12322 results for "cancer rna-seq"

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• 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

• 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

• 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

• 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

• Application of organoid culture system of human gastrointestinal and thoracic cancer in genome medicine

  In order to establish preclinical models, we have established three kinds of esophageal tumoroids derived from esophageal cancer patient. We performed whole exome sequencing to analyze genetic background of the tumoroids.

  Study JGAS000749

• Duplex sequencing of selected breast cancer patients

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primaty tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000769

• WES of breast cancer patients and controls

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primary tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000770

• Breast_Cancer_Matched_Pair_Cell_Line_Whole_Genomes

  We propose to definitively characterise the somatic genetics of matched pair breast cancer cell lines through generation of comprehensive catalogues of somatic mutations by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000166

• Y_chromosome_mis_segregation_in_the_DLD_1_cell_line

  Study of the well-established DLD-1 colorectal cancer cell line, engineered with an inactivatable Y centromere that leads to mis-segregation. The goal is to gain insights into the mechanism of chromothripsis due to chromosome mis-segration.

  Study EGAS00001002551

• Triple_Negative_Breast_Cancer_Whole_Genomes

  We propose to definitively characterise the somatic genetics of Triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses.

  Study EGAS00001000092

• Transcriptome_Sequencing_of_Cancer_Cell_Lines

  In this study we will sequence the transcriptome of Verified Cancer Cell lines. This will be married up to whole exome and whole genome sequencing data to establish a full catalog of the variations and mutations found.

  Study EGAS00001000261

• Colorectal cancer genomics with primary and metastatic samples

  We performed whole genome sequencing of metastatic colorectal cancer from 16 patients. Normal adjacent tissue, primary tissue, and metastatic tissue were analyzed to uncover metastatic progression and difference between primary and distant metastatic lesions.

  Study EGAS00001006465

• Colorectal cancer transcriptomics with primary and metastatic samples

  We performed RNAseq analysis of metastatic colorectal cancer from 16 patients. Normal adjacent tissue, primary tissue, and metastatic tissue were analyzed to uncover metastatic progression and difference between primary and distant metastatic lesions.

  Study EGAS00001006464

• Whole exome and targeted sequencing of non-muscle-invasive bladder cancer

  Tumor-blood paired whole-exome sequencing of 58 pairs of non-muscle-invasive bladder cancer samples (stageT1). Targeted sequencing of 112 non-muscle-invasive bladder cancer samples (34 stage T1; 78 stage Ta) Please note the following files have been removed: EGAR00003025153, EGAR00003025435, EGAR00003025294, EGAR00003025262, EGAR00003025224.

  Dataset EGAD00001008332

• RNASeq data from one small cell prostate cancer patient (4 samples from 3 time points)

  RNASeq data from one small cell prostate cancer patient - 4 cancer samples (FFPE) from Patient 1 collected at 3 different time points. mRNA was selected using the Magnetic mRNA Isolation Module (NEB) and sequenced on the Illumina NextSeq 500 as 75bp paired end reads (total read length 150bp).

  Dataset EGAD00001011154

• Whole-genome sequencing of paired tumor and blood samples from 65 bladder cancer patients

  65 paired tumor and normal whole-genome sequencing samples from urothelial bladder carcinomas (UBC, the most common type of bladder cancer) are used to uncover the whole-genome mutational landscape of UBC. Recurrent mutations in noncoding regions affecting gene regulatory elements and structural variations leading to gene disruptions are prevalent in this type of cancer.

  Dataset EGAD00001004545