Advanced image analysis for immunotherapy response prediction in melanoma

Pathological assessment in cancer patients is essential to determine the correct diagnosis, which has a significant impact on the prognosis and success of their therapeutic plan. The recent introduction of spatial proteomics techniques allows pathologists to evaluate an increasing number of putative biomarkers at the level of the individual cell. This single-cell analysis has pathological assessment in cancer patients is essential to determine the correct diagnosis, which has a significant impact on the prognosis and success of their therapeutic plan. The recent introduction of spatial proteomics techniques allows pathologists to evaluate an increasing number of putative biomarkers at the level of the individual cell. This 'single-cell' analysis ultimately created the space to achieve the fine biological dissection of the tumor required for precision medicine. Our group, in collaboration with European partners, has developed a new tool called 'Multiple Iterative Labelling by Antibody Neodeposition' (MILAN), which makes it possible to analyse multiple (> 70) proteins in a single tissue section with unprecedented resolution (' single-cell 'level). Despite the potential of spatial proteomics, its applications have not yet been exploited by the scientific community. To date there are no methods available in the literature based on spatial proteomics to measure the activity of biological pathways in situ. However, the ability to evaluate pathway activity on top of other phenotypic and functional features at the single cell level in a spatial context would greatly contribute to our understanding of the different relationships between the cell types present in tumour tissue. Therefore, within this project I will develop a method to estimate specific pathway activities at the single cell level and use this information to classify cancer patients. As a case study, I will analyse the activity of HLA-DR, which may be aberrantly expressed in melanoma tumours, activating various pathways within and around the tumour cells as identified by preliminary bulk RNA sequence analysis. To achieve this goal, I will first focus on the most important and challenging aspect of this ambitious and innovative project: integrating spatial information of individual cells in tissue sections with their protein expression in pathway activity scores. For this to happen, some basic steps must be accomplished: (1) identify and validate the most reliable antibodies that measure the proteins present in the HLA-DR pathway and its interactome; (2) integrate these insights on top of already available phenotypic and functional markers used to identify each cell type in the tissue; (3) use this information to derive the activity score of individual cells associated with the HLA-DR pathway; (4) Integrate this cell activity score into a spatial context to derive pathway / network activity scores; and (5) these findings correlate with clinical features of the included patients.