Search Results - EGA European Genome-Phenome Archive

Massive Genomic Rearrangment Acquired in a Single Catastrophic Event During Cancer Development

Cancer is driven by mutation. Using Agilent exome hybridisation capture and Illumina GA massively parallel sequencing technology, we aim to sequence ~1600 microRNAs plus the protein coding genome of 25 matched human renal cancer samples. Bespoke algorithms are being developed to identify the somatically acquired point mutations, insertions and deletions in these samples. This project will give unprecedented insights into mutational processes, cellular repair pathways and gene networks associated with renal cancer development.Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 25 renal cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 50 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

Study EGAS00000000029

Identification of cis- and trans-regulatory variation modulating microRNA expression levels in human fibroblasts

MicroRNAs (miRNAs) are regulatory noncoding RNAs that affect the production of a significant fraction of human mRNAs via post-transcriptional regulation. Interindividual variation of the miRNA expression levels is likely to influence the expression of miRNA target genes and may therefore contribute to phenotypic differences in humans, including susceptibility to common disorders. The extent to which miRNA levels are genetically controlled is largely unknown. In this report, we assayed the expression levels of miRNAs in primary fibroblasts from 180 European newborns of the GenCord project and performed association analysis to identify eQTLs (expression quantitative traits loci). We detected robust expression for 121 miRNAs out of 365 interrogated. We have identified significant cis- (10%) and trans- (11%) eQTLs. Furthermore, we detected one genomic locus (rs1522653) that influences the expression levels of five miRNAs, thus unraveling a novel mechanism for coregulation of miRNA expression

Study EGAS00000000056

TenK10K Phase 1: Single Cell

Understanding the genetic basis of gene expression can shed light on the regulatory mechanisms underlying complex traits and diseases. Single-cell resolved measures of RNA levels and single-cell expression quantitative trait loci (sc-eQTLs) have revealed genetic regulation that drives sub-tissue cell states and types across diverse human tissues. Here, we describe the first phase of TenK10K, the largest- to-date dataset of matched whole-genome sequencing (WGS) and single-cell RNA-sequencing (scRNA-seq). We leverage scRNA-seq data from over 5 million cells across 28 immune cell types and matched WGS from 1,925 individuals. This provides power to detect associations between rare and low-frequency genetic variants that have largely been uncharacterised in their impact on cell-specific gene expression. We map the effects of both common and rare variants in a cell type specific manner using SAIGE-QTL.

Study EGAS50000001653

End motifs analysis of circulating DNA from the plasma of patients with stage II-III breast cancer (n=50), stage I-III non-small cell lung cancer (n=56), metastatic colorectal cancer (mCRC) (n=15) and healthy individuals (n=37)..

We have developed an algorithm designed to discriminate cancer patients and healthy individuals based on cirDNA fragment end motif analysis assisted by machine learning, using data obtained from shallow whole genome sequencing (a method we call EMA). We applied EMA to cirDNA from the plasma of patients with stage II-III breast cancer, stage I-III non-small cell lung cancer, and metastatic colorectal cancer (mCRC). CirDNA from 158 individuals was prepared following the conventional double-stranded DNA library preparation (DSP). We also performed a single-stranded DNA library preparation (SSP) using mCRC patients and healthy control cirDNA, which allowed us to make the first ever end motif analysis in the literature which compares the use of DSP and SSP.

Study EGAS50000001319

DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

Study EGAS50000001328

SCANDARE MACARON

Among gynecological cancers, high-grade serous ovarian cancer has the highest prevalence and more than 75% of patients have advanced stage at diagnosis with a 5-year survival of 40%. When the initial complete surgical removal is not possible (60% of patients), an interval surgery can be considered after three to four cycles of neoadjuvant chemotherapy to reduce the tumor mass. However, in approximately 50% of cases the tumor has little or no response to neoadjuvant chemotherapy. Therefore, identification of potential drug targets, biomarkers and/or pathways whose modulation can help in the prevention, interception, or curing of the disease is essential to address the unmet need. Therefore, MACARON project aims to address these issues through the identification of shared neoantigens arising out of somatic alterations and aberrant transcriptional programs in ovarian cancer DNA/RNA datasets.

Study EGAS50000000145

Co-culture experiment (hashed samples)

The principles governing tissue architecture and the mechanisms underlying its disruption in disease remain poorly understood. Here, we utilized single-cell and spatial mapping to interrogate the mechanisms directing immune cell organization in human lymph nodes and its disruption in architecturally distinct lymphoma entities: indolent follicular lymphoma (FL) and aggressive diffuse large B cell lymphoma (DLBCL). Our data substantiate the central role of lymph node stromal cells in chemokine-driven lymphocyte zonation and reveal an inflammatory feedback loop fueled by tumor-reactive T cells, triggering stromal remodeling, progressive loss of homeostatic chemokine gradients and tissue organization from non-malignant to FL and DLBCL. Loss of homeostatic chemokines was associated with adverse patient survival, identifying the underlying architectural rearrangement as a key event during lymphomagenesis. Collectively, our results highlight the principles of lymph node organization and suggest how lymphoma-induced microenvironmental reprogramming drives loss of tissue organization.

Study EGAS50000001252

Deregulation of FOXF1/FENDRR from t(14;16)(q32;q24) defines a subtype of high risk lineage ambiguous leukemia

Despite great progress in understanding the genomic basis of immature T-cell acute lymphoblastic leukemia/lymphoblastic lymphoma (T-ALL) and acute leukemias of ambiguous lineage (ALAL), there are still cases that lack defining genetic markers, complicating risk stratification and limiting targeted therapeutic options. Here, we describe a subtype of leukemia defined by the t(14;16)(q32;q24) translocation, which places the FOXF1 gene and its antisense long noncoding RNA gene FENDRR under the regulatory control of the BCL11B enhancer, leading to their ectopic transcriptional activation. Analysis of different high-throughput sequencing data, including WGS, RNA-seq, scDNA-seq, scRNA-seq, ChIP-seq, ATAC-seq, and HiChIP-seq, identified BCL11B-enhancer mediated deregulation of FOXF1/FENDRR as a hallmark of a subtype of high-risk lineage ambiguous leukemia that is potentially amenable to targeted therapeutic intervention.

Study EGAS50000001255

Clonally heritable gene expression imparts a layer of diversity within cell types

Cell types can be classified according to shared patterns of transcription. Non-genetic variability among individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. Using high coverage single cell RNA profiling, we asked whether long-term, heritable differences in gene expression can impart diversity within cells of the same type. Studying clonal human lymphocytes and mouse brain cells, we uncovered a vast diversity of heritable gene expression patterns among different clones of cells of the same type in vivo. We combined chromatin accessibility and RNA profiling on different lymphocyte clones to reveal thousands of regulatory regions exhibiting interclonal variation which could be directly linked to interclonal variation in gene expression. Our findings identify a source of cellular diversity, which may have important implications for how cellular populations are shaped by selective processes in development, aging and disease.

Study EGAS50000000161

Evolutionary Trajectories of Small Cell Lung Cancer under Therapy

Small cell lung cancer (SCLC) is one of the deadliest human cancers with a five-years survival rate of less than 7%. The standard of care for extensive-stage SCLC consists of systemic treatment with platinum and etoposide, recently combined with PD-L1 immune checkpoint inhibitors (ICI). SCLC patients show high sensitivity to platinum-based chemotherapy, followed by rapid recurrence, which distinguishes SCLC from most human cancers. Unfortunately, second-line treatment with other chemotherapeutics or immunotherapy is only marginally effective, and patients ultimately succumb to their disease. We performed whole exome sequencing, whole genome sequencing and transcriptome sequencing of multiple tumor regions from 65 patients with SCLC. We determined tumor phylogenies at diagnosis and throughout chemotherapy and immunotherapy by multi-region sequencing of 160 tumors from 65 patients, to thus decipher the evolutionary processes underlying the remarkable sensitivity of small cell lung cancer (SCLC) to chemotherapy.

Study EGAS50000000169

Origin of second malignancies in children

Pediatric cancers are rare diseases, and children without known germline predisposing conditions who develop a second malignancy during developmental ages are extremely rare. We present four such clinical cases and through whole-genome and error-correcting ultra-deep duplex sequencing of tumor and normal samples, we explored the origin of the second malignancy in four children, uncovering different routes of development. The exposure to cytotoxic therapies was linked to the emergence of a secondary AML. A common somatic mutation acquired early during embryonic development was the driver of two solid malignancies in another child. In two cases, the two tumors developed from completely independent clones diverging during embryogenesis. Importantly, we demonstrate that platinum-based therapies contributed at least in one order of magnitude more mutations per day of exposure than aging to normal tissues in these children.

Study EGAS50000000167

Spatiotemporal immune atlas of the first clinical-grade gene-edited pig-to-human kidney xenotransplant

Pig-to-human xenotransplantation is rapidly approaching the clinical arena; however, it is unclear which immunomodulatory regimens will effectively control human immune responses to pig xenografts. We transplanted a gene-edited pig kidney into a brain-dead human recipient on pharmacologic immunosuppression and studied the human immune response to the xenograft using spatial transcriptomics and single-cell RNA sequencing. Human immune cells were uncommon in the porcine kidney cortex early after xenotransplantation and consisted of primarily myeloid cells. Both the porcine resident macrophages and human infiltrating macrophages expressed genes consistent with an alternatively activated, anti-inflammatory phenotype. No significant infiltration of human B or T cells into the porcine kidney xenograft was detected. Altogether, these findings provide proof of concept that conventional pharmacologic immunosuppression is sufficient to restrict infiltration of human immune cells into the xenograft early after compatible pig-to-human kidney xenotransplantation.

Study EGAS50000000244

Single-cell RNA sequencing of 16 NPM1 mutated AML patients

NPM1 mutated AML is the largest class in WHO classification, however several subtypes within NPM1 were already reported. Here, we sequence 16 NPM1 mutated AML samples with single-cell RNA-sequencing and multi-color flow cytometry from three major NPM1 subtypes we previously identified, totaling more than half a million cells. We show that the differences among three NPM1 subtypes are mainly driven by cell composition, and these differences are also reflected at cell surface protein level. With the re-analysis of CITE-seq data from another cohort and single cell variant calling on our data, we also report two distinct stem cell phenotypes: one with leukemic (CD34dimCD38-CD45RA+) and another with pre-leukemic (CD34+CD38-CD45RA-) origin. We believe that our data and findings provide novel insights regarding the etiology of NPM1 mutated AML.

Study EGAS50000000332

"Distinct immunometabolic signatures in circulating immune cells define disease outcome in acute-on-chronic liver failure"

We performed single-cell transcriptomics of PBMC’s from healthy (n= 3), acute decompensated (AD) (n= 3) and Acute-on-chronic liver failure (ACLF) patients. Lay Summary: Acute-on-chronic liver failure (ACLF) develops in cirrhotic patients and is characterized by an hyper-inflammatory immune state driving multiple organ failure(s). As a paradox, circulating immune cells also show transcription and metabolic evidence of exhaustion, explaining why these patients are often susceptible to secondary infections. We characterized at a transcriptional level all circulating immune cells of ACLF patiens, and specifically unraveled a distinct recovery and non-recovery ACLF signature within the monocyte population. Moreover, these changes were closely linked to metabolic differences within these cells. The described alterations allowed for a robust prediction of recovery and non-recovery of patients at admission to the hospital.

Study EGAS50000000391

Identification and characterization of tertiary lymphoid structures in brain metastases

Brain metastases (BrM) are the most common cancers in the brain. We performed transcriptome-wide gene expression profiling combined with spatial immune cell profiling to characterize the tumor immune microenvironment in BrM from different primary tumors. We found that BrM from lung carcinoma and malignant melanoma showed overall higher immune cell infiltration as compared to BrM from breast carcinoma. RNA sequencing-based immune cell deconvolution revealed gene expression signatures indicative of tertiary lymphoid structures (TLS) in subsets of BrM from lung cancer and melanoma. This finding was corroborated by multiplex immunofluorescence staining of immune cells in BrM tissue sections. Detection of TLS signatures was associated with prolonged survival after BrM diagnosis in lung cancer patients. Our findings highlight the cellular diversity of the tumor immune microenvironment in BrM of different cancer types and suggest a role of TLS formation for BrM patient outcome.

Study EGAS50000000563

Cell-type, allelic and genetic signatures in the human pancreatic beta cell transcriptome

Pancreatic beta cells within the islets of Langerhans are centrally involved in the pathogenesis of both type 1 and type 2 diabetes. Describing the differentiated state of the human beta cell has been hampered so far by technical (low resolution microarrays) and biological limitations (whole islet preparations rather than isolated beta cells). We circumvent these by deep RNA sequencing of purified beta cells from 11 individuals, presenting here the first characterization of the human beta cell transcriptome. Additionally, we perform the first comparison of gene expression profiles between beta cells, whole islets (N=7) and beta cell depleted islet preparations (N=5), revealing thus beta cell specific expression signatures. Finally, we combine this with whole-genome sequencing data for 7 of our donors, describing here the first set of genetic variants controlling inter-individual variability in beta cell gene expression.

Study EGAS00001000442

ProstOmics: spatial and bulk multi-omics of prostate cancer

In this ERC-funded ProstOmics project we have used spatial and bulk multi-omics on fresh frozen prostate cancer samples to investigate cancer biology and find for biomarkers to improve patient treatment. All tissue material were collected from prostate cancer patients undergoing radical prostatectomy who had not received any prior cancer-specific treatment.Of the 498 prostate tissue samples (114 patients) included in our project, 176 samples (N=37 patients) have been analyzed with bulk transcriptomics (RNA-seq). Some of these 176 samples were also analyzed with spatial transcriptomics (n=32, N=8, Visium 10x RNA-seq) and DNA methylomics (n=96, N=24, array). All datasets include metadata for histopathological evaluation. Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

Study EGAS50000000413

RNA-seq data for study 'Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.'

RNA-seq data from nasal and bronchial tissues in 649 subjects, many with lung cancer. Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

Dataset EGAD50000000333

Heterogeneous endocrine cell composition defines human islet functional phenotypes

Phenotyping and genotyping initiatives within the Integrated Islet Distribution Program (IIDP), the largest source of human islets for research in the U.S., provide standardized assessment of islet preparations distributed to researchers, enabling the integration of multiple data types. Data from islets of the first 299 organ donors without diabetes, analyzed using this pipeline, highlights substantial heterogeneity in islet cell composition associated with hormone secretory traits, sex, reported race and ethnicity, genetically predicted ancestry, and genetic risk for type 2 diabetes (T2D). While α and β cell composition influenced insulin and glucagon secretory traits, the abundance of δ cells showed the strongest association with insulin secretion and was also associated with the genetic risk score (GRS) for T2D. These findings have important implications for understanding mechanisms underlying diabetes heterogeneity and islet dysfunction and may provide insight into strategies for personalized medicine and β cell replacement therapy.

Study EGAS50000000697

Anaplastic oligodendroglioma exome and RNA sequencing data

Anaplastic oligodendrogliomas (AOs) are rare primary brain tumors which are generally incurable, with heterogeneous prognosis and few treatment targets identified. Most oligodendrogliomas have chromosome 1p/19q co-deletion and IDH mutation. We analyzed 51 AOs by whole-exome sequencing, identifying previously reported frequent somatic mutations in CIC and FUBP1. We also identified recurrent mutations in TCF12 and in an additional series of 83 AO. Overall 7.5% of AO are mutated for TCF12, which encodes an oligodendrocyte-related transcription factor. 80% of TCF12 mutations identified were in either the bHLH domain, which is important for TCF12 function as a transcription factor, or were frame shift mutations leading to TCF12 truncated for this domain. We show that these mutations compromise TCF12 transcriptional activity and are associated with a more aggressive tumor type. Our analysis provides further insights into the unique and shared pathways driving AO.

Study EGAS00001001209

H3Africa Chip Design - Aim of designing a cost-effective GWAS chip with content appropriate for use in genomics studies of individuals from the African continent.

Since it is recognized that currently available chips may not be ideally suited to studying African populations, the H3Africa Genome Analysis working group undertook the task of designing a cost-effective GWAS chip with content appropriate for use in genomics research studies of individuals from the African continent. To address gaps in sequence data for some of the African populations being studied in H3Africa projects, a high coverage whole genome sequence dataset was generated at the Baylor College of Medicine with samples provided by H3Africa PIs and collaborators, funded by the National Institutes of Health. This dataset includes 350 high coverage and 160 medium coverage whole genome sequences from 348 populations. The data is accompanied by minimal metadata, including country, ethnic group and sex.

Study EGAS00001002976

Reconstructing the dispersals and adaptive history of Bantu-speaking populations in Africa and North America

Bantu languages are spoken by ~310 million Africans, yet the genetic history of Bantu-speaking populations remains largely unexplored. We generated genomic data for 1,318 individuals from 35 populations in western central Africa, where Bantu languages originated. We found that early Bantu speakers first moved southward, through the equatorial rainforest, before spreading toward eastern and southern Africa. We also found that genetic adaptation of Bantu speakers was facilitated by admixture with autochthonous populations, particularly for the HLA and LCT loci. Finally, we identified a major contribution of western central African Bantu speakers to the ancestry of African Americans, whose genomes present no strong signals of natural selection. Together, these results highlight the contribution of Bantu-speaking peoples to the complex genetic history of Africans and African Americans.

Study EGAS00001002078

Sequencing of pancreatic cancer primary tumors and metastases

The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

Study EGAS00001002186

The Simons Genome Diversity Project: 300 genomes from 142 diverse populations

Here we report the Simons Genome Diversity Project data set: high quality genomes from 300 individuals from 142 diverse populations. These genomes include at least 5.8 million base pairs that are not present in the human reference genome. Our analysis reveals key features of the landscape of human genome variation, including that the rate of accumulation of mutations has accelerated by about 5% in non-Africans compared to Africans since divergence. We show that the ancestors of some pairs of present-day human populations were substantially separated by 100,000 years ago, well before the archaeologically attested onset of behavioural modernity. We also demonstrate that indigenous Australians, New Guineans and Andamanese do not derive substantial ancestry from an early dispersal of modern humans; instead, their modern human ancestry is consistent with coming from the same source as that in other non- Africans.

Study EGAS00001001959

Measuring the level of relatedness between NGS datasets

Sequencing technologies are providing increasingly detailed insight in genetic makeup are paving their way into molecular diagnostics. The field will benefit from rigorous and bias-free measures for the quality of sequence data and for the proper representation of the complexity of the original samples. While current methodologies rely on the availability of a well-characterized reference genome, we propose kMer profiling for alignment-free assessment of the quality, comparability, and complexity of sequencing datasets. We show that kMer detects technical artefacts such as high duplication rates, library chimaeras, and differences in library preparation protocols in whole-genome, whole-exome, and RNA sequencing data. Additionally, it successfully captures the complexity and diversity of microbiomes. Thus, kMer allows for a robust evaluation of the quality and complexity of sequencing data without relying on any prior information and opens the way to a more reliable biological reasoning.

Study EGAS00001000600

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