BACKGROUND:Stomach cancer is the fourth leading cause of cancer-related deaths worldwide. Helicobacter pylori is the main risk factor for gastric adenocarcinoma (GAC), yet the precise mechanism underpinning this association remains controversial. Gastric intestinal metaplasia (GIM) represents the precancerous stage and follows H. pylori-associated chronic gastritis (CG). Sequencing studies have revealed fewer H. pylori and more non-H. pylori bacteria in GAC. However, the spatial organization of the gastric microbiota in health and disease is unknown. MATERIALS AND METHODS:Here, we have combined RNA in situ hybridization and immunohistochemistry to detect H. pylori, non-H. pylori bacteria, and host cell markers (E-cadherin, Mucins 5AC and 2) on tissue sections from patients with CG (n = 15) and GIM (n = 17). RESULTS:Quantitative analysis of whole slide scans revealed significant correlations of H. pylori and other bacteria in CG and GIM. In contrast to sequencing studies, significantly fewer non-H. pylori bacteria were detected in H. pylori-negative patients. Importantly, whilst H. pylori exclusively colonized the gastric glands, non-H. pylori bacteria invaded the lamina propria in 6/9 CG and 8/10 GIM H. pylori-positive patients. A rapid and cost-effective modified Gram stain was used to confirm these findings and enabled detection of non-H. pylori bacteria in GIM samples. CONCLUSIONS:The invasion of the gastric lamina propria by non-H. pylori bacteria during H. pylori-associated CG and GIM represents an overlooked phenomenon in cancer progression. Further work must determine the mechanisms underlying the synergistic roles of H. pylori and other bacteria in carcinogenesis. This observation should redirect attempts to prevent, diagnose, and treat GAC.

Abstract Head and neck cancer (HNC) is a heterogeneous group of malignancies that arise from the mucosal surfaces of the upper aerodigestive tract. The tumor microenvironment (TME) of HNC is characterized by the presence of immune cells, stromal cells, and extracellular matrix components. A key feature of the TME is hypoxia, which promotes tumor growth, invasion, and metastasis by altering the expression of genes involved in angiogenesis, cell survival, and metabolism. Understanding the complex interplay between hypoxia and immune infiltrates in the TME of HNC is crucial for the development of novel therapeutic strategies for the treatment of this disease. Whole transcriptome analysis by digital spatial profiling is an excellent method of probing the TME, but assessing large cohorts can be time consuming. Automating a profiling workflow to reduce hands-on time and region of interest (ROI) selection bias will enable exploration of large cohorts to identify mechanisms of action, potential drug targets, and biomarkers. We developed an optimized spatial multi-omic workflow to enable high-throughput spatial analysis on GeoMx® Digital Spatial Profiler (DSP) using the Whole Transcriptome Atlas (WTA) and immuno-fluorescent morphology markers: SYTO82 (nuclei), CAIX (hypoxia), pan-cytokeratin (epithelium), CD3 (T-cells). A.I.-based analysis (Oncotopix® Discovery) of serial section H&E images and GeoMx IF images was developed to identify ROIs for GeoMx collection. Immune hot and cold selection used leukocyte density; tumor/stromal interface selection used epithelial areas. Areas of illumination (AOI) were chosen using concentric CAIX expression gradients. Integrated analysis of digital images using Oncotopix Discovery and the whole transcriptome was done to assess the above TME compartments. Automated ROI placement based on tumor/stroma, hypoxia and immune infiltration and AI/Deep Learning based AOI segmentation reduced AOI selection time and improved accuracy of tissue compartment enrichment, especially between samples and tissue types. Automated development of hypoxia gradient-based AOI enabled a selection strategy not possible in the standard DSP software. Cell phenotyping using IF morphology scan was used to supervise cell deconvolution. DSP results correlated well with patient outcomes. This work shows that ROI-based spatial analyses can be used to explore the effects of hypoxia levels on immune infiltration in HNC. Automated AI-based ROI selection provides a means of sampling relevant tumor subtypes based on hypoxia and immune infiltrate criteria in an unbiased, reproducible manner, and can provide a standardized, automated method for selecting ROIs and segmenting AOIs across a cohort of mixed tissue types and pathological subtype, improving throughput. Citation Format: David Mason, Kyla Teplitz, James Robert Mansfield, Kelly Hunter, Joana Campos, Jill Brooks. Automating a spatial profiling workflow to explore the effects of hypoxia in the tumor microenvironment in head and neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5505.

Breast cancer poses a global health challenge, yet the influence of ethnicity on the tumor microenvironment (TME) remains understudied. In this investigation, we examined immune cell infiltration in 230 breast cancer samples, emphasizing diverse ethnic populations. Leveraging tissue microarrays (TMAs) and core samples, we applied multiplex immunofluorescence (mIF) to dissect immune cell subtypes across TME regions. Our analysis revealed distinct immune cell distribution patterns, particularly enriched in aggressive molecular subtypes triple-negative and HER2-positive tumors. We observed significant correlations between immune cell abundance and key clinicopathological parameters, including tumor size, lymph node involvement, and patient overall survival. Notably, immune cell location within different TME regions showed varying correlations with clinicopathologic parameters. Additionally, ethnicities exhibited diverse distributions of cells, with certain ethnicities showing higher abundance compared to others. In TMA samples, patients of Chinese and Caribbean origin displayed significantly lower numbers of B cells, TAMs, and FOXP3-positive cells. These findings highlight the intricate interplay between immune cells and breast cancer progression, with implications for personalized treatment strategies. Moving forward, integrating advanced imaging techniques, and exploring immune cell heterogeneity in diverse ethnic cohorts can uncover novel immune signatures and guide tailored immunotherapeutic interventions, ultimately improving breast cancer management.

Stomach cancer is the fourth leading cause of cancer-related deaths worldwide. Helicobacter pylori is the main risk factor for gastric adenocarcinoma (GAC), yet the mechanism underpinning this association remains uncharacterised. Gastric intestinal metaplasia (GIM) represents the pre-cancerous stage and follows H. pylori- associated chronic gastritis (CG). Sequencing studies have revealed fewer H. pylori and more non- H. pylori bacteria in GAC. However, the spatial organisation of the gastric microbiota in health and disease is unknown. Here, we have combined RNA in situ hybridisation and immunohistochemistry to detect H. pylori , non- H. pylori bacteria and host cell markers (E-cadherin, Mucins 5AC and 2) from patients with CG (n=9), GIM (n=12), GAC and normal tissue adjacent to tumours (NATs) (n=3). Quantitative analysis of whole slide scans revealed significant correlations of H. pylori and other bacteria in CG and GIM samples. In contrast to sequencing studies, significantly fewer non- H. pylori bacteria were detected in H. pylori- negative patients. Importantly, whilst H. pylori exclusively colonised the gastric glands, non- H. pylori bacteria invaded the lamina propria in 3/4 CG and 5/6 GIM H. pylori -positive patients. Bacterial invasion was observed in 3/3 GAC samples and at higher levels than matched NATs. We propose that H. pylori ‘holds the keys’ to disrupt the gastric epithelial barrier, facilitating the opportunistic invasion of non- H. pylori bacteria to the lamina propria. Bacterial invasion could be a significant driver of inflammation in H. pylori- associated carcinogenesis. This proposed mechanism would both explain the synergistic roles of H. pylori and other bacteria and redirect attempts to prevent, diagnose and treat GAC.### Competing Interest StatementThe authors have declared no competing interest.

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.

BackgroundThe incidence of oropharyngeal cancer (OPC) is increasing, due mainly to a rise in Human Papilloma Virus (HPV)-mediated disease. HPV-mediated OPC has significantly better prognosis compared with HPV-negative OPC, stimulating interest in treatment de-intensification approaches to reduce long-term sequelae. Routine clinical testing frequently utilises immunohistochemistry to detect upregulation of p16 as a surrogate marker of HPV-mediation. However, this does not detect discordant p16-/HPV+ cases and incorrectly assigns p16+/HPV- cases, which, given their inferior prognosis compared to p16+/HPV+, may have important clinical implications. The biology underlying poorer prognosis of p16/HPV discordant OPC requires exploration.MethodsGeoMx digital spatial profiling was used to compare the expression patterns of selected immuno-oncology-related genes/gene families (n=73) within the tumour and stromal compartments of formalin-fixed, paraffin-embedded OPC tumour tissues (n=12) representing the three subgroups, p16+/HPV+, p16+/HPV- and p16-/HPV-.ResultsKeratin (multi KRT) and HIF1A, a key regulator of hypoxia adaptation, were upregulated in both p16+/HPV- and p16-/HPV- tumours relative to p16+/HPV+. Several genes associated with tumour cell proliferation and survival (CCND1, AKT1 and CD44) were more highly expressed in p16-/HPV- tumours relative to p16+/HPV+. Conversely, multiple genes with potential roles in anti-tumour immune responses (immune cell recruitment/trafficking, antigen processing and presentation), such as CXCL9, CXCL10, ITGB2, PSMB10, CD74, HLA-DRB and B2M, were more highly expressed in the tumour and stromal compartments of p16+/HPV+ OPC versus p16-/HPV- and p16+/HPV-. CXCL9 was the only gene showing significant differential expression between p16+/HPV- and p16-/HPV- tumours being upregulated within the stromal compartment of the former.ConclusionsIn terms of immune-oncology-related gene expression, discordant p16+/HPV- OPCs are much more closely aligned with p16-/HPV-OPCs and quite distinct from p16+/HPV+ tumours. This is consistent with previously described prognostic patterns (p16+/HPV+ >> p16+/HPV- > p16-/HPV-) and underlines the need for dual p16 and HPV testing to guide clinical decision making.

Human Papilloma virus (HPV)-mediated oropharyngeal cancer (OPC) has significantly better prognosis compared with HPV-negative, stimulating interest in treatment de-intensification approaches to reduce long-term sequelae. Routine clinical testing frequently utilises immunohistochemistry to detect upregulation of p16 protein as a surrogate marker of HPV-mediation. However, this does not detect discordant HPV+/p16- cases and incorrectly assigns HPV-/p16+ cases, which, given their inferior prognosis compared to HPV+/p16+, may have important clinical implications. The biology underlying poorer prognosis of HPV/p16 discordant OPC requires exploration. Here, we utilised digital spatial profiling to compare the expression patterns of selected immune-oncology-related genes within the tumour and stromal compartments of HPV+/p16+, HPV-/p16+ and HPV-/p16- OPC tumour tissues (n=12). KRT and HIF1A were upregulated in HPV-/p16+ and HPV-/p16- tumours relative to HPV+/p16+. Conversely, multiple genes associated with antitumour immune responses (such as CXCL9, CXCL10, CD74) were upregulated in HPV+/p16+ tumours. Of note, HPV-/p16+ and HPV-/p16- tumours displayed highly similar gene expression profiles, with only CXCL9 showing differential expression in stromal regions. These results are consistent with described prognostic patterns (HPV+p16+ > HPV-/p16+ > HPV-/p16-) and underline the need for dual HPV and p16 testing to guide clinical decision making. ### Competing Interest Statement KH works for Propath. HM reports advisory board fees from AstraZeneca, MSD, Merck, Nanobiotix, and Seagen and is Director of Warwickshire head neck clinic and Docpsert Health. The other authors declare no competing interests. ### Funding Statement This work was funded by Cancer Research UK and National Institute for Health Research (NIHR) UK. The views expressed in this article are those of the authors and not necessarily those of the NIHR. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethical approval for use of tissue samples in translational research was granted by North West - Preston Research Ethics Committee (Reference: 16/NW/0265). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data is available on request from the corresponding author.

The interest and utility of high-plex spatial profiling of RNA and protein biomarkers has increased over the last few years. The implementation of high-plex analyte spatial platforms, such as GeoMx® Digital Spatial Profiler (DSP), is increasing within discovery and development approaches for biomarkers associated with clinical outcome. The surge in spatial platforms parallels the increase of digital pathology in translational and clinical research studies. The integration of these two workflows has the potential to benefit diagnostic and therapeutic development. This study aims to facilitate the implementation of DSP in tissue analysis workflows helping those involved in drug discovery and development efforts to (1) assess platform feasibility for their research, (2) design effective DSP experiments, and (3) enable generation of high-quality, usable spatial data from large cohort studies. The BioPharma GeoMx DSP Consortium has developed consensus-based best practices incorporating the expertise of panel members via virtual meetings. Best practices guidelines for spatial profiling of tissue biopsies in drug discovery and development using GeoMx stands to advance current standard practices in tissue analysis. These best practices recommendations encompass every step of the implementation of DSP in standard tissue analysis workflows, emphasizing the importance of multidisciplinary stakeholder involvement, testing, defining experimental conditions prior to execution of large-scale studies, and considerations in assessing assay performance. This study offers a practical reference for the optimal implementation of GeoMx DSP in exploratory sample analysis for drug discovery and development studies. Citation Format: Leslie Abad, Maxine McClain, Edward Bonnevie, Benjamin Chen, Sarah Church, Gokhan Demirkan, Premi Haynes, Kelly Hunter, Anil Kersarwani, David Krull, Yan Liang, Prithwish Pal, Corinne Ramos, Deniliz Rodriguez, Jessica Runyon, Julien Tessier, Esperanza Anguiano. A BioPharma best practices framework to enable successful morphology guided spatial biology studies using NanoString GeoMx® Digital Spatial Profiler [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 986.

Introduction: Inflammatory breast cancer (IBC) is an aggressive form of breast cancer with a poorly characterized immune microenvironment. Methods: We used a five-colour multiplex immunofluorescence panel, including CD68, CD4, CD8, CD20, and FOXP3 for immune microenvironment profiling in 93 treatment-naïve IBC samples. Results: Lower grade tumours were characterized by decreased CD4+ cells but increased accumulation of FOXP3+ cells. Increased CD20+ cells correlated with better response to neoadjuvant chemotherapy and increased CD4+ cells infiltration correlated with better overall survival. Pairwise analysis revealed that both ER+ and triple-negative breast cancer were characterized by co-infiltration of CD20 + cells with CD68+ and CD4+ cells, whereas co-infiltration of CD8+ and CD68+ cells was only observed in HER2+ IBC. Co-infiltration of CD20+, CD8+, CD4+, and FOXP3+ cells, and co-existence of CD68+ with FOXP3+ cells correlated with better therapeutic responses, while resistant tumours were characterized by co-accumulation of CD4+, CD8+, FOXP3+, and CD68+ cells and co-expression of CD68+ and CD20+ cells. In a Cox regression model, response to therapy was the most significant factor associated with improved patient survival. Conclusion: Those results reveal a complex unique pattern of distribution of immune cell subtypes in IBC and provide an important basis for detailed characterization of molecular pathways that govern the formation of IBC immune landscape and potential for immunotherapy.

IntroductionCharacterization of the tumour immune infiltrate (notably CD8+ T-cells) has strong predictive survival value for cancer patients. Quantification of CD8 T-cells alone cannot determine antigenic experience, as not all infiltrating T-cells recognize tumour antigens. Activated tumour-specific tissue resident memory CD8 T-cells (TRM) can be defined by the co-express of CD103, CD39 and CD8. We investigated the hypothesis that the abundance and localization of TRM provides a higher-resolution route to patient stratification.MethodsA comprehensive series of 1000 colorectal cancer (CRC) were arrayed on a tissue microarray, with representative cores from three tumour locations and the adjacent normal mucosa. Using multiplex immunohistochemistry we quantified and determined the localization of TRM.ResultsAcross all patients, activated TRM were an independent predictor of survival, and superior to CD8 alone. Patients with the best survival had immune-hot tumours heavily infiltrated throughout with activated TRM. Interestingly, differences between right- and left-sided tumours were apparent. In left-sided CRC, only the presence of activated TRM (and not CD8 alone) was prognostically significant. Patients with low numbers of activated TRM cells had a poor prognosis even with high CD8 T-cell infiltration. In contrast, in right-sided CRC, high CD8 T-cell infiltration with low numbers of activated TRM was a good prognosis.ConclusionThe presence of high intra-tumoural CD8 T-cells alone is not a predictor of survival in left-sided CRC and potentially risks under treatment of patients. Measuring both high tumour-associated TRM and total CD8 T-cells in left-sided disease has the potential to minimize current under-treatment of patients. The challenge will be to design immunotherapies, for left-sided CRC patients with high CD8 T-cells and low activate TRM,that result in effective immune responses and thereby improve patient survival.

Immunofibroblasts have been described within tertiary lymphoid structures (TLS) that regulate lymphocyte aggregation at sites of chronic inflammation. Here we report, for the first time, an immunoregulatory property of this population, dependent on inducible T-cell co-stimulator ligand and its ligand (ICOS/ICOS-L). During inflammation, immunofibroblasts, alongside other antigen presenting cells, like dendritic cells (DCs), upregulate ICOSL, binding incoming ICOS + T cells and inducing LTα3 production that, in turn, drives the chemokine production required for TLS assembly via TNFRI/II engagement. Pharmacological or genetic blocking of ICOS/ICOS-L interaction results in defective LTα expression, abrogating both lymphoid chemokine production and TLS formation. These data provide evidence of a previously unknown function for ICOSL-ICOS interaction, unveil a novel immunomodulatory function for immunofibroblasts, and reveal a key regulatory function of LTα3, both as biomarker of TLS establishment and as first driver of TLS formation and maintenance in mice and humans.

Tissue analysis of lymphoproliferative disease in the clinical or research settings demands multiple immunohistochemistry with the assessment of co-localisation of expression of markers. Multiplex immunohistochemistry (MIHC) is ideally suited to this task, enabling simultaneous assessment of a number of markers on a single section, thus reducing interpretive errors and preserving tissue for further analyses. The range of current and emerging MIHC platforms offer an opportunity to gain unprecedented insight into the cellular and immunological milieu of lymphoproliferative disease and have been applied in research. These include techniques which use more traditional chromogenic and fluorescent detection systems. They have been refined in the recent years with improved chemistries, iterative rounds of staining and advanced imaging techniques such as multispectral analysis. The newer generation of MIHC have overcome the limitations of the traditional techniques by utilizing novel detection systems such as imaging mass cytometry and molecular barcoding. In addition, by combining the identification of morphological features, large panels of proteins and mRNA transcripts into “digital spatial profiling”, MIHC techniques are contributing to the in-situ ‘multi-omic’ approach to pathology. MIHC has improved our understanding in several areas of lymphoma pathology, in particular, the role of the immune microenvironment in pathogenesis, prognosis and treatment stratification. Despite the exciting opportunities offered by MIHC platforms, few are used in routine diagnostics, reflecting the need for validation studies in the clinical settings. This paper provides an overview of MIHC, with notable examples of application in the research of lymphoproliferative processes and some relating to potential use in routine diagnosis.