embedded and frozen tissues. RNA profiling was developed at the whole transcriptome level for human and mouse samples and protein profiling of 100-plex for human samples. Tissue can be optically segmented for analysis of regions of interest or cell populations to study biology-directed tissue characterization. The GeoMx Breast Cancer Consortium (GBCC) is composed of breast cancer researchers who are developing innovative approaches for spatial profiling to accelerate biomarker discovery. Here, the GBCC presents best practices for GeoMx profiling to promote the collection of high-quality data, optimization of data analysis and integration of datasets to advance collaboration and meta-analyses. Although the capabilities of the platform are presented in the context of breast cancer research, they can be generalized to a variety of other tumor types that are characterized by high heterogeneity.

High-Plex and High-Throughput Digital Spatial Profiling of Non-Small-Cell Lung Cancer (NSCLC).

Profiling the tumour microenvironment (TME) has been informative in understanding the underlying tumour-immune interactions. Multiplex immunohistochemistry (mIHC) coupled with molecular barcoding technologies have revealed greater insights into the TME. In this study, we utilised the Nanostring GeoMX Digital Spatial Profiler (DSP) platform to profile a non-small-cell lung cancer (NSCLC) tissue microarray for protein markers across immune cell profiling, immuno-oncology (IO) drug targets, immune activation status, immune cell typing, and pan-tumour protein modules. Regions of interest (ROIs) were selected that described tumour, TME, and normal adjacent tissue (NAT) compartments. Our data revealed that paired analysis (n = 18) of matched patient compartments indicate that the TME was significantly enriched in CD27, CD3, CD4, CD44, CD45, CD45RO, CD68, CD163, and VISTA relative to the tumour. Unmatched analysis indicated that the NAT (n = 19) was significantly enriched in CD34, fibronectin, IDO1, LAG3, ARG1, and PTEN when compared to the TME (n = 32). Univariate Cox proportional hazards indicated that the presence of cells expressing CD3 (hazard ratio (HR): 0.5, p = 0.018), CD34 (HR: 0.53, p = 0.004), and ICOS (HR: 0.6, p = 0.047) in tumour compartments were significantly associated with improved overall survival (OS). We implemented both high-plex and high-throughput methodologies to the discovery of protein biomarkers and molecular phenotypes within biopsy samples, and demonstrate the power of such tools for a new generation of pathology research.

GeoMx™ RNA Assay: High Multiplex, Digital, Spatial Analysis of RNA in FFPE Tissue.

RNA in situ hybridization (ISH) is a widely used technique for the localization of mRNA in tissues. Limitations to traditional ISH include the number of targets that can be analyzed concurrently and the ability for many of these assays to be used in formalin-fixed, paraffin-embedded tissues (FFPE). Here, we describe the GeoMx™ RNA assay that is capable of the highly multiplexed detection of mRNA targets in FFPE tissues. This assay utilizes ISH probes linked to indexing oligo barcodes via a photocleavable linker and the GeoMx Digital Spatial Profiler (DSP) Instrument to enable profiling of RNA targets in a region-of-interest-based method. In brief, 5 µm FFPE sections are dewaxed, target retrieved, digested with proteinase K, post-fixed, and then incubated overnight with GeoMx RNA detection probes. Stringent washes are performed followed by the addition of fluorescently labeled antibodies for use as morphology markers. User-defined regions of interest are then profiled on the GeoMx DSP through region-specific cleaving and collecting the photocleaved indexing oligos. Cleaved indices are then quantified using NanoString nCounter® Technology generating digital quantification of RNA expression with spatial context.