Project description:We identify the specific contribution of each cell type to the human liver tumor microenvironment and reconstructed hepatocytes zonation of the human liver using a combined approach of single-cell RNA sequencing and laser capture microdissection. Our work constitutes an important resource for identifying potential sources of vulnerabilities in liver tumors and metastases.
Project description:Liver disease alters the gut microenvironment by liver-gut axis. To investigate the composition and transcriptome changes of various intestinal cell populations in liver cirrhosis, we delineated a single-cell atlas of the colon from mice treated CCl4 for 6 weeks.
Project description:To dissect the early aspects of liver haematopoiesis as well as the development of other liver cell lineages we generated a new single cell RNA-seq (scRNA-seq) atlas of the mouse E12.5 liver
Project description:The tumor immune microenvironment is a main contributor to cancer progression and a promising therapeutic target for oncology. However, immune microenvironments vary profoundly between patients and biomarkers for prognosis and treatment response lack precision. A comprehensive compendium of tumor immune cells is required to pinpoint predictive cellular states and their spatial localization. We generated a single-cell resolved tumor immune cell atlas, jointly analyzing >500,000 cells from 217 patients and 13 cancer types, providing the basis for a patient stratification based on immune cell compositions. Projecting immune cells from external tumors onto the atlas facilitated an automated cell annotation system for a harmonized interpretation. To enable in situ mapping of immune populations for digital pathology, we developed SPOTlight, a computational tool that identified striking spatial immune cell patterns in tumor sections. We expect the atlas, together with our versatile toolbox for precision oncology, to advance currently applied stratification strategies for prognosis and immuno-therapy response.
Project description:Metastasis is the primary cause of cancer-related mortality in colorectal cancer (CRC) patients. How to improve therapeutic options for patients with metastatic CRC (mCRC) is the core question for CRC treatment. However, the complexity and diversity of stromal context of the tumor microenvironment (TME) in liver metastases of CRC is not fully understood, and its influence on response to chemotherapy is unclear. Here we provide an in-depth analysis of transcriptional landscape of primary CRC, matched liver metastases and blood at single-cell resolution, and perform a systematic examination of transcriptional changes and phenotypic alteration of the TME in response to preoperative chemotherapy (PC). Based on 111,292 single-cell transcriptomes, our study reveals that TME of treatment-naïve tumors is characterized by higher abundance of less-activated B cells and higher heterogeneity of tumor-associated macrophages (TAMs). By contrast, in tumors treated with PC, we find activation of B cells, lower diversity of TAMs with immature and less activated phenotype, lower abundance of both dysfunctional T cells and ECM-remodeling cancer-associated fibroblasts (CAFs), and an accumulation of myofibroblasts. Our study provides a foundation for future investigation of the cellular mechanisms underlying liver metastasis of CRC and its response to PC, and opens up new possibilities for the development of therapeutic strategies for CRC.
Project description:Bulk analyses of pancreatic ductal adenocarcinoma (PDAC) samples are complicated by the tumor microenvironment (TME), i.e. signals from fibroblasts, endocrine, exocrine, and immune cells. Despite this, we and others have established tumor and stroma subtypes with prognostic significance. However, the interaction of underlying signals driving distinct immune and stromal landscapes is still unclear. Here we integrate 92 single cell RNA-seq samples from seven independent studies to build a reproducible PDAC atlas with a focus on tumor-TME interdependence. Patients with activated stroma are synonymous with higher myofibroblastic and immunogenic fibroblasts, and furthermore show increased M2-like macrophages and regulatory T-cells. Contrastingly, patients with ‘normal’ stroma showed M1 recruitment, elevated effector and exhausted T-cells. To aid interoperability of future studies, we provide a pretrained cell type classifier and an atlas of subtype-based signaling factors that we also validate in mouse data. Ultimately, this work leverages the heterogeneity among single-cell studies to create a comprehensive view of the orchestra of signaling interactions governing PDAC.