Mapping Melanoma: How MGI’s DCSP Framework Is Advancing Precision Oncology

Magdeburg, Germany, 25 May 2026 – What if understanding melanoma depended not only on identifying which cells exist within a tumour, but also on understanding where those cells are located and how their spatial organization influences biological behaviour and treatment response?

This question lies at the core of spatial biology, an emerging field that leverages spatial transcriptomics and spatially resolved multiomics technologies, often in combination with single-cell sequencing, to study tumours as spatially organized biological systems with functional microenvironments.

May, observed globally as Melanoma Awareness Month, underscores the growing relevance of genomic technologies in advancing melanoma research, tumour immunology and precision oncology. It also provides context for highlighting how spatial and multiomics approaches are improving resolution in cancer biology.

Researchers at University Hospital Magdeburg and University Hospital Schleswig-Holstein are conducting a melanoma profiling study using clinically annotated samples from an institutional biobank. The project is supported through collaboration with Dr. Jia Hui Khoo, Senior Product Manager at MGI Tech, who contributes expertise in spatial biology and enabling technologies. The study integrates DNA, cellular, spatial and proteomic data through MGI’s DCSP framework to support translational cancer research.

Melanoma and Spatially Resolved Oncology

Melanoma has been central to the development of cancer immunotherapy, particularly immune checkpoint inhibition targeting PD-1 and CTLA-4. Despite significant therapeutic advances, clinical variability remains a key challenge, with marked differences in patient response and resistance.

As Professor Andreas Braun explains, understanding this variability requires examining the interplay between tumour cells and the microenvironment — including endothelial cells that act as “a highway” controlling whether immune cells can enter the tumour.

This complexity reflects the nature of the tumour microenvironment, where immune cells, tumour cells and vascular structures interact within spatially defined tissue contexts. As Professor Thomas Tüting notes, tumour behaviour cannot be fully understood by studying malignant cells alone, but must be interpreted within the surrounding biological environment.

This understanding reflects a broader shift in oncology: tumour behaviour is increasingly understood as a product of spatial and functional context rather than isolated molecular alterations. Integrating spatial transcriptomics with single-cell and model-based systems allows researchers to investigate tumour heterogeneity, immune resistance and treatment failure at a systems level.

Spatial Profiling of the Melanoma Tumour Microenvironment

A central component of the Magdeburg study is its melanoma biobank, comprising clinically annotated samples across disease stages and treatment conditions. This resource enables direct correlation between molecular profiles and clinical outcomes.

The project integrates approximately 50 STOmics spatial transcriptomics datasets with matched single-cell RNA sequencing data from both human melanoma samples and complementary mouse models. This combined design supports cross-species validation while maintaining translational relevance.

Spatial transcriptomics enables gene expression profiling while preserving tissue architecture, allowing detailed mapping of tumour regions, immune infiltration patterns, stromal compartments and vascular structures. Variations in vascular structure and endothelial signalling may help explain why some melanomas respond to immunotherapy while others remain immune-excluded.

Professor Braun puts it concisely: the goal is to “achieve single-cell resolution on the transcriptomic side and anchor these in their spatial context — so we can understand what these cells do, how they communicate and what drives immune cells to either enter the tumour or not.”

Why Spatial Context Matters

Spatial context is a defining principle in modern cancer biology. The concept of “cellular neighbourhoods” or tissue “niches” highlights that cellular function is shaped not in isolation, but through continuous interaction with the surrounding microenvironment, as emphasized by Professor Tüting.

In melanoma, this spatial dependency becomes particularly critical, as tumour progression is influenced not only by genetic alterations but also by dynamic remodelling of tissue architecture. Variations in immune cell distribution, vascular accessibility and stromal organization may determine whether anti-tumour immune responses are effectively activated or remain spatially constrained within the tumour microenvironment.

Even cells with shared developmental origins can acquire distinct functional states depending on their spatial localization. This reinforces the concept that tumour behaviour is governed by spatial organization as much as by molecular identity.

Technologies such as Stereo-seq enable high-resolution mapping of gene expression within intact tissue sections, preserving spatial relationships that are often lost during tissue dissociation and conventional single-cell workflows.

As highlighted by Dr. Jia Hui Khoo, spatial datasets require integrated interpretation across gene expression, protein activity and spatial localization to understand tissue function as a coordinated system — marking a shift toward structured, ecosystem-level models of tumour biology.

MGI’s DCSP Multiomics Framework

The melanoma study demonstrates how MGI’s DCSP framework supports integrated multiomics research across DNA genomics, cell omics, spatial omics and proteomics. Designed to integrate multiple layers of biological information within a unified workflow, the framework enables researchers to study tumour biology with greater molecular and spatial resolution.

Within the study, STOmics Stereo-seq enables spatially resolved whole-transcriptome profiling of melanoma tissue, helping identify immune landscapes, invasive tumour fronts and hypoxic niches while preserving tissue architecture. Because the platform is unbiased and species-agnostic, researchers can analyse both human and mouse samples without redesigning targeted gene panels.

Single-cell sequencing provides deeper characterization of cellular identity and functional states, while proteomic integration adds a layer of biological insight in settings where RNA expression and protein abundance do not always directly correlate. Researchers are also exploring integration with multiplex immunofluorescence techniques to further improve characterization of endothelial and immune cell populations within the tumour microenvironment.

According to Dr. Jia Hui Khoo, integrating these technologies within a single ecosystem may also help reduce technical variability across workflows, supporting more consistent and scalable translational research.

Together, these approaches generate spatially informed, high-dimensional datasets that capture tumour complexity with greater biological depth and context than conventional methods alone.

Toward the Future of Precision Oncology

The integration of spatial biology and multiomics is driving a broader transformation in oncology research. Tumours are increasingly understood as dynamic, spatially organized ecosystems rather than static molecular entities.

While these approaches remain computationally demanding, they are already enabling deeper insights into tumour heterogeneity, immune evasion and therapeutic response.

As these technologies continue to mature, they are expected to strengthen biomarker discovery, improve patient stratification and support more precise therapeutic development across diverse patient populations.

As Professor Andreas Braun puts it, the goal remains fundamentally translational:

“At the end, we’re still trying to understand cancer to treat patients better in the future.”

By linking molecular insight with spatial context, spatial biology is helping bring precision oncology closer to that goal — one tissue landscape at a time.