17304 results for "fc 26 coins Buyfc26coins.com is EA Sports official for FC 26 coins They are definitely a top seller..rG5l"

in 37.22 milliseconds.

• Epigenetic age deceleration reflects fitness improvements following a six-month endurance exercise intervention

  Epigenetic clocks are emerging as promising biomarkers of biological aging, yet their sensitivity to short-term interventions remains unclear. This pilot study investigates whether the GrimAge clock can capture the effects of a six-month cycling-based endurance exercise training intervention, with cardiorespiratory fitness (VO₂ max) and body composition as primary outcomes. We enrolled 42 adults aged 35-65, of whom 38 completed the study and 33 adhered to the protocol (>66% adherence). Participants demonstrated significant improvements in VO₂ max (+20%, P < 0.001) and body composition (P < 0.001). High-quality epigenetic data preprocessing yielded highly reproducible GrimAge estimates (< 2 months measurement error), which strongly correlated with chronological age (R² = 0.86, P < 0.001). On average, GrimAge decreased by 7.44 months relative to the expected trajectory (P = 0.012), reflecting improvements in VO₂ max (R² = 0.27, P = 0.002) but not body composition changes. Notably, GrimAge changes strongly correlated with fluctuations in leukocyte composition, particularly neutrophil fraction (R² = 0.74, P < 0.001). Adjusting for leukocyte composition improved consistency in GrimAge changes, aligning them with additional intervention outcomes and explaining up to 81% of variance. These findings demonstrate that GrimAge is responsive to short-term endurance training, serving as a meaningful biomarker of improved cardiorespiratory fitness, while also capturing immune system variability. This study supports the use of GrimAge in evaluating longevity interventions and highlights the importance of accounting for leukocyte composition in epigenetic aging research.

  Study EGAS00001008221

• The endometrial transcription landscape of MRKH syndrome

  The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome (OMIM 277000) is characterized by agenesis of the uterus and upper part of the vagina in females with normal ovarian function. While genetic causes have been identified for a small subset of patients and epigenetic mechanisms presumably contribute to the pathogenic unfolding, too, the etiology of the syndrome has remained largely enigmatic. A comprehensive understanding of gene activity in the context of the disease is crucial to identify etiological components and their potential interplay. So far, this understanding is lacking, primarily due to the scarcity of samples and suitable tissue. In order to close this gap, we profiled endometrial tissue of uterus rudiments in a large cohort of MRKH patients using RNA-seq and thereby provide a genome-wide view on the altered transcription landscape of the MRKH syndrome.

  Study EGAS00001004601

• Identification of New Therapeutic Targets for Renal Medullary Carcinoma via Integrated Genomic and Transcriptomic Profiling

  Renal medullary carcinoma (RMC) is a rare, aggressive kidney cancer associated with sickle cell trait, characterized by SMARCB1 loss and resistance to conventional therapies used for other renal cell carcinomas (RCC). We conducted whole exome sequencing (WES) on RMC samples. This study provides a large molecular characterization of RMC, highlighting TROP2 and other cell surface markers as promising therapeutic targets.

  Study EGAS50000001280

• ENU_LS_411N_TripleTherapy

  BRAF V600E colorectal cancers do not respond to the only currently FDA approved targeted therapy for CRC. There is currently a trial underway in the UK recruiting V600E CRC patients for treatment with a triple therapy combination of Cetuximab, Trametinib and Dabrafenib. We have mutagenized a pool of V600E CRC cell lines and treated with this triple therapy to select out drug resistant clones. We will now sequence these drug resistant clones with the aim of identifying common point mutations engendering resistance to this new therapy.

  Study EGAS00001001777

• Collection: Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

  The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes.To request access to this collection, select phs003650 in the dbGaP when submitting a data access request.

  Study phs003650

• Search for new loci and low-frequency variants influencing glioma risk by exome-array analysis

  To identify protein altering variants (PAVs) for glioma we analysed Illumina HumanExome BeadChip exome array data on 1,882 glioma cases and 8,079 controls from three independent European populations. In addition to single variant tests we incorporated information on the predicted functional consequences of PAVs and analysed sets of genes with a higher likelihood of having a role in glioma on the basis of the profile of somatic mutations documented by large-scale sequencing initiatives. Globally tThere was a strong relationship between effect size and SNPs predicted to be damaging (P=2.29x10-49); however, these variants which are most likely to impact on risk, are rare (MAF<5%). While no single variant showed an association which was statistically significant at the genomewide threshold a number of represented promising Notable associations - were seen with the BRCA2:c.9976A>T, p.(Lys3326Ter)BRCA2 p.Lys332X variant, which has been shown documented to influence breast and lung cancer risks (OR=2.3, P=4.00x10-4 for glioblastoma [GBM]) and IDH2:c.782G>A, p.(Arg261His)IDH2 p.Arg261His (OR=3.21, P=7.67x10-3, for non-GBM). Additionally, gene burden tests revealed a statistically significant association for HARS2 and risk of GBM (P=2.20x10-6). Genome scans of low frequency PAVs represent a complementary strategy to identify disease-causing variants compared with scans based on tagSNPs. Strategies to lessen the multiple testing burden by restricting analysis to PAVs with higher priors affords an opportunity to maximise study power.

  Study EGAS00001001258

• Lebanon_HighCov_seq

  We propose to investigate the genomics of a Lebanese sample. we plan (1) genotyping (2.5M) of 120 Lebanese individuals, choosing this platform to allow comparison with the 1000 Genomes and African Genome Variation project populations, (2) 8x sequencing of 100 individuals to provide unbiased population-level sequence information including allele frequencies, and (3) 30x sequencing of four individuals to allow inferences such as from PSMC/MSMC to be obtained. The current form is for the high-coverage sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002085

• Lebanon_LowCov_seq

  we propose to investigate the genomics of a Lebanese sample. we plan (1) genotyping (2.5M) of 120 Lebanese individuals, choosing this platform to allow comparison with the 1000 Genomes and African Genome Variation project populations, (2) 8x sequencing of 100 individuals to provide unbiased population-level sequence information including allele frequencies, and (3) 30x sequencing of four individuals to allow inferences such as from PSMC/MSMC to be obtained. The current form is for the low-coverage sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002084

• Epidemiologic Architecture for Genes Linked to Environment (EAGLE) MetaboChip Study

  The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study is a study site of the larger Population Architecture using Genomics and Epidemiology (PAGE) I study.  EAGLE accessed two data resources during the course of study: the National Health and Nutrition Examination Surveys (NHANES) and BioVU, the Vanderbilt University Medical Center biorepository linked to de-identified electronic health records.The EAGLE MetaboChip Study, also known as EAGLE BioVU in the literature, is a data resource of Illumina MetaboChip genotypes for ~15,000 DNA samples from African American/Black, Hispanic, and Asian patients in BioVU (PMID: 26201699). Several EAGLE BioVU and PAGE I study phenotypes were extracted using structured and unstructured data available in de-identified electronic health records linked to the DNA samples. 

  Study phs002767

• Tumor Mutation Burden, Expressed Neoantigen and Immune Microenvironment in Diffuse Gliomas

  A consistent correlation between tumor mutation burden (TMB) and tumor immune microenvironment has not been observed in gliomas as in other cancers. Driver germline and somatic mutations, TMB, neoantigen, and immune cell signatures were analyzed using whole exome sequencing (WES) and transcriptome sequencing of tumor and WES of matched germline DNA in a cohort of 66 glioma samples (44 IDH-mutant and 22 IDH-wildtype). Fourteen samples revealed a hypermutator phenotype (HMP). Eight pathogenic (P) or likely pathogenic (LP) germline variants were detected in 9 (19%) patients. Six of these 8 genes were DNA damage repair genes. P/LP germline variants were found in 22% of IDH-mutant gliomas and 12.5%of IDH-wildtype gliomas (p= 0.7). TMB was correlated with expressed neoantigen but showed an inverse correlation with immune score (R =−0.46, p= 0.03) in IDH-wildtype tumors and no correlation in IDH-mutant tumors. Antigen Processing and Presentation (APP) score correlates with immune score. The APP is higher in non-hypermutator phenotype (NHMP) samples versus HMP samples in the IDH-wildtype gliomas, but higher in HMP samples versus NHMP samples in the IDH-mutant gliomas. Conclusion: TMB was inversely correlated with the immune score in the IDH-wildtype gliomas, and showed no correlation in the IDH-mutant tumors. The APP was correlated with the immune score, and may be further investigated as a biomarker for response to immunotherapy in gliomas. Studies of germline variants in a large glioma cohort are warranted.

  Study phs002653

• Efficient prediction of a spatial transcriptomics profile better characterizes breast cancer tissue sections without costly experimentation

  Spatial transcriptomics is an emerging technology requiring costly reagents and considerable skills, limiting the identification of transcriptional markers related to histology. Here, we show that predicted spatial gene-expressions in unmeasured regions and tissues can enhance biologists��� histological interpretations. We developed the Deep learning model for Spatial gene Clusters and Expression, DeepSpaCE and confirmed its performance using the spatial-transcriptome profiles and immunohistochemistry images of consecutive human breast cancer tissue sections. For example, the predicted expression patterns of SPARC, an invasion marker, highlighted a small tumor-invasion region that is difficult to identify using raw data of spatial transcriptome alone because of a lack of measurements. We further developed semi-supervised DeepSpaCE using unlabeled histology images and increased the imputation accuracy of consecutive sections, enhancing applicability for a small sample size. Our method enables users to derive hidden histological characters via spatial transcriptome and gene annotations, leading to accelerated biological discoveries without additional experiments.

  Study JGAS000290

• Biased allelic expression in human primary fibroblast single cells.

  The study of gene expression in mammalian single cells using genomic technologies now provides the possibility to investigate the patterns of allelic gene expression. We have used single-cell RNA sequencing to detect the allele-specific mRNA level in 203 single human primary fibroblast cells over 133,633 unique heterozygous single nucleotide variants (hetSNVs). We have observed that at the snapshot of analyses each cell contains mostly transcripts from one allele from the majority of genes; indeed 76.4% of the hetSNVs display stochastic monoallelic expression in single cells. Remarkably, adjacent hetSNVs exhibit haplotype consistent allelic ratio; in contrast distant sites located in two different genes are independent of the haplotype structure. Moreover, the allele-specific expression in single cells correlated with the abundance of the cellular transcript. We observed that genes expressing both alleles in majority of the single cells at a given time point are rare and enriched in highly expressed genes. The relative abundance of each allele in a cell is controlled by some regulatory mechanisms since we observed related single-cell allelic profiles according to genes. Overall, these results have direct implications in cellular phenotypic variability.

  Study EGAS00001001009

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Gastric_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003151

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Pancreatic_Organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001003520

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Mutagen_treated_organoids

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001004873

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__organoid_control_WGS

  The Mutographs project aims to advance our understanding of the causes of cancer through studies of mutational signatures. Led by Mike Stratton, together with Paul Brennan, Ludmil Alexandrov, Allan Balmain, David Phillips and Peter Campbell, this large-scale international research endeavour was awarded a Cancer Research UK Grand Challenge. Different patterns of somatic mutation are generated by the different environmental, lifestyle and genetic factors that cause cancer, many of them are still unknown. Within Mutographs, Kings College London will characterise the mutational signatures induced by putative human carcinogens in order to identify the origins of mutational signatures found in human cancers. To achieve this human organoid cell cultures will be exposed to a representative catalogue of known or suspected human carcinogens and mutagens and, using whole genome sequencing, the patterns of mutations induced by them will be determined. Somatic mutational signatures will be subsequently extracted by non-negative matrix factorisation methods and correlated with exposure data. Through an enhanced understanding of cancer aetiology, Mutographs unprecedented effort is anticipated to outline modifiable risk factors, lead to new approaches to prevent cancer, and provide opportunities to empower early detection, refine high-risk groups and contribute to further therapeutic development.

  Study EGAS00001005449

• NHLBI GO-ESP: Family Studies (Familial Interstitial Pneumonia)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The Familial Interstitial Pneumonia (FIP) project seeks to identify genetic variants in coding regions of the human genome that are linked to FIP by examining the coding regions among relatives with FIP. These data will be used in conjunction with our other genetic studies to help us better understand how and why some individuals develop pulmonary fibrosis.

  Study phs000582

• Clinical Resistance to Crenolanib in Acute Myeloid Leukemia Due to Diverse Molecular Mechanisms

  FLT3 mutations are commonly detected in Acute Myeloid Leukemia (AML) patients and are associated with poor prognosis. Crenolanib, a potent type I pan-FLT3 (GeneID:2322) inhibitor, is effective against both internal tandem duplications (ITD) and resistance-conferring tyrosine kinase domain (TKD) mutations. While crenolanib monotherapy has demonstrated significant clinical benefit in heavily pretreated relapsed/refractory AML patients, responses are transient and relapse eventually occurs. To investigate the mechanisms of crenolanib resistance, we performed whole exome sequencing of AML patient samples before and after crenolanib treatment (122 samples from 59 patients). Unlike other FLT3 inhibitors, crenolanib did not induce FLT3 activation loop mutations, and mutations of the FLT3 "gatekeeper" residue were infrequent. Instead, mutations of NRAS (GeneID:4893) and IDH2 (GeneID:3418) arose, mostly as FLT3-independent subclones, while TET2 (GeneID:54790) and IDH1 (GeneID:3417) predominantly co-occurred with the FLT3-mutant clone and were enriched in crenolanib poor-responders. The remaining patients exhibited post-crenolanib expansion of mutations associated with epigenetic regulators, transcription factors, and cohesion factors, suggesting diverse non-FLT3 genetic/epigenetic mechanisms of crenolanib resistance. Drug combinations in experimental models restored crenolanib sensitivity.

  Study phs001628

• scRNA-seq data of human nuclei collected from the temporal cortex of 17 individuals.

  Transcriptome analysis of single cells has tremendously increased our understanding of cellular heterogeneity in complex tissues. However, whole-cell transcriptomics cannot be applied to frozen tissue due to poor cell recovery after freezing. Human tissue is usually limited to tissue banks containing frozen material, and since single nuclei can be readily isolated from frozen tissues, human cell nuclei can substitute whole-cell analysis to extract single cell transcriptomes from human cells. Despite the importance of human tissue analysis, single-nucleus RNA-sequencing protocols are less developed than those for whole cells. SMARTSeq, either in form of custom-made SMARTSeq2 or as part of the Fluidigm C1 platform, provides a high resolution view of the transcriptome, has proven effective for whole-cell analysis and has recently been adapted to nuclei. Here, we show that the standard SMARTSeq2 protocol applied to single nuclei biases the amplification of single-nucleus transcriptomes due to unspecific capturing of transcripts, which can comprise the majority of reads in single-nucleus RNA-sequencing libraries. We demonstrate that modification of the SMARTSeq2 protocol with respect to template switching and cDNA amplification conditions generates sequencing libraries of higher complexity, allows for detection of more genes and reduces biases of the amplified transcriptome. In addition, modification of SMARTSeq2 chemistry allows for gene detection at shallower sequencing depth, thus increasing efficiency and decreasing cost.

  Study EGAS00001002882

• Identification_of_drug_resistance_genes_in_melanoma_by_mRNA_gene_expression

  We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistanceThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000815

• Identification_of_drug_resistance_genes_in_melanoma_by_small_RNAs_expression_analysis

  We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistanceThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000816

• Evolution of Chromatin Architecture and Transcriptional Regulation in Mammals

  Changes in gene expression are a critical force driving the evolution of form and function. As a result, the mechanisms by which gene expression evolves have become a subject of intense interest. A number of investigators have measured evolutionary changes in gene expression at the chromatin, mRNA, and protein levels, leading to new insights about how species evolve. However, studies of different stages in gene expression have not always been in agreement. For example, the extremely rapid rates of evolutionary changes that have been widely observed at enhancers appear to conflict with the slower rates observed in mRNA abundance. We recently completed a major comparative study in primates showing that this disparity between enhancer and mRNA evolution, in part, reflects extensive compensation at enhancers that jointly determine transcription at target genes. Likewise, related findings have demonstrated that post-transcriptional changes buffer protein abundance to relatively more common differences in mRNA expression. Together, these recent findings demonstrate that evolutionary changes affecting multiple stages of transcriptional regulation often have interdependent effects on gene expression. Here we propose to determine how stages early during transcriptional regulation work in concert, either to conserve gene expression through compensatory changes across stages, or, in rare cases, to change mRNA in ways that alter organism phenotypes. Our central hypothesis is that interactions between stages are common, especially at long evolutionary time-scales. To test this hypothesis we propose an ambitious plan to collect rich genomic data profiling distinct stages of gene expression in two cell types and three tissues from nine mammalian species. We have focused our study on several early rate-limiting steps in mRNA production, using molecular assays selected to provide orthogonal sources of information about chromatin architecture (Hi-C/Hi-ChIP), accessibility (ATAC-seq), transcription (PRO-seq), and mRNA levels (RNA-seq). This project will produce the largest resource of genomic data uniformly collected across mammals to date. We will integrate genomic data using a suite of new computational tools, which together will provide a new understanding of how distinct regulatory stages work in concert during regulatory evolution.

  Study phs002146

• Sensitive detection of tumor mutations from blood and its application to immunotherapy prognosis

  Cell-free DNA (cfDNA) is attractive for many applications, including cancer detection, locating, and monitoring. A fundamental task underlying these applications is the SNV calling from cfDNA, which, however, faces a new challenge, namely, the generally very low tumor content in cfDNA. Thus all existing callers fail to achieve satisfactory performance. Here we present cfSNV, a method incorporating multi-layer error suppression and hierarchical mutation calling, to address this important challenge. Furthermore, by leveraging cfDNA’s comprehensive coverage of clonal landscape, for the first time cfSNV can profile mutations even in subclones. In both simulated and real patient data, cfSNV vastly outperforms existing tools, showing tens of times increase in sensitivity in detecting mutations with low allele frequency while maintaining high precision. cfSNV can enhance the clinical utilities of cfDNA by dramatically reducing the required sequencing depth and therefore reduce the cost by magnitudes, and further make the Whole-Exome-Sequencing of cfDNA a viable option. As an example, we demonstrate that cfDNA-WES allows a new biomarker to effectively select patients for immunotherapy.

  Study EGAS00001004373

• CAGE analysis for endometrial carcinoma

  For endometrial cancer patients, lymphadenectomy is recommended to exclude rarely metastasized cancer cells. This procedure is performed even in patients with low risk of recurrence despite the risk of complications such as lymphedema. A method to accurately identify cases with no lymph node metastases (LN-) before lymphadenectomy is therefore highly required. We approached this clinical problem by examining primary lesions of endometrial cancers with CAGE (Cap Analysis Gene Expression), which quantifies promoter-level expression across the genome. Fourteen profiles delineated distinct transcriptional networks between LN?+?and LN- cases, within those classified as having the low or intermediate risk of recurrence.

  Study JGAS000124

• NPY methylated ctDNA is a promising biomarker for treatment response monitoring in metastatic colorectal cancer

  Study EGAS00001006820