Spatial analysis with SPIAT and spaSim to characterize and simulate tissue microenvironments.

Spatial proteomics technologies have revealed an underappreciated link between the location of cells in tissue microenvironments and the underlying biology and clinical features, but there is significant lag in the development of downstream analysis methods and benchmarking tools. Here we present SPIAT (spatial image analysis of tissues), a spatial-platform agnostic toolkit with a suite of spatial analysis algorithms, and spaSim (spatial simulator), a simulator of tissue spatial data. SPIAT includes multiple colocalization, neighborhood and spatial heterogeneity metrics to characterize the spatial patterns of cells. Ten spatial metrics of SPIAT are benchmarked using simulated data generated with spaSim. We show how SPIAT can uncover cancer immune subtypes correlated with prognosis in cancer and characterize cell dysfunction in diabetes. Our results suggest SPIAT and spaSim as useful tools for quantifying spatial patterns, identifying and validating correlates of clinical outcomes and supporting method development.

Tissue-resident memory T cells from a metastatic vaginal melanoma patient are tumor-responsive T cells and increase after anti-PD-1 treatment.

BACKGROUND: Vaginal melanoma (VM) is a rare cancer and has a poor response to immune checkpoint blockade (ICB). CD8+Tissue Resident Memory (TRM) T cells proliferate in response to ICB and correlate with longer survival in metastatic cutaneous melanoma. However, their capacity to respond to VM and their neoantigens is not known. METHODS: Using longitudinal samples, we explored the evolution of VM mutations by whole-exome sequencing and RNAseq, we also defined the immune context using multiplex immunohistochemistry and nanostring pan cancer immune profile. Then using fresh single cell suspensions of the metastatic samples, we explored VM T cells via mass cytometry and single cell RNAseq and T cell receptor sequencing (TCRseq). Finally, we investigated TRM, pre-TRM and exhausted T cell function against melanoma neo-antigens and melanoma differentiation antigens in vitro. RESULTS: Primary VM was non-inflamed and devoid of CD8+ TRM cells. In contrast, both metastases showed proliferating CD8+ TRM were clustered at the tumor margin, with increased numbers in the second ICB-refractory metastasis. The first metastasis showed dense infiltration of CD8+ T cells, the second showed immune exclusion with loss of melanoma cell Major histocompatibility complex (MHC)-I expression associated with downregulation of antigen presentation pathway gene expression. CD8+ TRM from both metastases responded to autologous melanoma cells more robustly than all other CD8+ T cell subsets. In addition, CD8+ TRM shared TCR clones across metastases, suggesting a response to common antigens, which was supported by recognition of the same neoantigen by expanded tumor infiltrating lymphocytes. CONCLUSIONS: In this study, we identified TRM clusters in VM metastases from a patient, but not primary disease. We showed TRM location at the tumor margin, and their superior functional response to autologous tumor cells, predicted neoantigens and melanoma differentiation antigens. These CD8+ TRM exhibited the highest tumor-responsive potential and shared their TCR with tumor-infiltrating effector memory T cells. This suggests VM metastases from this patient retain strong antitumor T cell functional responses; however, this response is suppressed in vivo. The loss of VG MHC-I expression is a common immune escape mechanism which was not addressed by anti-PD-1 monotherapy; rather an additional targeted approach to upregulate MHC-I expression is required.

Multiplex Immunohistochemistry Analysis of Melanoma Tumor-Infiltrating Lymphocytes.

Tumor-infiltrating lymphocytes (TILs) are an important prognostic indicator in melanoma and play a key role in the patient's response to immune checkpoint blockade. However, until recently, it was not possible to combine multi-parameter markers to define the TILs and their histological context. Multiplex immunohistochemistry (mIHC) is a new technology which addresses this issue and enables simultaneous detection of melanoma and multiple immune subsets in formalin fixed paraffin embedded tissue. Following antigen retrieval, melanoma tissue sections are stained by OPAL on an autostainer, including serial rounds of epitope labelling with monoclonal antibodies followed by tyramide signal amplification (TSA). The stained tissue sections are then imaged on the Vectra instrument, and digital images are processed by analysis software (inForm and HALO) to derive tissue segmentation and immune subset densities within the tumor and tumor stroma. Spatial relationships between immune cells and tumor cells are then analyzed using a novel R algorithm. Taken together, multiplex IHC describes the histological context of the immune system in melanoma. The data is objective and allows for characterization of individual melanomas as T cell inflamed (hot), immune excluded, or no immune cells (cold).