8420 results for "canc*"

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• A practical guide for mutational signature analysis in hematological malignancies

  Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data.

  Dataset EGAD00001005028

• Genomic Signatures Reveal DNA Damage Response Deficiency in Brain Metastases of Colorectal Cancer

  Brain metastasis (BM) of colorectal cancer (CRC) is rare but lethal and lacks effective therapies or a good understanding of its genomic landscapes. We conduct an analysis of whole-exome sequencing (WES, Illumina HiSeq 2500 sequencing platform) on 11 patient-matched BMs, primary CRC tumours, and adjacent normal tissues; and whole-genome sequencing (WGS, Illumina HiSeq X Ten platform) on 8 patient-matched BMs, primary CRC tumors, and adjacent normal tissues to uncover the whole-genome mutational landscape of colorectal cancer with brain metastasis.

  Dataset EGAD00001005030

• Bioinformatic Methods and Bridging of Assay Results for Reliable Tumor Mutational Burden Assessment in Non-Small Cell Lung Cancer

  Tumor mutational burden (TMB) has emerged as a predictive biomarker of response to immune checkpoint inhibitors. Standardization of TMB measurement is essential for implementing diagnostic tools to guide treatment. Here we evaluate bioinformatic TMB analysis by whole exome sequencing (WES) in formalin-fixed, paraffin-embedded samples. In CheckMate 026, TMB was retrospectively assessed in 312 patients with non-small cell lung cancer (58% of the intent-to-treat population) who received first-line nivolumab treatment or chemotherapy. We examined the sensitivity of TMB assessment to bioinformatic filtering methods and assessed concordance between TMB data derived by WES and the FoundationOne CDx™ assay. TMB scores comprising synonymous, indel, frameshift, and nonsense mutations (all mutations) were 3.1-fold higher than data including missense mutations only, but values were highly correlated (Spearman’s r = 0.99). Scores from CheckMate 026 samples including missense mutations only were similar to those generated from data in The Cancer Genome Atlas, but those including all mutations were generally higher. Using databases for germline subtraction (instead of matched controls) showed a trend for race-dependent increases in TMB scores. Parameter variation can therefore impact TMB calculations, highlighting the need for standardization. Encouragingly, WES and FoundationOne CDx outputs were highly correlated (Spearman’s r = 0.90) and differences could be accounted for by empirical calibration, suggesting that reliable TMB assessment across assays, platforms and centers is achievable.

  Dataset EGAD00001005035

• Targeted analysis of chondrosarcoma cancer genes (2019-04-01)

  Targeted analysis of chondrosarcoma cancer genes . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004877

• Evolution of the cancer epigenome in myeloproliferative neoplasms. (2019-04-01)

  Evolution of the cancer epigenome in myeloproliferative neoplasms. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004879

• Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

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

  Dataset EGAD00001004898

• Genetic vulnerability of knockout cancer lines (2019-04-01)

  Genome-wide CRISPR/Cas9 library screen was performed in isogenic cell lines. Three biological replicates were used. Cells were harvested at initiation of screen and at specific time points following cell culture. Using this approach we aim to identify genes specifically important in cell survival in engineered cell lines. Please perform 72, instead of 36, PCR reactions as the screen performed at 200x coverage. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004881

• Exome sequencing of synchronous colorectal cancers

  The data consists of 47 exome-sequenced synchronous colorectal cancers from 23 patients. The exomes of corresponding normal samples were used to remove germline variants. All patients are Finnish (white Caucasian). All except one patient (sync_11 who belongs to a LS family) were assumed sporadic. The sequence data was produced with Illumina HiSeq 4000.

  Dataset EGAD00001004884

• Genome and transcriptome sequence data from a invasive ductal carcinoma of right breast patient

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

  Dataset EGAD00001004899

• Somatic mutations in twin breast cancers (2019-04-03)

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004890