3331 results for "ovarian cancer"

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• Comprehensive Genomic Characterization of Translocation Renal Cell Carcinoma

  Xp11 translocation renal cell carcinoma (tRCC) is a rare, female-predominant cancer driven by a fusion between the TFE3 gene on chromosome Xp11.2 and a partner gene on either chrX or an autosome. It remains unknown what types of rearrangements underlie TFE3 fusions, whether fusions can arise from both the active (chrXa) and inactive X (chrXi) chromosomes, and whether TFE3 fusions from chrXi translocations account for the female predominance of tRCC. To address these questions, we performed haplotype-specific analyses of chrX rearrangements in tRCC whole genomes. We show that TFE3 fusions universally arise as reciprocal translocations and that oncogenic TFE3 fusions can arise from chrXi:autosomal translocations. Female-specific chrXi:autosomal translocations result in a 2:1 female-to-male ratio of TFE3 fusions involving autosomal partner genes and account for the female predominance of tRCC. Our results highlight how X chromosome genetics uniquely constrains somatic chrX alterations and underlies cancer sex differences.This version of the dbGaP study provides a comprehensive set of whole genome data and tables with clinical information collected for the 16 patients (15 pateints as tRCC and 1 patient as ccRCC) in the study cohort. The data also contains 12 RNA-seq samples used in the study and analyses. We anticipate that this data will considerably advance our molecular and genetic understanding of oncogenic translocations in TFE3-tRCC involving inactive chromosome X and its role in cancer sex bias.

  Study phs003008

• Cancer-associated fibroblasts promote drug resistance in ALK-driven lung adenocarcinoma cells by upregulating lipid biosynthesis

  Targeted therapy interventions using tyrosine kinase inhibitors (TKIs) provide encouraging treatment responses in ALK-rearranged lung adenocarcinomas, yet resistances occur almost inevitably. Apart from tumor cell-intrinsic resistance mechanisms, accumulating evidence supports a role of cancer-associated fibroblasts (CAFs) in affecting the therapeutic vulnerability of lung cancer cells. Here, we aimed to investigate underlying molecular networks shaping the therapeutic susceptibility of ALK-driven lung adenocarcinoma cells via tumor microenvironmental cues using three-dimensional (3D) spheroid co-culture settings. We show that CAFs promote therapy resistance of lung tumor cells against ALK inhibition by reducing apoptotic cell death and increasing cell proliferation. Using single-cell RNA-sequencing analysis, we show that genes involved in lipogenesis constitute the major transcriptional difference between TKI-treated homo- and heterotypic lung tumor spheroids. CAF-conditioned medium and CAF-secreted factors HGF and NRG1 were both able to promote resistance of 3D-cultured ALK-rearranged lung tumor cells via AKT signaling, which was accompanied by enhanced de novo lipogenesis and supression of lipid peroxidation. Notably, simultaneous targeting of ALK and SREBP-1 was able to overcome the established CAF-driven lipid metabolic-supportive niche of TKI-resistant lung tumor spheroids. Our findings highlight a crucial role of CAFs in mediating ALK-TKI resistance via lipid metabolic reprogramming and suggest new ways to overcome resistance towards molecular directed drugs by targeting vulnerabilities downstream of oncogenic signaling.

  Study EGAS50000000135

• Whole genome sequencing with linked reads of pediatric glioblastoma samples

  Pediatric glioblastoma (pGBM) is a lethal cancer with no effective therapies. To understand mechanisms of tumor evolution in this cancer, we performed whole genome sequencing with linked reads on longitudinally resected pGBM samples. Our analyses showed that all diagnostic and recurrent samples were collections of genetically diverse subclones. Clonal composition rapidly evolved at recurrence, with less than 8% of non-synonymous single nucleotide variants being shared in diagnostic-recurrent pairs. In order to track the origins of the mutational events we observed in pGBM, we generated whole genome datasets for two patients and their parents. These trios showed that genetic variants could be (i) somatic, (ii) inherited from a healthy parent, or (iii) arose de novo in the germlines of pGBM patients. Analysis of variant allele frequencies supported a model of tumor growth involving slow-cycling cancer stem cells that give rise to fast-proliferating progenitor-like cells and to non-dividing cells. Interestingly, radiation and anti-mitotic chemotherapeutics did not increase overall tumor burden upon recurrence. These findings support an important role for slow-cycling stem cell populations in contributing to recurrences, since slow-cycling cell populations are expected to be less prone to genotoxic stress induced by these treatments and to accumulate few mutations. Our results highlight the need for new targeted treatments that account for the complex functional hierarchies and genomic heterogeneity of pGBM.

  Study EGAS00001003432

• Partner-independent fusion gene detection by multiplexed CRISPR/Cas9 enrichment and long-read Nanopore sequencing

  Fusion genes are hallmarks of various cancer types and important determinants for diagnosis, prognosis and treatment possibilities. The promiscuity of fusion genes with respect to partner choice and exact breakpoint-positions restricts their detection in the diagnostic setting, even for known and recurrent fusion gene configurations. To accurately identify these gene fusions in an unbiased manner, we developed FUDGE: a FUsion gene Detection assay from Gene Enrichment. FUDGE couples target-selected and strand-specific CRISPR/Cas9 activity for enrichment and detection of fusion gene drivers (e.g. BRAF, EWSR1, KMT2A/MLL) - without prior knowledge of fusion partner or breakpoint-location - to long-read Nanopore sequencing. FUDGE encompasses a dedicated bioinformatics approach (NanoFG) to detect fusion genes from Nanopore sequencing data. Our strategy is flexible with respect to target choice and enables multiplexed enrichment for simultaneous analysis of several genes in multiple samples in a single sequencing run. We observe on average a 508-fold on-target enrichment and identify fusion breakpoints at nucleotide resolution - all within two days. We demonstrate that FUDGE effectively identifies fusion genes in cancer cell lines, tumor samples and on whole genome amplified DNA irrespective of partner gene or breakpoint-position in 100% of cases. Furthermore, we show that FUDGE is superior to routine diagnostic methods for fusion gene detection. In summary, we have developed a rapid and versatile fusion gene detection assay, providing an unparalleled opportunity for pan-cancer detection of fusion genes in routine diagnostics.

  Study EGAS00001003964

• Whole transcriptome profiling of liquid biopsies from tumour xenografted mouse models: validation cohort

  While cell-free DNA (cfDNA) in liquid biopsies is widely being used and investigated, free circulating RNA (extracellular RNA, exRNA) has the potential to improve therapy response monitoring and cancer detection due to its dynamic nature. A fundamental open question hampering the initiation of large-scale liquid biopsy collections for tumour exRNA analysis is that it remains unclear in which blood subcompartment tumour-derived exRNAs primarily reside. We set out to develop a host-xenograft deconvolution framework, exRNAxeno, with cDNA mapping strategies to either a combined human-mouse reference genome or both species genomes in parallel, that can be applied to exRNA sequencing data from liquid biopsies of human xenograft mouse models, enabling to distinguish (human) tumoural RNA from (murine) host RNA, and as such to specifically analyse tumour-derived exRNA. Subsequently, the preferred exRNAxeno combination pipeline was applied to total exRNA sequencing data from blood platelets and three plasma fractions from a breast cancer patient-derived and neuroblastoma cell line-derived xenograft mouse model. We show that tumoural exRNA concentrations are not determined by plasma platelet levels, while host exRNA concentrations increase with platelet content. Furthermore, a large variability in exRNA levels and gene content across individual mice is observed. In general, the tumoural gene detectability in plasma is correlated with the RNA expression levels in the tumour tissue or cancer cell line. Our results unravel new aspects of tumour-derived exRNA biology in xenograft mouse models.

  Study EGAS00001006582

• Rucaparib in patients presenting a metastatic breast cancer with Homologous Recombination Deficiency, without germline BRCA1/2 mutation, pronostic value of high LOH genomic score and predictive value of HRDetect (WGS)

  Study EGAS00001004756

• Point-of-care monitoring of head and neck cancer treatment response and recurrence development using nanopore-based ctDNA consensus sequencing

  Study EGAS00001007090

• V4_Colorectal_panel_test

  Targeted gene screen of cell line tumours for testing the new V4 Colorectal gene panel.

  Study EGAS00001001807

• Multiple_myeloma_precursor_genomics

  Whole genome sequencing of up to 45 multiple myeloma precursor samples and matched normals pairs.

  Study EGAS00001006312

• Mutational_signatures_and_clonal_dynamics_in_normal_human_tissues

  Somatic mutations (burdens and signatures) and clonal dynamics in normal human tissues

  Study EGAS00001002471

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Genomic Resistance Patterns to Second Generation Androgen Blockade in Paired Tumor Biopsies of Metastatic Castrate-Resistant Prostate Cancer

  We examined genetic resistance to second generation androgen targeting therapies (abiraterone acetate or enzalutamide) by analyzing whole exome sequencing of patient-matched pre-treatment and post-resistance tumors from a series of castrate-resistant prostate cancer (CRPC) patients. Abiraterone resistant tumors harbored alterations in AR and MYC, whereas patients treated with enzalutamide had acquired alterations in the cell cycle pathway. We experimentally confirmed expression of cell-cycle kinases sufficed to drive enzalutamide resistance, which was mitigated through CDK4/6 blockade. These observations link genetic resistance to specific therapeutic agents to inform strategies in genomically selected advanced CRPC.

  Study phs001447

• Contribution of systemic and somatic factors to clinical response and resistance in urothelial cancer: an exploratory multi-omic analysis

  Patients with metastatic urothelial cancer (n=29) were treated with atezolizumab (anti-PD-L1). All 29 patients had T-cell receptor sequencing (TCR-seq) of the pre-treatment blood; 24 also had TCR-seq on at least one post-treatment blood sample. 24 patients had TCR-seq of their pre-treatment tumors. TCR-seq data can be found at http://doi.org/10.5281/zenodo.546110. 26 patients also had RNAseq of their tumors and whole exome sequencing (WES) of their tumors and matched normal blood. WES results for one sample were excluded from our analysis after failing to meet coverage requirements.

  Study phs001743

• Characterization of Prostate Cancer Organoids

  Using models from the LuCaP series as well as those generated at the National Cancer Institute, we have established organoids for in vitro mechanistic testing, including drug screening and genetic manipulation. The major findings from these continuing studies is the durability of organoids for maintaining complex subpopulation and intratumoral heterogeneity and the parallels between in vitro testing and patient outcomes. Existing data from prior releases includes whole-genome sequencing, whole-exome sequencing, single-cell and bulk RNA-seq, single-cell ATAC-seq, and SNP array. New data in this release is ChIP-seq data from three models and RNA-seq data from one model.

  Study phs001587

• Radiation-Related Genomic Profile of Papillary Thyroid Cancer after the Chernobyl Accident

  The April 26, 1986 accident at the Chernobyl nuclear power plant in northern Ukraine resulted in the release of radioactive contaminants, which were deposited in the surrounding areas in Ukraine, Belarus, and Russia. The main radiation-related health effect resulting from these exposures is the increased occurrence of thyroid cancer among individuals who were children at the time of the accident or born shortly thereafter. The purpose of this study was to conduct a comprehensive genomic landscape analysis of papillary thyroid tumors arising in individuals who were exposed as children to radioactive iodine (I-131) from the Chernobyl nuclear power plant accident.

  Study phs001134

• Sensitive urothelial cancer detection via high volume urine DNA analysis

  Cystoscopy and imaging are the gold standard for urothelial cancer (UC) detection and surveillance, but cystoscopy is an uncomfortable procedure associated with adverse effects and a low diagnostic yield as only 10% of hematuria patients have UC. Urine tumor DNA (utDNA) is a non-invasive UC biomarker that has suffered from poor sensitivity for Ta stage tumors (<80%). We hypothesized that high urine volume analysis with a multi-gene panel could overcome these limitations, and developed a 100 mL utDNA laboratory platform (UroScout) that analyzes 25 commonly mutated UC genes and 8 copy number-altered loci for somatic alterations to detect UC.

  Study EGAS50000000630

• Single-Cell Genomic Analysis of Gastrointestinal Cancer

  Our study aimed to define the heterogeneity of gastrointestinal cancers at a single-cell resolution. We subjected single-cell suspensions derived from surgical resections of gastrointestinal cancer tissue, paired normal tissue, peripheral blood mononuclear cells (PBMCs) or their ex vivo cultures to high-throughput microfluidics based single-cell RNA and DNA sequencing. We analyzed the features of the tumor microenvironment including fibroblasts, endothelial cells, macrophages and lymphocytes to determine their contribution to tumor growth and progression. We also characterized the mechanisms of immunosuppression in these tumors. This analysis led to novel insights into the biology of the microenvironment and also enabled the identification of new treatment targets.

  Study phs001818

• plasma DNA LINE-1 targeted bisulfite sequencing: a new non-invasive multi-cancer detection marker

  The detection of circulating tumor DNA, which allows non-invasive tumor molecular profiling and disease follow-up, promises optimal and individualized management of patients with cancer. However, detecting small fractions of tumor DNA released when the tumor burden is reduced remains a challenge. We developed a PCR-based targeted bisulfite method coupled to deep sequencing to detect methylation patterns of L1PA elements,which we named DIAMOND (for Detection of Long Interspersed Nuclear Element Altered Methylation ON plasma DNA). We used sodium bisulfite chemical conversion to achieve base-pair resolution analysis and designed a multiplexed PCR based on 8 amplicons covering L1PAs .

  Study EGAS50000000446

• DNTR sequencing data of paediatric acute lymphoblastic leukemia

  This study used the DNTR-seq method in leukaemia samples to profile the whole-genome and mRNA jointly in single cells. Direct tagmentation is used in a collection of single-cell whole genome sequencing (scWGS) methods, including DNTR-seq, which provide high quality data at ultra-low to low coverage. The overall goal was to characterize the genetic and transcriptional heterogeneity of cancer samples. To infer clonal structure and evolutionary history, copy number analysis based workflows were implemented. Bone marrow mononuclear cells from pediatric acute lymphoblastic leukemia samples were FACS sorted into 384 plates to generate the DNA and RNA profiles.

  Study EGAS50000001247

• scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment.

  We performed scRNAseq analysis of CD8 T cells infiltrating the bladder and tumor of 4 non-muscle-invasive bladder cancer patients, before and after BCG treatment. In order to identify tumor-specific T cells, we selected CD8 T cells that were enriched in the tumor of the patient. We also selected CD8 T cells appearing in the bladder after BCG treatment, with the hypothesis that BCG treatment stimulates tumor-specific CD8 T cells. Next, we cloned the TCR of these T cells in a Jurkat cell line and tested these TCR for recognition of tumor-specific antigens.

  Study EGAS50000001384

• Use_of_Deep_Sequencing_to_Dectect_Clonal_Mutations_In_Sun_Exposed_Skin_Epidermis

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Study EGAS00001000515

• Inter and intra - tumor heterogeneity in Colorectal Cancer

  We used high depth massive parallel sequencing analyses to study 27 CRC (colorectal cancer) patients, with a total of 97 tumors (both primary and matched metastases) in addition to healthy control samples. We found inter-tumor concordance for coding mutations; in contrast, gene copy numbers were found to be highly discordant between primary tumors and metastases as validated by fluorescent in-situ hybridization. in a further step, we dissected a single tumor into 68 spatially defined samples and sequenced them separately. Here we identify evenly distributed coding mutations in APC and TP53 in all tumor areas, yet highly variable gene copy numbers in numerous genes.

  Study EGAS00001002150

• Use_of_Deep_Sequencing_to_Dectect_Clonal_Mutations_In_Sun_Exposed_Skin_Epidermis_PART2

  This study aims to define the landscape of somatic mutations in sun exposed human skin by deep sequencing, analyse their frequency and use the data to infer the effect of mutations on proliferating cell behaviour. The frequency of each mutation will reflect the size of the clone of cells in the tissue sample. By analyzing small samples, clones with as few as 100 cells will be detectable. Allele frequency distributions for each mutation will be used to infer cell fate using published methods (Klein et al. 2010). This study will shed unprecedented light on the early clonal events that lead to the emergence of cancer.

  Study EGAS00001000603

• Combination Therapies for Personalised Cancer Medicine in 11-18

  This study involves mutagenizing 11-18 with ENU to identify those mutations which engender resistance to targeted treatment. In the last decade we have begun to move towards the use of targeted therapeutics in the clinic, often resulting in dramatic response rates in cancer patients. However, clinical experience has demonstrated time and time again that such responses are invariably followed by the development of drug resistance. Identification of the underlying mechanisms may enable us to reverse such resistance. Traditional methods of modelling this resistance in vitro can lead to a plethora of potential resistance mechanisms that can be difficult to decipher.

  Study EGAS00001002579

• Exome array analysis of adverse reactions to fluoropyrimidine-based therapy for gastrointestinal cancer

  Fluoropyrimidines, including 5-fluororacil (5FU) and its pro-drug Capecitabine, are the common treatment for colorectal, breast, neck and head cancers – either as monotherapy or in combination therapy. Adverse reactions (ADRs) to the treatment are common and often result in treatment discontinuation or dose reduction. Factors contributing to ADRs, including genetic variation, are poorly characterized. We performed exome array analysis to identify genetic variants that contribute to adverse reactions.Our final dataset consisted of 504 European ancestry individuals undergoing fluoropyrimidine-based therapy for gastrointestinal cancer. A subset of 254 of these were treated with Capecitabine. All individuals were genotyped on the Illumina HumanExome Array.

  Study EGAS00001002763