Table 2.

Methods to detect and quantify TLS

Method of detecting/characterizing TLS	Features of method
Hematoxylin and eosin (H&E) staining27	Most basic histological analysis. Highly defined TLS with GCs can be confidently identified with this method, but distal sections (of the TLS structure) without clear B/T-cell zone borders or poorly formed TLS can be indistinguishable from other non-TLS lymphocytic aggregates.
Hematoxylin + 3,3′-diaminobenzidine (H-DAB) staining, H&E-DAB, H-DAB + alkaline phosphatase (AP) staining1,4,12,18,22,28,30–33,36–45,48,49,51	Single or double marker (H-DAB + AP) staining with a morphological stain increases confidence in accurately classifying lymphocytic aggregates as TLS. The drawback is that only 1–2 markers can be assessed per section; phenotypic composition of TLS with sequential sections using a variety of markers can be inferred but not quantified, and this approach introduces slice-to-slice variability. Assessment of the developmental/maturational status of TLS depends heavily on marker selection; at a minimum, a B-cell marker is required for a 1-marker panel, followed by a T-cell marker for a 2-marker panel.
Fluorescence immunohistochemistry (f-IHC)14,23,25	The ability to use 3–4 markers within a single slice facilitates basic cell phenotyping, which is a significant step up from H-DAB methods. However, several panels are still needed if maturational and organizational structures are to be identified; an example of this would be for the first panel to identify T and B cells as well as the CD4 status of the former, while the second panel would look for the presence of Ki67+ cells, lymphatics and FDCs.
Multiplex IHC19,34	These methods are able to simultaneously identify 5+ markers within the same tissue section. As a result, a variety of phenotypes, as well as the TLS maturation/organizational status, can be identified without being hampered by section-to-section variability.
Multiplex IHC + histocytometry16	The addition of a histocytometric analysis approach allows accurate phenotypic characterization of cells using all the available markers, resulting in a large number of phenotypes that can be identified with high specificity. Phenotypes can be quantified and advanced approaches can also derive statistical analyses from spatial relationships between phenotypes of interest. Analysis can be automated (after machine learning) allowing for high throughput.
RNA seq5,17,46,47	Identifying the presence of TLS within a whole-tissue RNA digest is a relatively simple method, provided that a reference signature dataset is available and is ideal for high-throughput analysis. However, this method is subject to any limitations and bias inherent in the reference dataset. Establishing a reference signature dataset is a significant undertaking; requiring access to large numbers of samples both in order to generate and validate a signature.
Laser capture microdissection (LCM) + RNA seq23	LCM allows specific targeting of TLS tissue, removing contaminating non-TLS RNA in the downstream analysis. This is the best RNA analysis approach of TLS short of spatial transcriptomics; however, this approach is driven by a minimum RNA quantity requirement (and therefore minimum region of interest size for dissection), which may restrict the specificity of the area selection. The laser capture-dissection step is the most time-consuming step of the procedure, and requires an uncommon piece of equipment.
Flow cytometry14	Flow cytometry requires a single-cell suspension of tissue, which results in a homogenous population from various tissue structures. Determining the presence of TLS with flow cytometry is difficult, as immune cells from non-TLS regions are mixed with ones from TLS. However, under certain conditions: careful tissue collection (e.g., ensuring if possible that no lymph nodes are present in the tissue sample) and use of markers to identify cell populations mainly present in lymphoid follicles can detect for the presence of TLS within a sample. Relative proportions of key cells (e.g., Ki67+ B cells) can also be assessed with this method.
Spatial transcriptomics21	Regions of interest on tissue section are selected based on H&E or with a limited selection of protein markers and are transcriptionally analyzed for a large selection of RNA markers or proteins. Histocytometric approaches depend on the method employed, with some methods such as GeoMx chosen due to the requirement of 20–200 cells for minimum RNA/protein content per comparative sample to be analyzed; therefore, histocytometric approaches are not feasible. Currently, there is only one other commercially available system (Visium from 10X Genomics). Both require significant operator expertize across several aspects of the procedure.