Purpose: In NABUCCO, the safety and efficacy of preoperative ipilimumab plus nivolumab were assessed in stage III urothelial cancer. Encouraging responses were achieved, and ipilimumab 3 mg/kg (ipilimumab-high) seemed more effective than ipilimumab 1 mg/kg (ipilimumab-low). We explored ipilimumab plus nivolumab response biomarkers and tumor microenvironment (TME) treatment dynamics. Patients and Methods: Baseline formalin-fixed, paraffinembedded tumor tissue was analyzed using PD-L1 IHC (n ¼ 51) and whole-exome and transcriptome sequencing (both n ¼ 53) and correlated with response. Baseline infiltration of CD8⁺ T cells (n ¼ 51) and at cystectomy (n ¼ 42) was examined. Single-cell RNA sequencing (scRNA-seq) of CD3⁺ T cells was conducted on on-treatment resection tissue of two responders to ipilimumab-high to explore the characteristics of CD8⁺ T cells within the TME. Results: High tumor mutational burden and PD-L1 positivity were associated with response to ipilimumab plus nivolumab. Nonresponding patients exhibited increased expression of a TGFβ signature. We observed increased transcription of the g2m checkpoint and e2f target in responders to ipilimumab-high and enhanced transcription of IFN-α and IFN-γ hallmarks in responders to ipilimumab-low. CD8⁺TCF7⁺ T cells accumulated in the TME of responders to ipilimumab-high. scRNA-seq of CD8A⁺TCF7⁺ T cells demonstrated enhanced expression of IL7R, CCR7, GPR15, XCL1, SELL, and LEF1. Conclusions: Our data indicate that tumor mutational burden, PD-L1, and TGFβ are potential biomarkers for response to ipilimumab plus nivolumab in stage III urothelial cancer. An inflammatory TME might be relevant for responding to ipilimumab-low. We found that in responders to ipilimumabhigh, TCF7⁺CD8⁺ T cells accumulated in the TME. scRNA-seq in two responders suggested that TCF7⁺CD8A⁺ T cells express genes associated with immunologic memory formation and T-cell homing.

Immune checkpoint inhibitors (ICI) can achieve remarkable responses in urothelial cancer (UC), which may depend on tumor microenvironment (TME) characteristics. However, the relationship between the TME, usually characterized by immune cell density, and response to ICI is unclear. Here, we quantify the TME immune cell densities and spatial relationships (SRs) of 24 baseline UC samples, obtained before pre-operative combination ICI treatment, using multiplex immunofluorescence. We describe SRs by approximating the first nearest-neighbor distance distribution with a Weibull distribution and evaluate the association between TME metrics and ipilimumab+nivolumab response. Immune cell density does not discriminate between response groups. However, the Weibull SR metrics of CD8⁺ T cells or macrophages to their closest cancer cell positively associate with response. CD8⁺ T cells close to B cells are characteristic of non-response. We validate our SR response associations in a combination ICI cohort of head and neck tumors. Our data confirm that SRs, in contrast to density metrics, are strong biomarkers of response to pre-operative combination ICIs.

Candidate immune biomarkers have been proposed for predicting response to immunotherapy in urothelial cancer (UC). Yet, these biomarkers are imperfect and lack predictive power. A comprehensive overview of the tumor immune contexture, including Tertiary Lymphoid structures (TLS), is needed to better understand the immunotherapy response in UC. We analyzed tumor sections by quantitative multiplex immunofluorescence to characterize immune cell subsets in various tumor compartments in tumors without pretreatment and tumors exposed to preoperative anti-PD1/CTLA-4 checkpoint inhibitors (NABUCCO trial). Pronounced immune cell presence was found in UC invasive margins compared to tumor and stroma regions. CD8⁺PD1⁺ T-cells were present in UC, particularly following immunotherapy. The cellular composition of TLS was assessed by multiplex immunofluorescence (CD3, CD8, FoxP3, CD68, CD20, PanCK, DAPI) to explore specific TLS clusters based on varying immune subset densities. Using a k-means clustering algorithm, we found five distinct cellular composition clusters. Tumors unresponsive to anti-PD-1/CTLA-4 immunotherapy showed enrichment of a FoxP3⁺ T-cell-low TLS cluster after treatment. Additionally, cluster 5 (macrophage low) TLS were significantly higher after pre-operative immunotherapy, compared to untreated tumors. We also compared the immune cell composition and maturation stages between superficial (submucosal) and deeper TLS, revealing that superficial TLS had more pronounced T-helper cells and enrichment of early TLS than TLS located in deeper tissue. Furthermore, superficial TLS displayed a lower fraction of secondary follicle like TLS than deeper TLS. Taken together, our results provide a detailed quantitative overview of the tumor immune landscape in UC, which can provide a basis for further studies.