9296 results for "cancer rna-seq"

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• Defining structural variation associated with breast cancer susceptibility by long-read genome sequencing

  Defining structural variation associated with breast cancer susceptibility by long-read genome sequencing

  Dataset EGAD50000000283

• Exploration of CNV’s and SNV’s in cancers with well-known genetic rearrangements: Identification of additional genetic changes in rearrangements-driven cancer

  Specific cancers are well known to have specific gene rearrangements. Representative cancer is chronic myeloid leukemia (CML) which is famous for BCR/ABL gene rearrangements. By the way, also genetic rearrangements are not infrequently found in acute leukemia, and those include CBFB/MYH11 rearrangements, PML/RARA rearrangements, AML/ETO rearrangements, and BCR/ABL rearrangements. The situation is same is for lung adenocarcinoma of non-smokers and prostate cancers, and ALK and RET gene rearrangements are recently found. However, not all these rearrangements are sufficient to develop cancer, and it is suggested that some genetic aberrations are required for the development and progression of cancer in addition to these genetic rearrangements. In this study, we have a plan to explore the existence of additional genetic changes including single nucleotide variants (SNV’s) and copy number variations (CNV’s) in cancers with specific genetic rearrangements so as to define additional genetic changes that confer full oncogenic potential to cancer cells. So as to look at SNV’s and small indels, we are going to use whole exome sequencing (WES) data. And as for CNV’s, we are going to use array-CGH data. Also, to check the functionality of these genetic changes, we are going to use whole transcriptome data (WTS). In addition, in samples with whole genome sequencing (WGS ) data, we are going to explore genetic changes in intronic regions also. In fact, we sequenced 10 AML samples which are known to have specific genetic rearrangements. Analysis of these WGS, WES and WTS data are under the way. If we have a chance to access WES, array-CGH and WTS data of other cancer samples with specific genetic rearrangements, we would be able to compare additional genetic changes required for oncogenesis in cancer cells with various genetic rearrangements. We hope this result will enlighten our understanding of cancer genetics further.

  Study EGAS00001000673

• Whole Exome Sequencing of DNA from Pre-and Post-Chemotherapy Needle Biopsies of Triple Negative and Inflammatory Breast Cancers Enrolled in the S0800 Trial

  Purpose: The purpose of this study was to assess the somatic mutation landscape of breast tumors before and after neoadjuvant chemotherapy. The data includes whole exome sequencing of pre- and post- tissues that were collected in the context of an already published clinical trial SWOG S0800 (ZA Nahleh et al. Breast Cancer Research and Treatment. 158:485-495, 2016). The trial compared the efficacy of sequential nab-paclitaxel followed or preceded by doxorubicin/cyclophosphamide anthracycline chemotherapy with or without bevacizumab as preoperative therapy for stage II-III breast cancer. Experimental Design: 29 pre-treatment biopsies and 9 matching post-treatment surgically resected cancer tissues were available for analysis and were subjected to whole exome sequencing to identify mutational patterns associated with response to neoadjuvant chemotherapy. The 9 paired samples with residual invasive cancer after therapy were also analyzed to assess changes in mutational patterns in response to therapy. No matching normal tissues were available for germline sequencing and therefore we used n=7 post-treatment breast tissues without residual cancer (i.e. complete eradication of cancer by therapy) as a normal cohort to facilitate somatic variant calling.Conclusion: These results suggest that genomic disturbances in BRCA-related DNA repair mechanisms, reflected by a dominant mutational signature 3, confer increased chemotherapy sensitivity. Cancers that survive neoadjuvant chemotherapy, frequently have alterations in cell cycle regulating genes but different genes are affected in different patients.

  Study phs001883

• Defining structural variation associated with breast cancer susceptibility by long-read genome sequencing

  Germline structural variants (SVs) are challenging to identify by conventional genetic testing assays. Long-read sequencing has improved the global characterization of SVs, but its sensitivity at genetic loci associated with high- and moderate-penetrance cancer susceptibility has not been reported. This study used long-read genome sequencing performed on the Oxford Nanopore Technologies' PromethION to resolve variants underlying breast cancer susceptibility in sixteen individuals with pathogenic germline SVs in BRCA1, BRCA2, CHEK2 or PALB2.

  Study EGAS00001005872

• A Comparative Analysis of Algorithms for Somatic SNV Detection in Cancer

  Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer- normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterised and compared to investigate the strengths and weaknesses of each SNV calling algorithm.

  Study EGAS00001000927

• Sequencing of serial plasma and multiregional tumor samples in a patient with metastatic breast cancer

  Circulating tumor DNA analysis can be used to track tumor burden and analyze cancer genomes non-invasively but the extent to which it represents metastatic heterogeneity is unknown. Here, we follow a patient with metastatic ER and HER2 positive breast cancer receiving two lines of targeted therapy over 3 years. We characterize genomic architecture and infer clonal evolution in 8 tumor biopsies and 9 plasma samples collected over 1,193 days of clinical follow-up using exome and targeted amplicon sequencing.

  Study EGAS00001001466

• Mutations conferring differential treatment response in breast cancer

  Poor prognosis primary breast cancer patients usually receive cytotoxic chemotherapy as a component of treatment, but despite this aggressive therapy recurrences remain common. Improved understanding of chemoresistance pathways would allow better stratification of chemotherapy using predictive markers, and may allow therapeutic inhibition of resistance mechanisms in order to chemosensitise tumours. We aimed to identify molecular pathways that define chemoresponse using the novel approach of examining the selection exerted by neoadjuvant chemotherapy on sub-clonal somatic mutational profiles of cancer cells.

  Study EGAS00001003626

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes (TIL/Tc) could determine disease course at different stages in cancer progression. We show that the diversity of the TIL/Tc TCR at baseline is prognostic in various cancers, whereas in metastatic melanoma TIL/Tc TCR clonality at baseline is predictive for activity and efficacy of PD1 blockade immunotherapy.

  Study EGAS00001005201

• Deep whole genome sequencing identifies recurrent genomic alterations in breast cancer cell lines and patient derived xenograft models

  Breast cancer cell lines (BCCLs) and patient-derived xenografts (PDX) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Here we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60x coverage.

  Study EGAS00001006285

• Defining structural variation associated with breast cancer susceptibility by long-read genome sequencing

  Germline structural variants (SVs) are challenging to identify by conventional genetic testing assays. Long-read sequencing has improved the global characterization of SVs, but its sensitivity at genetic loci associated with high- and moderate-penetrance cancer susceptibility has not been reported. This study used long-read genome sequencing performed on the Oxford Nanopore Technologies' PromethION to resolve variants underlying breast cancer susceptibility in sixteen individuals with pathogenic germline SVs in BRCA1, BRCA2, CHEK2 or PALB2.

  Study EGAS50000000286