12216 results for "cancer rna-seq"

in 34.90 milliseconds.

• Transcriptomic sequencing of early and late passage of mCRC tumoroids

  Dataset of 46 mCRC tumoroids from different passages (23 early-passage 3, 23 late-passage 8-12). FASTQ files of paired sequencing of PolyA-enriched total RNA

  Dataset EGAD50000000153

• Sequencing data for oesophageal and related samples - BOs release 3 (RNA)

  Dataset EGAD00001003901

• Hospital for Sick Children 2020 Pediatric Low-Grade Glioma RNA and Targeted DNA Sequencing

  Whole transcriptome and targeted dna sequencing (Ampliseq) of pediatric low-grade glioma samples at the Hospital for Sick Children

  Dataset EGAD00001005987

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas

  This dataset contains BAM files for RNA-sequencing of stage I lung adenocarcinomas from Asian patients. In total, there are 107 patients and 107 tumor samples.

  Dataset EGAD00001006187

• anti-SARS-CoV-2 IgG and Fostamatinib treated human primary IL10-M2 macrophages

  RNA sequencing data of anti-SARS-CoV-2 spike IgG (monoclonal or patient serum), poly(I:C) and Fostamatinib treated human primary IL10-M2 macrophages

  Dataset EGAD00001007512

• single cell RNAseq data of lung adenocarcinoma

  Single-cell RNA sequencing was performed for cells from five early-stage LUADs and fourteen multi-region normal lung tissues of defined spatial proximities from the tumors.

  Dataset EGAD00001006936

• NCI Expanded Genome-Wide Association Study of Renal Cell Carcinoma

  The National Cancer Institute (NCI) expanded genome-wide association study (GWAS) of renal cell carcinoma (RCC) was a 2nd GWAS of this cancer performed by NCI to further investigate common genetic variants associated with RCC risk. The GWAS includes 2,781 cases and 2,940 controls of European background from 13 studies conducted in the US and Finland (10 cohorts, 2 case series, 1 hospital biorepository), scanned using the Illumina OmniExpress and Omni2.5 SNP arrays. SNP-level results from this GWAS were combined by meta-analysis with results from the earlier NCI RCC GWAS (phs000351.v1.p1; 1,311 cases and 3,424 controls) and others conducted by the International Agency for Research on Cancer (scan 1: 2,438 cases and 5,071 controls; scan 2: 2,781 cases and 2,940 controls), The University of Texas MD Anderson Cancer Center (893 cases and 556 controls) and the Institute for Cancer Research, UK (944 cases and 4,024 controls). Only data from the second NCI scan are included in this dbGaP submission. Data from 239 cases and 229 controls from this scan will be deposited in dbGaP separately under the Women's Health Initiative (phs000200).

  Study phs001736

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__organoid_control_WGS

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

  Study EGAS00001005449

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Pancreatic_Organoids

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

  Study EGAS00001003520

• PDAC organoid genomic heterogeneity

  The establishment of patient-derived pancreatic cancer organoid culture in recent years creates an exciting opportunity for researchers to perform a wide range of in vitro studies on a model that closely recapitulates the tumor. Among the outstanding questions in pancreatic cancer biology are the causes and consequences of genomic heterogeneity observed in the disease. However, to use pancreatic cancer organoids as a model to study genomic variations, we need to first understand the degree of genomic heterogeneity and its stability within organoids. Here, we used single-cell whole-genome sequencing to investigate the genomic heterogeneity of two independent pancreatic cancer organoids, as well as their genomic stability with extended culture. Clonal populations with similar copy number profiles were observed within the organoids, and the proportion of these clones was shifted with extended culture, suggesting the growth advantage of some clones. However, sub-clonal genomic heterogeneity was also observed within each clonal population, indicating the genomic instability of the pancreatic cancer cells themselves. Furthermore, our transcriptomic analysis also revealed a positive correlation between copy number alterations and gene expression regulation, suggesting the “gene dosage” effect of these copy number alterations that translates to gene expression regulation.

  Study EGAS00001006782

• Research on the identification of cancer stem cells for peidatric and adult malignancies.

  In recent years, "cancer stem cells" have been reported to exist in many cancers. Many reports have shown that they are the main cause of cancer recurrence. The aim of this study is to test whether cancer stem cells can be identified using patient samples. We will perform omics analysis of rare pediatric cancers by integrating genomics, transcriptomics, proteomics and metabolomics, including somatic and germline mutations, to deepen our understanding of the biological characteristics of the target disease. Based on the knowledge gained and clinical information from patients, we will conduct preclinical pharmacological studies using mouse models and in vitro models to investigate the therapeutic effects of novel therapeutic agents and novel therapeutic strategies such as cellular therapies.

  Study JGAS000623

• Pilot data of PDiamond Lung Cancer Data

  RNAseq pilot data of PDiamond Korean lung cancer data

  Dataset EGAD50000000843

• Esophageal cancer

  Genome-wide NanoRCS of cfDNA from plasma of Esophageal cancer patients

  Dataset EGAD50000000221

• SNParray copy number dataset

  4 oesophageal cancer derived organoid lines and 2 ovarian cancer derived organoid lines

  Dataset EGAD00010002002

• Whole genome sequencing of 64 HER2-Positive Breast Cancer

  Whole genome sequencing of 64 HER2-Positive Breast Cancer

  Dataset EGAD00001001844

• Deep sequencing of 151 cancer genes

  Deep sequencing of 151 cancer genes in 6 synchronous CRC of 3 patients

  Dataset EGAD00001001870

• Exceptional Outcomes in a Phase Ib Study Combining PARP and MEK Inhibition, With or Without Anti-PD-L1, for BRCA-Wildtype Platinum-Sensitive Recurrent Ovarian Cancer

  To evaluate regimens combining PARP and MEK inhibition, with or without PD-L1 inhibition, for BRCA-wildtype platinum-sensitive recurrent ovarian cancer (PSROC).

  Study EGAS00001007496

• Primary ER-positive Breast Cancer Treated with Neoadjuvant Letrozole

  These are tumor biopsies and corresponding normal samples from patients with early stage ER+/HER2- breast cancer who had received the aromatase inhibitor letrozole for 10-21 days prior to surgery.

  Study phs000857

• Molecular Classification of Hormone Sensitive and Castration Resistant prostate cancer, using non-negative matrix factorization molecular subtyping

  We aim to identify molecular subtypes of prostate cancer using consensus non-negative matrix factorization and correlate these with existing biomarkers to inform future immunotherapeutic strategies.

  Study EGAS00001006204

• Integrative modeling of tumor genomes and epigenomes for enhanced cancer diagnosis by cell-free DNA.

  3784 whole genome sequencing bam files were generated from plasma cell-free DNA of healthy individuals and patients with cancer. Paired reads were mapped to hg19 human reference genome.

  Study EGAS00001006553

• Integrated whole-genome and transcriptome sequencing reveals divergent evolutionary processes across biliary tract cancer subtypes (WTS data from biliary tract cancer molecular subtype study)

  WTS data for biliary tract cancer samples (Consensus molecular subtypes define distinct evolutionary trajectories of biliary tract cancers). The dataset includes tumour bam files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=85 tumours)

  Dataset EGAD50000002529

• The dataset for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  The dataset for “Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers” includes 409 cram files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD50000000695

• The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer

  The dataset for Genome-wide cell-free DNA fragmentation in patients with cancer includes 538 bam files from whole genome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include plasma samples from healthy individuals and patients with cancer.

  Dataset EGAD00001005339

• Low-coverage whole-genome sequencing of cancer and healthy plasma circulating DNA

  Plasma samples from patients with melanoma (stage II/III/IV) and breast cancer (stage IV) as well as healthy individuals were subjected to low-coverage whole-genome sequencing (less than 10x average depth). This dataset contains raw fastq files from 39 breast cancer, 127 melanoma and 42 healthy control plasma samples.

  Dataset EGAD00001011817

• RRBS data from TRACERx non-small cell lung cancer (NSCLC) tumours and matched normal adjacent tissue.

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC).

  Dataset EGAD00001015534

• Exploration of CNV’s and SNV’s in cancers with well-known genetic rearrangements: Identification of additional genetic changes in rearrangements-driven cancer

  Specific cancers are well known to have specific gene rearrangements. Representative cancer is chronic myeloid leukemia (CML) which is famous for BCR/ABL gene rearrangements. By the way, also genetic rearrangements are not infrequently found in acute leukemia, and those include CBFB/MYH11 rearrangements, PML/RARA rearrangements, AML/ETO rearrangements, and BCR/ABL rearrangements. The situation is same is for lung adenocarcinoma of non-smokers and prostate cancers, and ALK and RET gene rearrangements are recently found. However, not all these rearrangements are sufficient to develop cancer, and it is suggested that some genetic aberrations are required for the development and progression of cancer in addition to these genetic rearrangements. In this study, we have a plan to explore the existence of additional genetic changes including single nucleotide variants (SNV’s) and copy number variations (CNV’s) in cancers with specific genetic rearrangements so as to define additional genetic changes that confer full oncogenic potential to cancer cells. So as to look at SNV’s and small indels, we are going to use whole exome sequencing (WES) data. And as for CNV’s, we are going to use array-CGH data. Also, to check the functionality of these genetic changes, we are going to use whole transcriptome data (WTS). In addition, in samples with whole genome sequencing (WGS ) data, we are going to explore genetic changes in intronic regions also. In fact, we sequenced 10 AML samples which are known to have specific genetic rearrangements. Analysis of these WGS, WES and WTS data are under the way. If we have a chance to access WES, array-CGH and WTS data of other cancer samples with specific genetic rearrangements, we would be able to compare additional genetic changes required for oncogenesis in cancer cells with various genetic rearrangements. We hope this result will enlighten our understanding of cancer genetics further.

  Study EGAS00001000673

• WGS, DuplexSeq and NanoSeq genomic data from histologically normal tissue in cancer patients

  The extent to which mutagenic and non-mutagenic processes, including cancer treatment, contribute to somatic evolution in histologically normal tissue remains unclear. We subjected 168 cancer-free normal samples representing 16 different organs from 22 patients with metastatic cancer enrolled in the PEACE research autopsy study to high-depth duplex panel sequencing (coverage >20,000x). In every sample we identified somatic mutations (range 170 - 2,978) at exceedingly low variant allele frequencies (median VAF 0.0000323), consistent with a patchwork of mutated cells in normal tissue. By analysing the mutational spectra of each sample, we extracted 16 distinct single base substitution mutational signatures, reflecting somatic mutational processes that have moulded the genomes of normal cells. Signatures were found to be associated with diverse aetiologies, including alcohol-related mutation acquisition in liver tissue, smoking-induced mutagenesis in lung and cardiac tissue, and multiple distinct treatment-induced processes, which correlated with treatment and its duration. On average, in this cohort in which patients had each received several lines of anti-cancer therapy, exogenous sources, including treatment-related mutagenesis, underpinned >40% of mutations in liver samples, yet <10% in brain samples. Finally, we observed clear differences in the extent and effects of selection in different tissues, with positive selection in certain tissues, including lung (TP53, EGFR and PIK3CA), liver (NF2L2) and spleen (BRAF, NOTCH2), and limited selection in others, such as brain and cardiac. Over 25% of driver mutations in normal tissue exposed to systemic anti-cancer therapy, including mutations in TP53, could be attributed to treatment-induced mutagenesis. Immunotherapy, while not associated with mutagenesis, was linked to an excess of driver mutations in PPM1D and TP53, illustrating how non-mutagenic treatment can sculpt somatic evolution. Our study reveals the rich tapestry of mutational processes and driver mutations in cancer-free normal tissue, and the profound impact of cancer therapeutic and life-time environmental exposures on normal tissue somatic evolution.

  Study EGAS00001008326

• CALGB 80303:Genome-Wide Association Study of Advanced Pancreatic Cancer Patients - A Randomized Phase III trial of Gemcitabine Plus Bevacizumab versus Gemcitabine Plus Placebo in Patients with Advanced Pancreatic Cancer

  CALGB 80303 was a randomized, phase III study in advanced pancreatic cancer patients treated with Gemcitabine plus either Bevacizumab or placebo. No difference in overall survival (OS) was observed between the two arms. We prospectively collected germline DNA and conducted a genome-wide association study (GWAS).

  Study phs000250

• Genomic evolution of pancreatic cancer at single-cell resolution

  This project assesses genomic evolution of pancreatic cancer using the Mission Bio Tapestri platform and Whole Exome Sequencing. The Mission Bio Tapestri platform is a single-cell DNA sequencing platform using a targeted gene panel to assess SNV/CNV. Several samples, including primary and metastatic tissue, were used to investigate changes at single-cell resolution.

  Study EGAS50000001351

• CAGEKID: Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Study EGAS00001000083

• Comprehensive NGS Profiling to Enable Detection of ALK Gene Rearrangements and MET Amplifications in Non-Small Cell Lung Cancer

  We evaluate the analytical performance of the PGDx™ elio™ tissue complete assay, a 505 gene next-generation sequencing (NGS) tissue-based assay, that has now been FDA-cleared for use by physicians to help guide treatment decisions for cancer patients, using a NSCLC cohort of 38 patients.

  Study EGAS50000000010

• Identification of drug resistance genes in cancer cell lines by insertional mutagenesis

  Our aim is to identify genes involved in resistance to anti-cancer therapies. In order to do this we have taken advantage of a lentiviral vector (LV)-based insertional mutagen to mutagenize cancer cell lines. LV-transduced cell lines were then treated with anti-cancer therapies and the emergence of resistant clones scored. DNA from pools of resistant clones was collected, subjected to custom capture by baits designed against the LV sequence, and then sequenced to identify the LV-genomic junction. We hope that the identification of recurrently targeted genes in resistant cell population will allow us to identify genes that mediate drug resistance.

  Dataset EGAD00001002207

• AVENIO Expanded ctDNA panel sequence alignments (BAMs) from plasma DNA of BC, CRC and NSCLC patients

  The AVENIO ctDNA Expanded Kit is a next-generation sequencing (NGS) liquid biopsy assay with a 77 gene panel (192 kb) containing genes in U.S. National Comprehensive Cancer Network (NCCN) Guidelines and emerging cancer biomarkers. This pan-cancer assay was applied to 48 plasma samples from patients with breast, colorectal and non-small cell lung cancer. After sequencing 150bp paired-end, reads were aligned to the hg38 genome with the AVENIO Oncology Analysis Software (version 2.0). These files are the deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Dataset EGAD00001006301

• Whole Exome Sequencing of DNA from Pre-and Post-Chemotherapy Needle Biopsies of Triple Negative and Inflammatory Breast Cancers Enrolled in the S0800 Trial

  Purpose: The purpose of this study was to assess the somatic mutation landscape of breast tumors before and after neoadjuvant chemotherapy. The data includes whole exome sequencing of pre- and post- tissues that were collected in the context of an already published clinical trial SWOG S0800 (ZA Nahleh et al. Breast Cancer Research and Treatment. 158:485-495, 2016). The trial compared the efficacy of sequential nab-paclitaxel followed or preceded by doxorubicin/cyclophosphamide anthracycline chemotherapy with or without bevacizumab as preoperative therapy for stage II-III breast cancer. Experimental Design: 29 pre-treatment biopsies and 9 matching post-treatment surgically resected cancer tissues were available for analysis and were subjected to whole exome sequencing to identify mutational patterns associated with response to neoadjuvant chemotherapy. The 9 paired samples with residual invasive cancer after therapy were also analyzed to assess changes in mutational patterns in response to therapy. No matching normal tissues were available for germline sequencing and therefore we used n=7 post-treatment breast tissues without residual cancer (i.e. complete eradication of cancer by therapy) as a normal cohort to facilitate somatic variant calling.Conclusion: These results suggest that genomic disturbances in BRCA-related DNA repair mechanisms, reflected by a dominant mutational signature 3, confer increased chemotherapy sensitivity. Cancers that survive neoadjuvant chemotherapy, frequently have alterations in cell cycle regulating genes but different genes are affected in different patients.

  Study phs001883

• Circulating Tumor Cell Heterogeneity in Neuroendocrine Prostate Cancer by Single Cell Copy Number Analysis

  Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may arise de novo or develop from pre-existing prostate adenocarcinoma as a mechanism of treatment resistance. Combined loss of tumor suppressors RB1, TP53, PTEN are frequent in NEPC but also present in a subset of prostate adenocarcinomas. Most clinical and preclinical studies support a trans-differentiation process, whereby NEPC arises clonally from a prostate adenocarcinoma precursor during the course of treatment resistance. Here we highlight a case of NEPC with significant intra-patient heterogeneity observed across metastases. We further demonstrate how single-cell genomic analysis of circulating tumor cells combined with phenotypic evaluation of cellular diversity can be considered as a window into tumor heterogeneity in patients with advanced prostate cancer. We performed whole genome sequencing of circulating tumor cells (CTCs) from patients with castration resistant adenocarcinoma (n=4) and neuroendocrine prostate cancer (n=8). CTCs were collected via Epic Sciences platform and single CTC genomic data (n=215) generated via Illumina NextSeq500. 

  Study phs002462

• Genomic Alterations in Normal Breast Tissues Preceding Breast Cancer Diagnosis (GANPBC)

  This study was designed to examine the genomic alterations in histologically normal breast tissues of women who subsequently developed breast cancer and compare it to breast tissues from women who did not. Breast core needle biopsy tissues from 160 healthy women at the Susan G. Komen Tissue Bank were requested for this study and sequenced using whole exome sequencing. The samples included tissues from 79 participants who, during the annual follow-up with Susan G. Komen self-reported a subsequent diagnosis of invasive or non-invasive breast cancer after tissue submission; these cases were classified as pre-diagnosis normal tissues. The remaining 81 samples were from women who had no cancer diagnosis at their last follow-up and were classified as healthy control samples. Among the pre-diagnosis samples, the average time from tissue donation to breast cancer diagnosis was 4.7 years (range: 0-11). For the healthy controls, the average time from tissue donation to the last follow up was 6.1 years (range: 0-14).

  Study phs003822

• Identification and Characterization of Cancer Mutations in Japanese LungAdenocarcinoma without Sequencing of Normal Tissue Counterparts

  We analyzed whole-exome sequencing data from 97 Japanese lung adenocarcinomapatients and identified several putative cancer-related genes and pathways. Particularly, we observed that cancer-related mutation patterns were significantly different between different ethnic groups. As previously reported, mutations in the EGFR gene were characteristic to Japanese, while those in the KRAS gene were more frequent in Caucasians. Furthermore, during the course of this analysis, we found that cancer-specific somatic mutations can be detected without sequencing normal tissue counterparts. 64% of the germline variants could be excluded using a total of 217 external Japanese exome datasets. We also show that a similar approach may beused for other three ethnic groups, although the discriminative power depends on the ethnic group. We demonstrate that the ATM gene and the PAPPA2 gene could be identified as cancer prognosis related genes. By bypassing the sequencing of normaltissue counterparts, this approach provides a useful means of not only reducing the time and cost of sequencing but also analyzing archive samples, for which normal tissue counterparts are not available.

  Study JGAS000001

• Whole Genome Sequencing of Gingivo-buccal Cancer: ICGC-India Project_YR03

  As a part of the ICGC, India has undertaken genomic studies on gingivobuccal cancer of the oral cavity, which is the most prevalent form of cancer among men in India. There are various known environmental (life-style) correlates of this cancer, the most important of which are tobacco chewing and HPV infection. Whole genome sequencing of paired DNA samples – isolated from the tumor tissue and from the blood of twenty five patients – have been performed to catalog germline and somatic mutations. Association between each observed genomic alteration and exposure to environmental risk factors is being explored. Detailed clinical characterization of the patients, collection of data on demographic and environmental exposures, and isolation of DNA samples from blood and tumor tissues collected from each patient are being done at the Advanced Centre for Research, Treatment and Education on Cancer, Mumbai. Whole genome sequencing is being performed at the National Institute of Biomedical Genomics, Kalyani. We have completed whole genome sequencing of paired blood and tumor DNA samples using Illumina HiSeq-2000 and 2500.

  Study EGAS00001001901

• CPC-GENE Prostate Cancer Heterogeneity Study

  Herein we describe a molecular portrait of potentially curable, Gleason 7 and intermediate risk prostate cancer based on genome-wide CNV profiles of 96 patients, and subsequent whole-genome sequencing of 28 tumours from 10 patients, using DNA quantities that are achievable in diagnostic biopsies (50 ng). We show that Gleason 7 cancer is highly heterogeneous at the SNV, CNV, and intra-chromosomal translocation levels, and is characterized by a very low number of recurrent SNVs but significant structural variation. We identified a novel recurrent MYCL1 amplification, which was strongly associated with TP53 deletion and prognostic for biochemical recurrence in this cohort. Moreover, we identified clear evidence of divergent tumour evolution in multi focal cancer and, in 2/5 cases evaluated, multiple tumours of independent clonal origin. Taken together, these data represent the first systematic evaluation of the differential genomics of potentially curable prostate cancer, and strongly suggest that a more robust understanding of the relationship between genetic heterogeneity and clinical outcomes is required to effectively develop biomarkers of prognosis based on tumour genomics.

  Study EGAS00001000549

• Mitochondrial-Nuclear Mutational Cross-Talk Drives Recurrence of Localized Prostate Cancer

  Prostate cancer remains the most prevalent non-skin cancer in men, but has a remarkably quiet mutational profile. Exome sequencing studies have revealed few recurrent somatic single nucleotide variants (SNVs). Whole-genome sequencing studies have not yet identified highly recurrent driver non-coding SNVs (ncSNVs) or genomic rearrangements (Grs). As a result, the underlying events that drive this frequent disease remain unknown. While mitochondrial mutations have been linked to several tumour types, including prostate cancer, their global frequency and impact has remained unknown. To determine if mitochondrial mutations might drive some prostate cancers, we analyzed the mitochondrial genomes of 216 tumours from patients with the most commonly diagnosed form of prostate cancer. We developed a pipeline that conservatively identified only mitochondrial SNVs (mitoSNVs) that differed in the heteroplasmy fraction as compared to their paired-normal by at least 20%. We identified several features of the mitochondrial genome that were correlated with nuclear genomic mutations, as well as features that were significantly associated with biochemical recurrence.

  Study EGAS00001001782

• Mapping the breast cancer metastatic cascade onto circulating tumour DNA using genetic and epigenetic clonal tracking

  Circulating tumour DNA (ctDNA) allows tracking the evolution of human cancers at high resolution, overcoming many limitations of tissue biopsies. However, exploiting ctDNA to determine how a patient’s cancer is evolving in order to aid clinical decisions remains difficult. This is because ctDNA is a mix of fragmented alleles, and the contribution of different cancer cell subpopulations from distinct lesions to ctDNA remains largely unknown. Profiling of ctDNA almost invariably requires prior knowledge of what genomic alterations to track. Here we leverage on a rapid autopsy programme to demonstrate that unbiased genomic characterisation of several metastatic sites and concomitant ctDNA profiling at whole-genome resolution reveals the extent to which ctDNA is representative of widespread disease. We also present a ctDNA methylation profiling method that allows tracking evolutionary changes in the cancer cell population at single-molecule resolution without prior knowledge. These results have critical implications for the use of liquid biopsies to monitor cancer evolution in humans and potentially guide treatment.

  Study EGAS00001004014

• Yale Policy for head and neck cancer and HPV clinical trials

  Yale Policy for human controlled access data associated with head and neck cancer and HPV clinical trials

  Dac EGAC50000000403

• Whole_Genome_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008280

• Bulk_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008282

• Single_cell_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008281

• Single_cell_ATAC_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008283

• Bulk_RNA_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008278

• Identification_and_functional_validation_of_driver_mutations_in_colorectal_cancer

  Targeted exome sequencing of human colorectal cancers for the identification of novel cancer drivers.

  Study EGAS00001000044

• Single_cell_ATAC_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008279

• Methylation profiles in blood (breast cancer cases)

  Raw methylation data from blood samples in breast cancer cases.

  Dataset EGAD00010002470