Laboratory of High-Resolution Cancer Biology

Abstract Tumor stroma plays a critical role in fostering tumor progression and metastasis. Cancer-associated fibroblasts (CAF) are a major component of the tumor stroma. Identifying the key molecular determinants for the protumor properties of CAFs could enable the development of more effective treatment strategies. In this study, through analyses of single-cell sequencing data, we identified a population of CAFs expressing high levels of sulfatase 1 (SULF1), which was associated with poor prognosis in patients with colorectal cancer. Colorectal cancer models using mice with conditional SULF1 knockout in fibroblasts revealed the tumor-supportive function of SULF1+ CAFs. Mechanistically, SULF1+ CAFs enhanced the release of VEGFA from heparan sulfate proteoglycan. The increased bioavailability of VEGFA initiated the deposition of extracellular matrix and enhanced angiogenesis. In addition, intestinal microbiota–produced butyrate suppressed SULF1 expression in CAFs through its histone deacetylase (HDAC) inhibitory activity. The insufficient butyrate production in patients with colorectal cancer increased the abundance of SULF1+ CAFs, thereby promoting tumor progression. Importantly, tumor growth inhibition by HDAC was dependent on SULF1 expression in CAFs, and patients with colorectal cancer with more SULF1+ CAFs were more responsive to treatment with the HDAC inhibitor chidamide. Collectively, these findings unveil the critical role of SULF1+ CAFs in colorectal cancer and provide a strategy to stratify patients with colorectal cancer for HDAC inhibitor treatment.  Significance: SULF1+ cancer-associated fibroblasts play a tumor-promoting role in colorectal cancer by stimulating extracellular matrix deposition and angiogenesis and can serve as a biomarker for the therapeutic response to HDAC inhibitors in patients.

Pancreatic ductal adenocarcinoma (PDAC) remains a highly lethal malignancy because of its aggressive nature and the paucity of effective treatment options. Almost all registered drugs have proven ineffective in addressing the needs of patients with PDAC. This is the result of a poor understanding of the unique tumor–immune microenvironment (TME) in PDAC. To identify druggable regulators of immunosuppressive TME, we performed a kinome- and membranome-focused CRISPR screening using orthotopic PDAC models. Our data showed that receptor-interacting protein kinase 2 (RIPK2) is a crucial driver of immune evasion of cytotoxic T-cell killing and that genetic or pharmacologic targeting of RIPK2 sensitizes PDAC to anti–programmed cell death protein 1 (anti–PD-1) immunotherapy, leading to prolonged survival or complete regression. Mechanistic studies revealed that tumor-intrinsic RIPK2 ablation disrupts desmoplastic TME and restores MHC class I (MHC-I) surface levels through eliminating NBR1-mediated autophagy-lysosomal degradation. Our results provide a rationale for a novel combination therapy consisting of RIPK2 inhibition and anti–PD-1 immunotherapy for PDAC.

Immune-checkpoint blockade (ICB) combined with neoadjuvant chemotherapy improves pathological complete response in breast cancer. To understand why only a subset of tumors respond to ICB, patients with hormone receptor-positive or triple-negative breast cancer were treated with anti-PD1 before surgery. Paired pre- versus on-treatment biopsies from treatment-naive patients receiving anti-PD1 (n = 29) or patients receiving neoadjuvant chemotherapy before anti-PD1 (n = 11) were subjected to single-cell transcriptome, T cell receptor and proteome profiling. One-third of tumors contained PD1-expressing T cells, which clonally expanded upon anti-PD1 treatment, irrespective of tumor subtype. Expansion mainly involved CD8+ T cells with pronounced expression of cytotoxic-activity (PRF1, GZMB), immune-cell homing (CXCL13) and exhaustion markers (HAVCR2, LAG3), and CD4+ T cells characterized by expression of T-helper-1 (IFNG) and follicular-helper (BCL6, CXCR5) markers. In pre-treatment biopsies, the relative frequency of immunoregulatory dendritic cells (PD-L1+), specific macrophage phenotypes (CCR2+ or MMP9+) and cancer cells exhibiting major histocompatibility complex class I/II expression correlated positively with T cell expansion. Conversely, undifferentiated pre-effector/memory T cells (TCF7+, GZMK+) or inhibitory macrophages (CX3CR1+, C3+) were inversely correlated with T cell expansion. Collectively, our data identify various immunophenotypes and associated gene sets that are positively or negatively correlated with T cell expansion following anti-PD1 treatment. We shed light on the heterogeneity in treatment response to anti-PD1 in breast cancer.

How the innate and adaptive host immune system miscommunicate to worsen COVID-19 immunopathology has not been fully elucidated. Here, we perform single-cell deep-immune profiling of bronchoalveolar lavage (BAL) samples from 5 patients with mild and 26 with critical COVID-19 in comparison to BALs from non-COVID-19 pneumonia and normal lung. We use pseudotime inference to build T-cell and monocyte-to-macrophage trajectories and model gene expression changes along them. In mild COVID-19, CD8+ resident-memory (TRM) and CD4+ T-helper-17 (TH17) cells undergo active (presumably antigen-driven) expansion towards the end of the trajectory, and are characterized by good effector functions, while in critical COVID-19 they remain more naïve. Vice versa, CD4+ T-cells with T-helper-1 characteristics (TH1-like) and CD8+ T-cells expressing exhaustion markers (TEX-like) are enriched halfway their trajectories in mild COVID-19, where they also exhibit good effector functions, while in critical COVID-19 they show evidence of inflammation-associated stress at the end of their trajectories. Monocyte-to-macrophage trajectories show that chronic hyperinflammatory monocytes are enriched in critical COVID-19, while alveolar macrophages, otherwise characterized by anti-inflammatory and antigen-presenting characteristics, are depleted. In critical COVID-19, monocytes contribute to an ATP-purinergic signaling-inflammasome footprint that could enable COVID-19 associated fibrosis and worsen disease-severity. Finally, viral RNA-tracking reveals infected lung epithelial cells, and a significant proportion of neutrophils and macrophages that are involved in viral clearance.

The stromal compartment of the tumor microenvironment consists of a heterogeneous set of tissue-resident and tumor-infiltrating cells, which are profoundly moulded by cancer cells. An outstanding question is to what extent this heterogeneity is similar between cancers affecting different organs. Here, we profile 233,591 single cells from patients with lung, colorectal, ovary and breast cancer (n = 36) and construct a pan-cancer blueprint of stromal cell heterogeneity using different single-cell RNA and protein-based technologies. We identify 68 stromal cell populations, of which 46 are shared between cancer types and 22 are unique. We also characterise each population phenotypically by highlighting its marker genes, transcription factors, metabolic activities and tissue-specific expression differences. Resident cell types are characterised by substantial tissue specificity, while tumor-infiltrating cell types are largely shared across cancer types. Finally, by applying the blueprint to melanoma tumors treated with checkpoint immunotherapy and identifying a naïve CD4+ T-cell phenotype predictive of response to checkpoint immunotherapy, we illustrate how it can serve as a guide to interpret scRNA-seq data. In conclusion, by providing a comprehensive blueprint through an interactive web server, we generate the first panoramic view on the shared complexity of stromal cells in different cancers.

The communication between cells and between cellular organelles is often controlled by the interaction of membrane proteins. Although many methods for the detection of protein–protein interactions (PPIs) exist, membrane PPIs remain difficult to detect. Here we developed a proximity-based tagging system, PUP-IT (pupylation-based interaction tagging), to identify membrane protein interactions. In this approach, a small protein tag, Pup, is applied to proteins that interact with a PafA-fused bait, enabling transient and weak interactions to be enriched and detected by mass spectrometry. Pup does not diffuse from the enzyme, which allows high-specificity labeling. We applied this approach to CD28, a critical costimulatory receptor for T lymphocyte activation, and identified known CD28 binding partners and multiple potential interacting proteins. In addition, we demonstrated that this method can identify the interaction between a cell surface receptor and its ligand.