Project description:Aberrant DNA methylation is common in cancer. To associate DNA methylation with gene function, we performed RNAseq upon tumor tissue and matched normal tissues of two ccRCC (clear cell renal cell carcinoma) patients. To quantify 5mC and 5hmC level in each CG site at genome-wide level, we performed BS-seq and TAB-seq upon tumor tissue and matched normal tissues of two ccRCC (clear cell renal cell carcinoma) patients, respectively. mRNA profiles of tumor and matched normal tissues from two ccRCC patients were generated by deep sequencing, using Hiseq 2000. Single-nucleotide-resolution, whole-genome, 5mC and 5hmC profiles of tumor and matched normal tissues from two ccRCC (clear cell renal cell carcinoma) patients were generated by deep sequencing, using Hiseq 2000.
Project description:This study investigates the immune characteristics of tissue-resident memory T cells in the human fallopian tube in high-grade serous ovarian cancer (HGSOC). Single-cell RNA sequencing (scRNA-seq) and paired T-cell receptor sequencing (scTCR-seq) were performed on samples from non-cancerous fallopian tube tissue, metastatic omental tumors, and peripheral blood from HGSOC patients. The dataset enables analysis of tissue-resident T cell populations, clonal relationships across tissues, and immune features associated with tumor progression. These data provide a resource for studying tissue-resident T cell heterogeneity, clonal expansion, and tumor-associated immune responses in ovarian cancer.
Project description:Aberrant DNA methylation is common in cancer. To associate DNA methylation with gene function, we performed RNAseq upon tumor tissue and matched normal tissues of two ccRCC (clear cell renal cell carcinoma) patients. To quantify 5mC and 5hmC level in each CG site at genome-wide level, we performed BS-seq and TAB-seq upon tumor tissue and matched normal tissues of two ccRCC (clear cell renal cell carcinoma) patients, respectively.
Project description:This single cell RNA-seq experiment was performed to quantify DLL3 expression in circulating tumor cells in small cell lung cancer patients to predict response to tarlatamab treatment. CTCs enriched from the blood of three SCLC patients prior or post tarlatamab treatment using the CTC-iChip followed by magnetic depletion of RBCs were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system. Corresponding EGA study number: EGAS50000001401, EGA dataset number: EGAD50000002035
Project description:In order to investigate heterogeneity and dynamics of cancer-associated immune cells, we performed single-cell sequencing on peripheral and tumor-infiltrating immune cells in three renal clear cell carcinoma patients. We chose renal clear cell carcinoma tumors based on the responsive of these tumors to immune checkpoint blockade in the context of low mutational loads, which implies a strong influence from the tumor microenvironment. Using the 10x Genomic 5 expression platform a total of 25,672 immune cells were isolated and passed filtering for quality control, with 13,433 cells from peripheral blood and 12,239 tumor-infiltrating cells. In addition, we used the Chromium Single Cell V(D)J kit to enrich for T cell receptor sequences for nearly 10,000 T cells in with accompanying expression information, allowing for the investigation of clonality and transcriptional phenotypic diversity. We generated a comprehensive immune profile using single-cell RNA-seq data from 25,000 immune cells from three renal cell carcinoma along with matched peripheral blood. In addition, we performed VDJ sequencing on the isolated single T cells.
Project description:We generated a comprehensive immune profile using single-cell RNA-seq data from 25,000 immune cells from three renal cell carcinoma along with matched peripheral blood. In addition, we performed VDJ sequencing on the isolated single T cells. In order to investigate heterogeneity and dynamics of cancer-associated immune cells, we performed single-cell sequencing on peripheral and tumor-infiltrating immune cells in three renal clear cell carcinoma patients. We chose renal clear cell carcinoma tumors based on the responsive of these tumors to immune checkpoint blockade in the context of low mutational loads, which implies a strong influence from the tumor microenvironment. Using the 10x Genomic 5 expression platform a total of 25,672 immune cells were isolated and passed filtering for quality control, with 13,433 cells from peripheral blood and 12,239 tumor-infiltrating cells. In addition, we used the Chromium Single Cell V(D)J kit to enrich for T cell receptor sequences for nearly 10,000 T cells in with accompanying expression information, allowing for the investigation of clonality and transcriptional phenotypic diversity.
Project description:To further define the role of piRNAs in the development of renal cancer, we employed piRNA microarray expression profiling as a discovery platform to identify differentially expressed piRNAs. Radical nephrectomy was performed on 3 patients with renal cancer, and the postoperative pathology was clear cell renal cell carcinoma. The cancer tissues and adjacent normal tissues of the patients were taken for piRNA sequencing. And the differentially high-expressed and differentially low-expressed piRNAs were analyzed by bioinformatics.
Project description:This dataset contains single-cell RNA sequencing (scRNA-seq) data generated from patients with M1-stage metastatic prostate cancer, comprising two complementary sample types: metastatic lesion biopsies from five patients and peripheral blood mononuclear cells (PBMCs) from seven patients. Together, these datasets support integrated profiling of the metastatic tumor microenvironment and the systemic immune landscape. The processed data include log-normalized gene expression matrices and detailed cell-level metadata, enabling analyses of tumor–immune interactions, circulating immune phenotypes, and molecular features associated with metastatic disease progression. A related bulk RNA-seq dataset from primary tumor biopsies is available (see Related Series: GSE297742), providing opportunities for comparative transcriptomic analyses between primary and metastatic disease states.
Project description:This dataset contains bulk RNA sequencing data from primary tumor biopsy samples of patients with prostate adenocarcinoma. TPM-normalized expression values are provided along with sample metadata. The data were generated to support transcriptomic profiling of human prostate tumors and are related to a companion single-cell RNA-seq dataset from the same cohort.