6052 results for "canc*"

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• Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy

  Recurrent locally advanced head and neck cancer (HNC) patients, receiving re-radiotherapy (re-RT), are presented with short progression-free (PFS) and overall survival. Hence, biomarkers predicting therapy failure are urgently needed. We analyzed copy number variations (CNVs) in blood plasma of HNC patients collected before, during and after re-RT. Detectable CNVs after five and ten fractions of re-irradiation as well as at the end of re-RT were associated with short PFS. Furthermore, we found that CNV kinetics in longitudinally collected plasma reflected therapy response and could detect disease progression in advance of radiographic tumor assessments.

  Study EGAS50000000163

• Dataset for WGS head and neck cancer samples

  This dataset contain WGS sequencing data of head and neck cancer samples as well as blood plasma controls. Sequencing was performed on Illumina Novaseq 6000 using KAPA HyperPrep Kit. The sequencing was always paired.

  Dataset EGAD50000000233

• DAC for "Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy"

  This is the DAC for "Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy" with Florian Janke f.janke@dkfz-heidelberg.de German Cancer Research Center, Division of Cancer Genome Research Holger Sültmann h.sueltmann@dkfz-heidelberg.de German Cancer Research Center, Division of Cancer Genome Research Magdalena Görtz magdalena.goertz@dkfz-heidelberg.de German Cancer Research Center, Multiparametric Methods for Early Detection of Prostate Cancer

  Dac EGAC50000000114

• Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype"

  Dac for "Combined single-cell transcriptomics and T-cell receptor sequencing reveal heterogeneity of mycosis fungoides between and within patients and identify a CD4+ cytotoxic subtype" with Name: Menghong Yin Email address: menghong.yin@dkfz-heidelberg.de Associated affiliation: Translational Skin Cancer Research Lab (DKFZ)

  Dac EGAC50000000168

• Clinical panel sequencing of cancer of unknown primary using Comprehensive cancer panel (CCP)

  This database includes comprehensive cancer panel (CCP) on paired tumour and germline DNA from cancer of unknown primary samples, all of which are matched to WGS data under this study. This data was used to compare biomarker yield against what was achieved with WGS. This dataset contains n=34 tumour-germline paired samples. All samples are in BAM format aligned with GRCh38 reference genome.

  Dataset EGAD50000000655

• Clinical panel sequencing of cancer of unknown primary using TruSight Oncology 500 (TSO500)

  TruSight Oncology 500 (TSO500) cancer panel sequencing data on paired tumour and germline DNA from cancer of unknown primary samples. All of the samples in this dataset are matched to WGS data. This data was used to compare biomarker yield against what was achieved with WGS and contains n=51 tumour-only samples. All samples are in BAM format aligned with GRCh38 reference genome.

  Dataset EGAD50000000657

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 15)

  The dataset contains whole genome sequencing data of 8 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 16 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000526

• Identification of germline variants in Medullary thyroid carcinoma (MTC) by whole- exome sequencing

  Medullary thyroid cancer (MTC) is a rare malignant tumor that arises from parafollicular cells. Approximately 8% of thyroid cancer cases are MTC, and about 25% of these have a hereditary component. Incorporating molecular parameters into tumor classification is important. Besides, the presence of pathogenic germline variants can impact directly on cancer prevention. Thus, the aim of this study was to perform whole exome sequencing (WES) on a consecutive series of hereditary RET wild-type MTC patients to identify genetic variants that may be involved in the carcinogenesis of this tumor. WES was performed on 28 patients negative for germline RET pathogenic variants using the NovaSeq 6000 platform. Variant classification followed American College of Medical Genetics and Genomics guidelines.Our study represents a significant advancement in gene discovery for MTC genetics.

  Study EGAS50000000061

• Brazilian Thyroid WES

  Medullary thyroid cancer (MTC) is a rare malignant tumor that arises from parafollicular cells. Approximately 8% of thyroid cancer cases are MTC, and about 25% of these have a hereditary component. Incorporating molecular parameters into tumor classification is important. Besides, the presence of pathogenic germline variants can impact directly on cancer prevention. Thus, the aim of this study was to perform whole exome sequencing (WES) on a consecutive series of hereditary RET wild-type MTC patients to identify genetic variants that may be involved in the carcinogenesis of this tumor. WES was performed on 28 patients negative for germline RET pathogenic variants using the NovaSeq 6000 platform. Variant classification followed American College of Medical Genetics and Genomics guidelines.Our study represents a significant advancement in gene discovery for MTC genetics.

  Dataset EGAD50000000086

• DAC Barretos Cancer Hospital

  Dac EGAC50000000013

• A 3D genome atlas of breast cancer progression (BRCA3D)

  In this study, we aimed to understand how the 3D genome changes during breast cancer development and progression, in situ. Towards this goal, we collected cells from patient biopsies and performed Hi-C on four types of biopsies representing different stages of disease progression: healthy mammary tissue, primary breast tumours, liver metastasis and malignant pleural effusions. We survey the changes in the 3D genomes at the level of structural variation, compartments and TADs, as well as ERα associated distal interactions.

  Study EGAS50000000444

• ERa ChIP-seq in breast healthy, primary cancer and metastatic tissues

  ChIP-seq has been perfomed on fresh-frozen tissue derived from healthy breast (HB), primary breast cancer (PB), BCa-derived liver metastasis (LM). Immunoprecipitation has been performed for ERa (sc-542, SantaCruz). Raw paired-end fastq.gz files are provided for both immunoprecipitated DNA and input samples.

  Dataset EGAD50000000642

• Hi-C in breast healthy, primary cancer and metastatic tissues

  Hi-C libraries have been prepared by enzymatic digestion with MboI restriction enzyme and sonication (Covaris). Illumina single-indexig primers have been use to amplify ligated fragments. Hi-C experiments have been performed on 10 slices (50um thick) of fresh-frozen tissues or 10x10e6 Pleural Effusion cells. Raw paired-end fastq.gz files are provided.

  Dataset EGAD50000000643

• Genome analysis of oesophageal cancer and Barrett's oesophagus

  The median survival of oesophageal cancer this year is only 13 to 19 months after diagnosis and more than 90% will die from their disease. Therefore better treatment options are needed. The likelihood of cure for early screen-detected cancers is much higher. Barrett's oesophagus is a pre-cancerous lesion associated with a 30-40 fold increased risk of developing cancer. In an attempt to detect cancer early many patients with Barrett's are enrolled into surveillance programs involving regular endoscopies. A major problem with this approach is that the prevalence of BO in the population is estimated to be around 2%, but most patients with BO will never develop cancer. We are undertaking genomic and/or transcriptomic analysis of oesophageal tumours, Barrett's oesophagus and matched normal samples. The aim is to identify oesophageal-related genomic and transcriptomic alterations, which may reveal mutational process occurring, suggest biomarkers of tumour progression and treatment and identify novel treatment strategies.

  Study EGAS00001002864

• Angiopredict Whole genome Shallow Sequencing

  Shallow sequencing of metastatic colorectal cancer samples for the Angiopredict and Nobev cohorts described in: van Dijk et al., JCO, in revision

  Dataset EGAD00001003990

• DELFI low-coverage WGS of plasma cfDNA

  The dataset "DELFI low-coverage WGS of plasma cfDNA" includes paired FASTQ files produced by WGS of 689 plasma cfDNA samples from 153 patients with colorectal cancer. WGS (100bp PE) was performed on a NovaSeq 6000 with a target depth of coverage of 8x.

  Dataset EGAD50000000630

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

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

  Study EGAS00001007877

• Time series analysis of neoadjuvant chemotherapy and bevacizumab treated breast carcinomas reveals a systemic shift in genomic aberrations

  Study EGAS00001003287

• Primary prostate Hi-C

  Prostate cancer is a heterogeneous disease whose progression is linked to genome instability. Despite large-scale tumour sequencing efforts, the impact of mutations on the genetic architecture in cancer remains ill-defined due to limited integration of genomics data across dimensions. We addressed this limitation by assessing the impact of structural variants on the chromatin states and the three-dimensional organization across benign and malignant primary prostate genomes. We find high concordance in the three-dimensional genome organization between malignant and benign prostate tissues, arguing for constraints to the three-dimensional genome of prostate tumours. Moreover, we identify structural variants as effectors of changes to focal chromatin interactions, guiding cis-regulatory element hijacking that imposes opposing expression changes on genes found at antipodes of a rearrangement. This leads to the repression of tumour suppressor gene expression and up-regulation of oncogenes, such as at the TMPRSS2-ERG and PMEPA1-ZNF156 loci. Collectively, our results argue that cis-regulatory element hijacking by structural variants overshadows large-scale topological changes to alter gene regulation and promote oncogenesis.

  Study EGAS00001005014

• Whole Genome Sequencing Data of High Grade Serous Ovarian Cancer

  Longitudinal whole genome sequencing data to study chemoresponse in ovarian cancer. These samples belong to an ongoing sample collection and the data already includes hundreds of samples from over 200 patients. Samples are from primary and metastatic tissues and ascites. All patients have been treated with platinum-taxane based chemotherapy and majority of them are diagnosed with high-grade serous ovarian cancer.

  Study EGAS00001006775

• Genetics and therapeutic responses to TIL therapy of pancreatic cancer PDX models

  Pancreatic cancer is the 7th leading cause of cancer-related deaths worldwide. Checkpoint immunotherapy has not yet showed encouraging results in pancreatic cancer possibly owing to a poor immunogenicity and/or an immune suppressive microenvironment. The aim of this study was to develop patient-derived xenografts (PDX) models and to assess if autologous tumor-infiltrating lymphocytes (TILs) would have anti-tumoral activity in pancreatic cancer. Tumor biopsies from 29 patients were subcutaneously transplanted into NOG mice. Tumor growths were confirmed in 11 out of 29 transplantations. The PDX tumors histologically resembled their original biopsies, but since stromal cells in the PDX model tumors were from mouse, their gene expression differed from the original biopsies. Immune checkpoint ligands other than PD-L1 were expressed in pancreatic cancers but PD-L1 was rarely expressed. One of the three tumors that did express PD-L1 was an adenosquamous cancer and another had a mismatch repair deficiency. TILs were expanded from six tumors and were injected into NOG or human interleukin-2 transgenic-NOG (hIL2-NOG) mice carrying PDX tumors. Regression of tumors could be verified in hIL2-NOG mice in 3 of the 6 PDX models treated with autologous TILs, including the adenosquamous PDX model. In conclusion, PDX models of pancreatic cancer can be used to learn more about tumor characteristics and biomarkers, and to evaluate responses to ACT and combination therapies. The major benefit of the model is that modifications of T cells can be tested in an autologous humanized mouse model to gain preclinical data to support the initiation of a clinical trial.

  Study EGAS00001005596

• Multi-institutional collaboration to characterize 5hmC in prostate cancer, both tumor biopsies and cfDNA.

  This study used pull-down sequencing to measure 5-hydroxymethylcytosine (5hmC) levels in tissue biopsy specimens from patients with localized and metastatic castration-resistant (mCRPC) prostate cancer. For a subset of the cohort, the same technique was used to sequence cell-free DNA (cfDNA) isolated from patient plasma. To assess 5hmC levels in cfDNA from a larger number of specimens, plasma samples from another mCRPC cohort were also assayed with this method. The larger cohort of cfDNA samples was further anlayzed with a targeted sequencing gene panel.

  Study EGAS00001004942

• XClone for analyzing somatic copy number alterations

  Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

  Study EGAS00001007854

• BRCA1 secondary splice-site mutations

  BRCA1 splice isoforms d11 and d11q can contribute to PARP inhibitor (PARPi) resistance by splicing-out mutation-containing exons, producing truncated, partially-functional proteins. However, the clinical impact and underlying drivers of BRCA1 exon skipping remain undetermined. We analyzed nine ovarian and breast cancer patient derived xenografts (PDX) with BRCA1 exon 11 frameshift mutations for splice isoform expression and therapy response.

  Study EGAS50000000022

• Hi-C analysis of metastatic prostate tumors

  DNA strands have a complex and highly structured three-dimensional shape within the nucleus that has profound but poorly characterized impacts on transcriptional activity. Herein, we performed the first integrated deep Hi-C sequencing on 80 metastatic castration-resistant prostate cancer biopsy samples from the West Coast Dream Team consortium.

  Study EGAS00001006604