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The dual tumor-suppressive and -promoting functions of TGF-β signaling has made its targeting challenging. We examined the effects of TGF-β depletion by AVID200/BMS-986416 (TGF-β-TRAP), a TGF-β ligand trap, on the tumor microenvironment of pancreatic ductal adenocarcinoma (PDAC) murine models with different organ-specific metastasis. Our study demonstrated that TGF-β-TRAP potentiates the efficacy of anti-programmed cell death 1 (anti-PD-1) in a PDAC orthotopic murine model with liver metastasis tropism, significantly reducing liver metastases. We further demonstrated the heterogeneous response of cytotoxic effector T cells to combination TGF-β-TRAP and anti-PD-1 treatment across several tumor models. Single-nuclear RNA sequencing suggested that TGF-β-TRAP modulates cancer-associated fibroblast (CAF) heterogeneity and suppresses neutrophil degranulation and CD4+ T cell response to neutrophil degranulation. Ligand-receptor analysis indicated that TGF-β-TRAP may modulate the CCL5/CCR5 axis as well as costimulatory and checkpoint signaling from CAFs and myeloid cells. Notably, the most highly expressed ligands of CCR5 shifted from the immunosuppressive CCL5 to CCL7 and CCL8, which may mediate the immune agonist activity of CCR5 following TGF-β-TRAP and anti-PD-1 combination treatment. This study suggested that TGF-β depletion modulates CAF heterogeneity and potentially reprograms CAFs and myeloid cells into antitumor immune agonists in PDAC, supporting the validation of such effects in human specimens.

This study delves into the proteomic intricacies of drug-resistant cells (DRCs) within prostate cancer, which are known for their pivotal roles in therapeutic resistance, relapse, and metastasis. Utilizing single-cell proteomics (SCP) with an optimized high-throughput Data Independent Acquisition (DIA) approach with the throughput of 60 sample per day, we characterized the proteomic landscape of DRCs in comparison to parental PC3 cells. This optimized DIA method allowed for robust and reproducible protein quantification at the single-cell level, enabling the identification and quantification of over 1,300 proteins per cell on average. Distinct proteomic sub-clusters within the DRC population were identified, closely linked to variations in cell size. The study uncovered novel protein signatures, including the regulation of proteins critical for cell adhesion and metabolic processes, as well as the upregulation of surface proteins and transcription factors pivotal for cancer progression. Furthermore, by integrating SCP and single-cell RNA-seq (scRNA-seq) data, we identified six upregulated and ten downregulated genes consistently altered in drug-treated cells across both SCP and scRNA-seq platforms. These findings underscore the heterogeneity of DRCs and their unique molecular signatures, providing valuable insights into their biological behavior and potential therapeutic targets.