11925 results for "cancer rna-seq"

in 15.61 milliseconds.

• Ontario Familial Colon Cancer Registry Single Nucleotide Polymorphisms and CpG Methylation (OFCCR SNP-CpG)

  We profiled the methylation landscape of ~2100 DNA samples (~1100 cases of colorectal cancer and ~1000 controls) from the Ontario Familial Colon Cancer Registry (OFCCR) using the HumanMethylation450 array from Illumina. DNA was extracted from lymphocyte pellets, except for 99 samples for which DNA was extracted from lymphoblastoid cell lines. Samples were genotyped on the Affymetrix Human Mapping 100k and 500k arrays. The aim the study was to evaluate the interplay between genetic variation and methylation, including long-range epigenetic regulation.

  Study phs000779

• Human Skin Cancer Atlas, Medical University of Vienna Data Access Policy

  Cancer-associated fibroblasts (CAFs) play a key role in cancer progression and treatment outcome. Here, we elucidate the yet unresolved intra-tumoral CAF variety in three skin cancer types at molecular and spatial single-cell resolution in a large cohort. We show that two out of three CAF subtypes contribute to tumor immune surveillance with distinct mechanisms. Matrix CAFs (mCAFs) ensheath tumor nests and synthesize extracellular-matrix to prevent T cell invasion. Immunomodulatory CAFs (iCAFs), which express proinflammatory and immunomodulatory factors, are only detected in high abundance in aggressive tumors. Strikingly, iCAFs but not tumor cells are (apart from immune cells) the exclusive cell type producing chemokines and, thus, play a key role in immune cell recruitment and activation. Mechanistically, we show that cancer cells transform adjacent healthy fibroblasts into cytokine-expressing iCAFs, which subsequently recruit immune cells and modulate the immune response. In conclusion, targeting CAF variants holds promise for improved efficacy of immunotherapy.

  Dac EGAC50000000154

• WES of breast cancer patients and controls

  This study assessed the variant profiles of 408 samples from 126 breast cancer patients with various survival outcomes, including paired uninvolved mammary gland samples collected at proximal distances from primary lesions. As a reference, control samples from 15 mammoplasty individuals without cancer history were studied. Whole exome sequencing was performed to identify post-zygotic and germline variants present in the studied samples. Variant annotation in known databases, interpretation, and statistical analyses followed to discern the clinical relevance of called variants.

  Study EGAS50000000539

• analysis of immune infiltration in colorectal cancer metastasis

  Metastatic colorectal cancer (mCRC) is the main cause of CRC mortality, with limited treatment options. Although immunotherapy has benefited some cancer patients, mCRC typically lacks the molecular features that respond to this treatment. However, recent studies indicate that the immune microenvironment of mCRC may be modified to enhance the effect of immune checkpoint inhibitors. This study aimed to explore the metastatic immune microenvironment by comparing immune cell populations in colorectal liver (CLM), lung (mLu) and peritoneal (PM) metastases.

  Study EGAS50000000652

• Uncovering Principles of Adaptive Regulation in Cancer Resistance Through Deep Evolutionary Profiling

  A comprehensive understanding of the emergence of therapy resistance in cancer requires new approaches capable of generating and characterizing drug resistant cell lines at scale. Here, we present the EVolution Of Lineages in Vitro (EVOLV) platform, a high-throughput approach for generating diverse libraries of viable, drug-resistant cell lines from a common progenitor. EVOLV enables deeper insights into the genomics of drug resistance as well as into the complex interplay among genomic, transcriptomic, and functional layers during cancer evolution.

  Study phs003851

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• Cancer-independent, second somatic NF1 mutation of normal tissues in neurofibromatosis type 1

  Cancer predisposition syndromes mediated by recessive cancer genes generate tumours via somatic variants (second hits) in the unaffected allele. Second hits may or may not be sufficient for neoplastic transformation. Here, we performed whole genome and exome sequencing on 479 tissue biopsies from a child with neurofibromatosis type 1, a multi-system cancer-predisposing syndrome mediated by constitutive monoallelic NF1 inactivation. We identified multiple independent NF1 driver variants in histologically normal tissues, but not in 610 biopsies from two non-predisposed children. We corroborated this finding using targeted duplex sequencing, including a further nine adults with the same syndrome. Overall, truncating NF1 mutations were under positive selection in normal tissues from individuals with neurofibromatosis type 1. We demonstrate that normal tissues in neurofibromatosis type 1 commonly harbour second hits in NF1, the extent and pattern of which may underpin the syndrome's cancer phenotype.

  Dataset EGAD00001015398

• 20 Matched Pair Breast Cancer Genomes

  20 Matched Pair Breast Cancer Genomes

  Dataset EGAD00001000082

• University of Hull

  Tumour Regulatory Molecules in Early Pancreatic Cancer Detection (TEM-PAC) and EARLY DIAgnosis of PAncreatic Cancer by combined proteomics and genomics testing of pancreatic cyst fluid (DIA-PAC) studies.

  Dac EGAC50000000402

• 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

• KiCS cancer panel academic only data

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009733

• EORTC RP1335 SPECTA Lung cancer data - Oncomine

  EORTC RP1335 SPECTA Lung cancer data - Oncomine dataset

  Dataset EGAD00001006594

• Circulating Tumor Cell Heterogeneity in Neuroendocrine Prostate Cancer by Single Cell Copy Number Analysis

  Neuroendocrine prostate cancer (NEPC) is an aggressive variant of prostate cancer that may arise de novo or develop from pre-existing prostate adenocarcinoma as a mechanism of treatment resistance. Combined loss of tumor suppressors RB1, TP53, PTEN are frequent in NEPC but also present in a subset of prostate adenocarcinomas. Most clinical and preclinical studies support a trans-differentiation process, whereby NEPC arises clonally from a prostate adenocarcinoma precursor during the course of treatment resistance. Here we highlight a case of NEPC with significant intra-patient heterogeneity observed across metastases. We further demonstrate how single-cell genomic analysis of circulating tumor cells combined with phenotypic evaluation of cellular diversity can be considered as a window into tumor heterogeneity in patients with advanced prostate cancer. We performed whole genome sequencing of circulating tumor cells (CTCs) from patients with castration resistant adenocarcinoma (n=4) and neuroendocrine prostate cancer (n=8). CTCs were collected via Epic Sciences platform and single CTC genomic data (n=215) generated via Illumina NextSeq500. 

  Study phs002462

• Genomic Alterations in Normal Breast Tissues Preceding Breast Cancer Diagnosis (GANPBC)

  This study was designed to examine the genomic alterations in histologically normal breast tissues of women who subsequently developed breast cancer and compare it to breast tissues from women who did not. Breast core needle biopsy tissues from 160 healthy women at the Susan G. Komen Tissue Bank were requested for this study and sequenced using whole exome sequencing. The samples included tissues from 79 participants who, during the annual follow-up with Susan G. Komen self-reported a subsequent diagnosis of invasive or non-invasive breast cancer after tissue submission; these cases were classified as pre-diagnosis normal tissues. The remaining 81 samples were from women who had no cancer diagnosis at their last follow-up and were classified as healthy control samples. Among the pre-diagnosis samples, the average time from tissue donation to breast cancer diagnosis was 4.7 years (range: 0-11). For the healthy controls, the average time from tissue donation to the last follow up was 6.1 years (range: 0-14).

  Study phs003822

• Identification and Characterization of Cancer Mutations in Japanese LungAdenocarcinoma without Sequencing of Normal Tissue Counterparts

  We analyzed whole-exome sequencing data from 97 Japanese lung adenocarcinomapatients and identified several putative cancer-related genes and pathways. Particularly, we observed that cancer-related mutation patterns were significantly different between different ethnic groups. As previously reported, mutations in the EGFR gene were characteristic to Japanese, while those in the KRAS gene were more frequent in Caucasians. Furthermore, during the course of this analysis, we found that cancer-specific somatic mutations can be detected without sequencing normal tissue counterparts. 64% of the germline variants could be excluded using a total of 217 external Japanese exome datasets. We also show that a similar approach may beused for other three ethnic groups, although the discriminative power depends on the ethnic group. We demonstrate that the ATM gene and the PAPPA2 gene could be identified as cancer prognosis related genes. By bypassing the sequencing of normaltissue counterparts, this approach provides a useful means of not only reducing the time and cost of sequencing but also analyzing archive samples, for which normal tissue counterparts are not available.

  Study JGAS000001