To understand the impact of enzymatic treatments on gene expression and epitope preservation on major immune cell populations, skin dissociation (SkinD) and solid soft tumor dissociation (TumorD) were tested on three healthy PBMC samples in triplicate (D1, D2, D3), against an untreated control. CITE-seq performance was assessed on a solid biopsy cohort of 11 samples (5 healthy skin samples, 3 primary melanoma samples, 3 melanoma metastasis samples) as well as on a liquid biopsy PBMC cohort consisting of three healthy donors and three immunotherapy-treated melanoma patients. This dataset contains the ADT/SPEX data for each sample. Data is provided in the form of pooled BAM files. Linkage between samples, BAM files and hashtags is provided in a separate linkage file.
This dataset is part of a study that aims to compare in vivo human trophoblast differentiation into EVTs to different in vitro trophoblast organoids using single-cell and single-nuclei RNA sequencing. This specific dataset includes scRNA-seq and snRNA-seq data from trophoblast stem cells (TSCs). Trophoblast stem cell (TSC) lines BTS5 and BTS11 derived by Okae and colleagues were grown as described previously (Okae et al. 2018) together with EVT differentiation media. This study shows that the main regulatory programs mediating EVT invasion in vivo are preserved in in vitro models of EVT differentiation from primary trophoblast organoids and trophoblast stem cells. Data for primary trophoblast organoids is available under E-MTAB-12650.
Targeted cancer therapy inevitably selects for tumor cells that harbor some form of therapy resistance. This phenomenon is a principle reason why advanced prostate cancer, which can be treated with agents targeting androgen signaling dependency and DNA repair failure, is a lethal condition. The influence of a patient's clinical history and disease evolution on how their disseminated tumors develop resistance has been difficulty to study, because few autopsy studies have been performed in heavily treated patients with DNA-repair deficient metastatic castration-resistant prostate cancer (mCRPC). Here, we assessed how resistance to targeted cancer therapies evolved in an autopsy cohort of 54 mCRPC tumors from six men. This dataset includes targeted sequencing, exome sequencing, and RNA-seq conducted on these biopsies.
Deep single-cell RNA sequencing data for 11,138 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive CRC patients. The DATA ACCESS AGREEMENT is provided at https://github.com/zhangyybio/single-T-cell-data-access. Applicants can request access to the data by directly downloading it or by sending an email to cancerpku@pku.edu.cn. The process that is used to approve an application includes verifying the institution, participants and research purposes of the application. In general this process will take about two weeks. In principal, any academic research institutions complying with the laws and bioethic regulation policies of China will be approved.
Tumor DNA was extracted from formalin-fixed and paraffin embedded tumors of a large cohort of bladder cancer patients before treatment with anti-PD-L1. Normal DNA was extracted from matched PBMCs. Whole exome sequencing was performed. This is a subset of patients for which RNA sequencing is also provided (with more detailed phenotypic information).
Low and high birth weight are not only major causes of neonatal morbidity and mortality, but epidemiological data have established an association between birth weight and later life risk of adult metabolic diseases. Fetal growth is determined by complex interactions between fetal genes and the maternal uterine environment. Subtle or overt variation in maternal glucose tolerance, which is, in part, genetically determined, is related to fetal size at birth. Moreover, new emerging data suggest that genetic variation in the fetus can impact maternal metabolism (e.g., blood pressure and glucose tolerance). Given the above, we are addressing the hypothesis that, during pregnancy, gene-environment interactions in the context of the maternal-fetal unit impact fetal size at birth and maternal metabolism. Genes that control fetal growth or maternal metabolism during pregnancy are largely unknown, so the first step to address our hypothesis will be to identify genetic variation that impacts fetal growth and maternal metabolism and to determine the interaction of that variation with the intrauterine and fetal environment. To accomplish this, we are performing genome wide association (GWA) mapping on a subset of ~37,000 DNA samples that were collected from mothers and their offspring as part of the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study. HAPO is a multicenter, international study in which high quality phenotypic data related to fetal growth and maternal glucose metabolism has been collected from 25,000 pregnant women of varied racial and socio-demographic backgrounds using standardized protocols that were uniform across centers. For these studies, we are genotyping 1,500 infants and their mothers of European descent, 1,250 Afro-Caribbean infants and mothers, 800 Hispanic (Mexican-American) infants and mothers, and 1200 Thai infants and mothers. Genotyping is being performed using the Illumina Human610 Quad (European ancestry participants), Human1M Duo (Afro-Caribbean and Hispanic participants), and Omni1-Quad_v1-0_B (Thai participants). The specific aims for the project are as follows: (1) To apply analytic approaches for conducting GWA mapping studies on quantitative phenotypes related to offspring size at birth (birth weight, ponderal index, head circumference and adiposity) allowing for other known influences such as gestational age, parity, and maternal weight gain. (2) To apply the above approaches to identify genetic variation that impacts maternal glucose tolerance at ~28 weeks of gestation (fasting glucose, glucose during an oral glucose tolerance test, and insulin sensitivity expressed as quantitative traits) allowing for other known influences such as maternal weight gain, parity and age. (3) To examine the interaction between maternal genes, the intrauterine environment, and fetal genes to identify interactions that modulate genetic regulation of size at birth and fetal genetic variation that impacts on maternal glucose tolerance. GWA mapping will provide initial evidence for association of specific SNPs with the quantitative traits outlined above. As low and high birth weight are not only major causes of neonatal morbidity and mortality but have also been associated with increased risk of metabolic diseases in adults, identification of genes that regulate fetal growth and maternal metabolism will provide novel information about the pathways that regulate these processes as well as important insight into susceptibility genes for chronic diseases like type 2 diabetes. The Version 1 (v1) dbGaP release will include data only from the Hispanic study participants. The Version 2 (v2) dbGaP release will include data from the Hispanic and European ancestry study participants. The Version 3 (v3) dbGaP release will include data from the Afro-Caribbean, Hispanic and European ancestry participants. The Version 4 (v4) dbGaP release will include data from all participants (i.e., Afro-Caribbean, Hispanic, European ancestry, and Thai participants). This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to maternal metabolism and birthweight through large-scale genome-wide association studies of infants and their mothers at multiple international sites. Genotyping was performed at the Broad Institute of MIT and Harvard, and at CIDR of Johns Hopkins University, GENEVA genotyping centers. Data cleaning and harmonization was performed at the GEI-funded GENEVA Coordinating Center at the University of Washington.
Transcriptomic sequencing on pre-immunotherapy melanoma patients.
This is a Next Generation Sequencing approach based on whole Usher Syndrome genes sequencing with the aim of diagnosing USH patients and USH2A-associated RP patients
Single-nuclei sequencing data from four neuroblastoma patients. Each patient was run on two lanes, resulting in two runs per patient. Data is provided in paired-end fastq files.
