Abstract Pancreatic ductal adenocarcinoma (PDAC) is characterized by relatively low tumor purity and an abundant tumor microenvironment. To dissect the contribution of the biologic components, we developed DECODER, which performs de novo compartment deconvolution and weight estimation of tumor samples. DECODER is a sophisticated framework that integrates runs of non-negative matrix factorization (NMF) and non-negative least square (NNLS) algorithms and can be applied to any non-negative matrices without the need to know the number of resultant factors or compartments. DECODER was used to deconvolve the TCGA pancreatic adenocarcinoma (PAAD) RNA-seq dataset, which resulted in the identification of 7 major compartments (basal tumor, classical tumor, activated stroma, normal stroma, immune, endocrine, and exocrine), confirming prior manual NMF-based solutions. These results were then used for single-sample based weight estimation in the COMPASS trial and ICGC PACA-AU RNA-seq dataset. We saw a significant positive correlation between DECODER immune weight and leukocyte fraction (r = 0.757, p < 0.001) or ESTIMATE immune score (r = 0.773, p < 0.001). Samples with high immune weights corresponded to immune infiltration by histology. A significant correlation was found between the sum of basal and classical tumor weights, and tumor purity based on both ABSOLUTE (r = 0.699, p < 0.001) and methylation (r = 0.71, p < 0.001). Similarly, the sum of activated and normal stroma weights correlated with ESTIMATE stromal score (r = 0.729, p < 0.001). Interestingly, we found that the ratio between the basal and classical compartment (bcRatio) was significantly associated with survival outcome (p = 0.049 in TCGA and 0.008 in ICGC) in all patients and treatment response in basal-like patients (r = 0.884, p < 0.001 in COMPASS trial), suggesting that bcRatio may help explain the molecular basis for tumor behavior in PDAC. DECODER was also applied for de novo deconvolution for all the cancer types in TCGA RNA-seq dataset and identified the cancer type specific compartments. Results from DECODER can then be used for single-sample weight estimation of new samples for any cancer type. In addition, we applied DECODER on the PanCan ATAC-seq dataset containing 23 cancer types in a combined fashion, and identified compartments associated with cancer types or organ systems. This proves that DECODER is highly feasible to data of multiple platforms. In summary, we present an automated method for de novo deconvolution that may be used across tumor and data types. With deconvolved results as the reference, DECODER enables the single-sample weight estimation for a new sample, which is plausible in the clinical setting. Citation Format: Xianlu L. Peng, Richard A. Moffitt, Robert J. Torphy, Keith E. Volmar, Jen Jen Yeh. Compartment deconvolution in pancreatic cancer with biologic and clinical implications [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer: Advances in Science and Clinical Care; 2019 Sept 6-9; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2019;79(24 Suppl):Abstract nr B41.
The lymphatic system plays a central role in lipid absorption, which transports chylomicrons from the small intestine to the circulation. However, the molecular mechanism by which chylomicrons get into the intestinal lymphatics is unknown. Here we demonstrated that GPR182, a receptor in lymphatic endothelial cells (LECs), mediates dietary fat absorption. GPR182 knockout mice are resistant to dietary-induced obesity. GPR182 ablation in mice leads to poor lipid absorption and thereby a delay in growth during development. GPR182 binds and endocytoses lipoproteins broadly. Mechanistically, loss of GPR182 prevents chylomicrons from entering the lacteal lumen of the small intestine. GPR182 blockage with a monoclonal antibody (mAb) protects mice from dietary induced obesity. Together, our study identifies GPR182 as a lipoprotein receptor that mediates dietary fat absorption.
Abstract The recently identified G-protein-coupled receptor GPR171 and its ligand BigLEN are thought to regulate food uptake and anxiety. Though GPR171 is commonly used as a T cell signature gene in transcriptomic studies, its potential role in T cell immunity has not been explored. Here we show that GPR171 is transcribed in T cells and its protein expression is induced upon antigen stimulation. The neuropeptide ligand BigLEN interacts with GPR171 to suppress T cell receptor-mediated signalling pathways and to inhibit T cell proliferation. Loss of GPR171 in T cells leads to hyperactivity to antigen stimulation and GPR171 knockout mice exhibit enhanced antitumor immunity. Blockade of GPR171 signalling by an antagonist promotes antitumor T cell immunity and improves immune checkpoint blockade therapies. Together, our study identifies the GPR171/BigLEN axis as a T cell checkpoint pathway that can be modulated for cancer immunotherapy.
Desmoplasia describes the deposition of extensive extracellular matrix and defines primary pancreatic ductal adenocarcinoma (PDA). The acellular component of this stroma has been implicated in PDA pathogenesis and is being targeted therapeutically in clinical trials. By analyzing the stromal content of PDA samples from numerous annotated PDA data sets and correlating stromal content with both anatomic site and clinical outcome, we found PDA metastases in the liver, the primary cause of mortality to have less stroma, have higher tumor cellularity than primary tumors. Experimentally manipulating stromal matrix with an anti–lysyl oxidase like-2 (anti-LOXL2) antibody in syngeneic orthotopic PDA mouse models significantly decreased matrix content, led to lower tissue stiffness, lower contrast retention on computed tomography, and accelerated tumor growth, resulting in diminished overall survival. These studies suggest an important protective role of stroma in PDA and urge caution in clinically deploying stromal depletion strategies.
