Unveiling the Significance of Tertiary Lymphoid Structures in Cancer

Tumor microenvironments (TMEs) are dynamic ecosystems shaped by intricate interactions between cancer cells, stromal cells, and immune components. Amidst this complexity, Tertiary lymphoid structures (TLS) stand out as organized lymphoid-like structures that orchestrate local immune responses. Initially observed in chronic inflammatory conditions, TLS have garnered increasing attention for their presence and significance in various cancer types.

Pathological Features:

TLS exhibit structural resemblance to secondary lymphoid organs, comprising B-cell follicles, T-cell zones, and dendritic cell networks. Their formation within tumors is spurred by persistent antigen exposure, cytokine signaling, and interactions between chemokines and adhesion molecules. Histologically, TLS manifest as densely packed lymphoid aggregates surrounded by stromal cells and infiltrating immune populations, reflecting ongoing immune activation and antigen presentation.

Biological Functions:

In cancer, TLS exert multifaceted roles in shaping the antitumor immune response. They serve as hubs for priming and activation of tumor-specific T and B cells, fostering adaptive immunity against malignant cells. Furthermore, TLS facilitate the recruitment and differentiation of immune effector cells, including cytotoxic T lymphocytes and natural killer cells, thereby bolstering tumor surveillance and elimination. Additionally, TLS contribute to the generation of tertiary lymphoid neogenesis, promoting sustained antitumor immunity within the TME.

Figure 1. Initiation and maturation of TLS. Image source: Tertiary lymphoid structures in cancer: immune mechanisms and clinical implications. MedComm (2020). 2024 Mar; 5(3): e489.

The research on tertiary lymphoid structures (TLS) faces several challenges:

1. Mechanisms of TLS formation and function remain unclear. Current understanding is largely based on models of autoimmune diseases and chronic infections, which may differ from TLS in cancer.
2. Lack of standardization in defining TLS heterogeneity and status. Different cancer types and patients may exhibit varying TLS types, and factors such as cellular composition, location, maturity, and function may impact their prognostic and predictive value.
3. Further exploration is needed on the potential and risks of TLS as therapeutic targets. Inducing or enhancing TLS function may improve tumor control, but it could also increase autoimmune toxicity or other adverse reactions.

The solutions for TLS by Tissue Cytometry

1. TissueGnostics introduces a 10+1 tumor immune microenvironment multicolor solution (mIHC TSA Kits). Built on TG’s unique tissue cytometry analysis method, it includes a comprehensive set of multi-label staining reagents, large-size high-magnification fully automated spectral imaging, and AI-based spatial quantitative analysis for tumor microenvironment. This system resolves core issues of multi-color labeling, severe spectral overlaid, and complex data analysis in a single tissue section.
2. For TLS-related immunological studies, TG’s multi-color staining scheme enables precise tissue cell labeling. Subsequent quantitative analysis of target cell in situ. Moreover, extensive data statistics on the distance between target cells and certain signal pathway receptors within the tumor microenvironment can reveal their relationship with surrounding tissues/cells.
3. Through quantitative data from in situ multi-immunofluorescence staining of clinical samples, correlated with other clinical indicators, precise assessments can be made regarding TLS formation mechanisms, cellular composition, functional status, and immune prognostic impacts.

Figure 2. Left: Schematic representation of CD8+ T cell clustering analysis. The network structure formed by CD8+ T cells within a 50 μm radius is depicted to explore the relationship. Right: Schematic illustration of T-B lymphocyte interaction analysis. The distribution and quantity of CD8+ T cells (blue) surrounding CD20+ B cells (red) within a 30 μm radius are analyzed to investigate the involvement of T-B cell interactions in immune responses.

Figure 3. AI classifier identified the TLS regions.

Figure 4. Foreward and Backward connection. Double-clicking on the contours of individual cells/tissue in the original image highlights the corresponding data point in the scatter plot in real-time; conversely, selecting any quadrant/gate/point in the scatter plot highlights the represented cells/tissues/groups in real-time in the original image. This unique tracking technique in Tissue Cytometry enables precise assessment of data analysis accuracy.

Figure 5. Proximity measurement around the tumor area. Schematic illustration of the spatial relationship and cellular distribution within the tumor microenvironment. Utilizing the AI Classifier feature within Tissue Cytometry technology, specific identification of tumor and stromal regions in tissue samples. With the tumor region as the focal point, single-cell quantification analysis of immune cell spatial distribution within the microenvironment is conducted with micron-level precision. Different colors represent varying distance ranges from the tumor.

Further Study

1. How Tissue Cytometry Improve Your Image Analysis in Tissue Context
2. Macrophage-coated tumor cluster aggravates hepatoma invasion and immunotherapy resistance via generating local immune deprivation
3. Tertiary lymphoid structures in cancer: immune mechanisms and clinical implications.

Contact Us

For further information, please reach out to us at Asia-Pacific office@tissuegnostics.cn or felix.tsai@tissuegnostics.com (Felix Tsai, APAC regional business manager)

TissueGnostics GmbH

Address: Taborstrasse 10/2/8, A-1020 Vienna, AUSTRIA, EU

Website: www.tissuegnostics.com