14480 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

in 18.69 milliseconds.

• Single cell transcriptomics of human adrenal gland reveal chromosomal alterations in adrenocortical cells

  Adrenocortical cells get replenished throughout our lifetime and as such they are a cellular population of high interest in relation to adrenocortical tumours. Single cell transcriptomics of human adrenal gland were performed to identify rare subpopulations of cells, dynamics of cellular turnover and clone expansions in the adrenal cortex. The adrenal gland of this particular individual is characterized by the presence of mutant clone charecterized by aneuploidy in chromosomes 8, 9, 13 and 22, occupying the zona glomerulosa and zona fasciculata. Differential expression analysis of the mutant cells revealed upregulation of MC2R (adrenocorticotropic hormone receptor), CYP21A2, HSD3B2 genes (enzymes involved in cortisol production). Overall, this donor sample is an example of clonal tissue expansions carrying chromosomal rearrangements that likely impact organ morphology and function but are seemingly benign.

  Study EGAS00001007488

• Mutations in the SIX1/2 pathway and the DROSHA/DGCR8 miRNA microprocessor complex underlie high-risk blastemal type Wilms tumors

  Blastemal histology in chemotherapy-treated pediatric Wilms tumors (nephroblastoma) is associated with adverse prognosis. In order to find novel therapeutic leads for this subgroup of patients, we analyzed 58 such Wilms tumors by exome and transcriptome analysis and validated our findings in larger independent cohorts. Recurrent mutations identified either somatically or in the germline included a hotspot mutation (Q177R) in the homeodomain of SIX1 and SIX2 in tumors with high proliferative potential, mutations in microprocessor genes like DROSHA, DGCR8, DICER1 and DIS3L2, and alterations in IGF2, MYCN, and TP53, the latter being strongly associated with dismal outcome. DROSHA and DGCR8 mutations had a strong effect on miRNA profiles in tumors, which we confirmed in cell lines transfected with mutant DROSHA.

  Study EGAS00001000906

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Dataset EGAD00001005448

• Spatial and temporal evolution of distal 10q deletion, a prognostically unfavorable event in diffuse low-grade gliomas

  Background: The disease course of patients with diffuse low-grade glioma is notoriously unpredictable. Temporal and spatially distinct samples may provide insight into the evolution of clinically relevant copy number aberrations (CNAs). The purpose of this study is to identify CNAs that are indicative of aggressive tumor behaviour and can thereby complement the prognostically favorable 1p/19q co-deletion. Results: Genome-wide, 50 base pair single-end, sequencing was performed to detect CNAs in a clinically well-characterized cohort of 98 formalin-fixed paraffin-embedded low-grade gliomas. CNAs are correlated with overall survival as an endpoint. Seventy-five additional samples from spatially distinct regions and paired recurrent tumors of the discovery cohort were analysed to interrogate the intratumoral heterogeneity and spatial evolution. Loss of 10q25.2-qter is a frequent subclonal event and significantly correlates with an unfavorable prognosis. A significant correlation is furthermore observed in a validation set of 126 and confirmation set of 184 patients. Loss of 10q25.2-qter arises in a longitudinal manner in paired recurrent tumor specimens, whereas the prognostically favorable 1p/ 19q co-deletion is the only CNA that is stable across spatial regions and recurrent tumors. Conclusions: CNAs in low-grade gliomas display extensive intratumoral heterogeneity. Distal loss of 10q is a late onset event and a marker for reduced overall survival in low-grade glioma patients. Intratumoral heterogeneity and higher frequencies of distal 10q loss in recurrences suggest this event is involved in outgrowth to the recurrent tumor.

  Dataset EGAD00001001000

• Genomics Define Malignant Transformation in Myeloma Precursor Conditions

  Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.

  Dataset EGAD00001015768

• Southern African Prostate Cancer Study (SAPCS) Ethnic Disparity

  The cohort (n=130) consists of prostate cancer patients from South Africa (n=123) and Brazil (n=7). For each patient, a pair of blood and tumour samples were collected. The sequencing data was mapped to hg38 reference. Blood BAMs are named with “-B” as suffix and tumour BAMs are named with “-T” as suffix.

  Dataset EGAD00001009067

• RNA-seq data from 224 advanced prostate tumors generated by the West Coast Dream Team

  224 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node.

  Dataset EGAD00001008487

• RNA-seq data from 164 advanced prostate tumors generated by the West Coast Dream Team including 42 paired samles

  164 pairs of FASTQ files from metastatic Castration-Resistant Prostate Cancer (mCRPC) sequenced on HiSeq 4000 instruments. Patients were enrolled in the West Coast Dream Team study. Biopsies include various tissue sites including bone, soft tissue, and lymph node. 42 pairs prior to enzalutamide treatment and at progression from 21 patients are included.

  Dataset EGAD00001009065

• Genome-wide associations of human gut microbiota variation and implications for causal inference analyses

  Here we use appropriate taxon-specific models along with support from independent cohorts to show association between human host genotype and gut microbiome variation. Using fecal derived 16S rRNA gene sequences and host genotype data from the Flemish Gut Flora Project (FGFP) we identify genetic associations involving multiple microbial traits. Mendelian randomization analysis was able to estimate associations between microbial traits and disease, however in the absence of clear microbiome driven effects, caution is needed in interpretation. This work marks a growing catalog of genetic associations which will provide insight into the contribution of host genotype to gut microbiome. Despite this, the uncertain origin of association signals will likely complicate future work looking to dissect function or use associations for causal inference analysis.

  Study EGAS00001004420

• FOXM1 is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer that is detectable using metabolic imaging (RNA-seq data)

  PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires novel predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. Since the transcription factor drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II), changes in FOXM1 expression can be detected using magnetic resonance imaging of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by PET measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose.

  Study EGAS00001004452