15013 results for "cancer studies using rna-seq"

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• Development of New Diagnostics, Therapeutics, and Prevention Methods for Personalized Medicine Based on Comprehensive Cancer-Related Gene Exome Analysis and Information Analysis Using Cancer Specimens Stored in TMDU Biobank.

  Biobanked tumor samples are a valuable resource in real-world solid tumor research. Panel-based genomic profiling enables the identification of clinically significant alterations that inform personalized diagnostic and treatment decisions. This study aimed to characterize the genomic landscape of solid tumors collected through the TMDU Biobank by summarizing mutational, copy number, and gene fusion alterations in a large and diverse patient cohort. This dataset contains summary-level genomic information from 1,996 tumor samples analyzed by ACT Genomics and ACT med using the ACTOnco Comprehensive 440-Gene Cancer Panel. Data provided includes (1) gene-level mutation counts, (2) a summary of copy number alterations, and (3) a summary of detected fusion events. Clinical attributes such as ICD-10 codes, age group, sex, tumor mutational burden (TMB), and microsatellite instability (MSI) status were included at the aggregate level. Summary statistics were generated from three source tables (gene, sample, and copy number data) using standardized processing rules. Due to contractual and ethical considerations, individual-level mutation locations and raw sequence data are not included; only summary-level information is provided. This dataset will support future research in tumor-type-specific genomic patterns, molecular characterization of solid malignancies, and precision oncology.

  Study JGAS000863

• Pan Cancer Investigation of Human Leukocyte Antigen Loss of Heterozygosity

  Cancer cells can escape immune recognition through human leukocyte antigen (HLA) loss of heterozygosity (LOH) which results in deletion of HLA alleles, causing a reduction in presentation of tumor neoantigens. Despite its influence on immunotherapy response, few methods exist to detect HLA LOH, and accuracy of the approaches is poorly defined. Here, we present DASH (Deletion of Allele-Specific HLAs), a machine learning-based algorithm developed to detect HLA LOH from paired tumor-normal sequencing data. Using DASH to characterize HLA LOH in 610 patients across 15 cancer types, we found that 18% of patients had loss of heterozygosity in at least one HLA allele, suggesting the HLA LOH is a widespread, and potentially key immune resistance strategy in multiple cancers.

  Study phs002783

• Deciphering the genomic, epigenomic and transcriptomic landscapes of pre-invasive lung cancer lesions to determine prognosis

  Background: Lung carcinoma-in-situ (CIS) lesions are the pre-invasive precursor to lung squamous cell carcinoma. However, only half progress to invasive cancer in three years, while a third spontaneously regress. Whether modern molecular profiling techniques can identify those pre-invasive lesions that will subsequently progress and distinguish them from those that will regress is unknown. Methods: Progressive and regressive CIS lesions were laser-captured and their genome, epigenome and transcriptome interrogated. We analysed 83 progressive lesions, 41 regressive and 33 normal epithelial control samples. DNA methylation and gene expression profiles were further validated using publicly available lung cancer data. Results: Somatic mutation burden was higher in progressive lesions than regressive CIS lesions, across base substitutions, rearrangements, and copy number changes. Driver mutations were present in both progressive and regressive CIS lesions, but were more numerous in progressive cases. Progressive and regressive CIS lesions had distinct epigenomic and transcriptional profiles, with a strong chromosomal instability signature. Gene expression, methylation and copy number profiles can all predict accurately which CIS lesions will progress to lung cancer. Conclusion: Pre-invasive CIS lesions that will subsequently progress to invasive lung cancer can be distinguished from those that will regress using molecular profiling. Progression is associated with a strong chromosomal instability signature. These findings inform the development of novel therapeutic targets.

  Dataset EGAD00001003883

• Accurate detection of tumor-specific fusion genes reveals strongly immunogenic personal neo-antigens

  Fusion genes arising from cancer-associated somatic mutations are a potential rich source for highly immunogenic neo-antigens. However, their exploitation as targets for personalized cancer immunotherapy is currently limited by the lack of computational tools allowing transcriptome-wide identification of unique fusion genes in an accurate and sensitive manner. Here, we present EasyFuse, a computational pipeline, to detect individual and cancer-specific fusion genes in next-generation-sequencing transcriptome data obtained from human cancer samples. Using machine learning, EasyFuse predicts personal fusion genes with high precision and sensitivity and outperforms previously described approaches as qualified by an unprecedented ground-truth dataset of >1500 verification experiments in relevant patient samples. By testing immunogenicity with autologous blood lymphocytes from cancer patients we detected pre-established CD4+ and CD8+ T cell responses for 10 of 21 (48%), and for 1 of 30 (3%) of identified fusion genes, respectively. In conclusion, we demonstrate accurate detection of cancer-specific fusion genes. The high frequency of T cell responses detected in cancer patients support the relevance of private fusion genes as neo-antigens for personalized immunotherapies, especially for tumors with low point mutation burdens.

  Study EGAS00001004877

• Combination Immune Checkpoint Inhibition in Australian Rare Cancers_WES

  Combination immune checkpoint inhibition (ICI) with anti-CTLA-4 and anti-PD-1 blockade has demonstrated significant clinical activity across tumour types. Rare cancer patients have limited treatment options due to the scarcity of studies of novel treatment options, so they are often offered chemotherapies untested in their disease. ONJ2016-001/CA209-538 is a prospective, multicentre clinical trial of combination ICI (ipilimumab and nivolumab) in patients with advanced rare cancers, including biliary tract, adrenocortical, rare gynaecological and neuroendocrine cancers (https://clinicaltrials.gov/ct2/show/NCT02923934). The primary endpoint is clinical benefit rate (complete response + partial response + stable disease >3 months) by RECIST 1.1. This study involves generation and analysis of pre-treatment formalin fixed paraffin embedded (FFPE) tumour DNA sequencing data, paired with germline DNA sequencing data, to potentially identify genomic biomarkers that may associate with clinical benefit or other clinical efficacy / toxicity metrics.

  Dataset EGAD00001015465

• Dataset for other_cancer-EXON

  Rare cancer sequencing data of 137 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008896

• Dataset for neuroendocrine_adrenal_tumor-EXON

  Rare cancer sequencing data of 164 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008891

• Single-Cell Genomic Analysis of Gastrointestinal Cancer

  Our study aimed to define the heterogeneity of gastrointestinal cancers at a single-cell resolution. We subjected single-cell suspensions derived from surgical resections of gastrointestinal cancer tissue, paired normal tissue, peripheral blood mononuclear cells (PBMCs) or their ex vivo cultures to high-throughput microfluidics based single-cell RNA and DNA sequencing. We analyzed the features of the tumor microenvironment including fibroblasts, endothelial cells, macrophages and lymphocytes to determine their contribution to tumor growth and progression. We also characterized the mechanisms of immunosuppression in these tumors. This analysis led to novel insights into the biology of the microenvironment and also enabled the identification of new treatment targets.

  Study phs001818

• Pediatric Papillary Thyroid Carcinoma RNA-Seq

  Papillary thyroid carcinoma (PTC) is the most common malignancy amongst adolescent and young adult women. Clinical and genomic features of PTC in children differ from those in adults. Historically, a substantial proportion (~50%) of pediatric PTC (PPTC) lack any of the common driver mutations typical of adult PTC. Thus, molecular diagnostics developed for adults may not be valid in children. We applied novel bioinformatic pipelines to RNASeq analysis of pediatric thyroid tumors to identify known and novel fusion oncogenes as drivers of tumorigenesis and to define gene expression patterns among tumors. Analysis of 38 samples resulted in identification of 16 previously reported oncogenic fusions and three novel candidate fusions. In conducting these analyses, we reduced the proportion of cancers with unknown drivers from approximately 50% to 6%. Gene expression analysis identified three distinct categories of tumors. These studies represent the first unbiased genomic approach to childhood PTC. Novel bioinformatic pipeline. GEC Identified 3 distinct classes. DICER1, PTEN segregated with benign tumors. >90% of PPTC carry identifiable ongognic driver variants, however, the landscape differs from that in adults and existing tools for tumor genotyping in adults may not be applicable to pediatric tumors. BACKGROUND: Papillary thyroid carcinoma demonstrates clinically distinct behaviour in pediatric patients when compared to adults, with increased regional and distal metastases, more frequent recurrence, yet overall highly favourable prognosis. Recent tumor genotyping has demonstrated that in pediatric tumors, ***-*** do not carry the most common genomic variants found in adult PTC, leaving a substantial proportion of driver-unknown or “dark matter” tumors. METHODS: We established a cohort of 52 pediatric PTC and performed quantitative-PCR genotyping followed in a subset by whole exome and whole transcriptome (RNASeq) sequencing using a novel, robust bioinformatic pipeline to identify oncogenic fusion transcripts. Gene expression analysis was used to derive distinct clusters. RESULTS: In 52 pediatric PTC, genotyping identified BRAFV600E(21%), NRASQ61R(2%), RET/PTC1 (21%), RET/PTC3 (17%) or PAX8-PPAR in 33 (63%) of tumors. Among the remaining 19 tumors, oncogenic variants were identified in /19 (%). The variants included SNVs in DICER1, ETV6-NTRK3, PTEN and 9 additional oncogenic fusions including two previously-undescribed fusion transcripts, *** and ***. CONCLUSIONS: The genomic landscape of PTC differs between children and adults. In children, there is a substantial fraction of tumors that are unexplained by variants typical of adult PTC. This discrepancy is explained largely by uncommon oncogenic fusions which can be identified by whole-transcriptome analysis.

  Study EGAS00001005182

• Chromatin Accessibility Landscape of Human Pancreatic Ductal Adenocarcinoma (PDAC)

  Therapeutic options in pancreatic ductal adenocarcinoma (PDAC) are largely limited to cytotoxic chemotherapy without the benefit of molecular markers predicting response. By ATAC-seq analyses of EpCAM+ PDAC malignant epithelial cells sorted from 54 freshly resected human tumors, we discovered a signature of 1092 chromatin loci displaying differential accessibility between patients with disease-free survival (DFS) < 1 year and patients with DFS > 1 year. Using this signature, we further develop a chromatin accessibility microarray methodology termed “ATAC-Array”, an easy-to-use platform obviating the time and cost of next-generation sequencing. PDAC prognosis can be predicted by ATAC-array, which represents a low-cost, clinically feasible technology for assessing chromatin accessibility profiles.

  Study phs002394

• Renal_habitat_WXS

  This project aims at correlating genetic diversity (as well as transcriptomic, metabolic and immune diversity) observed in multiple targeted tumour biopsies and circulating tumour DNA with heterogeneity on multiparametric MRI. To this end, 20 patients with RCC (15 patients with localised/locally advanced disease and 5 with mRCC) will undergo multiparametric MRI including metabolic assessment by 13C-MRSI as well as measurements of tumour perfusion, oxygenation and water diffusion. Based on unique combinations of these imaging parameters, tumour habitats will be defined through cluster mapping. Intra-operative biopsy and immediate freezing of tumour cores from different imaging habitats will be performed. Multiregional ex-vivo tumour biopsies will be spatially registered to the MR data by using 3D printed tumour moulds generated from high-resolution volumetric sequences. These moulds allow slicing tumour specimens in identical planes to the MR acquisition and increase the accuracy of tissue sampling. The biopsies will then undergo molecular profiling such as metabolomic and RNA sequencing (including mRNA immune profiling), as well as DNA sequencing to assess driver and clonal mutations in different tumour habitats and guide design of appropriate cfDNA probes. The targeted cfDNA capture panel will be employed to determine the ability of cfDNA to capture the full genetic diversity observed in the primary tumour and to relate cfDNA to various imaging habitats in both renal and pancreatic cancer. Data integration will be undertaken between imaging habitats and molecular profiles for each region.

  Study EGAS00001003703

• DAC for human-derived clonal organoid studies

  This is the DAC for human-derived clonal organoid culture studies. It includes the study to investigate the clonal evolution of metastatic CRC at the single-cell level, where we performed WGS in 58 clonal organoids and 18 fresh-frozen (FT) bulk-tissue samples from surgically resected primary and metastatic tumors before and after anticancer therapies in 6 patients. This approach enabled detailed phylogenetic reconstruction of individual clones. We discovered the timing and burden of treatment-related mutations as well as the heterogeneous evolution in driver mutations and genomic rearrangements in late-stage clonal evolution under anticancer therapies in metastatic CRC.

  Dac EGAC50000000628

• Comprehensive genetic analysis of pediatric germ cell tumors

  Germ cell tumors (GCTs) are relatively rare tumors in children. Previous studies showed that adult testicular GCTs had some genomic alterations, but genetic basis of pediatric GCTs is still to be elucidated. We applied DNA methylation array analysis, whole-transcriptome sequencing, targeted capture sequencing, and SNP array analysis to fifty-one GCT samples.

  Study JGAS000204

• Precursor lesions, clonal architecture and relapse in Wilms nephroblastoma

  Targeted resequencing at high depth (21 genes, 9 chromosomal regions): at least 4 FFPE samples per case and matched germline DNA: * 100 cases with detailed outcome data, including 15 cases with tumour relapse (515 samples) * 40 cases with matched pre-chemotherapy biopsies (240 samples) * 50 nephrogenic rests matched to above cases (50 samples) We expect a proportion (possibly 10%) of cases to be mutationally silent on the above studies, and propose to subsequently carry out integrated whole-genome, methylome and transcriptome studies on matched frozen tissue from these cases

  Dataset EGAD00001003217

• HipSci-RNAseq-healthy volunteers

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sup-study we perform RNAseq on iPS cells generated from skin biopsies from healthy volunteers.

  Study EGAS00001000593

• Targeted sequencing data and shallow whole genome sequencing data of Follicular lymphoma.

  Contain data of 2 studies 1: 82 nodal stage 1 FL cases and 139 stage III/IV cases 2: 44 watch and wait stage III/IV and 46 Immediate treatment stage III/IV targeted sequencing data of 369 genes and 12 translocation regions whole genome shallow sequencing data

  Study EGAS00001005755