12101 results for "cancer rna-seq"

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• Integrative single-cell and cell-free plasma RNA transcriptomics elucidates placental cellular dynamics

  The human placenta is a dynamic and cellular heterogeneous organ, which is critical in fetomaternal homeostasis and the development of preeclampsia. Previous work has shown that placenta-derived cell-free RNA increases during pregnancy. We applied large-scale microfluidic single-cell transcriptomic technology to comprehensively characterize cellular heterogeneity of the human placentas and identified multiple placental cell-type–specific gene signatures. Analysis of the cellular signature expression in maternal plasma enabled noninvasive delineation of the cellular dynamics of the placenta during pregnancy and the elucidation of extravillous trophoblastic dysfunction in early preeclampsia.

  Study EGAS00001002449

• RNA sequencing in primary inflammatory (TPP) macrophages treated with a MEK1/2 inhibitor

  By investigating an intergenic haplotype on chr21q22, independently linked to inflammatory bowel disease (IBD), ankylosing spondylitis, primary sclerosing cholangitis and Takayasu’s arteritis, we discover that the causal gene, ETS2, is a master regulator of inflammatory responses in human macrophages and delineate how the risk haplotype increases ETS2 expression. Using a database of cellular signatures, we identified drugs that could modulate this pathway. To validate the anti-inflammatory activity of one class of small molecules in vitro, we treated TPP macrophages with vehicle control or a selective, non-ATP competitive MEK inhibitor (PD-0325901) at 2 doses (100nM and 500nM) and performed RNA sequencing.

  Study EGAS00001007552

• Genome-Wide Association Study of Endometrial Cancer in the Epidemiology of Endometrial Cancer Consortium (E2C2)

  Endometrial cancer, the most common gynecological malignancy in the United States, has both an environmental and genetic component. To this end, we conducted a genome-wide association study to identify genes involved in endometrial cancer using studies from the NCI-supported Epidemiology of Endometrial Cancer Consortium (E2C2). For the discovery stage we included samples from 6 cohort and 7 case control studies through 2007. The total number of cases genotyped were 2,307, white women of European descent, and 2,307 matched controls using the Illumina HumanOmniExpress platform. We conducted the replication using the Infinium HumanExome BeadChip, which successfully genotyped 177,139 variants in 1055 cases and 1778 controls from four ethnically diverse studies that are part of the Epidemiology of Endometrial Cancer Consortium (E2C2). The overall goal is to determine whether certain genotypes are predictive of future endometrial cancer risk, and whether the genotypes interact with established endometrial risk factors.

  Study phs000893

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Chromosomal copy number heterogeneity predicts survival rates across cancers

  Survival rates of cancer patients vary widely within and between malignancies. While genetic aberrations are at the root of all cancers, individual genomic features cannot explain these distinct disease outcomes. In contrast, intra-tumour heterogeneity (ITH) has the potential to elucidate pan-cancer survival rates and the biology that drives cancer prognosis1,2. Unfortunately, a comprehensive and effective framework to measure ITH across cancers is missing3. Here, we introduce a scalable measure of chromosomal copy number heterogeneity that predicts patient survival across cancers. We show that the level of ITH can be derived from a single-sample copy number profile. Using gene-expression data we demonstrate that ongoing chromosomal instability underlies the observed heterogeneity. Analysing 11,534 primary cancer samples from 35 different malignancies, we find that copy number heterogeneity can be accurately deduced and predicts cancer survival across tissues of origin and stages of disease. Our results provide a unifying molecular explanation for the different survival rates observed between cancer types.

  Study EGAS00001004702

• SARS-CoV-2 induced alterations of the upper airway DNA methylome exert long-term impacts on ciliary genes involved in ciliary function

  Enzymatic DNA methylome (n=33) and single-cell RNA (n=24) sequencing were performed in nasal cells of COVID-19 patients and controls. In addition, we re-sampled a subset of patients for transcriptome analyses at 3 and 12 months post-infection and followed the expression of differentially regulated genes over time.

  Study EGAS50000000273

• Spatial transcriptome analysis of aging of healthy skin samples

  Previous studies have revealed that skin T cells accumulate and maintain immune responses in the elderly. However, we questioned why these functional T cells fail to recognize and eliminate malignant cells, making elderly skin more prone to developing malignant tumors. To address this question, we examined the overall skin microenvironment in aging using Xenium digital spatial RNA sequencing.

  Study JGAS000771

• Whole blood transcriptomics analysis in Antiphospholipid syndrome in patients with Systemic Lupus Erythematosus

  We analyzed whole-blood RNA-sequencing data from 299 SLE patients (108 SLE-aPL-positive, including 67 SLE-APS; 191 SLE-aPL-negative) and 72 matched healthy controls (HC). Pathway enrichment analysis, unsupervised WGCNA analysis and machine learning were applied to distinguish disease endotypes. Deconvolution analysis was performed to characterize the peripheral blood immune cell profile.

  Study EGAS00001007750

• Investigating transcriptional changes in rapidly differentiated iPSC-derived neurons (i3Ns) harbouring the SNCA A53T mutation +/- RSL3

  In this study we performed bulk RNA sequencing of a iPSC-derived rapid neuronal model harbouring the Parkinson's disease associated A53T mutation in SNCA. These neurons were subsequently treated with a low dose of RSL3 (300nM) for 6 hours to establish the transcriptional impact of ferroptosis induction in the presence or absence of SNCA A53T mutation.

  Study EGAS50000001536

• Fecal microbiome predicts treatment response after the initiation of semaglutide or empagliflozin uptake

  To investigate the effect of semaglutide and empagliflozin initiation on the gut microbiome of type 2 diabetes patients. In addition, to analyze whether the pre-treatment gut microbiome can predict the treatment efficacy. Gut microbiome fecal samples donated at four timepoints (Baseline, Month 1, Month 3; Month 12) were studied using 16S ribosomal RNA gene sequencing and analysis.

  Study EGAS50000000531