Dataset Information

Single-cell atlas of diverse immune populations in the advanced biliary tract cancer microenvironment

ABSTRACT: Immunotherapies have been explored in treating solid tumors, albeit with disparate clinical effects in distinct cancer types. Systematic interrogation of immune cells in the tumor microenvironment (TME) is vital to the prediction of immunotherapy response and the development of innovative immunotherapeutics. To comprehensively characterize the immune microenvironment in advanced biliary tract cancer (BTC), we utilized single-cell RNA sequencing in unselected viable cells from 16 matched samples. We identified nineteen cell subsets from a total of 45,851 cells, in which exhausted CD8+ T cells, macrophages, and dendritic cells (DCs) in BTC were shown to augment and communicate within the TME. Transcriptional profiles coupled with T cell receptor (TCR) sequences revealed that exhausted CD8+ T cells retained clonal expansion and high proliferation in the TME, and some of them highly expressed the endoplasmic reticulum stress (ER) sensor XBP1, indicating its key role in remodeling TME. Functional assays demonstrated that XBP1 and common immune checkpoints (PD1, TIGIT) were significantly upregulated in CD8+ T cells cocultured within the TME of BTC cell lines (GBC-SD, HCCC-9810). When treating the coculture groups with the specific inhibitor of IRE1α-XBP1 (4μ8C), the downregulation of TIGIT was observed in the treatment group. Collectively, comprehensive transcriptome profiling provides deeper insights into the immune atlas in advanced BTC, which might be instrumental in exploring novel immunotherapy strategies.

ORGANISM(S): Homo sapiens

PROVIDER: GSE201425 | GEO | 2022/08/26

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Cervical cancer (CC) is one of the most common malignancy in women worldwide. It is characterized by a natural continuous phenomenon, that is, it is in the initial stage of HPV infection, progresses to intraepithelial neoplasia, and then develops into invasion and metastasis. Determining the complexity of tumor microenvironment (TME) can deepen our understanding of lesion progression and provide novel therapeutic strategies for CC. We performed the single-cell RNA sequencing on the normal cervix, intraepithelial neoplasia, primary tumor and metastatic lymph node tissues to describe the composition, lineage, and functional status of immune cells and mesenchymal cells at different stages of CC progression. A total of 59913 single cells were obtained and divided into 9 cellular clusters, including immune cells (T/NK cells, macrophages, B cells, plasma cells, mast cells and neutrophils) and mesenchymal cells (endothelial cells, smooth muscle cells and fibroblasts). Our results showed that there were distinct cell subpopulations in different stages of CC. High-stage intraepithelial neoplasia (HSIL) tissue exhibited a low, recently activated TME, and it was characterized by high infiltration of tissue-resident CD8 T cell, effector NK cells, Treg, DC1, pDC, and M1-like macrophages. Tumor tissue displayed high enrichment of exhausted CD8 T cells, resident NK cells and M2-like macrophages, suggesting immunosuppressive TME. Metastatic lymph node consisted of naive T cell, central memory T cell, circling NK cells, cytotoxic CD8+ T cells and effector memory CD8 T cells, suggesting an early activated phase of immune response. This study is the first to delineate the transcriptome profile of immune cells during CC progression using single-cell RNA sequencing. Our results indicated that HSIL exhibited a low, recently activated TME, tumor displayed immunosuppressive statue, and metastatic lymph node showed early activated phase of immune response. Our study enhanced the understanding of dynamic change of TME during CC progression and has implications for the development of novel treatments to inhibit the initiation and progression of CC.

Project description:Immunotherapeutics represent highly promising agents with the potential to improve patient outcomes in a variety of cancer types. Unfortunately, single-agent immunotherapy has achieved limited clinical benefit to date in patients suffering from pancreatic ductal adenocarcinoma (PDAC). This may be due to the presence of a uniquely immunosuppressive tumor microenvironment (TME) present in PDACs, which creates a barrier to effective immune surveillance. Critical obstacles to immunotherapy in PDAC tumors include the dense desmoplastic stroma that acts as a barrier to T-cell infiltration and the high numbers of tumor-associated immunosuppressive cells. We have identified hyperactivated focal adhesion kinase (FAK) activity in neoplastic PDAC cells as a significant regulator of the fibrotic and immunosuppressive TME. We found that FAK activity was elevated in human PDAC tissues and correlates with high levels of fibrosis and poor CD8+ cytotoxic T-cell infiltration. Single-agent FAK inhibition (VS-4718) dramatically limited tumor progression, resulting in a doubling of survival in the p48-Cre/LSL-KrasG12D/p53Flox/+ (KPC) mouse model of human PDAC. This alteration in tumor progression was associated with dramatically reduced tumor fibrosis, decreased numbers of tumor-infiltrating immature myeloid cells and immunosuppressive macrophages. We postulated that these desirable effects of FAK inhibition on the TME might render PDAC tumors more sensitive to immunotherapy. Accordingly, we found that VS-4718 rendered the previously unresponsive KPC mouse model responsive to anti-PD1 and anti-CTLA4 antagonists leading to a nearly tripling of survival times. These data suggest that FAK inhibition increases immune surveillance by overcoming the fibrotic and immunosuppressive PDAC TME thus rendering tumors more responsive to immunotherapy. We treated KP orthotopic tumor-bearing mice with vehicle and FAK inhibitor (FAKi) for 14 days, then extracted total RNA from tumor tissues.

Dataset Information

Single-cell atlas of diverse immune populations in the advanced biliary tract cancer microenvironment

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure