Abnormal Cellular Populations Shape Thymic Epithelial Tumor Heterogeneity and Anti-Tumor by Blocking Metabolic Interactions in Organoids.

A variety of abnormal epithelial cells and immature and mature immune cells in thymic epithelial tumors (TETs) affect histopathological features, the degree of malignancy, and the response to treatment. Here, gene expression, trajectory inference, and T cell antigen receptor (TCR)-based lineage tracking are profiled in TETs at single-cell resolution. An original subpopulation of KRT14+ progenitor cells with a spindle cell phenotype is shown. An abnormal infiltration of immature T cells with a TCR hyper-rearrangement state is revealed, due to the lack of CCL21+ medullary epithelial cells. For thymic carcinoma, the novel biomarkers of MSLN, CCL20, and SLC1A5 are identified and observed an elevated expression of LAG3 and HAVCR2 in malignant tumorn-infiltrating mature T cells. These common features based on the single-cell populations may inform pathological reclassification of TETs. Meanwhile, it is found that macrophages (MACs) attract thymic tumor cells through the LGALS9-SLC1A5 axis, providing them with glutamine to elicit metabolic reprogramming. This MAC-based metabolic pattern can promote malignancy progression. Additionally, an interactive immune environment in TETs is identified that correlates with the infiltration of abnormal FOXI1+ CFTR- ionocytes. Collectively, the data broaden the knowledge of TET cellular ecosystems, providing a basis for tackling histopathological diagnosis and related treatment.

PD1hi CD200hi CD4+ exhausted T cell increase immunotherapy resistance and tumour progression by promoting epithelial-mesenchymal transition in bladder cancer.

BACKGROUND: Bladder cancer (BLCA) is one of the most diagnosed cancers in humans worldwide. Recently, immunotherapy has become a main treatment option for BC. However, most BLCA patients do not respond to immune checkpoint inhibitors or relapse after immunotherapy. Therefore, it is very important to identify novel biomarkers for the prediction of immunotherapy response in B patients. METHODS: Pancancer single-cell RNA sequencing (scRNA-seq) data were used to identify the clusters of CD4+ T cells in the tumour microenvironment (TME). The clinical significance of key CD4+ T-cell clusters was evaluated based on the survival data of two independent immunotherapy bladder cancer (BLCA) cohorts. We also investigated the function of key clusters of CD4+ T cell in the TME of BC cells in vitro. RESULTS: This study identified two novel exhausted CD4+ T-cell subpopulations with the expression of PD1hi CD200hi or PD1hi CD200low in BC patients. Moreover, BLCA patients with a high level of PD1hi CD200hi CD4+ exhausted T cell showed immunotherapy resistance. Cell function analysis demonstrated that PD1hi CD200hi CD4+ exhausted T cell can promote epithelial-mesenchymal transition (EMT) and angiogenesis in BLCA cells. In addition, PD1hi CD200hi CD4+ exhausted T cells were shown to communicate with malignant BLCA cells through the GAS6-AXL axis. Finally, we also found that GAS6 expression is upregulated in B cells by METTL3-mediated m6A modification. CONCLUSIONS: PD1hi CD200hi CD4+ exhausted T cell may serve as a novel biomarker for poor prognosis and immunotherapy resistance in B. Targeted inhibitors of PD1hi CD200hi CD4+ exhausted T cells may help improve the efficacy of immunotherapy.

G-Protein Subunit Gamma 4 as a Potential Biomarker for Predicting the Response of Chemotherapy and Immunotherapy in Bladder Cancer.

BACKGROUND: GNG4, a member of the G-protein γ family, is a marker of poor overall survival (OS) rates in some malignancies. However, the potential role of GNG4 in bladder cancer (BLCA) is unknown. It is also unclear whether GNG4 may be utilized as a marker to guide chemotherapy or immunotherapy. METHODS: Single-cell RNA sequencing data were used to explore the expression of GNG4 in tumor microenvironment of BLCA. Bulk RNA sequencing data from TCGA were used to evaluate the relationship between GNG4 expression and biological features, such as immune cell infiltrations and gene mutations. The associations between GNG4 expression and survival in BLCA patients under or not under immunotherapy were evaluated using seven BLCA cohorts. RESULTS: GNG4 was specifically expressed in exhausted CD4+ T cells. And the high expression of the GNG4 was associated with high level of immune cell infiltration. The high-GNG4-expression group displayed a better response to immunotherapy, whereas patients in the low-GNG4-expression group often benefited from chemotherapy. Moreover, the high-GNG4 group was more similar to the basal group, whereas the low-GNG4 group was similar to the luminal group. CONCLUSIONS: GNG4 may be a potential biomarker for the prediction of the response to therapy in BLCA. Higher GNG4 expression can be used as a predictor of response to immunotherapy, and lower GNG4 expression can be used as a predictor of response to chemotherapy.