5625 results for "canc*"

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• Whole exome sequencing of patients with esophageal squamous cell carcinoma receiving chemoradiotherapy

  We performed multi-region whole exome sequencing (WES) of pre-treatment and recurrent esophageal cancer receiving chemoradiotherapy in order to characterize clonal evolution of treatment resistant clones. Furthermore, additional solitary pre-treatment tumor samples were subjected to WES to detect biomarkers predicting clinical outcome.

  Study JGAS000227

• PanCancer genome analysis in 5143 Japanese cancer patients

  This study aimed to establish the Japanese Cancer Genome Atlas (JCGA) using data from fresh frozen tumor tissues obtained from 5143 Japanese cancer patients, including those with colorectal cancer (31.6%), lung cancer (16.5%), gastric cancer (10.8%) and other cancers (41.1%). The results are part of a single-center study called ���High-tech Omics-based Patient Evaluation��� or ���Project HOPE��� conducted at the Shizuoka Cancer Center, Japan. All DNA samples and most RNA samples were analyzed using whole-exome sequencing, cancer gene panel sequencing, fusion gene panel sequencing and microarray gene expression profiling.

  Study JGAS000274

• Whole-exome sequencing of Helicobacter pylori-uninfected normal gastric gland

  Recent studies showed that somatic mutations accumulate in normal tissues with age; however, mutation accumulation in the Helicobacter pylori-uninfected normal gastric mucosa has not been reported. A total of 18 biopsied gastric mucosa were obtained from nine subjects without Helicobacter pylori-infection or gastric cancer. Gastric epithelia were manually dissociated from the lamina propria. Subsequently, single glands were picked up under a stereomicroscope. Genomic DNA isolated from each gland was subjected to whole-exome sequencing.

  Study JGAS000313

• Exome-wide mutation analysis of cell-free DNA to simultaneously monitor the full spectrum of cancer treatment outcomes

  Purpose: Cell-free DNA (cfDNA) offers a non-invasive approach to monitor cancer. Here we develop a method using whole-exome sequencing (WES) of cfDNA for simultaneously monitoring the full spectrum of cancer treatment outcomes, including MRD, recurrence, evolution, and second primary cancers. Experimental Design: Three simulation datasets were generated from 26 cancer patients to benchmark the detection performance of MRD/recurrence and second primary cancers. For further validation, cfDNA samples (n=76) from cancer patients (n=35) with six different cancer types were used for performance validation during various treatments.Results: We present a cfDNA-based cancer monitoring method, named cfTrack. Taking advantage of the broad genome coverage of WES data, cfTrack can sensitively detect MRD and cancer recurrence by integrating signals across known clonal tumor mutations of a patient. In addition, cfTrack detects tumor evolution and second primary cancers by de novo identifying emerging tumor mutations. A series of machine learning and statistical denoising techniques are applied to enhance the detection power. On the simulation data, cfTrack achieved an average AUC of 99% on the validation dataset and 100% on the independent dataset in detecting recurrence in samples with tumor fraction ≥0.05%. In addition, cfTrack yielded an average AUC of 88% in detecting second primary cancers in samples with tumor fraction ≥0.2%. On real data, cfTrack accurately monitors tumor evolution during treatment, which cannot be accomplished by previous methods.Conclusion: Our results demonstrated that cfTrack can sensitively and specifically monitor the full spectrum of cancer treatment outcomes using exome-wide mutation analysis of cfDNA.

  Study EGAS00001005906

• cfMeDIP data for 30 CPC-GENE samples

  We analyzed the cell free DNA methylomes using 30 plasma samples from patients with localized prostate cancer in the CPC-GENE project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001007972

• cfMeDIP data for 67 VPC samples

  We analyzed the cell free DNA methylomes using 67 plasma samples from patients with mCRPC prostate cancer in the VPC project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008711

• cfMeDIP data for 22 WCDT samples

  We analyzed the cell free DNA methylomes using 22 plasma samples from patients with mCRPC prostate cancer in the WCDT project. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology.

  Dataset EGAD00001008713

• cfMeDIP data for 72 VPC samples for validation

  We analyzed the cell free DNA methylomes using 72 plasma samples from patients with mCRPC prostate cancer in the VPC project for validation. Methylation was profiled using the methylated DNA immunoprecipitation coupled to next generation sequencing (MeDIP) technology. Files from multiple lanes exists per sample.

  Dataset EGAD00001008737

• Molecular Characterization for Nasopharyngeal Carcinoma (NPC)

  Total RNA was isolated from 50 formalin-fixed paraffin-embedded nasopharyngeal cancer (NPC) specimens using the RecoverAll Total Nucleic Acid Isolation kit (Ambion). Tumor RNA libraries were prepared with 200ng RNA using the Illumina TruSeq Stranded Total RNA kit with Ribo-Zero Gold, and sequenced with >80 million 100 bp paired-end reads.

  Dataset EGAD00001009047

• Unraveling mutagenic processes influencing the tumor mutational patterns of individuals with Constitutional Mismatch Repair Deficiency

  Constitutional mismatch repair deficiency (CMMRD), caused by bi-allelic germline variants in one of the mismatch repair (MMR) genes, is a childhood cancer predisposition syndrome that often results in the development of multiple tumors early in life. A better understanding of mutational processes driving subsequent CMMRD tumors could advance optimal treatment. Therefore, we performed a genomic characterization of 41 tumors from 17 individuals with CMMRD. Mutational patterns in these tumors were found to be influenced by multiple factors, including the affected MMR genes, tumor types and somatic polymerase proofreading mutations. Temozolomide treatment left prominent mutational signatures in two second primary hematologic malignancies. Furthermore, a novel indel signature was found in 54% of the tumors, characterized by one base pair cytosine insertions in cytosine homopolymers. In conclusion, the analysis of sequential tumors in individuals with CMMRD reveals diverse mutational patterns influenced by the underlying mutated MMR gene, tumor type and treatment history.

  Study EGAS00001007660

• Multi-focal genomic dissection of synchronous primary and metastatic tissue from de novo metastatic prostate cancer

  De novo metastatic prostate cancer is highly aggressive, but the paucity of routinely-collected tissue in this setting has hindered genomic stratification and jeopardizes precision oncology efforts. Here, we leveraged a rare study of surgical intervention in 43 de novo metastatic prostate cancers to assess somatic genotype across 607 synchronous primary and metastatic tissue foci plus circulating tumor DNA. Intra-prostate heterogeneity was pervasive and impacted clinically-relevant genes, resulting in frequent discordance between select primary-restricted foci and synchronous metastases. Additional complexity was driven in several instances by polyclonal metastatic seeding from the reservoir of phylogenetically-related primary populations. When simulating standard clinical practice relying on a single tissue focus, genomic heterogeneity plus highly variable per-sample tumor fraction caused false genotyping of dominant disease. However, in silico modeling demonstrated that analysis of multiple biopsy cores can rescue misassigned somatic genotypes. Our results define the relationship between synchronous treatment-naive primary and metastatic lesions in de novo metastatic prostate cancer and provide a framework for implementing genomics-guided patient management.

  Study EGAS00001006466

• Clinical and genetic factors associated with tumor response to neoadjuvant (chemo)radiotherapy, survival and recurrence risk in rectal cancer

  Rectal cancer poses challenges in preoperative treatment response, with up to 30% achieving a complete response (CR). Personalized treatment relies on accurate identification of responders at diagnosis. This study aimed to unravel CR determinants, overall survival (OS), and time to recurrence (TTR) using clinical and targeted sequencing data. Analyzing 402 patients undergoing preoperative treatment, tumor stage, size, and treatment emerged as robust response predictors. CR rates were higher in smaller, early-stage, and intensively treated tumors. Targeted sequencing analyzed 216 cases, while 120 patients provided hotspot mutation data. KRAS mutation dramatically reduced CR odds by over 50% (odds ratio [OR]=0.3 in the targeted sequencing and OR=0.4 hotspot cohorts, respectively). In contrast, SMAD4 and SYNE1 mutations were associated with higher CR rates (OR=6.0 and 6.8, respectively). Favorable OS was linked to younger age, CR, and low baseline carcinoembryonic antigen levels. Notably, CR and an APC mutation increased TTR, while a BRAF mutation negatively affected TTR. Beyond tumor burden, SMAD4 and SYNE1 mutations significantly influenced CR. KRAS mutations independently correlated with radiotherapy resistance, and BRAF mutations heightened recurrence risk. Intriguingly, nonresponding tumors with initially small sizes carried a higher risk of recurrence. These findings offer insights into rectal cancer treatment response, guiding personalized therapeutic strategies. By uncovering factors impacting CR, OS, and TTR, this study underscores the importance of tailored approaches for rectal cancer patients. These findings, based on extensive analysis and mutation data, pave the way for personalized interventions, optimizing outcomes in the challenges of rectal cancer preoperative treatment.

  Study EGAS00001007501

• Sequencing data for the manuscript "Multi-focal sampling of de novo metastatic prostate cancer reveals complex polyclonality and enables accurate clinical genotyping"

  This submission includes targeted and whole exome paired-end fastq files.

  Dataset EGAD00001009651

• Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

  Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

  Dataset EGAD00001011048

• Clinical and genetic factors associated with tumor response to neoadjuvant (chemo)radiotherapy, survival and recurrence risk in rectal cancer

  Dataset consists of 216 samples, with each sample having a BAM, BAI and VCF file.

  Dataset EGAD00001011297

• Multi-focal genomic dissection of synchronous primary and metastatic tissue from de novo metastatic prostate cancer - Data Access Committee

  Dac EGAC00001002905

• Cancer Epigenetics Group

  Dac EGAC00001003349

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 9 part 2)

  Whole genome sequencing data of 35 high-grade serous carcinoma (HGSC) patients (112 samples) sequenced with Illumina Novoseq 6000

  Dataset EGAD00001011368

• Division of Molecular Oncology, National Cancer Center Research Institute Data Access Committee

  Dac EGAC00001003030

• Sequencing data for oesophageal and related samples - Katz-Summercorn, Jammula et al (WGS)

  Data supporting: “Multi-omic cross-sectional cohort study of pre-malignant Barrett’s esophagus reveals structural variation and retrotransposon activity occur early in cancer evolution.” Katz-Summercorn, Jammula et al. WGS (BAM files)

  Dataset EGAD00001006349

• DNA-methylation variability in normal mucosa of patients with adenomatous polyps: a marker of field cancerization

  A study linking DNA methylation modifications in the normal mucosa of the right colon in individuals with adenomatous polyp formation

  Study EGAS00001007666

• This DAC takes care of requests for data for the Swiss epigenetic colorectal cancer cohort study, SWEPIC

  Dac EGAC00001003471

• BCSA_Exome+SmartSeq3

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Dataset EGAD00001009781

• Intra-prostatic tumour evolution, steps in metastatic spread and histogenomic associations revealed by integration of multi-region whole genome sequencing with histopathological features

  We performed whole genome sequencing on 42 prostate cancer samples from the prostate, seminal vesicles and regional lymph nodes of five treatment-naive patients with locally advanced disease who underwent radical prostatectomy. Whole genome sequencing was performed as 150bp paired end reads on the Illumina NovaSeq 6000 platform.

  Dataset EGAD00001011174

• Singapore Gastric Cancer Consortium Data Access Committee

  Dac EGAC00001003138

• WGS of high grade serous ovarian tumours and matched blood normals

  FASTQ reads for 81 matched tumour-normal WGS pairs for high grade serous ovarian cancer patients. Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. Tumour samples were divided into two for DNA and RNA extraction and slivers of tissue were taken, fixed in formalin and embedded in paraffin wax (FFPE). Samples were only included if they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using H&E staining of the FFPE sections and pathology review. Somatic DNA was extracted from the tumour and germline DNA was extracted from whole blood. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality.

  Dataset EGAD00001009049

• WGS of high grade serous ovarian tumours and matched blood normals

  FASTQ reads for 34 matched tumour-normal WGS pairs for high grade serous ovarian cancer patients. Scottish HGSOC samples were collected via local Bioresource facilities at Edinburgh, Glasgow, Dundee and Aberdeen and stored in liquid Nitrogen until required. HGSOC patients were determined from pathology records and were included in the study where there was matched tumour and whole blood samples. Tumour samples were divided into two for DNA and RNA extraction and slivers of tissue were taken, fixed in formalin and embedded in paraffin wax (FFPE). Samples were only included if they were confirmed as HGSOC and there was greater than 40% tumour cellularity throughout the tumour, determined using H&sE staining of the FFPE sections and pathology review. Somatic DNA was extracted from the tumour and germline DNA was extracted from whole blood. Somatic DNA was extracted using the Qiagen DNeasy Blood and tissue kit (cat no 69504). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including RNase digestion step). Germline DNA was extracted from 1-3ml whole blood using the Qiagen FlexiGene kit (cat no 51206) following the manufacturers recommended protocol. The resulting DNA underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as surrogate measures of DNA purity. A260/280 had to be 1.8 or greater and A260/230 had to be 2.0 or greater. Then, DNA was quantified using LifeTechnologies Qubit dsDNA BR kit (cat no Q32850) and we required a minimum of 50ul at 25ng/ul for WGS. Thirdly, DNA was diluted to 25ng/ul and a representative sample was loaded onto a 0.8% TAE gel, ran at 100v for 60mins and then imaged using a BioRad ChemiDoc imaging system to visualise the DNA quality.

  Dataset EGAD00001010135

• Data from Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

  Data from Representation of genomic intratumor heterogeneity in multi-region non-small cell lung cancer patient-derived xenograft models

  Dataset EGAD00001012228

• Comprehensive analyses of clinicopathological features and genomic mutations of combined hepatocellular-cholangiocarcinoma

  Combined hepatocellular and cholangiocarcinoma (cHCC-CCA) is a rare primary liver cancer. We performed whole exome sequencing to clarify the relationship between genetic mutations and clinicopathological features in cHCC-CCA.

  Study JGAS000599

• CRUK Accelerator: oesophageal adenocarcinoma whole exome and RNA-seq raw sequencing data

  Whole exome and RNASeq raw sequencing data for a cohort of 7 male patients with oesophageal adenocarcinoma. Median age at diagnosis was 68. Tumour tissue and PBMCs were used for whole exome sequencing and RNA sequencing. This data was generated as part of a study funded by a Cancer Research UK Centres Network Accelerator Award Grant (A21998).

  Dataset EGAD00001008489

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010274

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  There is a need for quantitative measurements of evolutionary metrics in controlled clinical trials with long term follow-up information. This is particularly true in advanced localised prostate cancer, which can recur more than a decade after diagnosis. Here we mapped genomic intra-tumour heterogeneity in 642 tumour samples from 114 patients who took part in the IMRT and DELINEATE clinical trials, for which full clinical information and 12y median follow-up was available. We concomitantly assessed phenotypic (morphological) heterogeneity using Deep Learning in 1,923 histological sections from 250 IMRT patients (fully overlapping with the genetic set). This study shows that combining genomics with AI-aided histopathology in clinical trials leads to novel clinical biomarkers. This EGA repository contains data produced from tumour samples using low coverage whole genome sequencing and a prostate cancer specific gene panel data following compression of unique molecular identifiers.

  Dataset EGAD00001010295

• cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

  Dataset EGAD00001011178

• Data for noninvasive lung cancer subtyping study

  This dataset included cfMethyl-Seq data of 15 plasma cfDNA samples from 15 lung cancer patients and RRBS data of 58 lung tumor tissue samples from 58 lung cancer patients. The data were generated following the standard protocols.

  Dataset EGAD00001015344

• DAC for noninvasive lung cancer subtyping

  Dac EGAC00001003474

• Melanoma PEACE Dataset

  Dataset for the initial melanoma PEACE paper in Cancer Discovery, March 2023.

  Dataset EGAD00001010877

• Lung cancer cfDNA dataset DAC

  Dac EGAC00001002994

• cfDNA dataset from extracelular vesicles and paired non-fractionated samples

  Liquid biopsies contain multiple analytes that can be mined to improve the detection and management of cancer. Beyond cell-free DNA (cfDNA), mutations have been detected in DNA associated with extracellular vesicles (EV-DNA). The genome-wide composition and structure of EV-DNA remains poorly characterized, and whether circulating EVs are enriched in tumor signal compared to unfractionated cfDNA is still unclear. Here, using whole genome sequencing from selected lung cancer patients with a relatively high cfDNA tumor content >5%, we determined that the tumor fraction and heterogeneity are comparable between DNA associated with small (<200 nm) EVs and matched plasma cfDNA. DNA in EV fractions, obtained with standardized size-exclusion chromatography, are comprised of short ~150-180 bp fragments and long >1000 bp fragments that are poor in tumor signal. Other fractions only exhibit short fragments with similar tumor DNA content. The composition in bases at the end of EV-DNA fragments, as well as their fragmentation patterns are similar to total plasma cfDNA. Mitochondrial DNA however is relatively enriched in EV fractions. Our results suggests that cfDNA in plasma may be of dual nature, either bound to proteins (including the nucleosome) but also associated to EVs. cfDNA associated to small EV (including exosomes) is however not preferentially enriched in tumor signal.

  Study EGAS00001006848

• Ovarian cancer cfDNA dataset DAC

  Dac EGAC00001003234

• cfDNA from fractionated and paired unfractionated plasma samples of lung cancer patients

  Plasma from lung cancer patients from EDTA tubes was fractionated using size exclusion chromatography. Fractions 1-5, 7-11, 12-15, 16-20 were pooled, cfDNA was extracted from the fractions and paired unfractionated samples and PE150bp sequencing was performed on an Illumina Novaseq S4 flowcell. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001009780

• Ovarian cancer cfDNA dataset

  The dataset contains 23 ovarian cancer and 2 healthy control urine cfDNA samples. Shallow WGS was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001010848

• Targeted and shallow whole genome sequencing identifies therapeutic opportunities in p53abn endometrial cancers

  Shallow whole genome sequencing of 196 formalin-fixed paraffin-embedded p53abn endometrial cancers.

  Dataset EGAD00001015241

• The somatic mutation landscape of normal gastric epithelium - TGS

  The landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into embryogenesis, normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing and targeted panel sequencing of microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium.

  Dataset EGAD00001015352

• The somatic mutation landscape of normal gastric epithelium - WGS

  The landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into embryogenesis, normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing and targeted panel sequencing of microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium.

  Dataset EGAD00001015351

• Gastric_Mutational_Signatures__GMS_

  This study aims to characterise the mutation burdens and signatures of adult stem cells derived from different regions of the stomach in order to gain insight into the causes and preclinical evolution of the diverse cancer subtypes. Clonal populations of cells from different anatomical locations of the stomach will be derived through organoid culture and/or laser microdissection and interrogated by whole genome sequencing and/or targeted pulldown. A total of circa 300 samples from 20 – 30 donors (cancer and non-cancer patients undergoing total/partial gastrectomy) will be analysed for mutational burden and signatures and genomic findings correlated with topology, age, risk factors and different stages of pre-neoplastic or neoplastic progression.

  Study EGAS00001002938

• Gastric_Mutational_Signatures__GMS_

  This study aims to characterise the mutation burdens and signatures of adult stem cells derived from different regions of the stomach in order to gain insight into the causes and preclinical evolution of the diverse cancer subtypes. Clonal populations of cells from different anatomical locations of the stomach will be derived through organoid culture and/or laser microdissection and interrogated by whole genome sequencing and/or targeted pulldown. A total of circa 300 samples from 20 – 30 donors (cancer and non-cancer patients undergoing total/partial gastrectomy) will be analysed for mutational burden and signatures and genomic findings correlated with topology, age, risk factors and different stages of pre-neoplastic or neoplastic progression.

  Study EGAS00001002939

• Bulk BCR NGS data from metastatic breast tumours from donors with therapy-resistant lethal metastatic breast cancer.

  Bulk B Cell Receptor high-throughput sequencing data across 27 metastatic breast tumours obtained from 8 donors with therapy-resistant lethal metastatic breast cancer at the time of a warm autopsy. The 35 samples were sequenced on an Illumina MiSeq instrument and their raw FastQ files deposited here.

  Dataset EGAD00001010023

• Metastatic Breast Cancer Data Access Committee

  Dac EGAC00001003074

• Human genomic and phenotypic synthetic data for the study of rare diseases

  The purpose of this dataset is to facilitate development of technical implementations for rare disease data integration, analysis, discovery, and federated access. This synthetic dataset includes clinical and genomic data from 6 rare disease cases. It consists of 18 whole genomes (6 index cases with their parents) which have genetic background based on public human data sequenced in the context of the Illumina Platinum initiative (Eberle, MA et al. (2017)) and made available by the HapMap project (https://www.genome.gov/10001688/international-hapmap-project). In each of the cases, real causative variants correlating with the phenotypic data provided were spiked-in. The cases included in this synthetic dataset correspond to the following type of disorders: CASE 1- Congenital myasthenic syndrome (Autosomal Dominant -de novo variant) CASE 2- Macular dystrophy (Autosomal Dominant) CASE 3- Muscular dystrophy (Autosomal Recessive-compound heterozygous variants) CASE 4- Mitochondrial disorder (Autosomal Recessive-consanguineous case - homozygous variant) CASE 5- Breast cancer (Autosomal Dominant) CASE 6- Similar as case 1 for patient matchmaking tests: Congenital myasthenic syndrome (Autosomal Dominant-de novo variant) For each case you will be able to download the following data: clinical information (phenopackets per individual and pedigree per family), raw genomic data (FASTQ and BAMs) and processed genomic data (vcfs). When using the data, the following should be acknowledged: the RD-Connect GPAP (https://platform.rd-connect.eu/), EC H2020 project EJP-RD (grant # 825575), EC H2020 project B1MG (grant # 951724) and Generalitat de Catalunya VEIS project (grant # 001-P-001647).

  Study EGAS00001005702

• SDH_deficient_renal_tumours___RNA_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004103