For decades, cancer research has focused on identifying the molecular drivers of disease. Which mutation is present? Which gene is overexpressed? Which pathway is activated?
Answering these questions has transformed oncology, leading to targeted therapies, immunotherapies, and increasingly personalized treatment approaches. Yet a persistent challenge remains: patients with seemingly similar tumors often respond very differently to the same therapy.
Part of the explanation may lie in something that traditional molecular analyses often overlook: location. This is the promise of spatial omics.[1]
Looking Beyond the Tumor Cell
Cancer does not exist in isolation. Every tumor is embedded within a complex ecosystem known as the tumor microenvironment (TME), which includes immune cells, fibroblasts, blood vessels, extracellular matrix, and a wide range of signaling molecules. These surrounding components are not passive bystanders; they actively influence how cancer grows, spreads, evades immune surveillance, and responds to treatment.
Traditionally, many molecular techniques have measured average gene or protein expression across an entire tissue sample. While these approaches have generated invaluable insights, they often lose information about where cells are located and how they interact with one another.
Spatial omics changes that.
By preserving tissue architecture, spatial technologies allow researchers to see not only which cells are present, but also where they are positioned, which neighboring cells they interact with, and how biological signals are distributed throughout a tumor.
In effect, spatial omics transforms the tumor microenvironment from a background feature into a detailed biological map.[1][2]
Why Space Matters
Tumors are not uniform structures.
Within a single lesion, there may be regions rich in immune cells, areas largely devoid of immune activity, highly vascularized zones, and pockets of treatment-resistant cells. Although these regions exist within the same tumor, they can behave very differently.
This spatial organization can have profound consequences for treatment outcomes.
An immune checkpoint inhibitor, for example, may perform well in a region heavily infiltrated by activated T cells but have little effect in an immune-excluded area where those cells cannot penetrate. Likewise, a targeted therapy may effectively reach some tumor compartments while encountering physical barriers in others.
Viewed through a spatial lens, treatment resistance often reflects geography as much as genetics.
The challenge is not simply identifying resistant cells. It is understanding where they located, what supports their survival, and how they interact with their surroundings.[3]
Revealing Hidden Biology
One of the greatest strengths of spatial omics is its ability to uncover biological interactions that would otherwise remain invisible.
Spatial profiling can reveal:
• Patterns of immune cell infiltration
• Tumor–immune cell interactions
• Localized immune suppression
• Stromal barriers that limit drug penetration
• Compartment-specific resistance mechanisms
• Tertiary lymphoid structures associated with anti-tumor immunity
These insights are difficult to obtain using bulk sequencing approaches, which average signals across entire tissue samples, or even conventional single-cell analyses, which often lose spatial context during tissue processing.
By preserving the original architecture of the tissue, spatial methods allow researchers to study how cells communicate and cooperate within distinct microenvironments.
This has led to growing interest in what some researchers describe as “resistance zones”— localized regions where suppressive immune cells, fibroblasts, extracellular matrix components, and other factors combine to create conditions that protect cancer from treatment. [4]
Understanding these zones may prove just as important as understanding the cancer cells themselves.
Making Existing Therapies Smarter
The value of spatial omics is not primarily about discovering entirely new therapies.
Its greatest near-term impact may be helping clinicians and researchers use existing therapies more effectively.
By understanding the spatial organization of a tumor, researchers can gain insights into:
• Which patients are most likely to benefit from a specific therapy
• Which tumor regions may remain resistant
• Where immune activation is occurring
• Which microenvironmental pathways should be targeted alongside existing treatments
• How therapies may be sequenced or combined more effectively
This supports a more practical approach to innovation.
Rather than starting from scratch, researchers can use spatial insights to optimize current therapeutic strategies, improve patient selection, and design more rational combination approaches.
In this way, spatial omics aligns closely with a growing emphasis on making therapies smarter rather than simply developing more of them.[1-4]
Explaining Why Similar Tumors Behave Differently
One of the most intriguing applications of spatial omics is its potential to explain variability in treatment response.
Two individuals may share the same diagnosis, similar mutations, and comparable clinical characteristics, yet experience dramatically different outcomes.
Traditional biomarkers often struggle to explain these differences.
Spatial biomarkers may offer a more complete picture.
Emerging evidence suggests that the physical arrangement of immune and tumor cells can predict response to immunotherapy more accurately than some conventional biomarkers alone. In other words, tissue architecture itself may contain clinically meaningful information that has largely remained hidden.
By linking molecular information to spatial context, researchers can better understand why one patient achieves durable benefit while another develops resistance despite receiving the same treatment. [1-4]
A New Map for Precision Oncology
The most important contribution of spatial omics may not be the discovery of entirely new drug targets. Its greater value may like in helping us use existing therapies more intelligently.
By revealing how cancer cells interact with immune cells, stromal barriers, and other components of the tumor microenvironment, spatial technologies provide a cleaner picture of why treatments succeed in some settings and fail in others. They offer a way to identify resistance before it becomes clinically apparent and to design combination strategies that better reflect the biological realities of each tumor.
This represents an important shift in precision oncology. For years, the focus was on identifying the right target. Increasingly, the challenge is to understand the environment surrounding that target and how that environment influences treatment response.
Spatial omics adds a new layer of insight into that challenge. It helps explain why seemingly similar tumors can behave differently, why resistance emerges, and where intervention may have the greatest impact.
The result is not an entirely new oncology playbook.
It is a smarter one.
At Helix BioPharma, we believe progress in oncology comes not only from discovering new therapies, but also from understanding how to use existing therapeutic mechanisms more effectively. Emerging technologies such as spatial omics are helping reveal the biological context that shapes treatment response, creating new opportunities for more rational combinations, improved patient selection, and better long-term outcomes.
Ref:
1. Zhang Y, Lee RY, Tan CW, Guo X, Yim WW, Lim JC, Wee FY, Yang WU, Kharbanda M, Lee JJ, Ngo NT, Leow WQ, Loo LH, Lim TK, Sobota RM, Lau MC, Davis MJ, Yeong J. Spatial omics techniques and data analysis for cancer immunotherapy applications. Curr Opin Biotechnol. 2024 Jun;87:103111. doi: 10.1016/j.copbio.2024.103111. Epub 2024 Mar 22. PMID: 38520821.
2. See JE, Barlow S, Arjumand W, DuBose H, Segato Dezem F, Plummer J. Spatial omics: applications and utility in profiling the tumor microenvironment. Cancer Metastasis Rev. 2025 Dec 2;44(4):87. doi: 10.1007/s10555-025-10304-z. PMID: 41331191; PMCID: PMC12672822.
3. Wu Y, Cheng Y, Wang X, Fan J, Gao Q. Spatial omics: Navigating to the golden era of cancer research. Clin Transl Med. 2022 Jan;12(1):e696. doi: 10.1002/ctm2.696. PMID: 35040595; PMCID: PMC8764875.
4. Lan Z, Yang Y, Li L, Wang C, Sun Z, Wang Q, Liu Y. Spatial omics technology potentially promotes the progress of tumor immunotherapy. Br J Cancer. 2025 Sep;133(4):421-434. doi: 10.1038/s41416-025-03075-5. Epub 2025 Jun 2. PMID: 40456924; PMCID: PMC12356860.