TSG-6+ cancer-associated fibroblasts modulate myeloid cell responses and impair anti-tumor response to immune checkpoint therapy in pancreatic cancer.

Resistance to immune checkpoint therapy (ICT) presents a growing clinical challenge. The tumor microenvironment (TME) and its components, namely tumor-associated macrophages (TAMs) and cancer-associated fibroblasts (CAFs), play a pivotal role in ICT resistance; however, the underlying mechanisms remain under investigation. In this study, we identify expression of TNF-Stimulated Factor 6 (TSG-6) in ICT-resistant pancreatic tumors, compared to ICT-sensitive melanoma tumors, both in mouse and human. TSG-6 is expressed by CAFs within the TME, where suppressive macrophages expressing Arg1, Mafb, and Mrc1, along with TSG-6 ligand Cd44, predominate. Furthermore, TSG-6 expressing CAFs co-localize with the CD44 expressing macrophages in the TME. TSG-6 inhibition in combination with ICT improves therapy response and survival in pancreatic tumor-bearing mice by reducing macrophages expressing immunosuppressive phenotypes and increasing CD8 T cells. Overall, our findings propose TSG-6 as a therapeutic target to enhance ICT response in non-responsive tumors.

Myeloid-specific KDM6B inhibition sensitizes glioblastoma to PD1 blockade.

Glioblastoma (GBM) tumors are enriched in immune-suppressive myeloid cells and are refractory to immune checkpoint therapy (ICT). Targeting epigenetic pathways to reprogram the functional phenotype of immune-suppressive myeloid cells to overcome resistance to ICT remains unexplored. Single-cell and spatial transcriptomic analyses of human GBM tumors demonstrated high expression of an epigenetic enzyme-histone 3 lysine 27 demethylase (KDM6B)-in intratumoral immune-suppressive myeloid cell subsets. Importantly, myeloid cell-specific Kdm6b deletion enhanced proinflammatory pathways and improved survival in GBM tumor-bearing mice. Mechanistic studies showed that the absence of Kdm6b enhances antigen presentation, interferon response and phagocytosis in myeloid cells by inhibition of mediators of immune suppression including Mafb, Socs3 and Sirpa. Further, pharmacological inhibition of KDM6B mirrored the functional phenotype of Kdm6b-deleted myeloid cells and enhanced anti-PD1 efficacy. This study thus identified KDM6B as an epigenetic regulator of the functional phenotype of myeloid cell subsets and a potential therapeutic target for enhanced response to ICT.

ARID1A mutation plus CXCL13 expression act as combinatorial biomarkers to predict responses to immune checkpoint therapy in mUCC.

Immune checkpoint therapy (ICT) can produce durable antitumor responses in metastatic urothelial carcinoma (mUCC); however, the responses are not universal. Despite multiple approvals of ICT in mUCC, we lack predictive biomarkers to guide patient selection. The identification of biomarkers may require interrogation of both the tumor mutational status and the immune microenvironment. Through multi-platform immuno-genomic analyses of baseline tumor tissues, we identified the mutation of AT-rich interactive domain-containing protein 1A (ARID1A) in tumor cells and expression of immune cytokine CXCL13 in the baseline tumor tissues as two predictors of clinical responses in a discovery cohort (n = 31). Further, reverse translational studies revealed that CXCL13-/- tumor-bearing mice were resistant to ICT, whereas ARID1A knockdown enhanced sensitivity to ICT in a murine model of bladder cancer. Next, we tested the clinical relevance of ARID1A mutation and baseline CXCL13 expression in two independent confirmatory cohorts (CheckMate275 and IMvigor210). We found that ARID1A mutation and expression of CXCL13 in the baseline tumor tissues correlated with improved overall survival (OS) in both confirmatory cohorts (CheckMate275, CXCL13 data, n = 217; ARID1A data, n = 139, and IMvigor210, CXCL13 data, n = 348; ARID1A data, n = 275). We then interrogated CXCL13 expression plus ARID1A mutation as a combination biomarker in predicting response to ICT in CheckMate275 and IMvigor210. Combination of the two biomarkers in baseline tumor tissues suggested improved OS compared to either single biomarker. Cumulatively, this study revealed that the combination of CXCL13 plus ARID1A may improve prediction capability for patients receiving ICT.