Machine Learning Links T-cell Function and Spatial Localization to Neoadjuvant Immunotherapy and Clinical Outcome in Pancreatic Cancer.

Tumor molecular data sets are becoming increasingly complex, making it nearly impossible for humans alone to effectively analyze them. Here, we demonstrate the power of using machine learning (ML) to analyze a single-cell, spatial, and highly multiplexed proteomic data set from human pancreatic cancer and reveal underlying biological mechanisms that may contribute to clinical outcomes. We designed a multiplex immunohistochemistry antibody panel to compare T-cell functionality and spatial localization in resected tumors from treatment-naïve patients with localized pancreatic ductal adenocarcinoma (PDAC) with resected tumors from a second cohort of patients treated with neoadjuvant agonistic CD40 (anti-CD40) monoclonal antibody therapy. In total, nearly 2.5 million cells from 306 tissue regions collected from 29 patients across both cohorts were assayed, and over 1,000 tumor microenvironment (TME) features were quantified. We then trained ML models to accurately predict anti-CD40 treatment status and disease-free survival (DFS) following anti-CD40 therapy based on TME features. Through downstream interpretation of the ML models' predictions, we found anti-CD40 therapy reduced canonical aspects of T-cell exhaustion within the TME, as compared with treatment-naïve TMEs. Using automated clustering approaches, we found improved DFS following anti-CD40 therapy correlated with an increased presence of CD44+CD4+ Th1 cells located specifically within cellular neighborhoods characterized by increased T-cell proliferation, antigen experience, and cytotoxicity in immune aggregates. Overall, our results demonstrate the utility of ML in molecular cancer immunology applications, highlight the impact of anti-CD40 therapy on T cells within the TME, and identify potential candidate biomarkers of DFS for anti-CD40-treated patients with PDAC.

Altered liver metabolism post-wean abolishes efficacy of vitamin D for breast cancer prevention in a mouse model.

Young women have increased risk of vitamin D deficiency, which may increase breast cancer incidence. Here, we assessed the anti-cancer efficacy of vitamin D in mouse models of young-onset breast cancer. In never-pregnant mice, vitamin D supplementation increased serum 25(OH)D and hepatic 1,25(OH)2D3, reduced tumor size, and associated with anti-tumor immunity. These anti-tumor effects were not replicated in a mouse model of postpartum breast cancer, where hepatic metabolism of vitamin D was suppressed post-wean, which resulted in deficient serum 25(OH)D and reduced hepatic 1,25(OH)2D3. Treatment with active 1,25(OH)2D3 induced hypercalcemia exclusively in post-wean mice, highlighting metabolic imbalance post-wean. RNAseq revealed suppressed CYP450 expression postpartum. In sum, we provide evidence that vitamin D anti-tumor activity is mediated through immunomodulatory mechanisms and is ineffective in the post-wean window due to altered hepatic metabolism. These findings have implications for suppressed xenobiotic metabolism in postpartum women beyond vitamin D.

PI3Kγ inhibition circumvents inflammation and vascular leak in SARS-CoV-2 and other infections.

Virulent infectious agents such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and methicillin-resistant Staphylococcus aureus (MRSA) induce tissue damage that recruits neutrophils, monocyte, and macrophages, leading to T cell exhaustion, fibrosis, vascular leak, epithelial cell depletion, and fatal organ damage. Neutrophils, monocytes, and macrophages recruited to pathogen-infected lungs, including SARS-CoV-2-infected lungs, express phosphatidylinositol 3-kinase gamma (PI3Kγ), a signaling protein that coordinates both granulocyte and monocyte trafficking to diseased tissues and immune-suppressive, profibrotic transcription in myeloid cells. PI3Kγ deletion and inhibition with the clinical PI3Kγ inhibitor eganelisib promoted survival in models of infectious diseases, including SARS-CoV-2 and MRSA, by suppressing inflammation, vascular leak, organ damage, and cytokine storm. These results demonstrate essential roles for PI3Kγ in inflammatory lung disease and support the potential use of PI3Kγ inhibitors to suppress inflammation in severe infectious diseases.