Spatial Distribution Of Cells Research Articles

Mast cell density in Merkel cell carcinoma and its correlation with prognostic features and MCPyV status: a pilot study

Merkel cell carcinoma (MCC) is a rare, highly aggressive, primitive neuroendocrine carcinoma of the skin, the origin of which is not yet fully understood. Numerous independent prognostic factors have been investigated in an attempt to understand which are the most important parameters to indicate in the histological diagnostic report of MCC. Of these, mast cells have only been studied in one paper before this one. We present a retrospective descriptive study of 13 cases of MCC, received at the Department of Pathology over a 20-year period (2003–2023 inclusive) on which we performed a study using whole-slide (WSI) morphometric analysis scanning platform Aperio Scanscope CS for the detection and spatial distribution of mast cells, using monoclonal anti-tryptase antibody and anti-CD34 monoclonal antibody to study the density of microvessels. In addition, we analyzed MCPyV status with the antibody for MCPyV large T-antigen (Clone CM2B4). We found statistically significant correlation between mast cell density and local recurrence/distant metastasis/death-of-disease (p = 0.008). To our knowledge, we firstly reported that MCPyV ( −) MCC shows higher mast cells density compared to MCPyV ( +) MCC, the latter well known to be less aggressive. Besides, the median vascular density did not show no significant correlation with recurrence/metastasis/death-of-disease, (p = 0.18). Despite the small sample size, this paper prompts future studies investigating the role of mast cell density in MCC.

HER2 quantitative continuous scoring for accurate patient selection in HER2 negative trastuzumab deruxtecan treated breast cancer

Many targeted cancer therapies rely on biomarkers assessed by scoring of immunohistochemically (IHC)-stained tissue, which is subjective, semiquantitative, and does not account for expression heterogeneity. We describe an image analysis-based method for quantitative continuous scoring (QCS) of digital whole-slide images acquired from baseline human epidermal growth factor receptor 2 (HER2) IHC-stained breast cancer tissue. Candidate signatures for patient stratification using QCS of HER2 expression on subcellular compartments were identified, addressing the spatial distribution of tumor cells and tumor-infiltrating lymphocytes. Using data from trastuzumab deruxtecan-treated patients with HER2-positive and HER2-negative breast cancer from a phase 1 study (NCT02564900; DS8201-A-J101; N = 151), QCS-based patient stratification showed longer progression-free survival (14.8 vs 8.6 months) with higher prevalence of patient selection (76.4 vs 56.9%) and a better cross-validated log-rank p value (0.026 vs 0.26) than manual scoring based on the American Society of Clinical Oncology / College of American Pathologists guidelines. QCS-based features enriched the HER2-negative subgroup by correctly predicting 20 of 26 responders.

Immune cell patterns before and after neoadjuvant immune checkpoint blockade combined with chemoradiotherapy in locally advanced esophageal squamous cell carcinoma

BackgroundNeoadjuvant immune checkpoint blockade (ICB) combined with chemoradiotherapy offers high pathologic complete response (pCR) rate for patients with locally advanced esophageal squamous cell carcinomas (ESCC). But the dynamic tumor immune microenvironment modulated by such neoadjuvant therapy remains unclear.Patients and methodsA total of 41 patients with locally advanced ESCC were recruited. All patients received neoadjuvant toripalimab combined with concurrent chemoradiotherapy. Matched pre- and post-treatment tissues were obtained for fluorescent multiplex immunohistochemistry (mIHC) and IHC analyses. The densities and spatial distributions of immune cells were determined by HALO modules. The differences of immune cell patterns before and after neoadjuvant treatment were investigated.ResultsIn the pre-treatment tissues, more stromal CD3 + FoxP3 + Tregs and CD86+/CD163 + macrophages were observed in patients with residual tumor existed in the resected lymph nodes (pN1), compared with patients with pCR. The majority of macrophages were distributed in close proximity to tumor nest in pN1 patients. In the post-treatment tissues, pCR patients had less CD86 + cell infiltration, whereas higher CD86 + cell density was significantly associated with higher tumor regression grades (TRG) in non-pCR patients. When comparing the paired pre- and post-treatment samples, heterogeneous therapy-associated immune cell patterns were found. Upon to the treatment, CD3 + T lymphocytes were slightly increased in pCR patients, but markedly decreased in non-pCR patients. In contrast, a noticeable increase and a less obvious decrease of CD86 + cell infiltration were respectively depicted in non-pCR and pCR patients. Furthermore, opposite trends of the treatment-induced alterations of CD8 + and CD15 + cell infiltrations were observed between pN0 and pN1 patients.ConclusionsCollectively, our data demonstrate a comprehensive picture of tumor immune landscape before and after neoadjuvant ICB combined with chemoradiotherapy in ESCC. The infiltration of CD86 + macrophage may serve as an unfavorable indicator for neoadjuvant toripalimab combined with chemoradiotherapy.

Systematic analysis of ocular features and responses of cultured spotted wolffish (Anarhichas minor).

A better understanding of unique anatomical and functional features of the visual systems of teleost fish could provide key knowledge on how these systems influence the health and survival of these animals in both wild and culture environments. We took a systematic approach to assess some of the visual systems of spotted wolffish (Anarhichas minor), a species of increasing importance in North Atlantic aquaculture initiatives. The lumpfish (Cyclopterus lumpus) was included in these studies in a comparative manner to provide reference. Histology, light and electron microscopy were used to study the spatial distribution and occurrence of cone photoreceptor cells and the nature of the retinal tissues, while immunohistochemistry was used to explore the expression patterns of two photoreceptor markers, XAP-1 and XAP-2, in both species. A marine bacterial infection paradigm in lumpfish was used to assess how host-pathogen responses might impact the expression of these photoreceptor markers in these animals. We define a basic photoreceptor mosaic and present an ultrastructural to macroscopic geographical configuration of the retinal pigment tissues in both animals. Photoreceptor markers XAP-1 and XAP-2 have novel distribution patterns in spotted wolffish and lumpfish retinas, and exogenous pathogenic influences can affect the normal expression pattern of XAP-1 in lumpfish. Live tank-side ophthalmoscopy and spectral domain optical coherence tomography (SD-OCT) revealed that normal cultured spotted wolffish display novel variations in the shape of the retinal tissue. These two complementary imaging findings suggest that spotted wolffish harbour unique ocular features not yet described in marine teleosts and that visual function might involve specific retinal tissue shape dynamics in these animals. Finally, extensive endogenous biofluorescence is present in the retinal tissues of both animals, which raises questions about how these animals might use retinal tissue in novel ways for visual perception and/or communication. This work advances fundamental knowledge on the visual systems of two economically important but now threatened North Atlantic teleosts and provides a basic foundation for further research on the visual systems of these animals in health versus disease settings. This work could also be useful for understanding and optimizing the health and welfare of lumpfish and spotted wolffish in aquaculture towards a one health or integrative perspective.

Abstract PO4-26-01: Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine

Abstract While targeted cancer therapies often rely on subjective and semi-quantitative visual assessment of protein biomarkers by pathologists through immunohistochemically stained tissue, the transformative force of computational pathology is reshaping healthcare by unleashing unprecedented diagnostic accuracy and unlocking personalized treatments. In recent years, we have established a large integrated computational pathology unit to foster collaboration between interdisciplinary teams of computer scientists, pathologists, molecular biologists, and data scientists. This integration of cutting-edge technologies enabled us to develop a computational pathology approach called Quantitative Continuous Scoring (QCS). QCS deploys the power of Deep Learning (DL) to provide objective and continuous expression data of biomarkers in digitized IHC whole slide images (WSI), particularly of proteins expressed at low levels. While manual scoring of IHC WSIs is limited by subjectivity and semi-quantitative assessment of protein expression, QCS overcomes these limitations with an unprecedented accuracy. QCS utilizes two DL-based algorithms, which we developed fully supervised by using pathologist input as the reference standard. These algorithms identify invasive tumour areas and segment each tumour cell across the WSI into cell nuclei, cytoplasm and membrane. Based on an accurate subcellular segmentation, we can compute biomarker expression, on a continuous scale, as mean Optical Density (OD) in each subcellular compartment based on the Hue-Saturation-Density (HSD) model. Therefore, this approach enables precise detection of the low biomarker expression range with single-cell resolution. Importantly, it also allows the computation of the spatial distribution of tumour cells across the WSI. We have successfully used QCS to drive the selection of antibody clones for IHC assays and to delineate the mode of action and PK/PD mechanisms. Of note, the combination of assessing continuous target expression and capturing the spatial distribution of tumor cells has provided surrogate markers to predict potential bystander activity of antibody drug conjugates (ADCs). This approach outperformed traditional pathologist scoring in identifying patient populations having maximum treatment benefit through retrospective analysis of multiple clinical trials. At present, all computational pathology approaches are developed based on conventional IHC assays that have been optimized for manual scoring. Importantly, we draw a vision in which the assay serves as a critical catalyst for unleashing the full potential of computational pathology by providing high-quality, standardized data inputs. We suggest an approach utilizing orthogonal methods as a reference standard to develop highly sensitive IHC assays, capable of detecting even subtle molecular and cellular changes with precision and exhibiting exceptional specificity for accurately identifying and distinguishing target biomarkers from background noise. In summary, we here describe and discuss a computational pathology-based approach for precise biomarker quantification and superior patient selection with broad applicability and the potential to transform the very fabric of how we diagnose and treat cancer. Citation Format: Mark Gustavson, Markus Schick, Ansh Kapil, Anatoliy Shumilov, Carl Barrett, Hadassah Sade. Computational pathology: Revolutionizing diagnostics and clearing the way for precision medicine [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-01.

The spatial distribution of CFTR-rich Ionocytes cells in the postnatal mouse airway development

Ionocytes are a new type of rare airway epithelial cells expressing Ascl3 and Foxi1 transcription factors, as well as 50% of Cftr-transcripts in mouse airways. However, their role and precise location remain mostly unexplored. This research aimed to shed light on ionocyte ontogeny and distribution within the mouse airway epithelium. Mice were bred in the C57Bl6/J background and maintained in the Specific Pathogen Free mouse facility of Centro de Estudios Científicos (CECs) with access to food and water ad libitum. We used 1,7, 10, 14,21 and 28-days-old wild-type mice, 6 and 8-week-old, and 1 year wild-type and 14-days-old 6 and 8-week-old CftrΔF508/ΔF508 animals. The tracheas were sliced in frontal sections, and the ionocytes were identified by immunofluorescence against the FOXI1 transcription factor. All values were expressed as mean ± S.E.M. All animal procedures were approved by the institutional IACUC (CECS-2022-03). We found that FOXI1+cells had a triangular shape with a basolateral process. Unexpectedly, we observed that FOXI1+cells appear postnatally close to the submucosal glands (SMG), and its number increases drastically between 6 and 8-week-old wild type mice. The quantity of FOXI1+cells cells in the adult trachea decreased towards the distal part (proximal=11.2±1.2 vs distal=4.0±0.9 FOXI1+cells/mm basal lamina, n=7, P=<0,001, t-test), and we did not find significative differences between WT and CftrΔF508/ΔF508 adult mouse. FOXI1+cells were often observed in the epithelia around the collecting duct exit and in the collecting duct epithelium of the SMG. In conclusion, our study provides new insights into the localization and distribution of ionocytes in the mouse airway epithelium. Our results indicate that ionocytes may play a role in regulating mucus composition in upper airways. We suggest that age-dependent changes in cell quantity might reflect the need of increased CFTR function in adult stages. Further research is needed to fully understand the function of ionocytes in the airway and their potential role in respiratory diseases such as cystic fibrosis. Proyecto Postdoctoral 3220672 Proyecto FONDECYT 1221257. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Hematopoietic Clonal Evolution Goes Spatial.

The spatial distribution of cells carrying clonal hematopoiesis mutations in the bone marrow and the potential role of interactions with the microenvironment are largely unknown. This study takes clonal evolution to the spatial level by describing a novel technique examining the spatial location of mutated clones in the bone marrow and the first evidence that mutated hematopoietic clones are spatially constrained and have heterogenous locations within millimeters of distance. See related article by Young et al., p. 153 (10).

Acute intoxication with diisopropylfluorophosphate promotes cellular senescence in the adult male rat brain.

Acute intoxication with high levels of organophosphate (OP) cholinesterase inhibitors can cause cholinergic crisis, which is associated with acute, life-threatening parasympathomimetic symptoms, respiratory depression and seizures that can rapidly progress to status epilepticus (SE). Clinical and experimental data demonstrate that individuals who survive these acute neurotoxic effects often develop significant chronic morbidity, including behavioral deficits. The pathogenic mechanism(s) that link acute OP intoxication to chronic neurological deficits remain speculative. Cellular senescence has been linked to behavioral deficits associated with aging and neurodegenerative disease, but whether acute OP intoxication triggers cellular senescence in the brain has not been investigated. Here, we test this hypothesis in a rat model of acute intoxication with the OP diisopropylfluorophosphate (DFP). Adult male Sprague-Dawley rats were administered DFP (4mg/kg, s.c.). Control animals were administered an equal volume (300µL) of sterile phosphate-buffered saline (s.c.). Both groups were subsequently injected with atropine sulfate (2mg/kg, i.m.) and 2-pralidoxime (25mg/kg, i.m.). DFP triggered seizure activity within minutes that rapidly progressed to SE, as determined using behavioral seizure criteria. Brains were collected from animals at 1, 3, and 6months post-exposure for immunohistochemical analyses of p16, a biomarker of cellular senescence. While there was no immunohistochemical evidence of cellular senescence at 1-month post-exposure, at 3- and 6-months post-exposure, p16 immunoreactivity was significantly increased in the CA3 and dentate gyrus of the hippocampus, amygdala, piriform cortex and thalamus, but not the CA1 region of the hippocampus or the somatosensory cortex. Co-localization of p16 immunoreactivity with cell-specific biomarkers, specifically, NeuN, GFAP, S100β, IBA1 and CD31, revealed that p16 expression in the brain of DFP animals is neuron-specific. The spatial distribution of p16-immunopositive cells overlapped with expression of senescence associated β-galactosidase and with degenerating neurons identified by FluoroJade-C (FJC) staining. The co-occurrence of p16 and FJC was positively correlated. This study implicates cellular senescence as a novel pathogenic mechanism underlying the chronic neurological deficits observed in individuals who survive OP-induced cholinergic crisis.

Spatial Distribution of Macrophage and Lymphocyte Subtypes within Tumor Microenvironment to Predict Recurrence of Non-Muscle-Invasive Papillary Urothelial Carcinoma after BCG Immunotherapy.

Non-muscle-invasive papillary urothelial carcinoma (NMIPUC) of the urinary bladder is the most common type of bladder cancer. Intravesical Bacille Calmette-Guerin (BCG) immunotherapy is applied in patients with a high risk of recurrence and progression of NMIPUC to muscle-invasive disease. However, the tumor relapses in about 30% of patients despite the treatment, raising the need for better risk stratification. We explored the potential of spatial distributions of immune cell subtypes (CD20, CD11c, CD163, ICOS, and CD8) within the tumor microenvironment to predict NMIPUC recurrence following BCG immunotherapy. Based on analyses of digital whole-slide images, we assessed the densities of the immune cells in the epithelial-stromal interface zone compartments and their distribution, represented by an epithelial-stromal interface density ratio (IDR). While the densities of any cell type did not predict recurrence, a higher IDR of CD11c (HR: 0.0012, p-value = 0.0002), CD8 (HR: 0.0379, p-value = 0.005), and ICOS (HR: 0.0768, p-value = 0.0388) was associated with longer recurrence-free survival (RFS) based on the univariate Cox regression. The history of positive repeated TUR (re-TUR) (HR: 4.93, p-value = 0.0001) and T1 tumor stage (HR: 2.04, p-value = 0.0159) were associated with shorter RFS, while G3 tumor grade according to the 1973 WHO classification showed borderline significance (HR: 1.83, p-value = 0.0522). In a multivariate analysis, the two models with a concordance index exceeding 0.7 included the CD11c IDR in combination with either a history of positive re-TUR or tumor stage. We conclude that the CD11c IDR is the most informative predictor of NMIPUC recurrence after BCG immunotherapy. Our findings highlight the importance of assessment of the spatial distribution of immune cells in the tumor microenvironment.

Spatial and single-cell colocalisation analysis reveals MDK-mediated immunosuppressive environment with regulatory T cells in colorectal carcinogenesis

Cell-cell interaction factors that facilitate the progression of adenoma to sporadic colorectal cancer (CRC) remain unclear, thereby hindering patient survival. We performed spatial transcriptomics on five early CRC cases, which included adenoma and carcinoma, and one advanced CRC. To elucidate cell-cell interactions within the tumour microenvironment (TME), we investigated the colocalisation network at single-cell resolution using a deep generative model for colocalisation analysis, combined with a single-cell transcriptome, and assessed the clinical significance in CRC patients. CRC cells colocalised with regulatory T cells (Tregs) at the adenoma-carcinoma interface. At early-stage carcinogenesis, cell-cell interaction inference between colocalised adenoma and cancer epithelial cells and Tregs based on the spatial distribution of single cells highlighted midkine (MDK) as a prominent signalling molecule sent from tumour epithelial cells to Tregs. Interaction between MDK-high CRC cells and SPP1+ macrophages and stromal cells proved to be the mechanism underlying immunosuppression in the TME. Additionally, we identified syndecan4 (SDC4) as a receptor for MDK associated with Treg colocalisation. Finally, clinical analysis using CRC datasets indicated that increased MDK/SDC4 levels correlated with poor overall survival in CRC patients. MDK is involved in the immune tolerance shown by Tregs to tumour growth. MDK-mediated formation of the TME could be a potential target for early diagnosis and treatment of CRC. Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Science Research; OITA Cancer Research Foundation; AMED under Grant Number; Japan Science and Technology Agency (JST); Takeda Science Foundation; The Princess Takamatsu Cancer Research Fund.

UFObow: A single-wavelength excitable Brainbow for simultaneous multicolor ex-vivo and in-vivo imaging of mammalian cells.

Brainbow is a genetic cell-labeling technique that allows random colorization of multiple cells and real-time visualization of cell fate within a tissue, providing valuable insights into understanding complex biological processes. However, fluorescent proteins (FPs) in Brainbow have distinct excitation spectra with peak difference greater than 35 nm, which requires sequential imaging under multiple excitations and thus leads to long acquisition times. In addition, they are not easily used together with other fluorophores due to severe spectral bleed-through. Here, we report the development of a single-wavelength excitable Brainbow, UFObow, incorporating three newly developed blue-excitable FPs. We have demonstrated that UFObow enables not only tracking the growth dynamics of tumor cells in vivo but also mapping spatial distribution of immune cells within a sub-cubic centimeter tissue, revealing cell heterogeneity. This provides a powerful means to explore complex biology in a simultaneous imaging manner at a single-cell resolution in organs or in vivo.

Abstract 913: Automated reasoning artificial intelligence (AI) to model the cell-cell biochemical and cellular interactions in the tumor microenvironment (TME) of oral cancer (OC)

Abstract Our goal was to study the spatial complexity of HPV negative OC by integrating scRNAseq and spatial transcriptomics from 11 samples including 5 from never smokers never drinkers (NSND). We used Turing Biosystems proprietary graph database engine and automated reasoning AI to analyze and model the cell-cell biochemical and cellular interactions in the TME. The tumors H&E images, Visium 10X, and single cell 10X data were pre-processed using standard methods. QC-based genes and cells filtering, gene expression normalization, dimensionality reduction, clustering of Visium spots, and identification of spatially variable genes were performed. We generated multiple networks from tumor data and prior biological knowledge to integrate different layers of information: single-cell and spatial transcriptomics data, cell-cell interactions networks, cell neighboring, spatial correlation networks. We first used a novel network-based technique to identify the spatial distribution of any cell subtypes (e.g. CAF, T cells), by integrating differentially expressed genes from scRNAseq, prior knowledge and prior data (e.g. TCGA). We used a multilayer network approach to integrate the different networks of data and an automated reasoning AI analysis which allows to interpret the results based on a reasoning on biological and clinical knowledge in opposition to machine learning methods based on statistical patterns. We identified CAFs/T cells/IFN-g to be strongly correlated within the tumor islets interacting with the stroma in NSND while they were more correlated within the stromal regions in smokers. We also identified 2 or 3 subtypes of tumor islets areas based on their functional states (e.g., immune pathways activated or metabolic differences), allowing us to unravel a more detailed map of the intratumoral heterogeneity when compared to histopathology annotations. In order to get some insights into the functional impact of the spatial distribution of cells, the tumors were then represented as multilayer networks to identify all possible cell-cell interactions in the TME. This was followed by a spatial simulation of these interactions using logic (e.g., inhibition, activation) and correlative (e.g., gene expression, imaging features correlations) interactions in the networks to identify spatial interactions. From that we analysed all the possible known protein-protein and metabolite-protein interactions between the cell types analysed and mapped the tumors with the gene expressions corresponding to the pairs of interacting proteins (or enzymes linked to metabolites). We found an interaction between CAF and Tregs via CXCL12 (CAFs) and CXCR4 (Tregs). In conclusion, automated reasoning AI integrating scRNAseq and spatial transcriptomics allows an in-depth analysis of cells spatial distribution and its functional impact in OC. Citation Format: Karène Mahtouk, Maxime Vincent, Yannick Le Meitour, Béatrice Vanbervliet-Defrance, Sonia Canjura, Cyril Degletagne, Laurie Tonon, Lucas Michon, Jebrane Bouaoud, Aude Excoffier, Philippe Zrounba, Rémy Boutonnet, Adam Amara, Pierre Saintigny. Automated reasoning artificial intelligence (AI) to model the cell-cell biochemical and cellular interactions in the tumor microenvironment (TME) of oral cancer (OC) [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 913.

Abstract 6853: Spatial proteomic and transcriptomic characterization of the inflammatory landscape of formalin fixed paraffin embedded Barrett’s esophagus tissues

Abstract Esophageal adenocarcinoma (EAC), a significant cause of morbidity and mortality, develops from its metaplastic precursor lesion termed Barrett’s esophagus (BE). BE progresses to EAC within an inflammation rich environment, however a detailed understanding of the types of inflammatory cells present, how that population changes over time or diagnosis, and the related immunomodulatory pathways that may mediate BEs progression is still understudied. Traditional immunohistochemistry is often inadequate to provide detailed information about a broad number of cells, local cellular proportions, and cellular heterogeneity; while bulk or single cell RNA sequencing lose the spatial context and relationships between the stroma and epithelium. Utilizing modern multiplex profiling technologies such as Nanostring’s GeoMx digital Profiler (DSP) aid in identifying both cellular composition and distribution of cells within the epithelium and stroma. Therefore, our aim of this study was to determine the suitability of the DSP platform for analyzing formalin fixed paraffin embedded (FFPE) endoscopic samples of BE and determine any differences between non-dysplastic BE (NDBE) samples from patients who eventually progressed (progressors) compared to those who did not (non-progressors), with the goal to gain deeper insights about cellular composition and spatial distribution of immune cells that may dictate progression of BE. Our secondary goal was to investigate the relationship of these cells to the BE epithelial cells through understanding the immune signaling and regulatory pathways. Our pilot study utilizing a 49-plex antibody panel on 7 NDBE samples from progressors and 8 NDBE samples from non-progressors showed good quality metrics and deciphered an immune rich microenvironment in BE with several immune markers including CD66b (neutrophils), CD14 (monocytes), CD68 (macrophages) and CD56 (NK cells) being overexpressed in the stroma of progressors compared with non-progressors, corrected p value less than 0.05. The myeloid activation marker CD80 was overexpressed in the BE epithelial cells of progressors. To determine how spatial transcriptomic profiling performed in FFPE endoscopic samples, 1,812 transcripts within 48 regions of interest of four BE, HGD, and EAC samples was interrogated. Only 36 (2%) probes fell below the limit of detection quality threshold. Thus, our pilot results show that robust proteomic and transcriptomic profiling can be obtained from endoscopic BE biopsies using this system. Based on these results, we systematically interrogated the immune cell makeup and distribution as well as their related inflammatory and immunoregulatory pathways in 40 NDBE biopsies (20 progressors and 20 with stable non-progressing disease) within discrete compartments (stroma and epithelium) through spatial whole transcriptome profiling. Citation Format: Qurat ul Ain, Nicola Frei, Amir M. Khoshiwal, Pim Stougie, Robert Odze, Sophie Camilleri-Broet, Lorenzo Ferri, Lucas C. Duits, Jacques Bergman, Matthew D. Stachler. Spatial proteomic and transcriptomic characterization of the inflammatory landscape of formalin fixed paraffin embedded Barrett’s esophagus tissues [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 6853.

Abstract 3644: Uncover spatial signatures of tumor microenvironment and oncogenic pathways using 6,000-plex single-cell spatial molecular imaging on FFPE skin squamous cell carcinoma

Abstract Background: Tumor progression and therapeutic response are regulated by the tumor microenvironment. Understanding the spatial association and architecture of molecular characteristics and composition of tumor immune microenvironment at single-cell and subcellular resolution encourages improvements in clinical prognosis and immunotherapy benefits. Single-cell Spatial profiling technologies permit the study of transcriptional activity at the spatial, single-cell level and provide abundant, high-resolution information required for the identification of clinical-related features in immuno-oncology. Methods: We performed an ultra-high-plex RNA assay to detect 6,000 targets simultaneously in situ on FFPE human skin squamous cell carcinoma using the CosMx™ Spatial Molecular Imager (SMI). For the selection of regions of interest, four protein markers and DAPI were co-detected on the same tissue slide. Tertiary analysis algorithms were developed for cell typing, co-localization of genes and ligands, cell-cell interaction, and pathway analysis. Results: Thousands of transcripts were simultaneously detected with high sensitivity and specificity on the FFPE skin squamous cell carcinoma tissue section at single-cell subcellular resolution. We investigated the tumor microenvironment including cell types, their spatial distribution and proportion of diversified immune cells in the tumor compartment. The cell typing results revealed many cancerous subpopulations, which resolved spatially from cells that lacked any defining marker genes. We also assessed distances between immune cells and their nearest functional-related neighbors. Moreover, we revealed the ligands co-localization, as well as spatial patterns of direct cell-cell interactions and signaling pathways. We found that some genes have elevated expression in macrophages which are near cancer compared to those are far from cancer cells, empowering the molecular investigation of novel signaling between immune and cancer cells in tumor immune microenvironment. Conclusions: Single-cell spatial measurements of 6,000 RNA and four proteins on the same tissue section, along with a large viewing area on archival FFPE tissue, provide a novel tool to reveal the spatial signature of tumor microenvironment and oncogenic pathways, facilitating the next level of cancer and therapeutic research. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. FOR RESEARCH USE ONLY. Not for use in diagnostic procedures. Citation Format: Michael Patrick, Shanshan He, Saskia Ilcisin, David Kroeppler, Patrick Danaher, Jason Reeves, Mark Gregory, Haiyan Zhai, Michael Rhodes, Joseph Beechem. Uncover spatial signatures of tumor microenvironment and oncogenic pathways using 6,000-plex single-cell spatial molecular imaging on FFPE skin squamous cell carcinoma [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 3644.

Abstract 7392: Machine learning-based identification of H&E-derived morphologic features associated with CD8+ T cell immune exclusion

Abstract Background: Immune exclusion is characterized by a predominance of CD8+ T cells in the stroma of the tumor microenvironment (TME) which are not in contact with tumor cells. Immune exclusion is a significant obstacle to effective cancer immunotherapy and reversing it has emerged as a new therapeutic opportunity. However, the objective assessment of immune exclusion remains a challenge due to the complexity of the TME and the need for immunostaining to quantify CD8+ cells in tumor and stroma. While artificial intelligence (AI) models applied to H&E images can quantify spatial tissue and cell features at scale, they are unable to identify the molecular subtypes of cells. Here we describe the development of a machine learning model that classifies tumors by their CD8-defined immune phenotypes using features extracted from H&E whole slide images alone. Methods: Al-powered TME models (PathAI PathExplore™) were deployed on H&E images from 39 non-small lung cancer (NSCLC) and triple-negative breast cancer (TNBC) samples. CD8-based assessment of immune phenotypes was done using an adjacent section. 115 H&E-derived features from each of the 25 tumor samples (12 NSCLC, 13 TNBC) classified as immune excluded and 7 tumor samples (3 NSCLC, 4 TNBC) classified as immune infiltrated were used as input into a feature selection process to identify the subset of H&E features predictive of immune phenotype. The feature selection process was driven by an ensemble L1 norm support vector machine (Ens-L1-SVM) model containing 500 L1-SVM base models each trained by 80% of the data. The degree of immune exclusion was determined in the feature space by the distance to the separation hyperplane defined by the model. Out-of-bag error estimation was employed on the remaining 20% of data from each base model to assess model performance. Results: The Ens-L1-SVM model identified 6 H&E features predictive of CD8-defined immune phenotypes, including the density ratio of lymphocytes to macrophages in the cancer epithelium, the density of fibroblasts, and the spatial distributions of cancer cells, macrophages, and lymphocytes. Immune phenotypes were classified by the Ens-L1-SVM model with an estimated accuracy of 97%. Additionally, all selected features and their direction of association aligned with prior knowledge of the mechanisms or manifestations of immune exclusion or infiltration in the TME. Conclusion: This work illustrated that morphologic features derived from H&E images using AI-powered models can be effective predictors of CD8-defined immune exclusion, providing an option for patient stratification by immune phenotype using widely-available H&E images. While the Ens-L1-SVM model showed robust performance on a small number of samples and is expected to have good generalizability due to the linear nature of the model, additional validation across diverse datasets and various tumor indications is needed. Citation Format: Yanchao Wang, Fredrick D. Gootkind, Florent Peyraud, Jean-Philippe Guégan, Antoine Italiano, G. Travis Clifton, Laura A. Dillon, Xinwei Sher. Machine learning-based identification of H&E-derived morphologic features associated with CD8+ T cell immune exclusion [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 7392.

Abstract 2581: Measuring interstitial fluid flow to predict and optimize spatial CAR-T dynamics in the clinic

Abstract Interstitial fluid flow dynamics in brain tumors are known to be an important indicator for tumor invasion into healthy tissue, as cancerous cells follow the interstitial flow towards tumor-stimulating chemokines. These flow gradients not only carry tumor-stimulating chemokines, but also carry cytokines secreted by immune response. CAR-T cells are known to also depend highly on the cytokines present in the CSF and serum. For these reasons, we have developed a novel method, Localized Convolutional Function Regression (LCFR) for measuring interstitial fluid flow, perfusion, and diffusion using dynamic contrast-enhanced MRI. LCFR works by applying the known physics of contrast agent transport, and fitting the observed contrast agent dynamics to the known physics. From LCFR, we can recover standard Tofts-Kety perfusion dynamics, including Ktrans and Vp, and also recover the underlying flow field and diffusivity. These new measurements allow for the prediction of where tumors invade, and allow for us to model how CAR-T cells move within a tumor. In a case study, we model the spatial distribution of CAR-T cells and glioblastoma cells over time, assuming that the fluid velocity field drives CAR-T spread throughout the tumor. Using multiple delivery locations, we identify the optimal catheter placement to optimally distribute CAR-T cells through the tumor, improving the 50% kill rate of simulated tumor cells by over 25% from a naive delivery strategy. Further, we collect longitudinal cytokine levels from patients undergoing CAR-T therapy, allowing us to understand how interstitial flow, CAR-T dynamics, and tumor dynamics interact with each other. We report a case study wherein a patient is longitudinally followed through their treatment with CAR-Ts. Perfusion imaging reveals that the patient experienced a steady increase in perfusion and decrease in fluid leakage into surrounding tissue. VEGF and IL12 levels are observed to increase as tumor volume increases. To better understand this patient's dynamics, we use the fluid velocity field measured by LCFR to simulate the development of CAR-T cells within the tumor, using the cytokine profile as a surrogate measurement of CAR-T population. These results demonstrate the importance of fluid flow and cytokines in understanding how brain tumors develop and respond to treatment. Citation Format: Ryan T. Woodall, Cora Esparza, Christine C. Brown, Jennifer M. Munson, Russell C. Rockne. Measuring interstitial fluid flow to predict and optimize spatial CAR-T dynamics in the clinic [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 2581.

Abstract 6859: A novel immune checkpoint CD97/CD55 in the initiation and progression of papillary thyroid cancer by scRNA-seq

Abstract Thyroid cancer (TC), as the most common endocrine malignancy, has exhibited a significant increasing trend in incidence in China and globally, with papillary thyroid cancer (PTC) being the most common pathological type. However, the molecular mechanisms driving the initiation and progression of TC remains scarce, posing a bottleneck problem for the precise diagnosis and treatment. Tumors, as a complex heterogeneous composite consisting of tumor cells, immune cells, and stromal cells, have long been considered to play a key role in driving tumor occurrence and malignant progression through the proportion, spatial distribution, and interaction of tumor cells and immune cells in the tumor immune microenvironment(TIME).We performed single-cell RNA sequencing (scRNA-seq) on 16 clinical samples, including normal thyroid tissue, benign nodules, PTC, and PTC with cervical lymph node metastasis(LNM), delineating the cell atlas of the tumor microenvironment (TME) at various stages from normal thyroid to PTC development. Among these, we discovered a previously undefined TNFSF9highCD8+ T cell subset with a distinct transcriptional profile from classical exhausted T cells, which was highly enriched in PTC tumor tissues. Further cell interaction analysis revealed that the highly expressed CD97 receptor on these CD8+ T cells binds to the highly expressed CD55 molecule on PTC tumor cells, promoting the exhaustion of CD8+ T cells, suggesting that CD97/CD55 may be a key new immune checkpoint (IC) inducing CD8+ T cell exhaustion and promoting immune escape of PTC tumor cells. We validated the co-localization of CD97/CD55-mediated CD8+ T cell and tumor cell interactions in PTC patient specimens and spontaneous tumor samples from a mouse PTC model using multiplex immunofluorescence (mIHC). Flow cytometry analysis of the proportion of CD97+ CD8+ T cells in patient and mouse specimens revealed a significant increase in the proportion of CD97+ CD8+ T cells in PTC tumor tissues. Co-culture experiments of activated and expanded CD8+ T cells from peripheral blood mononuclear cells(PBMC) of PTC patients with PTC tumor cells showed that CD55 overexpressing tumor cells inhibited the secretion of cytotoxic cytokines IFN-γ and IL-2 by activated CD8+ T cells through the CD97/CD55 IC signal, thereby weakening the cytotoxity on PTC tumor cells. In summary, the IC regulatory signal formed by the highly expressed CD55 molecule on the surface of PTC tumors and the CD97 receptor on the surface of PTC-specific inhibitory TNFSF9highCD8+ T cells can reshape the TIME, promoting the formation of an immunosuppressive microenvironment, which may represent a novel molecular mechanism promoting immune escape of tumor cells during PTC initiation and progression. Citation Format: Xuan Qin, Jia Li, Dapeng Li, Xing Wan, Xianhui Ruan, Yimeng Liu, Weijing Hao, Kejia Xu, Yi Shi, Yongjun Piao, Xiangqian Zheng. A novel immune checkpoint CD97/CD55 in the initiation and progression of papillary thyroid cancer by scRNA-seq [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 6859.

Abstract 5485: Spatial characterization of the immunosuppressive tumor microenvironment in estrogen receptor positive breast cancer at single cell level

Abstract We characterized immune cell exclusion in estrogen receptor positive (ER+) breast cancer through the study of spatial relationships among various subsets of cancer-associated fibroblasts (CAFs), tumor-associated macrophages (TAMs), and other immune cells using a novel in-situ spatial transcriptomic technology. ER+ breast cancer is the most common breast cancer subtype. While endocrine therapy and immune checkpoint inhibitors have considerably reduced relapse and mortality for breast cancer patients, tumor resistance to treatment remains a major challenge. The tumor microenvironment (TME) plays an important role in this mechanism of resistance. Our previous spatial proteomic analysis of ER+ breast FFPE samples demonstrated the intricate relationship between tumor and immunosuppressive cells such as CAFs and TAMs via the CXCR4-CXCL12 axis associated with the exclusion of CD8 T cells from the TME. However, the limited number of antibodies in the panel made it challenging to investigate the diversity of those CAF and TAM populations and better understand their contribution to T cell exclusion. For this purpose, we further characterized the TME of 4 human ER+ breast cancer FFPE cores using the Xenium in-situ transcriptomic platform with a breast cancer-focused panel of 280 genes from 10x Genomics plus 100 additional genes selected from literature and publicly available single cell datasets to delineate CAF and TAM sub-populations. Image analysis enabled the quantification and spatial mapping of the target genes within each cell boundary. Cells were manually annotated through unsupervised clustering of over 1 million cells. The cell phenotyping analysis allowed us to annotate major cell types including tumor cells, macrophages, T cells and fibroblasts. With our curated panel, we further characterized CAF and TAM sub-populations by identifying myofibroblastic CAFs (myCAFs), inflammatory CAFs (iCAFs), and antigen-presenting CAFs (apCAFs) in addition to M1 and M2-like macrophages as reported in the literature. We then performed spatial neighborhood analysis based on the similarity of the cell type composition in the vicinity of each cell. The results showed that myCAFs and M2-like macrophages are found in proximity to tumor cells and may play a role in T-cell exclusion. In addition, iCAFs mainly express CXCL12, a chemokine known to attract immunosuppressive cells such as regulatory T cells and M2-like macrophages as well as repel cytotoxic T cells from infiltrating the tumor via the CXCR4-CXCL12 axis. Overall, our work shows the potential of spatial transcriptomics to elucidate the spatial distribution of cells and their contribution to the immunosuppressive TME, which may enable researchers to improve understanding of tumor biology and drug target discovery efforts. Citation Format: Julien Tessier, Sandra Curras-Alonso, Joon Sang Lee, Fabien Delahaye, Hong Ma, Katie Malley, Dinesh Bangari, Donald Jackson, Angela Hadjipanayis. Spatial characterization of the immunosuppressive tumor microenvironment in estrogen receptor positive breast cancer at single cell level [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 5485.

Fibrochondrogenic Differentiation Potential of Human Adiposederived Mesenchymal Stem Cells in a Type I Collagen-based Meniscus Scaffold with Activated Platelet-Rich Plasma Stimulation In-vitro

Introduction: Despite efforts to use scaffolds to treat meniscus tears, minimal progress has been made in facilitating meniscus regeneration and return of function. Our research objective was to develop a meniscus repair and regeneration implant by applying a resorbable scaffold in combination with cells and growth factors. We report here the results of using Platelet-Rich Plasma (PRP) as a source of growth factors to induce fibrochondrogenic differentiation of human Adipose- Derived Mesenchymal Stem Cells (hADSC) in a three-dimensional (3D) Type I collagen-based scaffold in-vitro. Methods: Scaffold Preparation: Type I collagen scaffolds were prepared following a protocol previously published. Two different densities of scaffolds, High Density (HD) and Low Density (LD), were produced for in-vitro study. hADSC and PRP Preparation. hADSCs were cultured to the fifth passage to reach the desired number for experimentation. PRP was collected from human blood and activated. Cell Culture Procedure: Effects of PRP on hADSC proliferation and differentiation into fibrochondrogenic cells were examined in four scaffold groups: LD, HD, LD+PRP and HD+PRP. hADSCs were seeded onto scaffolds (n=5) at a concentration of 2 × 106 cells/scaffold. 1% of PRP was added to the experimental media. Cellular proliferation was assessed at 1, 7, 14 and 21 days. Differentiation was measured using qRT-PCR on Days 14 and 21. qRT- PCR analysis of gene expression was completed with primers for COLLAGEN 1 and AGGRECAN. Data Analysis: ANOVAs were conducted (two-tailed tests) at the .05 significance level. Results: Cellular proliferation of hADSCs seeded on each scaffold increased over time. Similar trend was observed for cells seeded on HD scaffolds with and without PRP. hADSC showed significant increase in cellular proliferation on the LD scaffolds at Days 1 and 7. At Day 21, PRP treatment and LD scaffold had a synergistic positive effect on Type I collagen gene expression. PRP did not elevate type I collagen gene in the HD group, the HD scaffold alone had the same level of type I collagen gene expression as LD+PRP. Aggrecan expression was elevated in the presence of PRP in both the HD and LD scaffold groups, indicating enhanced fibrochondrogenic differentiation of hADSCs. Effective cell infiltration was observed across both HD and LD scaffolds with and without PRP treatment. HD scaffolds displayed larger cell clusters and more extensive cell migration over time compared to LD scaffolds. However, LD scaffolds resulted a more uniform cellular distribution than HD scaffolds. Conclusion: Our study demonstrates that PRP can play an important role in directing hADSCs towards fibrochondrogenic differentiation in Type I collagen-based scaffolds in-vitro. Additionally, our study shows that collagen scaffold density can influence the spatial distribution and cellular behavior of infiltrated cells.

Tumor stroma ratio, tumor stroma maturity, tumor-infiltrating immune cells in relation to prognosis, and neoadjuvant therapy response in esophagogastric junction adenocarcinoma.

Accurate predictions on prognosis and neoadjuvant therapy response are crucial for esophagogastric junction adenocarcinoma (EGJA) patients. Therefore, we aimed to investigate the predictive abilities of several indicators, including tumor stroma ratio (TSR), tumor stroma maturity (TSM), and the density and spatial distribution of tumor-infiltrating immune cells (TIICs), such as T cells, B cells, and tumor-associated macrophages (TAMs). Resection and biopsy specimens of a total of 695 patients were included, obtained from the National Cancer Center (NCC) and The Cancer Genome Atlas (TCGA) cohorts. TSR and TSM were evaluated based on histological assessment. TIICs were quantified by QuPath following immunohistochemical (IHC) staining in resection specimens, while the Klintrup-Mäkinen (KM) grade was employed for evaluating TIIC in biopsy specimens. Patients with high stromal levels or immature stroma had relatively worse prognoses. Furthermore, high CD8+T cell count in the tumor periphery, as well as low CD68+ TAM count either in the tumor center or in the tumor periphery, was an independent favorable prognostic factor. Significantly, the combination model incorporating TSM and CD163+TAMs emerged as an independent prognostic factor in both two independent cohorts (HR 3.644, 95% CI 1.341-9.900, p = 0.011 and HR 1.891, 95% CI 1.195-2.99, p = 0.006, respectively). Additionally, high stromal levels in preoperative biopsies correlated with poor neoadjuvant therapy response (p < 0.05). In conclusion, our findings suggest that TSR, TSM, CD8+T cell, CD68+TAMs, and CD163+TAMs predict the prognosis to some extent in patients with EGJA. Notably, the combined model incorporating TSM and CD163+TAM can contribute significantly to prognostic stratification. Additionally, high stromal levels evaluated in preoperative biopsy specimens correlated with poor neoadjuvant therapy response.