15020 results for "cancer studies using rna-seq"

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• Evaluation of whole genome sequencing utility in identifying driver alterations in cancer genome

  This study aimed to assess the effectiveness of whole genome sequencing (WGS) compared to whole exome sequencing (WES) in identifying driver alterations in cancer genomes. Out of 177 cases with no driver alterations detected by WES, WGS identified driver alterations in 68.4% and likely driver alterations in 22.6% of cases. The most common alterations found were oncogene amplifications, tumor suppressor gene deletions, and small variants outside coding regions. WGS proved valuable in uncovering genomic changes associated with cancer development.

  Study JGAS000715

• Metabolomic and transcriptomic analyses identify metabolic alterations and immune suppression in ovarian cancer

  The objective of this study is to identify metabolic alterations and related phenotypes specific to ovarian cancer by performing metabolomic analysis of plasma and tissue samples. In addition, transcriptomic analysis is conducted to investigate the relationship between metabolic status and immune-related gene expression. By integrating metabolomic and transcriptomic data, this study aims to clarify how metabolic reprogramming contributes to tumor progression and immune suppression, particularly the reduction of natural killer (NK) cell activity, in ovarian cancer.

  Study JGAS000831

• 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

• 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

• 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

• Whole Genome Sequencing Data of High Grade Serous Ovarian Cancer

  Longitudinal whole genome sequencing data to study chemoresponse in ovarian cancer. These samples belong to an ongoing sample collection and the data already includes hundreds of samples from over 200 patients. Samples are from primary and metastatic tissues and ascites. All patients have been treated with platinum-taxane based chemotherapy and majority of them are diagnosed with high-grade serous ovarian cancer.

  Study EGAS00001006775

• 20 Matched Pair Breast Cancer Genomes

  20 Matched Pair Breast Cancer Genomes

  Dataset EGAD00001000082

• bulkRNAseq of ovarian cancer cell lines

  bulkRNAseq of four ovarian cancer cell lines (PA-1, A2780, A2780/CP20, TOV-21G)

  Dataset EGAD50000002059

• Cancer-associated genome-wide hypomethylation and copy number aberrations

  Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

  Dataset EGAD00001001093

• Amplicon sequencing data from organoids of colorectal cancer patients.

  The dataset includes 13 bam files. Each bam file is a different colorectal cancer patient organoid.

  Dataset EGAD00001004313