Cancer-induced nerve injury promotes resistance to anti-PD-1 therapy [scRNA-seq]

Peri-neural invasion (PNI) is a well-established poor prognostic factor in multiple cancer types. However, the mechanisms driving the PNI's detrimental clinical effect remain elusive. Here, we provide clinical and mechanistic insights into PNI and cancer-induced injury of tumor-associated nerves (TANs) and their role in resistance to anti-PD-1 therapy. Our work demonstrates that poor response to anti-PD-1 therapy in cutaneous squamous cell carcinoma (cSCC), melanoma, and gastric cancer is associated with PNI and TANs injury. Ultrastructural electron microscopy analysis reveals that direct contact between cancer cells and nerve fibers leads to cancer-induced nerve injury (CINI) via myelin degradation. Injured neurons respond by autonomously initiating an interleukin (IL)-6 and interferon (IFN) type I inflammatory response. This inflammatory response alters the immune activity in the peri-neural niche in melanoma, cSCC, and pancreatic adenocarcinoma, leading to an immuno-suppressive activity aimed at nerve healing and regeneration. As the tumor grows, the CINI burden increases, the inflammatory signal within the niche becomes chronic, and eventually skews the general immune tone within the tumor microenvironment to a suppressive and exhaustive state. The CINI-driven anti-PD-1 resistance can be reversed by targeting multiple steps in the CINI signaling process: denervating the tumor, conditional knockout of the transcription factor mediating the injury signal within neurons (cKO-Atf3), knockout of the IFN-a receptor signaling (Ifnar1-/-), or by combining anti-PD-1 and anti-IL-6-receptor blockade. Our findings demonstrate the direct immuno-regulatory roles of TANs and their therapeutic potential. Overall design: B16F10-mCherry-OVA melanoma cells (5 × 105) were inoculated intradermally into the flank of eight-week-old male and female mice whose nociceptor neurons were either permissive (NaV1.8WT::ATF3fl/fl) or resistant (NaV1.8cre::ATF3fl/fl) to injury. Ten days after tumor inoculation, the tumors were excised, minced with a razor blade, and digested for 30 minutes in DMEM containing 10 mM HEPES, 1.6 mg/mL collagenase IV (Sigma, #C5138), and 10 µg/mL DNase I (Sigma, #4942078001). The resulting cell suspensions were filtered through a 40 µm mesh, and samples from two mice were pooled for each experiment. After red blood cell lysis (Gibco, #A10492-01), cells were stained with Zombie Aqua viability dye (BioLegend, #423105) and a FITC anti-mouse CD45 antibody (BioLegend, #103107). Approximately 500,000 live immune cells, which included ~80% CD45+ cells, were sorted on a BD FACSAria III cell sorter into a collection buffer (PBS, 0.04% BSA, and 50% FBS; Sigma, #F4135), then fixed and prepared for single-cell library construction using the Chromium 10x Fixed RNA kits (#PN-1000414 and #PN-1000497). Libraries were sequenced on an Illumina NovaSeq X, and reads were aligned to the mouse reference genome using Cell Ranger (10x Genomics). Low-quality cells (nFeature_RNA = 100 or percent.mt = 5%) were excluded from downstream analysis in Seurat, and the remaining cells were clustered using 20 principal components at a resolution of 0.8, yielding 10 distinct clusters. These clusters were annotated using standard markers and the Tabula Muris reference atlas, then grouped by major cell type (B cells, CD8+ T-cells, CD4+ T-cells, Tregs, and myeloid cells) to compare gene expression between experimental conditions. To investigate differences between conditional knockout (cKO) and intact (control) mice, a single library was used to define inflammation markers with the Seurat FindMarkers function. Four biological replicates per group (cKO vs. controls) were generated, and gene-expression comparisons were averaged for each cell type and sample.