The tumor immune microenvironment drives a prognostic relevance that correlates with bladder cancer subtypes - Pfannstiel, Carolin; Strissel, Pamela; Chiappinelli, Katherine B.; Sikic, Danijel; Wach, Sven; Wirtz, Ralph M.; Wullweber, Adrian; Taubert, Helge; Breyer, Johannes; Otto, Wolfgang; Worst, Thomas; Burger, Maximilian; et al. (Cancer Immunology Research, 2019)
Muscle-invasive bladder cancer (MIBC) represents approximately two-thirds of invasive urothelial bladder cancers (UBC) and has high morbidity and mortality. Men are over 3-fold more frequently affected by UBC than women. Despite intensive efforts to improve patient treatment and outcome, two-thirds of patients with UBC will have a recurrence or disease progression within 5 years. We demonstrated that the quantity and spatial distribution of stromal tumor-infiltrating lymphocytes (sTIL) within the tumor immune microenvironment (TIME) predict stages of tumor inflammation, subtypes, and patient survival and correlate with expression of immune checkpoints in an analysis of 542 patients with MIBC. High sTILs indicated an inflamed subtype with an 80% 5-year DSS, and a lack of immune infiltrates identified an uninflamed subtype with a survival rate of less than 25%. A separate immune evading phenotype with upregulated immune checkpoints associated with poor survival. Within the TIME are tertiary lymphoid structures (TLS), which can mediate antitumor activity via immune cells. High TLS amounts and close tumor distance correlated significantly with an inflamed phenotype and favorable survival. The uninflamed and evasion phenotypes showed lowest TLS numbers, farthest tumor distances, and shortest survival. High inflammation also correlated with increased neoantigen load and mutational burden. Patients treated with adjuvant chemotherapy showed a favorable prognosis, which was dependent on high sTILs. Determination of sTILs and tumor subtypes may stratify therapy success and patient survival, and considering sTILs can easily be quantified using simple morphologic parameters, like hematoxylin and eosin, sTILs can be implemented for predicting patient survival in a routine manner.
CRIS-Team Scopus Importer:2019-06-21