Search Results - EGA European Genome-Phenome Archive

Collagen XVII Promotes Pancreatic Cancer Through Regulation of PIK3R5

Pancreatic ductal adenocarcinoma (PDAC) contains a desmoplastic stroma that promotes the aggressive biology of this disease. While the varied mechanisms by which fibrillar collagens contribute to PDAC have been defined, little is known about the contribution of transmembrane collagens. Among this class of collagens, Collagen XVII uniquely contains an extensive intracellular domain that connects intracellular cytoplasmic components with the extracellular matrix. Collagen XVII is best characterized as the defining component of the type I hemidesmosome, an anchoring complex that attaches epithelial cells to the underlying basement membrane. In this study, we characterize the expression of collagen XVII in PDAC and the mechanisms by which it contributes to PDAC biology. We demonstrate that crosstalk between PDAC cells and cancer associated fibroblasts drive collagen XVII expression in vitro and xenograft tumor models in vivo. Genetic depletion of collagen XVII in low-passage patient derived cell lines diminishes their metastatic potential and ability to form tumors in mice. Whole transcriptome sequencing of tumors formed by cells with diminished collagen XVII levels revealed dramatically lower levels of PIK3R5, a regulatory subunit of class IB phosphatidylinositol-3-kinase (PI3K) that interacts with G protein-coupled receptors. Consistent with this, collagen XVII-deficient tumors exhibited lower levels of phosphorylated AKT, a downstream effector of PI3K. The studies highlight the importance of collagen XVII signaling in PDAC and define a novel mechanism by which collagen XVII mediates activation of PI3K.

Study phs003641

Panbody_nanoseq

Different cell types within the human body are subject to different endogenous and exogenous exposures which may result in distinct patterns of mutagenesis. In non-clonal tissues, it is difficult to assess these mutational patterns, including the rate at which they occur. This study will examine the mutational rates and signatures operating across a wide range of normal tissues using the nanoseq technology to reliably call variants, irrespective of their clonal composition. Each cell type will be enriched for using laser capture microdissection. This will serve as a reference against which future work on benign and malignant disease entities can be compared.

Study EGAS00001005521

Discovering the Genetic Basis of Cleft Palate: CIDR

Cleft palate (CP) is a common craniofacial structural birth defect caused by the incomplete closure of the palate (the structure separating the oral and nasal cavities), resulting in feeding, speech, and hearing problems. CP accounts for 33% of all orofacial clefts (OFCs) or approximately 1 in 1500 babies born worldwide. Although CP is commonly grouped with other types of orofacial clefts (e.g. cleft lip or cleft with cleft palate), CP is embryologically and epidemiologically distinct, suggesting a unique etiology. The risk of CP recurrence in first degree relatives is over 50-fold higher than the population risk, suggesting a strong genetic component. However, there have been a dearth of genetic studies for CP. Three well-powered genome-wide association studies and meta-analysis have revealed only two associated loci, neither of which account for a large portion of the genetic heritability in any population. The goal of this study is to elucidate the genetic architecture of CP by performing whole genome sequencing of case-parent trios in a well-phenotyped, multi-ethnic cohort. 

Study phs002220

Screening Protocol and Longitudinal Study of Bone Marrow Failure Syndromes and Cytopenias

The purpose of this study is to characterize patients with Bone Marrow Failure Syndromes (BMFS) and to track the clinical course of patients with these diseases over time. An exact and comprehensive diagnosis at presentation is essential. Due to the sporadic nature of BMFS (aplastic anemia, myelodysplastic syndrome, paroxysmal nocturnal hemoglobinuria, pure red cell aplasia, amegakaryocytic thrombocytopenic purpura and large granular lymphocyte leukemia) most diseases have not undergone systematic long-term outcome studies. Individual diseases, combined under the collective entity of bone marrow failure syndromes, frequently overlap and evolve from each other. The frequency of complications, associations with other diseases, and genetic factors such as allelic polymorphisms are not well studied. Some of these syndromes are likely mediated by the cellular immune system. However, while target antigens are likely to be expressed on early hematopoietic cells, their identification has been unsuccessful. Hypothesis: Clinical and epidemiologic studies may, through etiologic clues and intricate laboratory testing, facilitate the understanding of the pathophysiology of BMFS and ultimately lead to implementation of better diagnostic tools and more targeted and rational therapies.

Study phs000592

Kids First: Genomics of Orofacial Clefts in the Philippines

Orofacial clefts (OFCs) are the most common craniofacial structural birth defect in humans caused by incomplete formation of the upper lip and/or the palate. Over 4,000 children in the Philippines are born with an OFC every year, and the Filipino OFC birth prevalence rate of 1 in 500 live births is one of the highest in the world. Genome-wide association studies support a multifactorial etiology for OFCs, but common variants only account for up to ~25% of the heritable risk in any one population. Sequencing studies in diverse populations is essential to fully understand the genetic architecture of OFCs. The study goals of the Kids First project are to sequence a collection of case-parent trios from the Philippines, in order to identify de novo mutations and inherited rare variants, and understand the population differences in common variant signals in the Philippines versus other populations. Approximately 373 trios from the Philippines were selected for whole genome sequencing (WGS) as part of this Gabriella Miller Kids First project.

Study phs002595

Whole Exome Sequencing Study of TGFΒ Pathway Genes in HCV Liver Fibrosis

Despite the astonishing progress in treating chronic hepatitis C virus (HCV) infection with direct-acting antiviral agents, liver fibrosis remains a major health concern in HCV infected patients, in particular due to the treatment cost and insufficient HCV screening in many countries. Only a fraction of patients with chronic HCV infection develop liver fibrosis. While there is evidence that host genetic factors are involved in the development of liver fibrosis, the common variants identified so far, in particular by genome-wide association studies, were found to have limited effects. Here, we conducted an exome association study in 88 highly selected HCV-infected patients with and without fibrosis. A strategy focusing on TGF-β pathway genes revealed an enrichment in rare variants of the endoglin gene (ENG) in fibrosis patients. Replication studies in additional cohorts (617 patients) identified one specific ENG variant, Thr5Met, with an overall odds ratio for fibrosis development in carriers of 3.04 (1.39-6.69). Our results suggest that endoglin, a key player in TGF-β signaling, is involved in HCV-related liver fibrogenesis.

Study phs001902

HipSci - Human Induced Pluripotent Stem Cells Initiative

Human induced pluripotent stem (iPS) cells can be generated from adult tissues and differentiated into a range of specific cell types (Yamanaka and Blau, 2010). They therefore provide unprecedented opportunities for investigating disease mechanisms and understanding the phenotypic consequences of genetic variation within the normal population. HipSci brings together diverse constitutents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. Between 2013 and 2016 we aim to generate iPS cells from over 500 healthy individuals and 500 individuals with genetic disease. We will then use these cells to discover how genomic variation impacts on cellular phenotype and identify new disease mechanisms. Strong links with NHS investigators will ensure that studies on the disease-associated cell lines will be linked to extensive clinical information. Further key features of the project are an open access model of data sharing; engagement of the wider clinical genetics community in selecting patient samples; and provision of dedicated laboratory space for collaborative cell phenotyping and differentiation.

Study EGAS00001001465

Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

Metabolic reprogramming has been described in rapidly growing tumors, which are thought to mostly contain fast-cycling cells (FCCs) that have impaired mitochondrial function and rely on aerobic glycolysis. Here, we characterize the metabolic landscape of glioblastoma (GBM) and explore metabolic specificities as targetable vulnerabilities. Our studies highlight the metabolic heterogeneity in GBM, in which FCCs harness aerobic glycolysis, and slow-cycling cells (SCCs) preferentially utilize mitochondrial oxidative phosphorylation for their functions. SCCs display enhanced invasion and chemoresistance, suggesting their important role in tumor recurrence. SCCs also demonstrate increased lipid contents that are specifically metabolized under glucose-deprived conditions. Increased fatty acid transport in SCCs is targetable by pharmacological inhibition or genomic deletion of FABP7, both of which sensitize SCCs to metabolic stress. Furthermore, FABP7 inhibition, whether alone or in combination with glycolysis inhibition, leads to overall increased survival. Our studies reveal the existence of GBM cell subpopulations with distinct metabolic requirements and suggest that FABP7 is central to lipid metabolism in SCCs and that targeting FABP7-related metabolic pathways is a viable therapeutic strategy.

Study EGAS00001003251

Comprehensive molecular portrait reveals genetic diversity and distinct molecular subtypes of small intestinal neuroendocrine tumors

This study aims to characterize neuroendocrine tumors of the small intestine (siNETs) from genomic, transcriptomic, epigenomic, and clinical perspectives. Involving 122 patients and 219 samples, we generated whole-genome sequencing data, RNA sequencing data, genotyping arrays, and methylation arrays to conduct an integrative analysis of this rare tumor type. Our findings identify distinct molecular subtypes that correlate with siNET clinical features.

Study EGAS50000000642

Whole exome and RNA sequencing data from urothelial bladder cancer patients treated with anti-PD-(L)1

We have generated and analyzed genomic data from a cohort of metastatic urothelial carcinoma patients treated with ICI such as anti-PD-(L)1 monoclonal antibodies. The dataset contains whole exome sequencing data of 27 whole blood samples and 27 FFPE tumor samples. Further, it includes RNA sequencing data from 21 tumor samples. Following the RECIST criteria, 10 patients were classified as non-responders to the treatment, and 17 were responders. The dataset also contains a merged vcf file containing somatic mutations called by Strelka2 and Mutect2 following the gatk best practice pipeline.

Dataset EGAD00001010324

Single-cell RNA sequencing on 11,138 single T cells from 12 colon and rectal cancer (CRC) patients

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.

Dataset EGAD00001003910

Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: BioMe Biobank Program

The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the BioMe Biobank cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1294 1254 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 914 932 The BioMe Biobank study contributed 1294 cases and 1254 controls to T2D-GENES Follow-Up Study.

Study phs001490

Type 2 Diabetes Genetic Exploration by Next-generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow up Study: Pakistan Genomic Resource (PGR)

The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Pakistan Genomic Resource (PGR) cohort was part of the T2-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 903 930 The PGR study contributed 903 cases and 930 controls to T2D-GENES Follow-Up Study.

Study phs001552

The ALT pathway generates telomere fusions that can be detected in the blood of cancer patients

Telomere fusions (TFs) can trigger the accumulation of oncogenic alterations leading to malignant transformation and drug resistance. Despite their relevance in tumour evolution, our understanding of the patterns and consequences of TFs in human cancers remains limited. Here, we characterize the rates and spectrum of somatic TFs across >30 cancer types using whole-genome sequencing data. TFs are pervasive in human tumours with rates varying markedly across and within cancer types. In addition to end-to-end fusions, we find novel patterns of TFs that we mechanistically link to the activity of the alternative lengthening of telomeres (ALT) pathway. We show that TFs can be detected in the blood of cancer patients, which enables cancer detection with high specificity and sensitivity even for early-stage tumours and cancers of high unmet clinical need. Overall, we report a novel genomic footprint that enables characterization of the telomere maintenance mechanism of tumours and liquid biopsy analysis.

Dataset EGAD00001012101

Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

Molecular cancer paper (https://doi.org/10.1186/s12943-021-01327-5): This dataset contain shallow whole-genome sequencing (sWGS) of plasma cell-free DNA from cancer patients and healthy subjects, obtained with both Nanopore and Illumina technology. A total of 6 cancer patients and 5 healthy subjects have been sequenced with Nanopore; 4 of the cancer patients have been also sequenced with Illumina. In addition, genomic DNA from white blood cells of one healthy subjects, genomic and 160bp DNA from HEK cells have been sequenced with Nanopore. Genome Biology paper: 3 additional healthy samples have been sequenced (HU), two different bioinformatic pipeline were applied. 2019: Fastqs from the molecular cancer paper were re-demultiplexed and adapter-trimmed (using guppy for multiplex samples, and porechop for singleplex) preserving 5' ends to allow fragmentomics analysis. HAC: All the samples were basecalled with the same updated High Accuracy model (the latest at the time of the analysis) and post-processed as the 2019 dataset. Raw FAST5 are currently available upon request, but will be uploaded soon.

Dataset EGAD00001006888

PCNSL single-cell dataset

This dataset includes 4 samples with scRNA-seq and 3 sample with CITE-seq, scTCR-seq and scBCR-seq.

Study EGAS50000000474

Multimodal Mapping of the Immune Landscape in Human Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDA) is characterized by an immune-suppressive tumor microenvironment that has rendered it largely refractory to immunotherapy. We used single-cell RNA sequencing on patient tumors and matched blood, and we uncovered a previously unappreciated, complex environment of immune-suppressive cellular interactions. These experiments reveal immune checkpoint expression heterogeneity on individual patient T cells, with corresponding ligands on neoplastic and myeloid cells. TIGIT was upregulated on tumor infiltrating CD8+ T cells and was the only checkpoint receptor consistently expressed by exhausted CD8+ T cells. Clinical annotation of the samples revealed that the exhausted signature is most prominent in patients with advanced stages of disease. Our findings suggest individualized combination therapy, involving anti-TIGIT therapies, may be necessary to extend the benefits of immunotherapy to pancreatic cancer patients.

Study phs002071

The Precision Medicine in Liver Cancer across an Asia-pacific NETwork (PLANET)

Hepatocellular carcinoma (HCC) is the 2nd most important cause of cancer deaths in the world. The outcomes of treatment in HCC are poor compared to other common cancers because there are no good systemic therapy drugs. We designed a prospective study that will involve 5 different sites within the established Asia-Pacific Hepatocellular Carcinoma Trials Group to study both the genetics as well as immune profiles of HCC in different ethnicities. In this study, patients will be followed-up and at recurrence the tissues to understand the evolution of disease progression. Here, we presented both the genomic (DNA) and phenotypic (RNA) evolution for the first batch of 56 patients. The detailed findings will be listed in the corresponding publication soon.

Study EGAS00001003813

Two lung cancer cell lines with EGFR mutations, PC-9 and KHM-3S, were either treated with Tarceva for 24 hours or left untreated. The gene expression profiles were examined by RNAseq, and the genome wide binding profiles of total STAT3 and pSTAT3 were characterized by ChIPseq.

Lung cancers harboring activating EGFR mutants show dramatic responses to EGFR TKIs, such as Tarceva. However, nearly all patients show relapse within 1 year after initial treatment. To investigate the early signaling switches that are involved in the formation of drug resistance, and the role of STAT3 in the early signaling switches involved in the formation of drug resistance, we have treated two lung cancer cell lines with EGFR mutations, PC-9 and KMH-3S, with Tarceva for 24hours. The RNA samples with and without treatment were collected in triplicate for RNAseq experiment.The total STAT3 and pSTAT3 chromatinIP were done on samples with and without treatment for ChIPseq.

Study EGAS00001000793

15000 results for "cancer studies using rna-seq"

in 18.15 milliseconds.