Frontiers in Oncology 2022 June 20 [Link]
Hely Ollila, Mikko I Mäyränpää, Lassi Paavolainen, Juuso Paajanen, Katja Välimäki, Eva Sutinen, Henrik Wolff, Jari Räsänen, Olli Kallioniemi, Marjukka Myllärniemi, Ilkka Ilonen, Teijo Pellinen
Background: Pleural mesothelioma (MPM) is an aggressive malignancy with an average patient survival of only 10 months. Interestingly, about 5%-10% of the patients survive remarkably longer. Prior studies have suggested that the tumor immune microenvironment (TIME) has potential prognostic value in MPM. We hypothesized that high-resolution single-cell spatial profiling of the TIME would make it possible to identify subpopulations of patients with long survival and identify immunophenotypes for the development of novel treatment strategies.
Methods: We used multiplexed fluorescence immunohistochemistry (mfIHC) and cell-based image analysis to define spatial TIME immunophenotypes in 69 patients with epithelioid MPM (20 patients surviving ≥ 36 months). Five mfIHC panels (altogether 21 antibodies) were used to classify tumor-associated stromal cells and different immune cell populations. Prognostic associations were evaluated using univariate and multivariable Cox regression, as well as combination risk models with area under receiver operating characteristic curve (AUROC) analyses.
Results: We observed that type M2 pro-tumorigenic macrophages (CD163+pSTAT1-HLA-DRA1-) were independently associated with shorter survival, whereas granzyme B+ cells and CD11c+ cells were independently associated with longer survival. CD11c+ cells were the only immunophenotype increasing the AUROC (from 0.67 to 0.84) when added to clinical factors (age, gender, clinical stage, and grade).
Conclusion: High-resolution, deep profiling of TIME in MPM defined subgroups associated with both poor (M2 macrophages) and favorable (granzyme B/CD11c positivity) patient survival. CD11c positivity stood out as the most potential prognostic cell subtype adding prediction power to the clinical factors. These findings help to understand the critical determinants of TIME for risk and therapeutic stratification purposes in MPM.