Sponsored Content by TissueGnosticsReviewed by Maria OsipovaJul 31 2025
In this interview, we spoke with Associate Professor Diana Mechtcheriakova about how lymphoid structures and germinal centers are unlocking new prognostic insights into colorectal cancer, and with Anastasiia Marchuk of TissueGnostics about the imaging technologies powering this research.
Can you please introduce yourself and your role at the Medical University of Vienna?
Diana Mechtcheriakova: I am Diana Mechtcheriakova, affiliated with the Institute of Pathophysiology and Allergy Research at the Medical University of Vienna, where I serve as head of the research group Molecular Systems Biology and Pathophysiology.
My recent presentation, titled "Unlocking the Lymphoid Structures with Germinal Centers: Architectural Complexity, Functionality, and Clinical Relevance," reflects the core themes of our research.
Our group operates within a conceptual framework that transitions from systems biology to systems medicine, aligning with the broader vision of personalized medicine. This approach is based on the Aristotelian principle that “the whole is greater than the sum of its parts” and emphasizes a holistic methodology for deciphering biological complexity through a hierarchical flow from data to information to knowledge.
Our primary research areas include the development of systems biology approaches applied to various projects, with a focus on B-cell biology, immune oncology, lymphoid structures, AID/APOBEC-associated biological events, and the cellular sphingolipid/lysophosphatidate system in immunity and cancer.
In addition, I lead the Tissue Image Cytometry Unit at Austrian Bioimaging and serve as head of the Basic and Translational Research Module at the Austrian Platform for Personalized Medicine.
Could you tell us more about your recent research on lymphoid structures and their clinical relevance in cancer?
Diana Mechtcheriakova: My recent work focuses on the biology of lymphoid structures, which are highly organized formations characterized by dense cellular interactions and functional cooperation among various immune cell types. These include B-cell subsets, follicular helper T cells, and follicular dendritic cells.
When fully developed, these structures contain germinal centers, which are functional niches where B cells proliferate, differentiate, undergo affinity maturation, and switch antibody classes. A key marker of active germinal centers is activation-induced cytidine deaminase (AID), which can be visualized through tissue staining, such as in tonsil samples.
The germinal center reaction results in the production of plasma cells and memory B cells. These lymphoid structures are typically located in secondary lymphoid organs; however, they can also be assembled in ectopic locations within chronically inflamed tissues, including tumors. In such cases, they are referred to as ectopic lymphoid structures (ELS) or tertiary lymphoid structures (TLS).
A particularly important aspect of this research is the clinical relevance of B cells and ELS in cancer. It has been demonstrated—an insight I consider one of the major breakthroughs of recent years—that the local presence of B cells and ectopic lymphoid structures correlates with favorable patient prognosis in more than ten cancer types. Notable examples include non-small cell lung cancer, breast cancer, and colorectal cancer with liver metastases.
Can you describe your research findings on ectopic lymphoid structures in colorectal cancer with liver metastases?
Diana Mechtcheriakova: In the context of colorectal cancer with liver metastases, our research group was among the first to demonstrate the accumulation of B cells assembled in ectopic lymphoid structures (ELS) with active germinal centers in the liver. These ELS were observed forming a ring-like pattern around the metastases.
To investigate this further, we conducted a precise quantification of B cells and ELS at the tumor-liver interface, using defined zones extending both toward the tumor and into the adjacent liver tissue. This analysis was performed through quantitative tissue image cytometry, utilizing TissueFAXS-based computerized microscopy. Our findings revealed that a higher density of B cells and ELS at the tumor-liver border correlated with improved clinical outcomes, particularly in terms of patient survival.
This prognostic value exceeded that of conventional clinicopathological parameters. Based on these observations, we proposed the hypothesis that the anti-tumor immune response at the metastatic site in the liver may be pre-instructed either at the primary colorectal cancer site or potentially within the non-tumorous colon mucosa, where isolated lymphoid structures (ILS) are normally present.
Image Credit: Anusorn Nakdee/Shutterstock.com
What was the primary objective of your study on lymphoid structures in metastatic colorectal cancer?
Diana Mechtcheriakova: The main objective of our study was to determine whether specific characteristics of lymphoid structures across three distinct tissue entities influence the pathobiology of metastatic colorectal cancer (CRC). To investigate this, we developed a multi-modular approach called DIICO, which stands for Digital Immune Imaging to Clinical Outcome.
The first module of the DIICO strategy involved immunostaining tissue samples using a defined set of immune markers. These included CD20 as a general B-cell marker, AID to identify functionally active germinal centers, Ki67 for proliferating cells, CD27 for memory B cells and plasma cells, CD138 for plasma cells, and CD3 as a general T-cell marker.
We applied these markers to both colon cancer specimens and tonsil tissues to characterize the immune cell composition and assess the functional activity of lymphoid structures.
How did you implement the DIICO strategy, and what did your tissue analysis reveal?
Diana Mechtcheriakova: The second module of the DIICO strategy focused on assessing the immunological imprint using quantitative tissue image cytometry. Stained specimens were digitized through the automated microscope-based TissueFAXS platform, and quantitative analysis was performed using the HistoQuest and TissueQuest software packages.
Lymphoid structures were defined as distinct objects, and the analysis was carried out at the single-cell level with marker-positive cell detection based on specific expression profiles.
We have had the TissueFAXS platform at our institute since 2008, and in 2022, we were recognized as a Center of Excellence for Quantitative Digital Microscopy. For this project alone, we analyzed more than 700 colon cancer tissue slides and over 120 tonsil samples.
This analysis transformed tissue-encoded information into numerical variables, categorized by anatomical region and staining characteristics for each patient. These variables were then aligned with clinicopathological parameters to generate insights into disease mechanisms and patient outcomes.
What did your analysis reveal about the clinical importance of lymphoid structure characteristics in metastatic colorectal cancer?
Diana Mechtcheriakova: In our study, we identified 24 variables related to lymphoid structure characteristics. These included parameters such as anatomical site, number and size of lymphoid structures, cellular density, and the percentage of marker-positive cells for each defined immune marker.
A central question we addressed was the clinical relevance of these variables in characterizing the immune phenotype of lymphoid structures. Notably, in non-tumorous (NT) tissue, we found that variables reflecting the percentage of CD20-positive B cells and Ki67-positive proliferating cells—individually and in combination—demonstrated strong prognostic value.
This was supported by statistically significant patient stratification into low- and high-risk groups using Kaplan-Meier survival estimates. One of the most significant findings was that B-cell-enriched and highly proliferative isolated lymphoid structures (ILS) located in the non-tumorous colonic mucosa had a pronounced impact on patient survival outcomes.
This discovery indicates that the immunological imprint of lymphoid structures in normal colon tissue encodes valuable prognostic information for patients with colorectal cancer liver metastases.
What are the next steps in your research on lymphoid structures?
Diana Mechtcheriakova: Building upon our systems biology-based, multi-modular analysis strategy, we are now expanding our approach beyond quantitative tissue image cytometry—powered by the TissueFAXS platform—and transcriptomic data analysis through the GENEVESTIGATOR tool.
We have recently integrated two additional modules into our framework. The first is spatial transcriptomics using 10x Genomics Visium Spatial Gene Expression, which enables mRNA profiling directly within FFPE tissue sections, preserving spatial context.
The second is the application of artificial intelligence in biomedical research, introduced through our new ongoing project, LymphoidStructureMiner, in collaboration with AI specialists from Danube Private University in Austria.
Through the combined power of these technologies, we aim to develop advanced analytical models to further unravel germinal center biology. Our ultimate goal is the identification of novel biomarkers and therapeutic targets to enhance precision in cancer diagnosis and treatment.
Could you introduce TissueGnostics and explain how your technologies, especially tissue cytometry, support advanced research?
Anastasiia Marchuk: My name is Anastasiia Marchuk, and I represent TissueGnostics, a company headquartered in Vienna, Austria. We have been active in the field for over 20 years, specializing in whole slide imaging and image analysis. Our core focus is on a method we refer to as tissue cytometry, which involves detecting and phenotyping cells within their native tissue microenvironment.
The foundation of tissue cytometry is single-cell analysis, where individual cells—typically identified by nuclear staining—are detected and quantified. To define cell phenotypes, specific detection profiles are applied, allowing for quantification and characterization through spatial phenotyping. This process not only identifies cell types but also analyzes their spatial distribution within the tissue.
Tissue cytometry supports multicellular structure detection, enabling the analysis of anatomical features such as colon crypts, blood vessels, or glomeruli. It also facilitates the quantification of cellular pathogens and the detailed characterization of intracellular content.
We offer custom analysis solutions in the form of pre-configured, application-specific pipelines designed to address targeted research questions. For whole slide imaging, we provide TissueFAXS modular systems, which are fully automated platforms capable of processing immunofluorescence (IF) or immunohistochemistry (IHC) stained tissues or cells on glass slides, well plates, or tissue microarrays.
These systems are available in both upright and inverted configurations, with support for brightfield, fluorescence, or combined modalities, depending on research needs. Once a slide is placed and acquisition settings are selected, the automated system generates a fully digitized image, allowing researchers to focus on other tasks while the imaging is completed.
What advanced image analysis capabilities does TissueGnostics offer, and what innovations are you working on for the future?
Anastasiia Marchuk: TissueGnostics provides flexible and powerful imaging solutions designed to support a wide range of research needs. Users can define their own analysis pipelines and customize imaging settings, which can be saved and reused to ensure consistency across experiments.
As a modular and fully automated system, we also offer configurations for confocal, multispectral, and automated slide loading, depending on specific requirements. One of our most advanced image analysis platforms is StrataQuest, which includes modules for single-cell analysis, multicellular structure detection, neighborhood analysis, and more. Researchers can develop and save custom analysis workflows and reuse data for future studies.
To illustrate, in one example involving colon tissue stained with several immune markers, nuclei are detected using DAPI staining, followed by immune cell phenotyping and colon crypt detection. A distance map is then generated, which supports neighborhood analysis—examining the spatial proximity of immune cells to epithelial structures. This type of analysis yields critical insights into both cell identity and spatial organization.
In the latest version of our software, we have integrated advanced visualization and data interpretation tools, including 3D diagrams, violin plots, and manifold learning techniques such as SONG, UMAP, and t-SNE plots—all accessible directly within the platform.
Looking ahead, we are preparing to launch Colubris next year, an all-in-one acquisition and analysis system. Colubris will feature real-time AI-assisted image analysis and data mining, and is specifically engineered to handle high-volume data, delivering comprehensive solutions for modern biomedical imaging needs.
About Prof. Diana Mechtcheriakova
Assoc. Prof. Diana Mechtcheriakova is the head of the research group Molecular Systems Biology and Pathophysiology at the Medical University of Vienna. Her research interests include development of systems biology approaches, AI-powered solutions, with major focus on B-cell biology, immuno-oncology, lymphoid structures in immunity and cancer with translational perspectives.
About TissueGnostics
TissueGnostics (TG) is an Austrian company focusing on integrated solutions for high content and/or high throughput scanning and analysis of biomedical, veterinary, natural sciences, and technical microscopy samples.
TG has been founded by scientists from the Vienna University Hospital (AKH) in 2003. It is now a globally active company with subsidiaries in the EU, the USA, and China, and customers in 30 countries.
TissueGnostics portfolio
TG scanning systems are currently based on versatile automated microscopy systems with or without image analysis capabilities. We strive to provide cutting-edge technology solutions, such as multispectral imaging and context-based image analysis as well as established features like Z-Stacking and Extended Focus. This is combined with a strong emphasis on automation, ease of use of all solutions, and the production of publication-ready data.
The TG systems offer integrated workflows, i.e. scan and analysis, for digital slides or images of tissue sections, Tissue Microarrays (TMA), cell culture monolayers, smears, and other samples on slides and oversized slides, in Microtiter plates, Petri dishes and specialized sample containers. TG also provides dedicated workflows for FISH, CISH, and other dot structures.
TG analysis software apart from being integrated into full systems is fully standalone capable and supports a wide variety of scanner image formats as well as digital images taken with any microscope.
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