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.

BackgroundAssessment of the immune status of muscle-invasive bladder cancer (MIBC) has previously shown to be prognostically relevant after treatment with curative intent. We conducted this study to develop a clinically applicable immune gene expression assay to predict prognosis and adjuvant chemotherapy benefit.Patients and methodsGene expression ofCD3Z,CD8AandCXCL9, immune cell (IC) populations including stromal tumor infiltrating lymphocytes (sTILs), T-cells, natural killer cells (NK-cells), macrophages, Programmed cell death protein 1 positive (PD-1) IC and tumor subtypes (MD Anderson Cancer Center/MDACC-approach) were assessed in 187 MIBC patients (Comprehensive Cancer Center Erlangen-EMN/CCC-EMN-cohort). A gene expression signature was derived by hierarchical-clustering and validated in The Cancer Genome Atlas (TCGA)-cohort. IC populations in the TCGA cohort were assessed via CIBERSORT. Benefit of platinum-containing adjuvant chemotherapy was assessed in a pooled cohort of 125 patients. Outcome measurements were disease specific survival, disease-free survival and overall survival.ResultsThe gene expression signature ofCXCL9,CD3ZandCD8Acorrelates with quantitative amounts of specific IC populations and sTILs (CCC-EMN: ρ-range: 0.44–0.74; TCGA: ρ-range: 0.56–0.82) and allows stratification of three different inflammation levels (inflamed high, inflamed low, uninflamed). Highly inflamed tumors are preferentially basal subtype and show favorable 5-year survival rates of 67.3% (HR=0.27; CCC-EMN) and 55% (HR=0.41; TCGA). Uninflamed tumors are predominantly luminal subtypes and show low 5-year survival rates of 28% (CCC-EMN) and 36% (TCGA). Inflamed tumors exhibit higher levels of PD-1 and Programmed cell death 1 ligand 1 (PD-L1). Patients undergoing adjuvant platinum-based chemotherapy with ‘inflamed high’ tumors showed a favorable 5-year survival rate of 64% (HR=0.27; merged CCC-EMN and TCGA cohort).ConclusionThe gene expression signature ofCD3Z,CD8AandCXCL9can assess the immune status of MIBC and stratify the survival of MIBC patients undergoing surgery and adjuvant platinum-based chemotherapy. Furthermore, the assay can identify patients with immunological hot tumors with particular high expression of PD-L1 potentially suitable for immunotherapy.

<p>Antigen presenting cell signature TCGA: Full table of included genes.</p>

<p>CIBERSORT - Spearman rank correlations between predicted immune cell populations in the TCGA cohort.</p>

<p>Distribution of stromal tumor infiltrating lymphocytes in analyzed cohorts and subgroups.</p>

<p>Reference Sequences - Nanostring analysis for subtyping (CCC-EMN cohort).</p>

<p>Distribution of stromal tumor infiltrating lymphocytes in analyzed cohorts and subgroups.</p>

<p>Inflammation gene signature TCGA: Full table of included genes.</p>