Immune checkpoint inhibitors (ICIs), including CTLA-4- and PD-1-blocking antibodies, can have profound effects on tumor immune cell infiltration that have not been consistent in biopsy series reported to date. Here, we analyze seven molecular datasets of samples from patients with advanced melanoma (N = 514) treated with ICI agents to investigate clinical, genomic, and transcriptomic features of anti-PD-1 response in cutaneous melanoma. We find that prior anti-CTLA-4 therapy is associated with differences in genomic, individual gene, and gene signatures in anti-PD-1 responders. Anti-CTLA-4-experienced melanoma tumors that respond to PD-1 blockade exhibit increased tumor mutational burden, inflammatory signatures, and altered cell cycle processes compared with anti-CTLA-4-naive tumors or anti-CTLA-4-experienced, anti-PD-1-nonresponsive melanoma tumors. We report a harmonized, aggregate resource and suggest that prior CTLA-4 blockade therapy is associated with marked differences in the tumor microenvironment that impact the predictive features of PD-1 blockade therapy response.

Immune-checkpoint inhibitors (ICI), although revolutionary in improving long-term survival outcomes, are mostly effective in patients with immune-responsive tumors. Most patients with cancer either do not respond to ICIs at all or experience disease progression after an initial period of response. Treatment resistance to ICIs remains a major challenge and defines the biggest unmet medical need in oncology worldwide. In a collaborative workshop, thought leaders from academic, biopharma, and nonprofit sectors convened to outline a resistance framework to support and guide future immune-resistance research. Here, we explore the initial part of our effort by collating seminal discoveries through the lens of known biological processes. We highlight eight biological processes and refer to them as immune resistance nodes. We examine the seminal discoveries that define each immune resistance node and pose critical questions, which, if answered, would greatly expand our notion of immune resistance. Ultimately, the expansion and application of this work calls for the integration of multiomic high-dimensional analyses from patient-level data to produce a map of resistance phenotypes that can be utilized to guide effective drug development and improved patient outcomes.

Treatment with immune checkpoint blockade (ICB) has revolutionized cancer therapy. Until now, predictive biomarkers^1-10 and strategies to augment clinical response have largely focused on the T cell compartment. However, other immune subsets may also contribute to anti-tumour immunity^11-15, although these have been less well-studied in ICB treatment¹⁶. A previously conducted neoadjuvant ICB trial in patients with melanoma showed via targeted expression profiling¹⁷ that B cell signatures were enriched in the tumours of patients who respond to treatment versus non-responding patients. To build on this, here we performed bulk RNA sequencing and found that B cell markers were the most differentially expressed genes in the tumours of responders versus non-responders. Our findings were corroborated using a computational method (MCP-counter¹⁸) to estimate the immune and stromal composition in this and two other ICB-treated cohorts (patients with melanoma and renal cell carcinoma). Histological evaluation highlighted the localization of B cells within tertiary lymphoid structures. We assessed the potential functional contributions of B cells via bulk and single-cell RNA sequencing, which demonstrate clonal expansion and unique functional states of B cells in responders. Mass cytometry showed that switched memory B cells were enriched in the tumours of responders. Together, these data provide insights into the potential role of B cells and tertiary lymphoid structures in the response to ICB treatment, with implications for the development of biomarkers and therapeutic targets.