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In the run up to the International Spatial Biology Congress: ISBC 2025 we invited our speaker to share some of their thoughts with us.
Evan T. Keller DVM, PhD Director, Single Cell Spatial Analysis Program Richard and Susan Rogel Professor of Oncology, University of Michigan, USA in his open letter wrote about how applying single-cell spatial analysis, his team have identified potential biomarkers that may enhance the accuracy of tumor grading in prostate cancer. This advancement holds promise for more precise diagnostic assessments and tailored treatment strategies. Additional studies have delineated a mechanism through which renal clear cell carcinoma progresses to a renal sarcomatoid cancer subtype. He writes Understanding this transition is vital for developing targeted therapies and improving patient outcomes.
Charlotte Stadler, Co-Director Spatial Biology Platform at SciLife Lab, KTH and Science for Life Laboratories, Sweden was asked what recent technological advancements in spatial biology do you find most promising for clinical applications? She writes: “This depends on who you ask. Personally I believe the multiplexed proteomics is the closest to broader adaptation within clinics, as used for diagnostics and patient stratification. Immunohistochemistry is the golden standard for tissue pathology and is used extensively in clinic. Now, we have the possibility to combine many of them into one assay, saving material and time. This is useful not only for diagnosis, but also for patient stratification allowing for more individualised treatments. For many indications in cancer, more targeted therapies become available. But how do you then know which therapy is the best for every patient? This could be answered by implementing relevant multiplexed protein panels – or combination of proteins with transcripts or DNA – covering a few but highly relevant markers.”
Thinking about the future and the challenges Charlotte expressed that opinion that there are many technologically advanced methods and assays developed that gives a lot of information (hundreds to thousands of proteins or transcripts). She said: “While this is great for discovery research, clinical assays need more targeted approaches and a proven reason to include each marker in the assay. Shortly – for clinical applications less is more.” In her opinion this is also important when it comes to interpreting the data. In the end someone in a clinical setting should analyze the results and this must come from a simple readout. To summarise, she said: “there is a big gap between academic research and what is technically possible, to what is feasible to implement in a clinical setting and we need to understand the needs and questions from the clinicians to tailor relevant assays and result outputs.”
Charlotte Stadler will deliver a keynote address on A toolbox for Spatial Proteomics.
Linda Kvastad Postdoctoral Student in Lappalainen Lab, KTH Royal Institute of Technology commented that much of the field has focused on identifying structures, annotating data, and integrating spatial information, future opportunities lie in exploring the biological roles of these tissue structures. She said that “By developing computational tools for complex disease gene set enrichment, we can now integrate gene expression data with genetic evidence from population studies. These approaches allow us to analyze single-cell and spatial data to question whether spatial disease enrichment stems from a specific cell type and its high abundance in a given tissue structure as the primary disease driver. Another intriguing question is whether dysfunction in different tissue structures results from multiple colocated cell types that collectively—and possibly interactively—contribute to complex diseases.”
Ayse Koksoy, Senior Research Scientist, MD Anderson Cancer Center TMP-IL, USA thought that in oncology, spatial biology provides insights into the tumor microenvironment by revealing how cancer cells interact with surrounding cells such as the fibroblasts, immune cells and the extracellular matrix proteins. She said “This understanding is crucial for personalized medicine as it influences the selection and effectiveness of treatments, especially regarding immune-hot and immune-cold tumors. For instance, spatial proteomic analysis can identify microenvironmental niches that support tumor resistance to certain therapies. By characterizing these spatial patterns, clinicians can tailor treatments that not only target the tumor cells but also modulate the surrounding microenvironment to enhance treatment efficacy; such as through check point inhibitor therapies. Additionally, spatial biomarkers can be used to predict patient response to immunotherapies by assessing the presence and functionality of immune cells within the tumor.”
Turning to Bioinformatics and Data Analysis Ayse intemized what she felt as the key considerations for Developing computational tools for spatial data integration and visualization:
Adding that “Standardization of spatial data is critical for ensuring consistency and reproducibility” she suggested that the best approached included:
Ayse Koksoy will present on LS Finder: Advancing TLS Detection and Immune Microenvironment Insights
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