Spatial and Temporal Heterogeneity of Tumor-Infiltrating Lymphocytes in Advanced Urothelial Cancer

Abstract

Checkpoint inhibitors targeting PD-(L)1 induce objective responses in 20% of patients with metastatic urothelial cancer (UC). CD8⁺ T cell infiltration has been proposed as a putative biomarker for response to checkpoint inhibitors. Nevertheless, data on spatial and temporal heterogeneity of tumor-infiltrating lymphocytes in advanced UC are lacking. The major aims of this study were to explore spatial heterogeneity for lymphocyte infiltration and to investigate how the immune landscape changes during the disease course. We performed multiplex immunohistochemistry to assess the density of intratumoral and stromal CD3⁺, CD8⁺, FoxP3⁺ and CD20⁺ immune cells in longitudinally collected samples of 49 UC patients. Within these samples, spatial heterogeneity for lymphocyte infiltration was observed. Regions the size of a 0.6 tissue microarray core (0.28 mm²) provided a representative sample in 60.6 to 71.6% of cases, depending on the cell type of interest. Regions of 3.30 mm², the median tumor surface area in our biopsies, were representative in 58.8 to 73.8% of cases. Immune cell densities did not significantly differ between untreated primary tumors and metachronous distant metastases. Interestingly, CD3⁺, CD8⁺ and FoxP3⁺ T cell densities decreased during chemotherapy in two small cohorts of patients treated with neoadjuvant or palliative platinum-based chemotherapy. In conclusion, spatial heterogeneity in advanced UC challenges the use of immune cell infiltration in biopsies as biomarker for response prediction. Our data also suggests a decrease in tumor-infiltrating T cells during platinum-based chemotherapy.

Keywords: biomarkers; longitudinal changes; spatial heterogeneity; tumor-infiltrating lymphocytes; urothelial cancer.

Figure 1

Data processing and analysis of mIHC images. (A) Overview of a biopsy after spectral unmixing by PerKinElmer inForm^® image-analysis. The rectangle indicates the region depicted in (B–D) (B) Tissue segmentation by PerkinElmer inForm. An algorithm was trained based on the expression of pan cytokeratin, DAPI and autofluorescence to discriminate between tumor (black) and stroma (white). C/D. Cell segmentation (C) and phenotyping (D). A neural network was trained to identify T cells and B cells (white dots) based on the expression of the seven immunohistochemistry markers (red = CD3; cyan = CD8; green = FoxP3; magenta = CD20; yellow = CD45RO; white = tumor marker; dark blue = DAPI). The scalebar represents a distance of 100 µm.

Figure 2

Immune cell infiltrate per tissue site. (A) Multiplex immunohistochemistry images of the five most frequent tissue sites. The scalebar represents a distance of 100 µm. (B) CD3⁺, CD8⁺, FoxP3⁺ and CD20+ cell density in the tumor (upper panel) and stroma compartment (lower panel) per tissue site. For all cell subsets, we observed significant differences between tissue sites, both in the stromal and tumoral compartments (Kruskal-Wallis test, p < 0.05). Black lines indicate significant differences between pairs (Dunn’s test, *p < 0.05, **p ≤ 0.01, ***p ≤ 0.001). In some patients, no CD20+ cells were present. To enable visualization of cell densities on a log scale, the CD20+ densities of these patients was replaced by 0.5 cells/mm2 (~lowest value in this plot).

Figure 3

Immune cell infiltration in primary tumor and synchronous lymph node metastasis. Intratumoral (upper panel) and stromal (lower panel) CD3⁺, CD8⁺, FoxP3⁺ and CD20⁺ cell densities in paired urinary tract and lymph node samples. These samples were obtained during the same procedure.

Figure 4

Spatial heterogeneity. (A) Spatial heterogeneity in a lymph node metastasis (upper panel) and a primary tumor (lower panel). Images on the right and left side are derived from the same sample. The scalebar represents a distance of 100 µm. (B) Analysis of heterogeneity. In each sample, four tumor regions were selected. The mean cell density of these four regions was calculated. Based on the mean cell densities of the samples, quartiles were defined (upper part of the figure). Next, we evaluated whether the small regions were representative by checking whether the individual regions belonged to the same quartiles as the sample mean. (C) CD8⁺ T cell densities in the selected 0.28 mm2 (C1) and 3.30 mm² (C2) regions. The dots show the cell densities of the regions. The four regions of one sample are interconnected by a line. In some regions, no CD8⁺ cells were present. To enable visualization of cell densities on a log scale, the CD8⁺ densities of these patients was replaced by 5 cells/mm2 (~lowest value in C1 and C2).

Figure 5

Changes during chemotherapy. (A) Changes in intratumoral and stromal CD3⁺, CD8⁺, FoxP3⁺ and CD20⁺ cell density during neoadjuvant chemotherapy. Samples were obtained by transurethral resection (before) and cystectomy (after). (B) Changes during palliative platinum-based chemotherapy. Paired samples were obtained from the same tissue site.