7358 results for "canc*"

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• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data

  We present Epiclomal, a probabilistic clustering method arising from a hierarchical mixture model to simultaneously cluster sparse single-cell DNA methylation data and infer their corresponding hidden methylation profiles. Using synthetic and published single-cell CpG datasets we show that Epiclomal outperforms non-probabilistic methods and is able to handle the inherent missing data feature which dominates single-cell CpG genome sequences. Using a recently published single-cell 5mCpG sequencing method (PBAL), we show that Epiclomal discovers sub-clonal patterns of methylation in aneuploid tumour genomes, thus defining epiclones. We show that epiclones may transcend copy number determined clonal lineages, thus opening this important form of clonal analysis in cancer.

  Study EGAS00001003504

• whole-genome sequencing of gastric cancer

  Gastric cancer is one of the most common cancers. Genome-wide analysis of genomic signatures might reveal novel mechanisms for gastric cancer tumorigenesis. Here, we analyzed structural variations and mutational signatures via whole-genome sequencing of 168 gastric cancer samples. Our data demonstrates diverse models of complex structural variations operative in GC, which lead to high-level amplification of oncogenes.

  Study EGAS00001003512

• MutWP4__CRUK_Grand_Challenge_Mutographs_of_Cancer__Pancreatic_Organoids

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

  Study EGAS00001003520

• MutWP5__CRUK_Mutographs_of_Cancer__Cancer_Mastectomy__Exome__Novaseq_

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >60 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumor development.

  Study EGAS00001003528

• Melanoma_post_mortem_analysis

  This is a targeted pulldown validation in support of the existing whole-genome sequencing study of melanoma metastases (Canapps ID:1888). We are studying the genomic evolution of cutaneous melanoma metastases. In this pulldown analysis we are specifically sequencing the subclonal variants that we believe account for the variability between the metastases.

  Study EGAS00001003531

• Immune induction strategies to enhance the sensitivity to PD-1 blockade in metastatic triple negative breast cancer: the TONIC-trial

  The response rate in metastatic triple negative breast cancer (TNBC) to PD-1 blockade is low, highlighting an urgent clinical need for strategies that render the TNBC tumor microenvironment (TME) more sensitive to PD-1 blockade. Immunomodulatory mechanisms have been proposed for both chemotherapy and irradiation, but it has not been established whether these therapies may improve efficacy of PD-1 blockade by favorably changing the TME. In the first stage of this adaptive, non-comparative phase II trial (TONIC-trial; NCT02499367), 67 patients with metastatic TNBC were randomized to nivolumab without induction or to one of four induction treatments, consisting of irradiation of one metastatic lesion (3x8 Gy) or a two- week low-dose regimen of cyclophosphamide, cisplatin or doxorubicin, all followed by nivolumab. In the overall cohort of 66 evaluable patients, the objective response rate (ORR; iRECIST16) was 20% (95% CI: 11%-31%), with two complete responses and 11 partial responses. The majority of clinical responses were observed on nivolumab in the cisplatin (ORR 23%; 3/13) and doxorubicin (ORR 35%; 6/17) cohorts. After doxorubicin and cisplatin induction, we detected an upregulation of immune-related genes, involved in PD-1/PD-L1, and T-cell cytotoxicity pathways. This was further supported by enrichment among upregulated genes related to inflammation, JAK-STAT and TNFα-signaling after doxorubicin. In addition, we observed a trend towards increased T-cell infiltration, measured using T-cell receptor (TCR) sequencing, after doxorubicin. Together, the clinical and translational data of this study testing different immune induction strategies prior to nivolumab suggest that short-term doxorubicin and cisplatin may induce a more favorable TME and increase the likelihood of response to PD-1 blockade in TNBC. These data warrant further confirmation in TNBC and exploration of induction treatments prior to PD-1 blockade in other cancer types.

  Study EGAS00001003535

• MutWP1__CRUK_Grand_Challenge_Mutographs_of_Cancer__clear_cell_renal_cell_carcinoma___2

  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. 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.

  Study EGAS00001003542

• RNA sequencing of NK cells in human lung

  Human lung tissue-resident NK cells (trNK cells) are likely to play important roles in viral infections, inflammation and cancer. However, knowledge about lung trNK cells is lacking but is fundamental for exploiting these cells in therapeutic approaches. Here we analysed the transcriptome of CD69+CD49a+CD103+CD16-CD56bright, CD69+CD49a+CD103-CD16-CD56bright, CD69+CD49a-CD103-CD16-CD56bright, CD69-CD49a-CD103-CD16-CD56bright, and CD56dimCD16+NKG2A+CD57- NK cells isolated from human lung.

  Study EGAS00001003544

• Placental_mosaicism

  The aim of this study is to survey somatic mutations in human placentas.

  Study EGAS00001003549

• Arriba: accurate and efficient detection of gene fusions from RNA-Seq (H021)

  The identification of gene fusions from RNA sequencing data is a routine task in cancer research and precision oncology. However, despite the availability of many computational tools, fusion detection remains challenging. Existing methods suffer from poor prediction accuracy and are computationally demanding. We developed Arriba, a novel fusion detection algorithm with high sensitivity and short runtime. When applied to a large collection of published pancreatic cancer samples (n=803), Arriba identified a variety of driver fusions, many of which affected druggable proteins, including ALK, BRAF, FGFR2, NRG1, NTRK1, NTRK3, RET, and ROS1. The fusions were significantly associated with KRAS wild-type tumors and involved proteins stimulating the MAPK signaling pathway, suggesting that they substitute for activating mutations in KRAS. In addition, we confirmed the transforming potential of two novel fusions, RRBP1-RAF1 and RASGRP1-ATP1A1, in cellular assays. These results demonstrate Arriba’s utility in both basic cancer research and clinical translation.

  Study EGAS00001003554