5707 results for "canc*"

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• Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer

  The dataset for the study Elucidating the heterogeneity of immunotherapy response and immune-related toxicities by longitudinal ctDNA and immune cell compartment tracking in lung cancer includes 207 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 30 individuals with non-small cell lung cancer, alongside 46 bam files from whole exome sequencing of tumor and matched normal DNA for 21 individuals with non-small cell lung cancer who received immunotherapy-containing regimens.

  Dataset EGAD00001011991

• Discrepancies in Tumour Mutation Burden (TMB) reporting from sequential Endobronchial ultrasound trans bronchial needle aspiration (EBUS TBNA) samples within single lymph node stations

  Introduction: Tumour Mutation Burden (TMB) is a potential biomarker for immune therapies. Identifying factors that may affect TMB prediction is key to its utility as biomarker for treatment options. Here we investigated parameters that might affect TMB using cytology smears obtained from endobronchial ultrasound transbronchial needle aspiration (EBUS TBNA)-sampled malignant lymph nodes, which are often the only diagnostic samples collected in patients with advanced lung cancer. Methods: Individual Diff-Quik cytology smears were prepared for each needle pass from the same enlarged malignant mediastinal lymph nodes. DNA extracted from smears of each pass underwent sequencing using a large gene panel sequencing (TSO500, Illumina). TMB was estimated for each individual needle pass using the TSO500 Local App v. 2.0 (Illumina). Results: Twenty patients had two or more Diff-Quik smears (total 45 smears) which passed sequencing quality control. Average TMB for all smears was 8.7 ± 5.0 mutations per megabase (Mb). Sixteen of the 20 patients had paired samples with minimal differences in TMB score (average difference 1.3 ± 0.85). Paired samples from 13 patients had concordant TMB in terms of scores being below or above a threshold of 10 mutations/Mb. Samples from seven patients had discrepant TMB, with four cases in particular exhibiting an average difference of 11.3 ± 2.7 mutations/Mb. Factors affecting TMB calling involved tumour content of the samples, the amount of DNA used in sequencing as well as bone fide intra tumour heterogeneity between paired samples. Conclusions: TMB assessment is feasible from EBUS-TBNA derived Diff-Quik slides from a single needle pass. Repeated samples of one or more lymph nodes have minimal variation in TMB in most cases (80%), suggesting accuracy of the test overall. To enhance accuracy of the result, care should be taken in relation to the tumour content of the cytology smear. Further, clinicians should be aware that even slight differences in lymph node site selection could give rise to variable genomics and discrepant TMB due to tumour heterogeneity. Therefore, it would be reasonable for multi-lymph node site analysis of TMB to be performed using EBUS TBNA aspirates from different easily accessible lymph nodes. Further investigations need to determine whether these samples should be combined as one sample or tested separately.

  Study EGAS00001007484

• British Columbia Cancer Agency (BCCA) PHSAs Technology Development Office, Data Access Committee

  Dac EGAC00001002968

• British Columbia Cancer Agency (BCCA), PHSAs Technology Development Office, Data Access Committee

  Dac EGAC00001002903

• Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer

  The dataset for the study “Circulating tumor DNA, pathological and immunologic responses to neoadjuvant nivolumab or nivolumab plus relatlimab and chemoradiotherapy in resectable esophageal/gastroesophageal junction cancer” includes 173 bam files from hybrid capture targeted error-correction next-generation sequencing (TEC-Seq) from plasma cell-free DNA and matched white blood cell DNA from 32 individuals with esophageal/gastroesophageal junction cancer, who received immunotherapy-containing regimens.

  Dataset EGAD00001011822

• MutWP1: CRUK Grand Challenge Mutographs of Cancer: Kidney (1)

  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.

  Dataset EGAD00001006427

• MutWP1 CRUK Grand Challenge Mutographs of Cancer Colorectal

  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.

  Dataset EGAD00001007510

• OICR-DAC, Ontario Institute for Cancer Research

  Dac EGAC00001000591

• OICR-DAC, Ontario Institute for Cancer Research

  Dac EGAC00001000710

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• MESA colorectal cancer data access committee

  Dac EGAC00001002798

• sWGS of Pap test smears from healthy donors and HGSOC patients and matched tumor tissue

  Shallow whole genome sequencing was performed on Pap test smears considering at least 10 M reads per sample. The cohort consists of 77 samples from healthy women, i.e. no tumor diagnosis, and 65 samples from women with a diagnosis of high-grade serous ovarian cancer (HGSOC) taken months or years before diagnosis. 44 primary tumor samples matched to the respective HGSOC patients were sequenced in the same manner as the Pap test smears.

  Study EGAS00001007084

• To determine the genomic profiles of Triple Negative Breast Cancers (COH cohort)

  Specific BRCA and immune configurations determine optimal response to platinum-based chemotherapy in triple negative breast and ovarian carcinomas (COH_TNBC_WGS)

  Study EGAS00001006085

• WGS of COH TNBC

  WGS data relative to 42 primary and treatment-naive triple negative breast cancers, from independent donors.

  Dataset EGAD00001008617

• sWGS data of Pap test smears and tumor tissues

  Shallow whole-genome sequencing data divided into three groups: - sWGS data from Pap smears of patients with confirmed high grade serous ovarian cancer - sWGS data from matched tumor tissue (at diagnosis) from the same patients - sWGS data from Pap tests smears of healthy women

  Dataset EGAD00001010141

• Geographic variation of mutagenic exposures in kidney cancer genomes – sequence data (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – sequence data (Mutographs)

  Dataset EGAD00001012102