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Background: Testicular cancer is the most common solid malignancy in young men. Given the many histological classifications of testicular tumors, seminoma is one of the most treatable cancers. The survival rate in early-stage disease was more than 90%. Thus, seminoma at the cellular and molecular levels, especially at the single-cell level, is worth studying. Methods: We performed a single-cell RNA sequencing (scRNA-seq) study on a patient who was diagnosed with testicular seminoma with lymph node metastasis. This study presented tumor tissue, PBMC, pelvic and renal hilus lymph node in a total of 18,206 high-quality single-cell transcriptome information. The characteristics of metastatic cell lineage were revealed by the comparison between different tumor cell subtypes at the scRNA level. Results: A single-cell map of testicular seminoma with lymph node metastasis was constructed by scRNA-seq. We discovered the gene expression characteristics of the tumor cells in testicular seminoma, especially metastatic tumor cells. KRT8 and KRT18 were commonly expressed in the three tumor cell subtypes. However, TCF7L1 , SCG3 and SV2C were the specifically expressed genes of tumor cell subtypes in primary tumor sites. Some molecular markers specifically expressed by the metastatic cell lineage, such as POU5F1 , were identified. Conclusions: We revealed the molecular characteristics of testicular seminoma at the single-cell level, especially the metastatic tumor cells. This study could provide new insights into the diagnosis and treatment of testicular seminoma. [ABSTRACT FROM AUTHOR]

Background: Renal cell carcinoma (RCC) is the most common type of kidney cancer. Studying the pathogenesis of RCC is particularly important, because it could provide a direct guide for clinical treatment. Given that tumor heterogeneity is probably reflected at the mRNA level, the study of mRNA in RCC may reveal some potential tumor-specific markers, especially single-cell RNA sequencing (scRNA-seq). Methods: We performed an exploratory study on three pathological types of RCC with a small sample size. This study presented clear-cell RCC (ccRCC), type 2 pRCC, and chRCC in a total of 30,263 high-quality single-cell transcriptome information from three pathological types of RCC. In addition, scRNA-seq was performed on normal kidneys. Tumor characteristics were well identified by the comparison between different pathological types of RCC and normal kidneys at the scRNA level. Results: Some new tumor-specific markers for different pathologic types of RCC, such as SPOCK1, PTGIS, REG1A, CP and SPAG4 were identified and validated. We also discovered that NDUFA4L2 both highly expressed in tumor cells of ccRCC and type 2 pRCC. The presence of two different types of endothelial cells in ccRCC and type 2 pRCC was also identified and verified. An endothelial cell in ccRCC may be associated with fibroblasts and significantly expressed fibroblast markers, such as POSTN and COL3A1. At last, by applying scRNA-seq results, the activation of drug target pathways and sensitivity to drug responses was predicted in different pathological types of RCC. Conclusions: Taken together, these findings considerably enriched the single-cell transcriptomic information for RCC, thereby providing new insights into the diagnosis and treatment of RCC. [ABSTRACT FROM AUTHOR]

Osteosarcoma (OS), which occurs most commonly in adolescents, is associated with a high degree of malignancy and poor prognosis. In order to develop an accurate treatment for OS, a deeper understanding of its complex tumor microenvironment (TME) is required. In the present study, tissues were isolated from six patients with OS, and then subjected to single-cell RNA sequencing (scRNA-seq) using a 10× Genomics platform. Multiplex immunofluorescence staining was subsequently used to validate the subsets identified by scRNA-seq. ScRNA-seq of six patients with OS was performed prior to neoadjuvant chemotherapy, and data were obtained on 29,278 cells. A total of nine major cell types were identified, and the single-cell transcriptional map of OS was subsequently revealed. Identified osteoblastic OS cells were divided into five subsets, and the subsets of those osteoblastic OS cells with significant prognostic correlation were determined using a deconvolution algorithm. Thereby, different transcription patterns in the cellular subtypes of osteoblastic OS cells were reported, and key transcription factors associated with survival prognosis were identified. Furthermore, the regulation of osteolysis by osteoblastic OS cells via receptor activator of nuclear factor kappa-B ligand was revealed. Furthermore, the role of osteoblastic OS cells in regulating angiogenesis through vascular endothelial growth factor-A was revealed. C3_TXNIP+ macrophages and C5_IFIT1+ macrophages were found to regulate regulatory T cells and participate in CD8+ T cell exhaustion, illustrating the possibility of immunotherapy that could target CD8+ T cells and macrophages. Our findings here show that the role of C1_osteoblastic OS cells in OS is to promote osteolysis and angiogenesis, and this is associated with survival prognosis. In addition, T cell depletion is an important feature of OS. More importantly, the present study provided a valuable resource for the in-depth study of the heterogeneity of the OS TME. [ABSTRACT FROM AUTHOR]

Bilateral renal cell carcinoma (RCC) is a rare disease that can be classified as either familial or sporadic. Studying the cellular molecular characteristics of sporadic bilateral RCC is important to provide guidance for clinical treatment. Cellular molecular characteristics can be expressed at the RNA level, especially at the single-cell degree. Single-cell RNA sequencing (scRNA-seq) was performed on bilateral clear cell RCC (ccRCC). A total of 3,575 and 3,568 high-quality single-cell transcriptome data were captured from the left and right tumour tissues, respectively. Gene characteristics were identified by comparing left and right tumours at the scRNA level. The complex cellular environment of bilateral ccRCC was presented by using scRNA-seq. Single-cell transcriptomic analysis revealed high similarity in gene expression among most of the cell types of bilateral RCCs but significant differences in gene expression among different site tumour cells. Additionally, the potential biological function of different tumour cell types was determined by gene ontology (GO) analysis. The transcriptome characteristics of tumour tissues in different locations at the single-cell transcriptome level were revealed through the scRNA-seq of bilateral sporadic ccRCC. This work provides new insights into the diagnosis and treatment of bilateral RCC. [ABSTRACT FROM AUTHOR]