No abstract

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort.Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package “Seurat” was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the “ssGSEA” algorithm. In order to develop possible medications for patients with high-risk ccRCC, the “pRRophetic” package is employed.Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature’s biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications.Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient’s prognosis for ccRCC and reflect the disease’s complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.

Thymic epithelial tumors (TETs) are common tumors in human anterior mediastinum with limited biological understanding. Through decoding the immune landscape of tumors, we reclassify TETs into three types based on T cell developmental patterns. We uncover the developmental dysfunction and TCR repertoire of tumor-infiltrating T cells by cell atlas. Moreover, we identify the unique subset of tumor cells with distinct epithelial origin in each TETs type. Furthermore, we demonstrate that KRT14/GNB3+ mTECs-like cell accumulation inhibits the T cell positive selection in type 1 TETs, while CCL25+ cTEC-like cell promotes T cell positive selection in type 2. Interestingly, although CHI3L1+ mTEC-like cell in type 3 TETs loses the function of supporting T cell development, it acquires the capacity to induce CD8+TRMs-mediated response. Finally, we propose a new molecular classification of human TETs using GNB3 and CHI3L1 to distinguish the epithelial origin of tumor cells, which is promising in prognostic prediction.

No abstract