Search Results - EGA European Genome-Phenome Archive

TK-EP862 - Patient-derived xenograft model of Posterior Fossa A Ependymoma - WSG data

In Vivo Loss of Tumorigenicity in a Patient-Derived Orthotopic Xenograft Mouse Model of Ependymoma. Whitehouse et al. 2023 Frontiers in Oncology. We describe the establishment of a patient-derived orthotopic xenograft (PDOX) model of posterior fossa A (PFA) EPN, derived from a metastatic cranial lesion. Patient and PDOX tumors were analyzed using RNA sequencing. WSG data (paired end) provided here correspond to germline DNA, Surgical sample 4 (described in the above manuscript as a cranial metastasis of PFA ependymoma), and a patient-derived xenograft derived from the patient.

Dataset EGAD00001010008

RNA-sequencing of ex vivo exhausted human antigen-specific T cells

Tumor-specific T cells are frequently exhausted by chronic antigenic stimulation. To explore new pathways for reinvigoration of anti-tumor immune functions, we developed a human ex vivo exhaustion model by repetitive antigenic stimulation of primary CD8 T cells. This results in T cells that resemble patient-derived T cells in tumors on a phenotypic and transcriptional level.

Study EGAS00001006794

Local In Time Statistics for processual research

Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological differences like metastatic versus non-metastatic cancer, and the mode of cancer detection, i.e. screening detected versus clinically detected cancers. The dataset was used for examining whether the gene expression profile varies between cases and controls, with time, or between cases with and without metastases. Results: The null hypotheses of no differences between cases and controls, no time-dependent changes, and no differences between different strata were all rejected. For screening detected cancers the probability of correct prediction of metastasis status was best in year 1 before diagnosis compared to year 3 and 4 before diagnosis for clinically detected cancers. The predictor was not very sensitive to the number of genes included.Conclusions: Using a new statistical method, LITS, we have demonstrated time-dependent changes of the blood transcriptome up to eight years before breast cancer diagnosis.

Study EGAS00001002520

Same-day genomic and epigenomic diagnosis of brain tumors using realtime nanopore sequencing

Molecular classification of cancer has entered clinical routine to inform diagnosis, prognosis and treatment decisions. At the same time, new tumor entities have been identified that cannot be defined histologically. For central nervous systems tumors, the current World Health Organization classification explicitly demands molecular testing, e.g. for 1p/19q- codeletion or IDH mutations, to make an integrated histomolecular diagnosis. However, a plethora of sophisticated technologies is currently needed to assess different genomic and epigenomic alterations and turnaround times are in the range of weeks, which makes standardized and widespread implementation difficult and hinders timely decision making. Here, we explored the potential of a pocket-size nanopore sequencing device for multimodal and rapid molecular diagnostics of cancer. Low-pass whole genome sequencing was used to simultaneously generate copy number (CN) and methylation profiles from native tumor DNA in the same sequencing run. Single nucleotide variants in IDH1, IDH2, TP53, H3F3A and the TERT promoter region were identified using deep amplicon sequencing. Nanopore sequencing yielded ~0.1X genome coverage within six hours and resulting CN and epigenetic profiles correlated well with matched microarray data. Diagnostically relevant alterations, such as 1p/19q codeletion, and focal amplifications could be recapitulated. Using ad hoc random forests, we could perform supervised pan-cancer classification to distinguish gliomas, medulloblastomas and brain metastases of different primary sites. Single nucleotide variants in IDH1, IDH2 and H3F3A were identified using deep amplicon sequencing within minutes of sequencing. Detection of TP53 and TERT promoter mutations shows that sequencing of entire genes and GC-rich regions is feasible. Nanopore sequencing allows same-day detection of structural variants, point mutations and methylation profiling using a single device with negligible capital cost. It outperforms hybridization-based and current sequencing technologies with respect to time-to diagnosis and required laboratory equipment and expertise, aiming to make precision medicine possible for every cancer patient, even in resource restricted settings.

Study EGAS00001002213

Somatic copy number alteration and fragmentation analysis in circulating tumor DNA for cancer screening and treatment monitoring in colorectal cancer patients

Background: Analysis of circulating free DNA (cfDNA) is a promising tool for personalized management of colorectal cancer (CRC) patients. Untargeted cfDNA analysis using whole-genome sequencing (WGS) does not need a priori knowledge of the patient´s mutation profile. Methods: Here we established LIquid biopsy Fragmentation, Epigenetic signature and Copy Number Alteration analysis (LIFE-CNA) using WGS with ~6x coverage for detection of circulating tumor DNA (ctDNA) in CRC patients as a marker for CRC detection and monitoring. Results: We describe the analytical validity and a clinical proof-of-concept of LIFE-CNA using a total of 259 plasma samples collected from 50 patients with stage I-IV CRC and 61 healthy controls. To reliably distinguish CRC patients from healthy controls, we determined cutoffs for the detection of ctDNA based on global and regional cfDNA fragmentation patterns, transcriptionally active chromatin sites, and SCNAs. We further combined global and regional fragmentation pattern into a machine learning classifier to accurately predict ctDNA for cancer detection. By following individual patients throughout their course of disease, we show that LIFE-CNA enables the reliable prediction of response or resistance to treatment up to 3.5 months before commonly used CEA. Conclusion: In summary, we developed and validated a sensitive and cost-effective method for untargeted ctDNA detection at diagnosis as well as for treatment monitoring of all CRC patients based on genetic as well as non-genetic tumor-specific cfDNA features. Thus, once sensitivity and specificity have been externally validated, LIFE-CNA has the potential to be implemented into clinical practice. To the best of our knowledge, this is the first study to consider multiple genetic and non-genetic cfDNA features in combination with ML classifiers and to evaluate their potential in both cancer detection and treatment monitoring.

Study EGAS00001006490

EGAD00010000266

Metabric breast cancer samples (Genotype raw data)

Dataset EGAD00010000266

Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

Dataset EGAD00001000856

Exome sequencing

Exome sequencing of peripheral blood from 4 individuals of a family with familial colorectal cancer type X

Dataset EGAD00001001009

GIST SSGXVIII trial targeted gene sequencing

Targeted cancer gene sequencing of samples enrolled in the SSGXVIII trial from Finland.

Dataset EGAD00001001427

RTKs in Multiple Myeloma

Cancer amplicon reads consisting of BAM paired end reads from primary multiple myeloma samples.

Dataset EGAD00001001935

Illumina_RNA_T

RNAseq on Illumina HiSeq2000/2500 of colorectal cancer primary tumor sample

Dataset EGAD00001002077

Illumina_WXS_MET

Whole-exome sequencing on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample

Dataset EGAD00001002095

Prostate WGS data (late onset)

Whole genome sequencing for 12 late onset prostate cancer tumor/control pairs (ICGC)

Dataset EGAD00001003290

OT2_Illumina_RNA_T

RNAseq on Illumina HiSeq2000/2500 of colorectal cancer primary tumor sample (OT2_cohort)

Dataset EGAD00001003367

OT2_Illumina_RNA_MET

RNAseq on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample (OT2_cohort)

Dataset EGAD00001003364

OT2_Solid_WXS_T

Whole-exome sequencing on AB 5500xl Genetic Analyzer of colorectal cancer primary tumor sample (OT2_cohort)

Dataset EGAD00001003386

WGS of kidney cancer organoid biobank

Dataset EGAD00001005319

Heterogeneous Genomic Evolution and Immune Microenvironments in Metastatic Lung Cancer

WES data of paired primary and metastatic tumors

Dataset EGAD00001006213

SNP data

SNP data from 49 paired samples (tumor/germline) with muscle invasive bladder cancer.

Dataset EGAD00010001943

Raw count table

Raw count matrix of the 124 bulk tumor RNAseq samples from patients with hormone sensitive or castration resistant prostate cancer.

Dataset EGAD00001008762

Wilms_Tumour_organoid_sequencing_WGS

This study investigates the genomic and transcriptomic characteristics of Wilm's tumour organoids

Study EGAS00001002692

Osteosarcoma_X10

This is a continuation of the osteosarcoma work we have undertaken.

Study EGAS00001002167

Organoid Derivation Pilot: RNAseq

Sequencing of tissue samples and their derived organoids from oesophageal, pancreatic and colorectal cancer patients.

Dataset EGAD00001005001

DAC for Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

Dac EGAC00001001250

Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

Study EGAS00001007545

Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

Study EGAS00001007451

Genomic Landscape of Human Skin at a Single-Cell Resolution

Every cell in the human body has a unique set of somatic mutations, yet it remains difficult to comprehensively genotype an individual cell. Here, we developed solutions to overcome this obstacle in the context of normal human skin, thus offering the first glimpse into the genomic landscapes of melanocytes at single-cell resolution. We comprehensively genotyped 133 melanocytes from 19 sites across 6 donors. As expected, sun-shielded melanocytes had fewer mutations than sun-exposed melanocytes. However, within sun-exposed sites, melanocytes on chronically sun-exposed skin (e.g. the face) displayed a lower mutation burden than melanocytes on intermittently sun-exposed skin (e.g. the back). Melanocytes from donors with a history of skin cancer had higher mutation burdens than melanocytes from donors without skin cancer, implying that the mutation burden of normal skin can be harnessed to measure cumulative sun damage and skin cancer risk. Moreover, melanocytes from healthy skin commonly harbor pathogenic mutations, likely explaining the origins of the melanomas that arise in the absence of a pre-existing nevus. Phylogenetic analyses identified groups of related melanocytes, suggesting that melanocytes spread throughout skin as fields of clonally related cells, invisible to the naked eye. Overall, our study offers an unprecedented view into the genomic landscapes of individual melanocytes, revealing key insights into the causes and origins of melanoma.

Study phs001979

Genomic Analyses in Neoadjuvant Immunotherapy-Treated Head and Neck Cancers

This is a phase 2 multicenter interventional trial involving the preoperative (neoadjuvant) administration of pembrolizumab, an anti-programmed cell death protein-1 (anti-PD-1) agent, to patients with pathologically confirmed, surgically resectable advanced head and neck squamous cell carcinoma (HNSCC). Participating centers were Dana-Farber/Harvard Cancer Center, Alvin J. Siteman Cancer Center, Washington University and Memorial Sloan Kettering Cancer Center. The trial (NCT02296684) consisted of two cohorts: Cohort 1 enrolled and treated patients received one dose of pembrolizumab prior to surgical resection with curative intent, and adjuvant pembrolizumab was planned for patients with high risk pathological features (positive margins and/or extranodal extension) in the surgical specimen. Cohort 2 enrolled and treated patients received 2 doses of pembrolizumab prior to surgical resection with curative intent. Adjuvant treatment was not dictated by the trial protocol for Cohort 2. The primary endpoint was rate of at least 50% pathological tumor response (pTR), defined as the presence of tumor necrosis/keratinous debris in the tumor bed following neoadjuvant pembrolizumab. pTR was graded as follows: pTR0 (<10%), pTR1 (10-49%) and pTR2 (≥50%). Baseline, pre-treatment tumor biopsy and post-neoadjuvant pembrolizumab surgically resected tumor specimens were dissociated, and CD3+CD45+ cells were analyzed for T cell receptor (TCR) expression and 5' gene expression analysis using single cell sequencing technologies for a subset of patients.

Study phs002864

New England-Based Case-Control Study of Ovarian Cancer

The case-control data provided to dbGaP were collected under NCI grant number CA54419 which had 3 enrollment phases: I (1992-1997), II (1998-2002) and III (2003-2008). Altogether, CA54419 funded 15 years of data and specimen collection, resulting in one of the longest running population based case-control studies of ovarian cancer. The study goal was to examine reproductive factors, lifestyle exposures, and genetic background in relation to ovarian cancer risk. The project recruited cases from Eastern Massachusetts and New Hampshire, and became known as the New England-based Case-Control study (NECC) of ovarian cancer. 3957 ovarian cancer cases diagnosed at ages 18-80 and residing in Eastern Massachusetts and New Hampshire were identified through tumor boards and registries. Of these, 3083 (78%) were eligible and among those eligible, 2203 (71%) were enrolled. After excluding 127 non-epithelial and 35 mixed mesodermal tumors, 2041 cases with epithelial tumors of ovarian, primary peritoneal, and fallopian tube origin, including borderline malignancies were included. On average, cases were interviewed 10 months after their diagnosis. A pathologist reviewed pathology reports and recorded histologic subtype, grade, and stage. Mixed ovarian cancers described as predominantly one type were classified as that type. Undifferentiated, transitional cell tumors, or mixed serous/transitional cell tumors were counted as serous. Other mixed epithelial, malignant Brenner, and unspecified epithelial tumors were classified as other. 2100 controls were identified through random digit dialing (RDD), driver-license lists, and town-resident lists. During the first funding phase from 1992 to 1997, 420 (72%) controls identified through RDD and 102 (51%) through town-resident lists agreed to participate. From 1998 to 2008, only town-resident lists were used to identify potential controls. 4366 controls were identified, of whom 1426 (33%) were ineligible if they had died, moved, or were seriously ill or if they did not have a working telephone, speak English, or have at least one ovary. Of eligible controls, 1362 (46%) declined to participate by phone or via 'opt-out' postcard and 1578 (54%) were enrolled. Controls were frequency matched to cases by 5-year age groups and region of residence. In all phases, after written informed consent, demographic information, reproductive and medical history, and habits were assessed by in-person or telephone interview (in a few instances). All of the questions were framed with respect to a reference date defined as 1 year before the diagnosis date for women in the case group and the date of interview for those in the control group. This study was approved by institutional review boards at Dana Farber Harvard Cancer Center and Dartmouth Medical Center.

Study phs001034

ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

Dataset EGAD00001006293

Identification of neoantigen from MSI-CRC patient derived organoids and its application for targeting by autologous T cells

Targeting neoantigens expressed only by tumor cells enable tumor destruction without unexpected damages to healthy tissues. Here, we identified neoantigens from microsatellite instable (MSI) colorectal cancer (CRC) patient-derived organoids by genomics and immunopeptidomics approches. The neoantigens in this study were predicted from frame-shift mutation by whole-genome sequencing and confirmed its presentation on organoids surface class I HLA molecules by mass spectrometry. We utilized these neoantigens to isolate neoantigen-specific CD8 T cells from autologous PBMC, and proved tumor organoids killing ability of the CD8 T cells, whereas it did not attack normal organoids. This study provides a platform to identify neoantigen from patient-derived cancer organoids and a model to validate T cell recognition, which could be useful for adoptive CD8 T cell transfer treatment for MSI-CRC patient.

Study EGAS00001006633

Patient-derived organoids model treatment response of metastatic gastrointestinal cancers (targeted and whole-genome sequencing)

Patient-derived organoids (PDOs) have recently emerged as robust pre-clinical models, however, their potential to predict patient clinical outcomes remain unclear. We report a living biobank of PDOs from metastatic, heavily-pretreated colorectal and gastroesophageal cancer patients recruited in phase I/II clinical trials. Phenotypic and genotypic profiling of PDOs showed a high-degree of similarity to the original patient tumor. Molecular profiling of tumor organoids was matched to drug screening results, suggesting PDOs could complement existing approaches in defining cancer vulnerabilities and improving treatment responses. We compared ex vivo organoid responses to anticancer agents, and PDO-based orthotopic mouse tumor xenograft models to the response of the patient in clinical trials. Our data suggest that PDOs can recapitulate patient responses in the clinic, and have the potential to be implemented in personalized medicine programs.

Study EGAS00001002784

Screening_for_human_epigenetic_variation_at_CpG_islands

Many human characteristics, including susceptibility to disease, are determined genetically. An unexplored alternative to such genetic determination concerns epigenetic mechanisms such as DNA methylation. CpG islands (CGIs) are generally constitutively hypomethylated, however there are circumstances in which they become heavily methylated and, when coincident with a gene promoter, this invariably causes transcriptional silencing. CGI methylation occurs in normal tissues during processes such as X-inactivation, but abnormal patterns of methylation have also been implicated in disease. The vast majority of evidence relates to cancer, where silencing of multiple genes in this way appears to be a causal contributor to the cancer state. To address the role and extent of CGI methylation in ‘normal’ and diseased cells we applied MBD-affinity purification in conjunction with next generation sequencing in a panel of human brain autopsy samples. These samples represent a panel of individuals as well as specific brain regions and neurological pathologies.

Study EGAS00001000074

Pharmacogenomic landscape of patient-derived cells informs precision oncology therapy

Outcomes of anticancer therapy vary dramatically among patients, which may be caused by the specific molecular alterations in each patient’s tumor. Precision oncology aims to apply optimal therapies for each tumor based on its molecular characteristics. We have established a resource reporting the genomic and transcriptomic profiles of 462 patient tumor-derived cells (PDCs) across 14 cancer types, together with responses to 60 targeted agents. Compared with long-term cultured cancer cell lines, PDCs better recapitulate the molecular profiles of the original tumors. Among other unreported associations, we identify molecular factors inducing resistance to EGFR inhibitors in glioblastoma, and we suggest repurposing ibrutinib (currently used in hematological malignancies) for EGFR-specific therapy in gliomas. Lastly, using a retrospective clinical study, we find that PDC-derived sensitivities can be used to predict patient responses.

Study EGAS00001002515

Genetic makeup of agnospheres

Agnospheres are cultures of cancer stem cells isolated from tissue biopsies from patients with Cancer of Unknown Primary (CUPs). The latter is a lethal malignancy (median survival <1 year), representing approximately the 3% of all cancers, and characterized by metastatic dissemination in the absence of a primary tumor recognizable by a standardized protocol including thorough body imaging and histopathological analysis. Agnospheres are long-term propagated in culture and, after subcutaneous injection into immunocompromised mice, they display high tumorigenicity and quickly reproduce the clinical presentation of the original tumor, featuring a multi-organ metastatic pattern and poorly differentiated histology. The goal of the project is to analyse the mutational profile of agnospheres in detail, as to verify its correspondance with that of the original tumors. Genetic information will be exploited to investigate the genetic drivers of the CUP phenotype, in particular the hypermetastatic ability and the differentiative block.

Study EGAS00001004868

Establishment of xenogfafts and cultured cell lines from clinical samples

The purpose of the present study was to clarify the presence or absence of alterations in the molecular properties of patient-derived xenografts (PDXs) with up to eight passages in endometrial carcinomas. Alterations in the proportion of immunohistochemically positive/negative cells for PAX8, estrogen receptor, PAX2, and PTEN were observed in established PDXs of endometrioid carcinomas and carcinosarcomas, whereas proportions of cells with AE1/AE3, TP53, ARID1A PMS2, and MSH6 were maintained. Variants of cancer-associated genes in PDX compared to those in the parental tumors were examined in two cases, a frameshift deletion in BRCA1 was observed in the parental tumor tissue, and additional genomic alterations were found in the PDXs of this case. Genomic and phenotypic alterations in endometrial carcinoma PDXs relative to the parental tumors were observed and were partly associated with endometrial cancer-specific characteristics in cellular differentiation and gene mutations.

Study JGAS000585

Spatial atlas of clonal copy number alterations in co-existing benign and malignant tissue

Defining the transition from benign to malignant tissue is fundamental to improve early diagnosis of cancer. Here, we use a systematic approach to study spatial genome integrity in situ and describe previously unidentified clonal relationships. We employed spatially resolved transcriptomics to infer spatial copy number variations in >120,000 regions across multiple organs, in benign and malignant tissues. We demonstrate that genome-wide copy number variation reveals distinct clonal patterns within tumours and in nearby benign tissue using an organ-wide approach focused on the prostate. Our results suggest a model for how genomic instability arises in histologically benign tissue that may represent early events in cancer evolution. We highlight the power of capturing the molecular and spatial continuums in a tissue context and challenge the rationale for treatment paradigms, including focal therapy.

Study EGAS00001006124

Metabolic profiling of patient-derived organoids reveals nucleotide synthesis as a metabolic vulnerability in malignant rhabdoid tumors

Malignant rhabdoid tumor (MRT) is one of the most aggressive childhood cancers for which no effective treatment options are available. Reprogramming of cellular metabolism is an important hallmark of cancer, with various metabolism-based drugs being approved cancer treatment. In this study, we use patient derived tumor organoids (tumoroids) to map the metabolic landscape of several pediatric cancers. Combining gene expression analyses and metabolite profiling using mass spectrometry, we find nucleotide biosynthesis to be a particular vulnerability of MRT. Treatment of MRT tumoroids with de novo nucleotide synthesis inhibitors lowers nucleotide levels in MRT tumoroids and induces apoptosis. Lastly, we demonstrate invivo efficacy of methotrexate in an MRT PDX mouse model. Our study revealsnucleotide biosynthesis as an MRT-specific metabolic vulnerability, which can ultimately lead to better treatment options for children suffering from this lethal pediatric malignancy.

Study EGAS00001007877

Neuroblastoma Genome-Wide Association Study (NBL-GWAS)

Neuroblastoma is a malignancy of the developing sympathetic nervous system that most commonly affects young children and is often lethal. The etiology of this embryonal cancer is not known. We have performed a whole genome scan for association of neuroblastoma with SNP genotypes and copy number variation to discover predisposition loci. We therefore initiated a genome-wide association study (GWAS) in 2007 focused on neuroblastoma patients identified through the Children's Oncology Group (COG; 238 member institutions). Control patients for this study are children cared for at the Children's Hospital of Philadelphia (CHOP) without a diagnosis of cancer. The study was designed to collect up to 5000 neuroblastoma cases and 10,000 controls and is powered to detect common susceptibility variants in Caucasian and African American patients. Whole genome genotyping is being performed on the Illumina HH550 SNP array.

Study phs000124

The genomic complexity of sporadic and inherited retinoblastoma with a matched orthotopic xenograft

Retinoblastoma is a pediatric cancer of the developing retina. All retinoblastomas are believed to initiate with biallelic inactivation of the RB1 gene. To identify subsequent genetic lesions in retinoblastoma, we performed whole genome sequencing of tumor and normal DNA of 4 children with retinoblastoma and one matched orthotopic xenograft. Both alleles of RB1 were inactivated in the tumor samples. 3 of the patients had sporadic retinoblastoma and one patient had inherited retinoblastoma. Overall, there were few single nucleotide changes in coding regions of the genome and some of the tumors had few chromosomal lesions. There were very few new genetic lesions in the xenograft compared to the primary tumor. These data suggest that the genome in retinoblastoma is more stable than previously believed and there are relatively few recurrent genetic lesions in known cancer pathways other than the RB1 pathway.

Study phs000352

Genome Sequencing of Pancreatic Ductal Adenocarcinoma at The Human Genome Sequencing Center of Baylor College of Medicine (HGSC-BCM)

Pancreatic ductal adenocarcinomas (PDAC) is the 11th most common cancer in the USA but the 4th in fatalities. The onset and progression of cancer is driven by extensive rearrangement and mutation of the genome. We combined our capability to capture and enrich exome DNA with the next generation sequencing capacity to allow us to detect and characterize the somatic mutation profile of 24 patients with PDAC. Patient samples were collected by the Elkins Pancreatic Center in the Baylor College of Medicine Department of Surgery. Sequencing of the pancreatic ductal adenocarcinoma is one of the NHGRI Center Initiated Projects in progress in the Human Genome Sequencing Center at Baylor College of Medicine. These data are also contributed to an ICGC study and will be published with the ICGC collaborators.

Study phs000516

Whole Genome and Exon Capture Sequencing of Bladder Cancers

One primary bladder cancer and paired peripheral blood sample were subjected to whole genome sequencing on an Illumina HiSeq 2000 platform. This technology was utilized to investigate the genetic basis of a durable remission of metastatic bladder cancer in a patient treated with everolimus, a drug that inhibits the mTOR (mammalian target of rapamycin) signaling pathway. Among the somatic mutations found was a loss-of-function mutation in TSC1 (Tuberous Sclerosis Complex 1), a regulator of mTOR pathway activation. Targeted sequencing using an exon capture and sequencing assay was performed on 13 tumors derived from patients on the same everolimus trial as the index patient and the sequencing data from these tumors is included. TSC1 mutation status was correlated with response to everolimus. The index patient responder tumor and peripheral blood DNA were also subjected to exon capture and sequencing.

Study phs000535

PLCO - Limited Use Pilot Test Data

This is a sample of Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial data for limited use in a pilot test for remote data access. The PLCO is a randomized, controlled trial of screening tests for prostate, lung, colorectal and ovarian cancers. Approximately 155,000 participants were enrolled between November 1993 and July 2001. Participants were individually randomized to the control arm or intervention arm in equal proportions. Participants assigned to the control arm received usual care, whereas participants assigned to the intervention arm were invited to receive screening exams for prostate, lung, colorectal and ovarian cancers as outlined in the study protocol. The goal of the study was to assess whether these screening exams reduce mortality from prostate, lung, colorectal and ovarian cancers. Data were collected on cancer diagnoses and deaths from all causes that occurred through December 31, 2009. Median follow-up time was 12.4 years.

Study phs002011

Dynamics of Genomic and Immune Responses During Primary Immunotherapy Resistance in Mismatch Repair Deficient Tumors

We study a patient with dMMR lung cancer refractory to immunotherapy. Post-treatment tumor demonstrated compound heterozygous frameshift deletions located upstream of the kinase domain in the gene encoding JAK1 protein, downregulation of JAK1 and mediators of its signal transduction, and total loss of JAK1 phosphorylation. Importantly, one of the JAK1 mutations, despite not being detected in the pre-treatment tumor, was found at low variant allele frequency in the pre-treatment circulating tumor DNA, suggesting clonal selection of the mutation. This report provides the most detailed look yet of defective JAK1 signaling in the context of dMMR and immunotherapy-resistance. Together with observations of JAK1 frameshift indels being enriched in dMMR compared with MMR-proficient tumors, our findings demonstrate the critical function of JAK1 in immunological surveillance of dMMR cancer.

Study phs002089

Type

Repository

Study type

Dataset types

Dataset technologies

Phenotypes

Duo

Domain

9182 results for "cancer rna-seq"

in 38.33 milliseconds.