9296 results for "cancer rna-seq"

in 64.97 milliseconds.

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Oesophageal adenocarcinoma

  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, the International Agency for Research on Cancer is coordinating the recruitment of 5000 individuals with cancer (colorectal, renal, pancreatic, oesophageal adenocarcinoma or oesophageal squamous cancers) across 5 continents to explore whether different mutational signatures explain marked variation in incidence. In brief, through an international network of collaborators around the world, biological materials are collected, along with demographic, histological, clinical and questionnaire data. Whole genome sequences of tumour-germline DNA pairs are generated at the Wellcome Trust Sanger Institute (40X and 20X depth respectively). Somatic mutational signatures are subsequently extracted by non-negative matrix factorisation methods and correlated with risk factors 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. This dataset contains all the data available for this study on 2021-09-27.

  Dataset EGAD00001006083

• Field_effect_of_healthy_and_diseased_livers

  Recent work in the Campbell group has revealed somatic mutations present in normal, non-cancerous human skin. A subset of the mutations conferred selective advantages to the host cells, leading to clonal expansions and raising the risk for future cancer development. Capturing such somatic mutations in normal tissue is important to advance our understanding about carcinogenesis and could provide prospective medical insights. In this project, our goal is to detect somatic mutations in normal (pre-cancerous) liver tissue. Using Laser Microdissection technology, we will dissect individual liver lobules from patient samples and submit these to sequencing. For each patient sample, we aim to sequence multiple lobules to characterise the mutagenic burden. Samples will be taken from patients with different liver disease aetiologies, including alcoholism and obesity, with a view on distinguishing the prevalent mutation types occurring in each disease context. We will perform targeted sequencing, initially using the WTSI cancer panel. Later we aim to use a novel bait set that captures both cancer genes as well as genes relevant to the non-cancerous samples (ie. genes implicated in hereditary disorders, immune sequences).

  Study EGAS00001002382

• Circulating Tumor DNA Analysis Detects Minimal Residual Disease and Predicts Recurrence in Patients with Stage II Colon Cancer

  Detection of circulating tumor DNA (ctDNA) after resection of stage II colon cancer may identify those at the highest risk of recurrence and help inform adjuvant treatment decisions. We used massively-parallel-sequencing–based assays to evaluate the ability of ctDNA to detect minimal residual disease in 1046 plasma samples from a prospective cohort of 230 patients with resected stage II colon cancer. In patients not treated with adjuvant chemotherapy, ctDNA was detected post-operatively in 14 of 178 (7.9%) patients, 11 (79%) of whom had recurred at a median follow-up of 27 months; recurrence occurred in only 16 (9.8 %) of the 164 patients with negative ctDNA (HR, 18; 95% confidence interval [CI], 7.9 to 36; P<0.001). In patients treated with chemotherapy, the presence of ctDNA following completion of chemotherapy was also associated with an inferior recurrence-free survival (HR, 11; 95% CI, 1.8 to 68; P=0.001). ctDNA detection after stage II colon cancer resection provides direct evidence of residual disease and identifies patients at very high risk of recurrence.

  Study EGAS00001001839

• The Ovarian Cancer Association Consortium OncoArray genome-wide association study

  A custom Illumina genotyping array, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis as described in PMID:27697780.The array was used to genotype ovarian cancer cases and controls from multiple studies participating in the Ovarian Cancer Association Consortium, of which 54,747 passes QC.An initial principal components analysis was carried out using a method described in PMID:27697780 to assign subject to intercontinental ancestry groups: “European”, “African”, “Asian” and "Other". Within ancestry principal components analysis was carried using a set of ~33k unlinked markers. Subsequent analyses were adjusted for the ancestry specific PCs: 9 Eur, 10 Asian, 1 African and 6 Mixed. These PCs are included in the imputed dataset phenotypes file

  Study EGAS00001002305

• Somatic pathogenic variants in the normal mammary gland of sporadic breast cancer patients.

  The mammary gland undergoes hormonally stimulated cycles of proliferation, lactation and involution. We hypothesized that these factors increase the mutational burden in glandular tissue and may explain high cancer incidence rate in the general population and recurrent disease. Hence, we investigated the DNA sequence variants in the normal mammary gland, tumor and peripheral blood from 52 reportedly sporadic breast cancer patients, including breast-conserving surgery cases. Targeted resequencing of 542 cancer associated genes revealed mosaic somatic pathogenic variants of: PIK3CA, TP53, AKT1, MAP3K1, CDH1, RB1, NCOR1, MED12, CBFB, TBX3 and TSHR in the normal mammary gland, at considerable allelic frequencies (9x10-2 to 5.2x10-1) indicating clonal expansion. Further evaluation of the frequently damaged PIK3CA and TP53 genes by ultra-sensitive duplex sequencing demonstrated a diversified picture of multiple low level-mosaic (in 10-2 to 10-4 alleles) hotspot pathogenic variants. Our results raise a question about the oncogenic potential in non-tumor mammary gland tissue of breast-conserving surgery patients.

  Study EGAS00001005698

• Salivary Gland Cancer TSO500 dataset

  Salivary gland cancer (SGC) is a rare cancer for which systemic treatment options are limited. Therefore, it is important to characterize its genetic landscape in search for actionable aberrations. This research aimed to identify these actionable aberrations by NGS-based analysis of DNA (single and multiple nucleotide variants, copy number variants, microsatellite instability and tumor mutational burden) in a large cohort of SGC patients. DNA was extracted from archival tissue of 119 patients with various SGC subtypes and sequenced using a targeted NGS panel encompassing 523 cancer related genes (TruSight Oncology 500, TSO500). The 119 patients included 46 AdCC patients, 43 SDC patients, 15 MEC patients, 9 AciCC patients and 6 patients with other subtypes (1 secretory carcinoma, 1 polymorphic adenocarcinoma (PAC), 1 adenocarcinoma NOS, 1 myoepithelial carcinoma, 1 epithelial/myoepithelial carcinoma and 1 mixed PAC/myoepithelial carcinoma). Median exon coverage ranged from 80-904 (median 308) unique reads and the median percentage of exon coverage with at least 100 unique reads was median 96.6% in these 119 samples.

  Study EGAS00001006232

• Impact of germline pathogenic variants in 27 cancer-predisposing genes on the risk of lymphoma

  The application of advanced molecular technology has significantly expanded lymphoma classification, allowing risk stratification and treatment optimization. Limited evidence suggests the presence of a genetic predisposition in lymphoma, indicating the potential for better individualized clinical management based on a novel lymphoma classification. Herein, we examined the impact of germline pathogenic variants in 27 cancer-predisposing genes with lymphoma risk and explored the clinical characteristics of pathogenic variant carriers. This study included 2,066 lymphoma patients and 38,153 cancer-free controls from the Japanese population. Following quality control of sequencing data, samples from 1,982 lymphoma patients and 37,592 controls were further analyzed. Sequencing data of controls were obtained from JGAD000721. Germline pathogenic variants in some cancer-predisposing genes were associated with a high risk of lymphoma. Furthermore, germline pathogenic variants in these genes were especially associated with the higher risk of a certain subtype. These results would provide novel insights concerning monogenic form into lymphoma classification. Some lymphoma patients may benefit from surveillance and targeted treatment like other neoplasms.

  Study JGAS000347

• A combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancer

  The earlier diagnosis of cancer is one of the keys to reducing future cancer deaths. Here we describe our efforts to develop a non-invasive, blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinoma and 185 control patients without known cancers. KRAS mutations were detected in the plasma of 66 patients (30%) and every mutation found in the plasma was identical to that subsequently found in the patients' primary tumor (100% concordance). The use of KRAS in conjunction with two thresholded protein biomarkers (CA19-9 and prolactin) increased the sensitivity to 67%. Only one of the 185 plasma samples from the control cohort were positive for any of the three markers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

  Study EGAS00001002444

• Genetic and epigenetic variation at regulatory regions contribute to cancer evolution under endocrine treatment

  Comprehensive profiling of hormone-dependent breast cancer (HDBC) has identified hundreds of protein-coding alterations contributing to cancer initiation, but only a handful have been linked to endocrine therapy resistance, potentially contributing to 40% of relapses. If other mechanisms underlie the evolution of HDBC under adjuvant therapy is currently unknown. In this work, we employ integrative functional genomics to dissect the contribution of cis-regulatory elements (CREs) to cancer evolution by focusing on 12 megabases of non-coding DNA, including clonal enhancers, gene promoters, and boundaries of topologically associating domains. Massive parallel perturbation in vitro reveals context-dependent roles for many of these CREs, with a specific impact on dormancy entrance and endocrine therapy resistance9. Profiling of CRE somatic alterations in a unique, longitudinal cohort of patients treated with endocrine therapies identifies non-coding changes involved in therapy resistance. Overall, our data uncover actionable transient transcriptional programs critical for dormant persister cells and unveil new regulatory nodes driving evolutionary trajectories towards disease progression.

  Study EGAS00001006340

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations - WGS data

  We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. Clinically actionable variants were identified in 56% of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants, found in 54% of patients, were of unanticipated timing and type, with over 20% of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006610

• Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care (BASIC3) Clinical Exome Sequencing Study - Clinical Sequencing Exploratory Research Consortium

  The BASIC3 (Baylor College of Medicine Advancing Sequencing in Childhood Cancer Care) study is a National Genome Human Research Institute (NHGRI) and National Cancer Institute-funded Clinical Sequencing Exploratory Research (CSER) consortium project that focuses on prospective implementation of clinical whole exome sequencing in the pediatric oncology clinic. The primary study objective are to integrate information from CLIA-certified germline and tumor exome sequencing into the care of newly diagnosed solid tumor patients at Texas Children's Cancer Center, and to perform parallel evaluation of the impact of tumor and germline exomes on families and physicians. Blood and frozen tumor (if available) samples are collected from children undergoing surgery or biopsy of newly diagnosed solid tumors and subjected to exome sequencing in a CLIA-certified laboratory. Germline and tumor (if applicable) exome sequencing reports are generated and submitted into the electronic health record and returned to each patient/family by their primary oncologist. If specific (optional) consent is obtained, research sequencing studies (including transcriptome sequencing) are performed in addition to the clinical exome sequencing.

  Study phs001026

• Tumor Fraction Guided Cell-Free DNA Profiling in Metastatic Cancer Patients

  Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth. Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. The results show that cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.

  Study phs002290

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Gastric Organoids (2019-08-07)

  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. . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005234

• MutWP4: CRUK Grand Challenge Mutographs of Cancer: Pancreatic Organoids (2021-02-02)

  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. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006933

• Genomic Evolution of Breast Cancer Metastasis and Relapse

  Recurrent breast cancer is almost universally fatal. We characterize 170 patients locally relapsed or distant metastatic cancers using massively parallel sequencing. We identify that the relapse-seeding clone disseminates late from the primary tumor. TP53 and AKT1 appear to be enriched in ER-positive cancers predisposed to relapse. Mutation acquisition continues at relapse as the same mutation signatures continue to operate and new signatures, such as that caused by radiotherapy appear de novo. In 49% of cases we identify drivers mutations private to the relapse and these are sampled from a wider range of cancer genes, including SWI-SNF complex and JAK-STAT signaling.

  Dataset EGAD00001002697

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• Renal_Cancer_Exome_Sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 25 renal cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 50 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000006

• PV_Exome_Study

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 50 Polycythemia Vera Myeloproliferative Disease samples and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 100 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000028

• Osteosarcoma_Exome_Sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 50 osteosarcoma cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 100 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000163

• PMF_Exome_Study

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 50 Primary Myelofibrosis Myeloproliferative Disease samples and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 100 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000175

• ADCC_Exome_Sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from Adenoid cystic carcinomas and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000193

• Triple_Negative_Breast_Cancer_Whole_Genome_Validations

  We propose to definitively characterise the somatic genetics of Triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. This study will use a bespoke bait set to pulldown regions of interest found in whole genome sequencing to validate mutations found.

  Study EGAS00001000426

• CAGEKID: Cancer Genomics of the Kidney - Targeted Sequencing

  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 EGAS00001007004

• TCR β-chain repertoire characterization of regulatory and conventional T cells in breast tumors from breast cancer patients.

  Identification of tumor-specific effects on peripheral TCRβ repertoire formation in humans, investigation of the clonal origin of regulatory T cells in breast cancer patients and impact analysis of the tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral Treg repertoire in humans.

  Study EGAS00001004671

• TCR β-chain repertoire characterization of regulatory and conventional T cells in peripheral blood from breast cancer patients and healthy individuals.

  Identification of tumor-specific effects on peripheral TCRβ repertoire formation in humans, investigation of the clonal origin of regulatory T cells in breast cancer patients and impact analysis of the tumor-specific conversion of conventional T cells into induced regulatory T cells on the peripheral Treg repertoire in humans.

  Study EGAS00001002699

• Whole exome DNA sequence profiling of spatial biopsies of high grade serous epithelial ovarian cancer

  The study aims at dissecting the heterogeneity across multiple biopsies of high grade serous epithelial ovarian cancer (HGS-EOC) through a comprehensive characterization of variants and structural changes at the whole exome level. To this aim, the study uses samples from multiple bioptic sites taken from eight HGS-EOC patients.

  Study EGAS00001003048

• Identification of genetic mutations characteristic for recurrence and metastasis of colon and rectal cancer.

  We collected the cancerous tissues of the primary and recurrence tumors from the same patient with recurrent / metastatic colorectal cancer, and the purpose of this study is to find the characteristics of recurrent / metastatic colorectal cancers by carrying out a "molecular profiling", mainly the exome sequence analysis of these tissues.

  Study JGAS000091

• Integrative_Oncogenomics_of_Multiple_Myeloma

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from Multiple Myeloma patient DNA and matched normal DNA from the same patients. Two lanes of Illumina GA sequencing will be performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000036

• Oesophageal_Adenocarcinoma_Organoid_Hi_C

  Hi-C Sequencing of 6 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This Hi-C data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003122

• The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples

  A surrogate marker based on the epigenome that captures these components in easily accessible epithelial tissue could potentially identify women at risk. The WID-BC-index identifies women with breast cancer based on a DNA methylation signature derived from cervical smear samples.

  Study EGAS00001005055

• Whole exome sequencing from early stage non-small cell lung cancer patients at MDACC

  The purpose of the study is to evaluate the mutational landscape and tumor mutational burden in tumor from patients with early stage non-small cell lung cancer. Mutational landscape was compared to the T cell repertoire to determine the relationship between somatic mutations and T cell response in early-stage NSCLC.

  Study EGAS00001004026

• Modelling Multi-Dimensional ClinOmics for Precision Therapy of Children and Adolescent Young Adults with Relapsed and Refractory Cancer: A report from the Center for Cancer Research.

  The Center for Cancer Research (CCR), of the intramural NCI undertook a multidimensional clinical genomics study of children and adolescent young adults with relapsed and refractory cancers who were enrolled on other therapeutic trials to determine the feasibility of a genome guided precision therapy protocol in these patients.

  Study phs001052

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  This study evaluates integrated genomic models of response to immune checkpoint blockade for lung cancer patients. A computationally adjusted tumor mutation burden was combined with HLA class I genetic variation, mutational smoking signature and activating mutations in receptor tyrosine kinase genes to generate a prognostic classifier that outperforms tumor mutation burden.

  Study phs001940

• Hangzhou Cancer study

  Dac EGAC00001000765

• Colorectal cancer samples

  Dac EGAC00001002808

• Leeds Cancer Genomics

  Dac EGAC00001003010

• LITS

  Difference in gene expression values between case and control, log2 values. Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC) Post-genome Cohort taken up to eight years before brest cancer diagnosis. Illumina HumanWG-6 version 3 or Illumina HumanHT-12 expression bead chip, combined on identical nucleotide universal identifiers.

  Dataset EGAD00010001400

• Somatic mutation analysis based on Whole exome Sequencing (WES) of multiple tumor biopsies, patient-derived spheroids and leukocyte DNA from colorectal cancer patients (vcf files)

  Somatic mutations were called using whole exome Sequencing (WES) data from colorectal cancer samples (dataset EGAD00001003821) using MuTect2, with matched constitutional WES-data obtained from leukocytes samples as reference.

  Dataset EGAD00001003823

• 2014 sequenced WGS-Lung Cancer sample 30 pair

  This data is belong to WGS-Lung Cancer patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 30 paired tumor/normal samples from Samsung Hospital. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001003978

• 2014 sequenced Korean WES-Lung Cancer sample 36 pair

  This data is belong to WES-Lung Cancer patients' genome data which is aligned to human reference(human_g1k_v37.fasta). There are 36 paired tumor/normal samples from Samsung Hospital. All samples has passed QC and recalibration steps while aligning to reference.

  Dataset EGAD00001004027

• The dataset of breast cancer patients and benign breast tumor patients

  The dataset contains 438 plasma samples and 418 tissues samples from 102 breast cancer patients and 30 benign breast tumor patients. There are two kinds of file types: bam and fastq. Amplicon sequencing and Capture sequencing were used in our experiment.

  Dataset EGAD00001004175

• Evolution of neoantigen landscape during immune checkpoint blockade in non-small cell lung cancer

  The dataset for Evolution of neoantigen landscape during immune checkpoint blockade in non-small cell lung cancer includes 17 bam files from next-generation sequencing on the Illumina HiSeq2500. The biospecimens analyzed include matched tumor pre-treatment, post-progression and normal samples.

  Dataset EGAD00001004336

• Longitudinal breast cancer cohort in SMC

  Whole transcriptome sequencing (WTS) of a longitudinal breast cancer (BC) cohort consisting of 146 cases (281 tumors, 109 pairs), including 52 (38%) that achieved pathologic complete responses (pCR) and 85 (62%) that harbored residual diseases at time of surgery.

  Dataset EGAD00001004487

• Breast Cancer -Very young women with ER+ tumor

  Corresponding data set is composed of whole exome sequencing of Korean ER positive breast cancer under 35. This set provides 100 alignment files from normal-tumor paired whole exome sequencing of 50 patients. This is a part of total project data set.

  Dataset EGAD00001002256

• Combination Therapies for Personalised Cancer Medicine in drug resistant EGFR mutant lung cancer (2019-06-10)

  This study involves mutagenizing a range of different cell lines with ENU to identify those mutations which engender resistance to targeted treatment. . This dataset contains all the data available for this study on 2019-06-10.

  Dataset EGAD00001005080

• Colorectal cancer GWAS on the Spanish population

  Data on Affymetrix 6.0 arrays for Genome-Wide Association Study of colorectal cancer in the Spanish population. Additionally, geographical origin for each sample is provided, which constitutes the largest to-date Spanish genomic sample population

  Dataset EGAD00010001715

• Whole-genome sequencing data for inflammatory breast cancer patients

  This study reports the whole-genome sequencing data for 20 inflammatory breast cancer patients, each of whom has one normal blood sample and one breast tumor sample. Overall, there are 40 files included in this study, in the format of BAM.

  Dataset EGAD00001005749

• whole exome sequencing (WES) data of the HIPO head and neck cancer (HNC, n=83)

  Paired whole exome sequencing data of the HIPO head and neck cancer (HNC) (n=83), using Agilent SureSelect V4+UTRs and V6+UTRs with the sequencing platforms HiSeq2000 and HiSeq2500. The reads were aligned to hg19. This is part of project H019.

  Dataset EGAD00001006336

• MicroRNA profiling by next-generation sequencing for colorectal cancer screening

  The dataset contains raw miRNA sequencing data of plasma samples from 20 newly diagnosed colorectal cancer cases and 20 controls free of colorectal neoplasms matched by age and sex. It includes files in the FASTQ compressed (.gz) format.

  Dataset EGAD00001006966