Imaging MC & Data Analysis Session

Marseille Cancer Research Center, Marseille, France

Immunomonitoring of cervical tumors: identifying tertiary lymphoid structures and associated immune infiltrate as prognosis markers
Cervical tumors are usually treated using surgery, chemotherapy, and radiotherapy and would benefit from immunotherapies. However, the immune microenvironment in cervical cancer remains poorly described. Tertiary lymphoid structures (TLS) were recently described as markers for better immunotherapy response and overall better prognosis in patients with cancer. We evaluated the cervical tumor immune microenvironment, specifically focusing on TLS, using combined high throughput phenotyping, soluble factor concentration dosage in the tumor microenvironment, and spatial interaction analyses. We found that TLS presence was associated with a more inflammatory soluble microenvironment, with the presence of B cells as well as more activated macrophages and dendritic cells (DC). Furthermore, this myeloid cell activation was associated with the expression of immune checkpoints, such as PD-L1 and CD40, and the proximity of activated conventional type 2 DCs to CD8+ T cells, indicating better immune interactions and tumor control. Finally, we associated TLS presence, greater B-cell density, and activated DC density with improved progression-free survival, substantiating TLS presence as a potential prognostic marker. Our results provide evidence that TLS presence denotes cell activation and immunotherapy target expression.

Biosketch
Dr. Laurent Gorvel is an expert in Immunology specializing in myeloid cell functions and tumor microenvironments. After obtaining his PhD in 2013 on dendritic cell and macrophage responses to chronic bacterial infections, he completed a postdoctoral fellowship at Washington University in St. Louis in Eynav Klechevsky’s lab, focusing on dendritic cell regulation of cytotoxic cells in health and diseases. Currently a researcher within the Immunity & Cancer team and the Immunomonitoring platform at the CRCM (Marseille), his research investigates macrophage-mediated resistance to conventional cancer therapies as well as macrophage targeting therapies, in gynecological tumors. His studies rely on high-dimensional techniques such as mass and spectral cytometry as well as spatial characterization of tumor microenvironments to identify novel therapeutic targets. Recently Dr. Gorvel also co-founded the BIOHAFIA cytometry platform and master’s program in Guinea to help with the development of cytometry and immunology in this country.

Clinic for Internal Medicine II, University Medical Center Freiburg, Germany.

Imaging mass cytometry enables spatial chromatin modification profiling at single-cell level

Introduction:
Chromatin modification plays a crucial role in tumor development by regulating gene activation and repression. Current approaches primarily rely on sequencing-based methods that assess single modification and often lack spatial information. In this project, we employed imaging mass cytometry (IMC) to spatially characterize multiple chromatin modification profiles at the single-cell level in human liver and brain tissue.

Methods:
We profiled human liver tissue with a 42-antibody panel including immune, stromal, and parenchymal markers with 11 chromatin modification markers. After image segmentation, single-cell data were extracted to quantify marker expression and to define cellular and epigenetic heterogeneity.

Results:
We identified 17 cell types in the human liver based on lineage marker expression, as well as 14 distinct epigenetic states reflecting different levels of gene activation and repression. Within each cell type different epigenetic states coexisted, while certain states were preferentially associated with specific cell types.

Spatial neighborhood analysis classified the tissue into tumor-enriched, hepatocyte-enriched, central vein–associated, immune-enriched, and immune–stroma–enriched neighbourhoods. Clustering based on epigenetic states composition further defined three “Epi-niches”, which enriched for different chromatin modification states. Correlation analysis showed that hepatocyte-enriched and central vein–associated neighbourhood correlated to Epi-niche 3, and tumor-enriched regions with Epi-niche 1 while immune-enriched, and immune–stroma–enriched neighbourhood with Epi-niche 1 and 2.

Epigenetic state composition of neighboring cells (K=10) varied by cell type. For example, CD8⁺ T cells were most frequently surrounded by cells in epigenetic state 4. And within the tissue, CD8⁺ T cells interacted significantly with CD4⁺ T cells and Iba1⁺ macrophages. Consistently, epigenetic state 4 was associated with CD4⁺ T cells, Iba1⁺ macrophages, and CD8⁺ T cells, suggesting shared chromatin modification features within these interacting cells.

Conclusion:
In summary, we established the methods of chromatin modification profiling using imaging mass cytometry. Our results indicate that cellular epigenetic states are spatially organized and are shaped by local cell–cell interactions within the tissue microenvironment.

Lymphocytes B, Autoimmunité et Immunothérapies – LBAI (UMR 1227), Université de Bretagne-Occidentale
AltraBio SAS, Lyon, France

AltraFlowSOM: A Semi-Supervised Framework for Scalable Phenotyping of Imaging Mass Cytometry Data

Background : Imaging Mass Cytometry (IMC) enables high-dimensional spatial profiling of complex tissue microenvironments, yet current analysis pipelines still rely heavily on unsupervised clustering followed by manual post-hoc annotation. While expert annotation is essential for assigning biological meaningful populations, the upstream clustering step is performed without biological priors and can be strongly influenced by technical variation, leading to clusters that are not immediately biologically interpretable. This workflow is labour-intensive, difficult to scale, and becomes increasingly challenging in large multi-sample datasets, where batch effects and data heterogeneity can obscure rare but biologically important cell populations and reduce the biological meaningfulness of clustering.

Objectives : Develop and evaluate a semi-supervised clustering tool that better aligns with the biological knowledge that scales with larger datasets, possibly reducing the cons of classical workflow.

Methods : We developed AltraFlowSOM, a semi-supervised extension of the FlowSOM framework.AltraFlowSOM extends the FlowSOM framework by incorporating Supervised Self Organizing Maps (SSOM’s) an existing supervised extension of SOM to integrate partial expert annotations directly into the clustering process, thereby guiding the formation of clusters toward biologically meaningful populations. The framework merges raw marker expression with biological knowledge layers (e.g., manual gating labels) using a multi-layer SSOM architecture. This guides cluster formation toward biologically relevant phenotypes while preserving the ability to discover previously unrecognized populations.

We benchmarked the performances across major analytical strategies, including:

• Unsupervised (FlowSOM & Phenograph, with and without batch-effect correction)
• Supervised learning (Random Forest)
• AltraFlowSOM (semi-supervised)

Two independent IMC datasets were used for evaluation; Lupus Nephritis (n=22) and Sjögren’s Disease (n=10).

Results : AltraFlowSOM achieved the highest concordance with manually gated ground truth, outperforming FlowSOM, Phenograph (with and without batch correction), and Random Forest across Adjusted Rand Index (ARI) and F1-score metrics. High performance persisted even under full supervision and when only partial annotations were available; models trained on only a subset of samples performed comparably to those trained on fully annotated datasets. Using a leave-one-out strategy, training on (n-1) samples and testing on the remaining held-out sample, AltraFlowSOM demonstrated strong generalizability across unseen patient samples and across disease indications. The method improved resolution of rare and biologically meaningful cell populations, and produced phenotypes that aligned more closely with known immunobiology.

Conclusion : AltraFlowSOM integrates expert knowledge directly into cluster formation, bridging the gap between manual gating and automated phenotyping. It enhances biological interpretability, increases sensitivity to rare populations, and provides a scalable, generalizable tool for high-dimensional IMC data. This framework supports reproducible, biologically informed cellular phenotyping in autoimmune disease research and is broadly applicable across spatial and single-cell cytometry platforms.

German Cancer Research Center (DKFZ), Heidelberg, Germany

Metabolic reprogramming of neutrophils in colorectal cancer

Neutrophils constitute a major component of the tumor microenvironment and are increasingly recognized as more diverse and long-lived than previously thought. Yet, their specific roles and prognostic significance especially in colorectal cancer remain poorly defined, largely due to challenges in profiling them. Here, we reveal a stage-dependent prognostic effect of neutrophil infiltration in colorectal cancer: beneficial in early-stage disease but detrimental in late-stage disease. Early-stage neutrophils were enriched for inflammatory gene programs, including tumor necrosis factor alpha (TNFα), whereas late-stage neutrophils displayed signatures of metabolic reprogramming. Using spatial proteomics, we identified five distinct neutrophil clusters in human biopsies based on metabolic and phenotypic states. This included “netotic” neutrophils enriched in reactive oxygen species (ROS)-generating enzymes and MMP9-expressing neutrophils with impaired ROS activity. “Netotic”, possibly cytotoxic, neutrophils predominated in early stages, while MMP9-expressing, possibly angiogenic, neutrophils were more frequent in late stages.  Late-stage neutrophils appeared metabolically impaired, with reduced engagement of the pentose phosphate pathway essential for ROS production. Spatial analysis identifies that interaction with a highly glycolytic tumor cell niche is associated with the metabolically impaired neutrophils in late stage suggesting metabolic competition as a driver of neutrophil dysfunction.

Together, our findings uncover a stage-dependent prognostic effect of neutrophils in colorectal cancer, linking their functional rewiring to metabolic constraints within the tumor microenvironment.