7082 results for "canc*"

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• Whole genome sequencing of retinoblastoma reveals the diversity of rearrangements disrupting RB1 and uncovers a treatment related mutational signature

  Background: The development of retinoblastoma is thought to require pathological genetic changes in both alleles of the RB1 gene. However, cases exist where RB1 mutations are undetectable suggesting alternative pathways to malignancy. Methods: We applied comprehensive whole genome sequencing (WGS) and transcriptomics to sporadic retinoblastomas derived from twenty patients attending our clinic, contrasting these results to that obtained through customary clinical testing. We sought RB1 and other driver mutations, investigated mutation burden, mutational signatures and phylogenetic relatedness in one case of bilateral retinoblastoma. Results: At least one RB1 mutation was identified in all retinoblastomas. We confirmed RB1 mutations previously identified by clinical screening, identified three new RB1 mutations and provided clarity to the mechanism behind a further six mutations. Eight tumours carried structural rearrangements involving RB1 ranging from relatively simple to extremely complex rearrangement patterns, including a chromothripsis-like pattern in one tumour. Potential driver mutations included mutations in BCOR (5/20) and amplification of MYCN (2/20) and MDM4 (1/20). We show that RB1 mutations are not mutually exclusive of MYCN amplifications, and further reveal that all tumours demonstrate increased MYCN expression suggesting a universal role in retinoblastoma tumorigenesis.  Bilateral tumours obtained from one patient harboured conserved germline but divergent somatic RB1 mutations, indicating independent evolution. In-keeping with previous WGS of paediatric cancers, the mutation burden in retinoblastomas was extremely low. Mutational signature analysis showed a predominance of signatures associated with cell division and an absence of ultraviolet-related DNA damage. In a tumour exposed to chemotherapy prior to enucleation, a profound platinum-related mutational signature was observed. Conclusions: WGS provides a complete picture of the genomic landscape of retinoblastomas, allowing the discovery of mutations otherwise undetected by conventional clinical screening approaches. The presence of at least one RB1 mutation in all retinoblastomas and the relative paucity of driver mutations in other genes suggests mutations beyond RB1, MYCN and BCOR are rare. Whilst most RB1 mutations are identifiable by clinical screening, the increased resolution and ability to detect otherwise elusive rearrangements of RB1 by WGS, confirming whether they are somatic or germline, has important repercussions on clinical management and advice on recurrence risks.

  Dataset EGAD00001006431

• Sequence of breast cancer bone metastases PDX before and after palbociclib treatment resistance

  RNAseq sequencing of 10 breast cancer bone metastasis PDX. Samples were obtained from 5 PDX that acquired palbociclib resistance (palboR) and 5 from the parentale PDX (palboS).

  Dataset EGAD00001009068

• Combinatorial CRISPR screen identifies fitness effects of paralogues FAM50A and FAM50B

  Genetic redundancy has evolved as a way for human cells to survive the loss of genes that are single copy and essential in other organisms, but also allows tumours to survive despite having highly rearranged genomes. In this study we CRISPR screen 1,191 gene pairs, including paralogues and known and predicted synthetic lethal interactions to identify 105 gene combinations whose co-disruption results in a loss of cellular fitness. 27 pairs influence fitness across multiple cell lines including the paralogues FAM50A/FAM50B, two genes of unknown function. Silencing of FAM50B occurs across a range of tumour types and in this context disruption of FAM50A reduces cellular fitness whilst promoting micronucleus formation and extensive perturbation of transcriptional programmes. This dataset includes CRISPR screening of cancer cell lines, RNA sequencing studies of cancer cell lines and also data from the sequencing of tumour xenografts collected from mice.

  Dataset EGAD00001006649

• Transcriptome sequencing of replication repair deficient brain cancers

  Hypermutant tumors which harbor many somatic mutations may obscure the interpretation of targetable genomic events. This dataset contains transcriptome sequencing from 21 replication repair deficient brain tumor samples as well as healthy controls.

  Dataset EGAD00001006921

• Genome and transcriptome sequence data from an adnexal tumor probable of Wolffian origin patient

  Genome and transcriptome sequence data from an adnexal tumor probable of Wolffian origin patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002600

• RNAseq of breast cancer bone metastases PDX resistant of responder to IACS-010759 treatment

  Fastq files from RNAseq of breast cancer bone metastases PDX after treatment with IACS-010759. Five PDX are resistants to treatment and 6 are responders.

  Dataset EGAD00001009072

• Normal sample for patient SA239

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA239

  Dataset EGAD00001009364

• Tumour sample for patient SA1017

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009609

• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  ChIP-seq and matched input data of AR, FOXA1 and H3K27ac for mCRPC patient samples taken prior to and after treatment with AR targeted therapy

  Dataset EGAD00001008688

• Normal sample for patient SA674

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA674

  Dataset EGAD00001009374

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Cancer cells enter a reversible drug tolerant persister (DTP) state to evade death from both chemotherapies and targeted agents. It is increasingly appreciated that the DTP state is an important driver of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer xenograft models to identify and characterize the cancer cells capable of generating DTPs in response to standard-of-care chemotherapy. Barcode analysis revealed no loss in clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fits a mathematical model in which all cancer cells, and not a small subpopulation, possess an equipotent capacity to enter the DTP state. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides new insights into how cancer cells use a developmentally conserved mechanism to drive the DTP state pointing to novel therapeutic opportunities to target diapause-like DTPs.

  Dataset EGAD00001006849

• 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

• Distinct evolutionary trajectories of primary high grade serous ovarian cancers revealed through spatial mutational profiling

  High-grade serous ovarian cancer (HGSC) is characterized by poor outcome, often attributed to the emergence of treatment-resistant subclones. We sought to measure the degree of genomic diversity within primary, untreated HGSCs to examine the natural state of tumour evolution prior to therapy. We performed exome sequencing, copy number analysis, targeted amplicon deep sequencing and gene expression profiling on 31 spatially and temporally separated HGSC tumour specimens (six patients), including ovarian masses, distant metastases and fallopian tube lesions. We found widespread intratumoural variation in mutation, copy number and gene expression profiles, with key driver alterations in genes present in only a subset of samples (eg PIK3CA, CTNNB1, NF1). On average, only 51.5% of mutations were present in every sample of a given case (range 10.2 to 91.4%), with TP53 as the only somatic mutation consistently present in all samples. Complex segmental aneuploidies, such as whole-genome doubling, were present in a subset of samples from the same individual, with divergent copy number changes segregating independently of point mutation acquisition. Reconstruction of evolutionary histories showed one patient with mixed HGSC and endometrioid histology, with common aetiologic origin in the fallopian tube and subsequent selection of different driver mutations in the histologically distinct samples. In this patient, we observed mixed cell populations in the early fallopian tube lesion, indicating that diversity arises at early stages of tumourigenesis. Our results revealed that HGSCs exhibit highly individual evolutionary trajectories and diverse genomic tapestries prior to therapy, exposing an essential biological characteristic to inform future design of personalized therapeutic solutions and investigation of drug-resistance mechanisms

  Dataset EGAD00001000669

• MutWP5: CRUK Mutographs of Cancer: Lung: PD37920 (Targeted) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutation burden in different portions of the lung. Targeted sequencing will be conducted on samples to identify drivers of interest and clonality of the samples, well-performing samples will be sent for subsequent whole-genome sequencing. Results from this portion of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006929

• sWGS on cfDNA and matching tumor DNA in pediatric cancer

  This dataset contains shallow whole genome sequencing data from paired cfDNA - tumor DNA samples of various pediatric cancer entities (total 215 samples). Files are provided in fastq format. Samples were sequenced on an Ion Proton sequencer (Thermo Fisher Scientific) or a Hiseq3000 (Illumina). Data analysis is available at https://github.com/rmvpaeme/sWGS_pediatric_cancer.

  Dataset EGAD00001007508

• TMD-AMKL targeted follow-up

  Genomic libraries will be generated from total genomic DNA derived from 200+ patients with childhood Transient Myeloproliferative Disorder (TMD) and or Acute Megakaryocytic Leukemia (AMKL) as well some matched constitutional samples (n < 50 ). Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 96 Samples will be individually barcoded and subjected to up to two lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.

  Dataset EGAD00001000783

• MutWP5: CRUK Mutographs of Cancer: Lung: PD43291_Novaseq (Exome) (2021-02-02)

  Sequencing of LCM-derived microbiopsies from explanted lung from COPD patient. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Deep sampling throughout multiple regions of the lung will determine whether there are differences in smoking-related mutaiton burden in different portions of the lung. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to other individuals with smoking-related diseases (COPD, pulmonary fibrosis, lung cancer), and normal, non-smoking lungs. . This dataset contains all the data available for this study on 2021-02-02.

  Dataset EGAD00001006932

• 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

• Evaluation of triple negative breast cancer with heterogeneous immune infiltration

  This dataset contains the raw RNA-seq data (FASTQ files) of the samples used in the study title: "Evaluation of triple negative breast cancer with heterogeneous immune infiltration". The dataset is composed of 3 patients with 6 samples per patient (3 with high TILs and 3 with low TILs).

  Dataset EGAD00001010280

• 10x Genomics Single Cell Gene Expression for SA535X4XB05462

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 4

  Dataset EGAD00001009115

• 10x Genomics Single Cell Gene Expression for SA535X6XB03099

  10x Genomics Single Cell Gene Expression for Triple negative breast cancer patient-derived xenograft SA535 passage 6

  Dataset EGAD00001009116

• Cholangiocarcinoma

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting two datasets that contain NGS files from gastrointestinal rare cancers (n=119): - Dataset 2 (87 patients): Intra-hepatic cholangiocarcinoma (n=47), Extra-hepatic, cholangiocarcinoma (n=16), Not specified Cholangiocarcinoma (n=9), Small bowel adenocarcinoma (n=6) and other rare GI cancer (n=9)

  Dataset EGAD00001008968

• ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, as part of the International Human Epigenome Consortium.

  ChIP-Seq (H3K36me3) assays for reference epigenomes generated by Centre for Epigenome Mapping Technologies at Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001231

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002555

• Exome Sequencing of Gastric Cancer Samples

  We perform whole exome sequencing on 50 pairs of gastric cancer and matched normal samples.

  Dataset EGAD00001006957