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The architecture of neoplastic follicles in follicular lymphoma; analysis of the relationship between the tumor and follicular helper T cells

CD4+ T-follicular helper cells are essential for the survival, proliferation, and differentiation of germinal center B cells and have been implicated in the pathogenesis of follicular lymphoma (FL). To further define the role of these cells in FL, we used multiparameter confocal microscopy to compare the architecture of normal and neoplastic follicles and next generation sequencing to analyze the T-cell receptor repertoire in FL lymph nodes (LN). Multiparameter analysis of LN showed that the proportion of T-follic-ular helper cells (TFH) in normal and neoplastic follicles is the same and that the previously reported increase in TFH numbers in FL is thus due to an increase in the number and not content of follicles. As in normal germinal centers, TFH were shown to have a close spatial correlation with proliferating B cells in neoplastic follicles, where features of immunological synapse formation were observed. The number of TFH in FL correlate with the rate of B-cell proliferation and TFH co-localized to activation induced cytidine deaminase expressing proliferating B cells. T-cell receptor repertoire analysis of FL LN revealed that follicular areas are significantly more clonal when compared to the rest of the LN. These novel findings show that neoplastic follicles and germinal centers share important structural features and provide further evidence that TFH may play a role in driving B-cell proliferation and genomic evolution in TFH. Our results also suggest that targeting this interaction would be an attractive therapeutic option.

Sections were then incubated with combinations of 3 or 4 primary antibodies with 0.025% Triton X-100 for 12 hours at 4°C in a humidified chamber. The antibodies used and their concentrations are listed in Table S3. The antibodies used in each combination were raised in different species to facilitate detection by species-specific secondary antibodies. After primary antibody incubation, slides were washed and then incubated with the appropriate combination of fluorescently-conjugated secondary antibodies and 4',6-diamidino-2phenylindole dihydrochloride (DAPI) (Cell Signaling Technology, Danvers, USA) if a nuclear stain was required. Sections were mounted with coverslips using ProLong Gold Antifade mounting medium (Invitrogen, Carlsbad, California, USA).
Negative controls were run in parallel with all staining to ensure that the fluorescence detected was not due to non-specific binding of the secondary antibodies or tissue autofluorescence. Positive controls were reactive LNs or tonsil tissue. Additional controls were performed to ensure there was no spectral overlap of the fluorescently-conjugated antibodies.

Image acquisition
All images were acquired on a Nikon Eclipse Ti-E upright microscope equipped with Nikon A1R Si confocal imaging system and lasers emitting at 405nm, 488nm, 561nm, and 642nm (Nikon Corporation, Tokyo, Japan). Low power images were obtained with a Pan Fluor x10 objective and high power images with a Pan Apo oil immersion x60 objective. To maintain consistency and to permit comparative analyses, all images were acquired on the same microscope and laser power, photo multiplier tube (PMT) gain, pixel dwell time, pin hole size, optical section thickness, offset, and filter settings were kept the same for analysis of paired control slides.
These settings were maintained as closely as possible for all similarly stained sections but small differences in the thickness of tissue, quality of fixation, and the age of the specimen affected the strength of antibody binding, fluorescence and autofluorescence and accordingly, laser power, PMT gain, and offset were optimised for individual sections. 3-5 high power images (x60 objective) were obtained and analysed from representative follicular and interfollicular areas of each section.

Image analysis
Binary layers were generated for each channel by setting thresholds to define which areas of an image were positive signal and included in the binary layer, and which areas were negative or background and excluded from the binary layer. Thresholding was performed on the basis of intensity of fluorescence in each channel and a size restriction to reduce false positive signal from small areas of autofluorescence. Large areas of autofluorescence or artefact from blood vessels or formalin crystals were deleted manually from the binary layers.
Generating binary layers for each channel permitted the accurate, automated quantification of the area of positive signal in an image, and the analysis of cellular co-localization. Areas Follicular helper T-cells in FL where combinations of antigens were expressed were calculated by defining 'intersecting' binary layers where the signal in 2 or more channels overlapped. This was used for example for identifying CD4 pos cells that co-expressed PD-1 and ICOS; the proportion of CD4 pos cells co-expressing these antigens was calculated by dividing the area of the CD4 PD-1 ICOS intersecting binary layer by the total area of the CD4 layer.
The proportion of proliferating cells in contact with TFH cells was calculated by defining individual cells in the Ki67 binary layer and automatically quantifying the proportion that were in direct contact with the intersecting binary layer of CD4 PD-1 or PD-1 ICOS ( Figure S1).
For the analysis of CD20 pos cells that were in contact with TFH, manual, visual analysis had to be performed as the diffuse pattern of CD20 staining and the closely packed nature of CD20 pos cells meant that the automated analysis software was unable to reliably distinguish individual CD20 pos cells that were not Ki67 pos . To perform this, images were thresholded according to the method described above and binary layers of the intersecting CD3 and PD1 binary layers were created. A grid was superimposed over the image to aid visual assessment and to help ensure that each area of the image was inspected. A 'taxonomy tool' within the NIS elements software package was then used for the manual counting of Ki67 pos and Ki67 neg CD20 pos Bcells that were, or were not in contact with TFH.
Due to the manual visual assessment of these images, two separate investigators analysed a subset of these images in order to identify and reduce operator bias. The two investigators were blinded to each other's results. There was no significant difference in number of Ki67 pos cells counted by observer, the number of cells in contact with TFH was also concordant between operators.

Supplemental material Follicular helper T-cells in FL
Manual measurement was also used for analysis of BCL6 and FOXP3 images.
Images have been optimized for contrast using contrast settings and Look Up Tables (LUTs) and, where appropriate, magnification has been performed, no further image enhancement or manipulation has been used.

DNA extraction and TCR sequencing
Equivalent areas of tissue were dissected from follicular and interfollicular areas. Genomic DNA was extracted using the miniDNA extraction kit (Qiagen, Venlo, Netherlands) according to the manufacturer's instructions.

Clonality index
The clonality index was derived from Shannon's entropy, a measure of the certainty with which the identity of a clone selected randomly from a population of different clones can be