The research team turned to spatial transcriptomics, a technology that measures gene expression across intact tissue sections while preserving the physical coordinates of every measurement. Unlike single-cell RNA sequencing, which dissociates tissue and loses positional information, spatial transcriptomics allows researchers to ask not only which genes are active, but where. The investigators applied this approach to tumor samples containing TLS and used a computational framework called EcoTyper to infer cell states — transcriptionally coherent subpopulations within broader cell lineages — directly from the spatial data. In total, they identified 71 distinct cell states spanning all of the major immune lineages present in the tumor microenvironment, from B cells and T cells to dendritic cells and neutrophils.

This cell state-level resolution proved to be the study’s decisive methodological choice. When the researchers examined how each inferred state was distributed along a gradient running from the geometric core of a TLS to its surrounding periphery, they found that cells belonging to the same lineage could behave in dramatically different ways. Some lineages contained states that were enriched within the TLS and others that were depleted there, meaning that a coarse analysis lumping all cells of a lineage together would have averaged away the very patterns the researchers were seeking. Core-periphery organization, the authors conclude, is in an important sense invisible at the cell type level and only emerges at the cell state level.

Among the most notable discoveries were two TLS-enriched CD4 T cell states with clearly distinct marker gene programs. Although both belonged to the helper T cell lineage and both accumulated within tertiary lymphoid structures, they carried different transcriptional signatures, suggesting they perform different functions within the immune hub. One of these states, designated CD4.T_S02, was more abundant toward the geometric core of the TLS, while its counterpart occupied more peripheral positions. This kind of fine-grained spatial segregation within a single lineage hints at a division of labor inside TLS that mirrors, in miniature, the zoned organization of canonical lymphoid organs such as lymph nodes and the spleen.

To complement the abundance-gradient analysis, the team constructed weighted chemokine networks centered on three key signaling molecules: CXCL13, CXCL12, and the paired chemokines CCL19 and CCL21. Chemokines are the trafficking signals of the immune system, guiding cells to their destinations through gradients and receptor-ligand matching. CXCL13 and CCL19/21 are classically associated with lymphoid organization — they recruit B cells and helper T cells into structured aggregates and help maintain the boundary between distinct lymphoid zones — while CXCL12 has been implicated in both lymphoid organization and immunosuppressive niches. By mapping how these chemokine signals relate to the inferred cell states across space, the researchers could ask whether the transcriptional picture of TLS organization was corroborated by an independent, signaling-centered lens.

It was. The chemokine network analysis revealed two recurrent communities of cell states. The first was a lymphocyte activation community confined to the TLS themselves, consistent with the idea that the core of these structures is where immune cells are being primed and activated. The second was an effector-focused community that extended outward into the surrounding tumor tissue, suggesting that TLS do not merely house immune activity but actively export it — dispatching armed effector cells into the tumor proper, where they can encounter and attack malignant cells. This core-to-periphery functional gradient provides a mechanistic rationale for the clinical association between TLS presence and better outcomes: a tumor with well-organized TLS is not just decorated with immune cells, it is plugged into a production line for antitumor immunity.

One of the most intriguing recurring characters in this spatial drama was a neutrophil cell state of tentative identity that appeared as a hub across all three chemokine axes the researchers examined. Neutrophils are usually cast as short-lived, blunt instruments of innate immunity, and in many tumors they are associated with immunosuppression. The repeated emergence of a neutrophil state at the center of TLS-associated chemokine networks raises the possibility that a specialized neutrophil population may play an architectural or regulatory role within these structures — perhaps helping to organize the recruitment of lymphocytes, or modulating the signals that keep the TLS intact. The authors are careful to label this state’s identity as tentative, and defining it precisely will be a task for future work, but its centrality across independent analyses makes it one of the study’s most provocative leads.

Taken together, the two analytical strategies — the TLS-centric abundance gradient and the weighted chemokine networks — converge on a coherent model. Tertiary lymphoid structures, in this view, are spatially zoned organs: an active core where lymphocyte activation and germinal center-like processes dominate, surrounded by a more diffuse effector periphery where armed immune cells transition into the tumor tissue. The zones are not arbitrary; they are organized through a shared, key set of chemokine signaling pathways, with CXCL13, CXCL12, and CCL19/21 acting as the molecular mortar that holds the architecture in place. This zoned model reframes TLS from static histological features into dynamic, functionally compartmentalized machines for generating and deploying antitumor immunity.

The implications for cancer medicine are considerable. TLS are already the subject of intense interest as biomarkers for immunotherapy response, and numerous clinical efforts aim to induce or mature them in tumors that lack them. The new findings suggest that such efforts should be evaluated not simply by whether TLS appear, but by whether they acquire the correct internal organization — the right cell states in the right places, wired together by the right chemokine signals. A disorganized aggregate of lymphocytes may not function like a properly zoned TLS, and therapies that reshape chemokine signaling could, in principle, convert poorly structured infiltrates into fully functional immune hubs. The cell state atlas generated in this study offers a reference against which such interventions could be measured.

The study, conducted under ethics approvals from the University of Tokyo and Keio University School of Medicine and supported by JSPS KAKENHI grants, also demonstrates the maturing of spatial transcriptomics as a discovery platform. By combining computational state inference with explicit spatial modeling and network analysis, the researchers extracted organizational principles that neither approach alone would have revealed. As the technology spreads and atlases of this kind accumulate across cancer types, the field moves closer to a genuinely spatial understanding of the tumor immune microenvironment — one in which the arrangement of cells, not merely their presence, becomes a target of measurement, prediction, and ultimately therapy. For now, the message of this work is clear: to understand how tumors’ hidden immune organs work, one must look not just at who is there, but at who is where, and at the chemical conversations that put them there.

Subject of Research: Spatial organization and chemokine network architecture of tertiary lymphoid structures in tumors

Article Title: Spatial transcriptomics reveals cell state-level organization and chemokine network architecture within tertiary lymphoid structures

Article References: Yan, A., Iwasawa, T., Tanaka, N., Kakimi, K., Lysenko, A., & Tsunoda, T. (2026). Spatial transcriptomics reveals cell state-level organization and chemokine network architecture within tertiary lymphoid structures. Cancer Immunology, Immunotherapy. https://doi.org/10.1007/s00262-026-04529-2

Image Credits: AI Generated

DOI: 10.1007/s00262-026-04529-2

Keywords: tertiary lymphoid structures, spatial transcriptomics, chemokine signaling networks, cell states, tumor microenvironment, cancer immunology, CXCL13, CXCL12, CCL19, CD4 T cells, neutrophils, immunotherapy biomarkers