Spatial immune analyses in clinical cancer tissue

Cancer is a leading cause of premature death and lung cancer is the deadliest cancer type, with non-small cell lung cancer (NSCLC) representing 85% of lung cancer cases. Despite promising development in cancer treatment in recent decades, overall prognosis is poor. The aim of this thesis was to explore novel techniques in protein visualization in clinical cancer tissue to better our understanding of cancer immunity and to discover new biomarkers for improved cancer diagnostics. In Paper I traditional immunohistochemistry (IHC) was compared to the in-situ proximity ligation assay (isPLA). Both techniques were applied to stain 12 proteins in 39 cell lines and 37 tissue types. Two different antibodies were used in the IHC assay and in the isPLA, where binding by both antibodies is required to generate detection signals. The comparison of staining patterns showed that the isPLA presents a valuable alternative to traditional IHC. In Paper II cancer tissue from 357 NSCLC patients was immunophenotyped through IHC annotations of 11 different immune markers. A distinct group of cases with a signature of NK cells and/or plasma cells had favorable prognosis despite significantly lower T-cell activation signatures. This study provides a detailed description of the immune landscape in NSCLC, extending previous concepts, and highlights plasma and NK-cells as potential biomarkers for further validation. In Paper III a multiplex-multispectral pipeline was established to explore three immune marker panels in a NSCLC cohort, spatially quantifying 13 immune cell types. The immune composition of NSCLC was analyzed for the prognostic relevance of immune cell coordination. Cell densities and distances were found to contribute independently to prognosis, indicating that spatial information on local immune cell infiltration is crucial for understanding tumor immunity. In Paper IV an extensive characterization of the immune cell landscape of colon cancer identified a prognostic signature based on the ratio of CD8+ lymphocytes to CD68+CD163+ macrophages. This signature was superior to the state-of-the-art ‘Immunoscore’, and was also associated with longer survival when analyzed in other common cancer types. This presents a promising immunological biomarker that warrants further validation as a prognostic and predictive signature in common cancers. In summary, this thesis presents an in-depth study of immune cell infiltration in several cancer types to better understand cancer immunity. Through novel techniques and spatial metrics, we describe immunophenotypes that might contribute to cancer classification and prognostication. The identified immune phenomena may also present alternative treatment targets to overcome resistance to immunotherapy