Background Tumor-infiltrating immune cells play an important role against cancer and are critical to control tumor growth and spread. Immunotherapy and immune checkpoint inhibitors, which aim to reinvigorate exhausted T cells have revolutionized cancer therapy. Despite inducing long-term response in many cancer types, these therapies remain ineffective for most patients.

A better understanding of tumor microenvironment and in particular the presence of immune cells and other stromal cells, along with their abundance, distribution and interactions with other immune/or tumor cells, may help to better stratify patients and understand mechanisms of resistance to immunotherapy. Indeed, the distribution of T cells in tumor could be associated to favorable prognosis in different cancers and the relationship between cells could be linked to patient outcome. For instance, the presence of macrophages close to tumor cells in non-small cell lung cancer or the proximity of regulatory T cells (Treg) cells to cytotoxic CD8+ T-cells in gastric cancer are associated with worse outcome.

Methods The analysis of the spatial distribution of immune and non-immune cells and of their proximity in the tumor microenvironment seems relevant to understand response to immunotherapy. Here, we propose a new tool allowing the assessment of 3 spatial parameters: 1) Evaluation of cell-to-cell proximity metrics between 2 different populations or within the same population (clustering), 2) Interaction of two cell populations using nearest neighbor distance measurement (G-function) and 3) Spatial cell distribution highlighting hot spots ( Kernel’s heatmap).

Brightplex^® is a chromogenic multiplex immunohistochemistry technology allowing the detection of several biomarkers on a single FFPE slide to identify and quantify complex cell populations such as T-cells expressing immune checkpoints, M1 and M2 macrophages, Treg cells and myeloid-derived suppressor cells. Following staining and digitization, images are fused to create a virtual multi-channel image where cells of interest are detected by digital pathology (DP). With Brightplex and DP, we have developed a workflow to assess the spatial distribution and potentially cell-to-cell interactions within a slide or between two or three adjacent slides stained with different multiplex panels. Following cell detection, spatial analysis is performed using spatstat module on R-studio software.

Integrated to Immunogram, this new tool could help clinical researchers to understand tumor landscape, predict response to treatment and patient outcome.