10161 results for "cancer rna-seq"

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• The somatic mutation landscape of normal gastric epithelium - TGS

  The landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into embryogenesis, normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing and targeted panel sequencing of microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium.

  Dataset EGAD00001015352

• The somatic mutation landscape of normal gastric epithelium - WGS

  The landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into embryogenesis, normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing and targeted panel sequencing of microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium.

  Dataset EGAD00001015351

• Genetic landscape of pediatric Osteosarcoma

  We performed whole-genome sequencing of 37 paired tumor/normal OS genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes

  Study EGAS00001000263

• Genetic landscape of pediatric Rhabdomyosarcoma

  We performed whole-genome sequencing of 13 paired tumor/normal Rhabdomyosarcoma genomes and analyzed somatically acquired single nucleotide variations SNVs, insertion/deletions, structural variations and copy number variations in the cancer genomes

  Study EGAS00001000256

• WES and RNAseq dataset

  This dataset includes WES and RNAseq for 7 patients with metastatic melanoma (4), non-small cell lung adenocarcnioma (1), cervix adenocarcinoma (1), and Epidermoid nasophaeyngeal carcinoma (1), enrolled in phase I clinical trials (NCT03475134m NCT04643574 and NCT05195619). WES was performed on matched cancer and healthy tissues, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 4000/6000 and Illumina NextSeq 500/550 systems.

  Dataset EGAD50000000337

• Genetic and immune landscape evolution defines subtypes of MMR deficient colorectal cancer

  Genomic data from a cohort of 19 MMR deficient colorectal cancers and 1 MMR proficient colorectal cancer. All cases were target gene DNA sequenced using multiple primary and where available metastatic tumour regions from surgical resection samples.

  Dataset EGAD00001008334

• ICARUS-BREAST01-ExomeSeq

  Efficacy, safety and biomarker analysis of ICARUS-BREAST01: a phase 2 Study of Patritumab Deruxtecan in patients with HR+/HER2- advanced breast cancer. Whole-exome sequencing (WES) is available for 43 tumor samples and 43 blood samples collected at entry into the trial.

  Study EGAS50000000542

• WES data from primary CRCs tissues in ctDNA positive patients

  Whole exome data from primary colorectal cancer tissue samples were analysed in patients where mutations where found in circulating tumour DNA. DNA was extracted from FFPE blocks and exome libraries were prepared using the KAPA HyperPlus Kit (Roche diagnostics)

  Study EGAS50000000650

• Whole Genome Sequencing of Asian Lung Cancers: Second Hand Smoke is Not Responsible for Higher Incidence of Lung Cancer Among Asian Never-Smokers

  Background Asian nonsmoking populations have a higher incidence of lung cancer compared to their European counterparts. There is a long-standing hypothesis that the increase of lung cancer in Asian never-smokers is due to environmental factors such as second-hand smoke. Results We analyzed whole-genome sequencing of 30 Asian lung cancers. Unsupervised clustering of mutational signatures separated the patients into two categories: i) all of the never-smokers, and ii) only smokers or ex-smokers. Half of the ex-smokers / smokers were in the never-smoker-like cluster. The overall somatic variant profiles of Asian lung cancers were similar to that of European origin with G.C>T.A being predominant in smokers. We found EGFR and TP53 are the most frequently mutated genes with mutations in 50% and 27% of individuals, respectively. Among these Asian never-smokers, 71% had an EGFR mutation compared to 20% of the smokers in the smoking cluster. Other frequently mutated genes include RYR2, SATB2, C1orf88, FERMT1 and CTNNB1. Somatic alterations occurred in WNT signaling pathway genes, suggesting this pathway plays a role in both Western and Asian lung cancers. Conclusions Asian never-smokers have lung cancer signatures distinct from the smoker signature and their mutation profiles are similar to that of European never-smokers. The profiles of Asian and European smokers are also similar. This suggests that the same mutational mechanisms underlie the etiology for both ethnic groups, and the high incidence of lung cancer in Asian never-smokers might not be due to second hand smoke or other carcinogens that cause oxidative DNA damage. Half of the ex-smokers/smokers have a molecular phenotype similar to never-smokers; of which, 50% had EGFR mutations. This suggests that routine EGFR testing is warranted in the Asian population, regardless of smoking status.

  Study EGAS00001000621

• Childhood Cancer Data Initiative (CCDI): Genomic Analysis in Pediatric Malignancies

  Pediatric solid tumors are highly heterogeneous, encompassing a large number of histotypes. The genomic landscape of these diseases is characterized by few single-nucleotide variants (SNVs) compared to adult cancers. In contrast, many exhibit a high prevalence of structural or epigenetic changes that alter gene expression, underlining the need for comprehensive genomic approaches such as whole-genome sequencing (WGS). Several studies have specifically addressed the clinical utility of genomic analysis in the pediatric and AYA cancer setting. Review of these studies point to key challenges that must be addressed in order to advance the routine use of genomics in this population. We have established a large collection of solid tumor tissue samples through our biobanking efforts. Where possible, we obtain longitudinal samples from the same patient. These primary patient samples and their corresponding germline have been analyzed using whole genome and whole transcriptome sequencing methods and have been linked to clinical metadata using both manual curation and robust methods for automatic extraction from the electronic health record (EHR). Importantly, research-grade genomic analysis is performed in parallel to our CLIA-grade sequencing (“UCSF500”) efforts for some of the patients in this study cohort and have been submitted as part of the American Association for Cancer Research's project GENIE and/or the National Childhood Cancer Registry. For our sequenced tumor samples, we have retrospective clinical data and ongoing efforts to prospectively record key events throughout the patient's cancer journey. In our solid tumor program, we have developed many patient-derived xenograft models and a number of PDX-derived cell lines. These unique models have been evaluated using genomic and functional approaches including (in some cases) treatment with conventional chemotherapy or investigational agents. Lastly, these samples were collected from a population that is among the most diverse in the nation and includes significant numbers of Asian, Latino, Indigenous and African-American patients, groups that are traditionally underrepresented in many banking efforts.

  Study phs002430

• Recurrent somatic DICER1 mutations in non-epithelial ovarian tumors

  Study EGAS00001000135

• Validation of a targeted sequencing panel for multiple myeloma

  Study EGAS00001006164

• RNAseq analysis on primary sites Colorectal Cancer xenografts (PRX) samples

  Study EGAS00001007051

• UCL Cancer Institute DAC

  Dac EGAC00001001579

• AUBTRG - Whole Exome Sequencing of Diffuse Glioma Samples

  Study EGAS00001003035

• Treated and control Patient Derived Xenografts of colorectal cancer (CRC) samples

  Dac EGAC00001003073

• Accelerated single cell seeding in relapsed multiple myeloma

  Study EGAS00001004404

• Whole exome sequencing from small cell lung cancer patients

  Study EGAS00001005087

• Molecular analysis of inflammatory myofibroblastic tumor (WGS and WES)

  Study EGAS00001005081

• Data Access Commitee of Nanjing Medical University Affiliated Jiangsu Cancer Hospital

  Dac EGAC00001003206

• Molecular characterization of a renal cell carcinoma PDX cohort

  Study EGAS00001006249

• DAC: British Columbia Cancer Agency (BCCA), PHSAs Technology Development Office, Data Access Committee

  Dac EGAC00001000122

• DAC of Synergie Lyon Cancer

  Dac EGAC00001000382

• DAC for study Treg in breast cancer and healthy individuals

  Dac EGAC00001000638

• DAC for NKTL study. National Cancer Centre Singapore.

  Dac EGAC00001000640

• Stanford Data Access Committee for Breast Cancer Tumor Heterogeneity through Treatment

  Dac EGAC00001000993

• Genome-wide association study of cervical cancer in East Asian populations

  Dac EGAC00001001024

• University Clinic Erlangen/ German Cancer Research Center rare tumors data access committee

  Dac EGAC00001001053

• High-grade serous ovarian cancer (MDACC) data access committee

  Dac EGAC00001001288

• Single Cell RNAseq of blood and tumor from renal cancer patients

  Dac EGAC00001001494

• NKI (Netherlands Cancer Institute)

  Dac EGAC00001001648

• Data Access Commitee of Nanjing Medical University Affiliated Jiangsu Cancer Hospital

  Dac EGAC00001001774

• Long-read isoform in breast cancer - Data Access Commitee

  Dac EGAC00001001821

• Data Access Commitee of Nanjing Medical University Affiliated Jiangsu Cancer Hospital

  Dac EGAC00001002086

• University of Melbourne Centre for Cancer Research (UMCCR) Data Access Committee

  Dac EGAC00001002442

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001002975

• EGAD00010000622

  SNP array data for gastric cancer cell lines

  Dataset EGAD00010000622

• nanostring analysis

  mRNA expression profile of kidney cancer

  Dataset EGAD00010001535

• OvCan1

  Digital images of ovarian cancer sections

  Dataset EGAD00010000881

• Study of the microenvironment of angioimmunoblastic T-cell lymphoma

  Study EGAS00001006401

• Array-based methylation analysis of SDHB-deficient pheochromocytoma and paraganglioma

  Study EGAS00001007844

• Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial

  Summary of the Design and Aims: The Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial (CAF-PINT) is an ancillary study to the HALF PINT (NCT01565941) randomized, controlled trial that was originally designed to study changes in inflammatory and thrombosis pathways in the setting of an interventional trial. The parent HALF PINT study was designed to study the impact of tight glycemic control (TGC) using an explicit insulin titration algorithm to safely achieve a normal glucose in target range of 80-110 mg/dL versus 150-180mg/dL on clinical outcomes among critically ill hyperglycemic children with Heart and Lung Failure. The CAF PINT study collected blood samples pre randomization and at 2 and 4 days after randomization. Blood samples collected in EDTA tubes were centrifuged at local sites to separate the plasma from cell pellets and frozen prior to shipment. In addition, 0.5 mL of whole blood collected in PAXgene tubes modified for use in pediatrics frozen 24 hours after collection prior to shipment.Population Information: Setting: Twenty-one academic children's hospitals (HALF-PINT) and 1 academic children's hospital (IIT-SBPP). Participants: Critically ill hyperglycemic children requiring mechanical ventilation/vasoactive support (n=293).Interventions and Exposures: Patients in HALF PINT were randomized to achieve a low target glucose (80-110 mg/dL) vs. a higher target (150-180 mg/dL). The primary trial was stopped early due to low likelihood of achieving a statistically significant difference in the primary outcomes. Molecular Technologies Employed: Plasma biomarkers were assayed on thawed plasma using a Luminex panel. RNA was extracted from PAXgene Blood RNA Kits modified for pediatric use. Extracted RNA was sequenced with the Novaseq S4 system (Illumina) to generate 2 x 150 base paired end reads to a target depth of 50 million read-pairs per sample.Principal Findings of the Study: We tested for heterogeneity of treatment effects according to baseline blood inflammatory proteins using logistic regression with individual biomarkers as interaction terms and Cox regression analysis using biomarker-derived latent classes. Children with higher inflammatory proteins including TNFR-1, IL-6, IL-8, and IL-10 had lower mortality when treated with insulin to a target glucose of 80-110 mg/dL as compared to 150-180 mg/dL (interaction p<0.05). Causal forest estimates ranged from a 40% mortality reduction to a 15% mortality increase with TGC, depending on each patient’s individual biomarker profile. Latent class categorization strongly interacted with TGC with respect to mortality (Cox regression interaction p=0.005). Specifically, patients with higher inflammation benefited from TGC (6% mortality with TGC vs. 48% mortality, p=0.004) whereas hypoinflamed patients showed a trend towards harm (14% mortality with TGC vs. 7% mortality, p=0.055).Data available through dbGaP: Transcriptomic (Gene Counts) and phenotype data

  Study phs003016

• Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

  These data relate to Abbosh et al 2023 'Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA'. Some patients were included in this work that were excluded from the other TRACERx 421 papers (Frankell et al and Al-bakir et al) often due to exclusion criteria in the TRACERx clinical trial. Reasons include partial contamination with C>A artefact mutational signature (CRUK0480 ,0490) which were included for ctDNA detection analyses using high confidence clonal mutations but not clonality analyses, incomplete resection at primary surgery (CRUK0291, 0234, 0230, 0387, 0622) and a concurrent oesophageal second primary cancer (CRUK0498). The primary tissue exome sequencing for these patients that were used in this study are included in this repository. Deep targeted sequencing of (median 200) tumour specific mutations in plasma for 1069 samples from 198 TRACERx patients are also included. Additional details related to these patients and samples can be found in the supplementary or data repositories from Frankell et al and Abbosh et al.

  Study EGAS00001006923

• The immunopeptidome landscape associated with T cell infiltration, inflammation and immune-editing in lung cancer

  One key barrier for improving efficacy of cancer immunotherapy remains patient stratification. While patients with CD3+CD8+ T cell inflamed ‘hot’ tumors typically show better response to immune checkpoint inhibitors, it is still unknown if the repertoire of HLA bound peptides (HLAp) presented in ‘hot’ and ‘cold’ tumors is substantially different. We surveyed 61 tumor regions and adjacent non-malignant lung tissues from eight lung cancer patients and performed deep antigen discovery combining immunopeptidomics, genomics, bulk and spatial transcriptomics and explored the heterogenic expression and presentation of tumor (neo)antigens. We associated diverse immune cell populations with the immunopeptidome in CD3+CD8+ T cell excluded, infiltrated, hot and cold tumors and found evidence for lack of immune-editing and higher presentation efficiency of tumor antigens in cold and CD3+CD8+ T cell excluded tumors. This could have implications for the choice of combination therapies tailored to the patient’s mutanome and microenvironment.

  Study EGAS00001006298

• Real-time response profiling through serial plasma analyses during FOLFOX treatment in patients with colorectal cancer

  Response evaluation of cancer therapeutics relies on the assessment of the change in tumor burden, which is performed in accordance with defined criteria every 8-12 weeks. However, predictive factors for response are not available for the majority of patients with advanced stage colorectal cancer. Here we show that measurement of circulating tumor DNA (ctDNA) levels during one of the most commonly administered drug regimens, i.e. FOLFOX, allows an early, real-time assessment of treatment response. During the 48-hour FOLFOX application, we serially assessed plasma DNA and observed that ctDNA levels initially decreased during the first 23 hours. In patients with stable disease or partial response, ctDNA levels remained low, whereas in patients with progressive disease, ctDNA levels increased at the end of the treatment cycle predicting clinical and radiologic response correctly. Hence, ctDNA monitoring during treatment may contribute to an early outcome prediction with significant implications for the management of patients.

  Study EGAS00001004213

• The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  High-grade serous ovarian cancer exhibits extensive intratumoral heterogeneity coupled with widespread intraperitoneal disease. Despite this, metastatic spread of tumor clones is non-random, implying the existence of local microenvironmental factors that shape tumor progression. We interrogated the molecular interface between tumorinfiltrating lymphocytes (TIL) and cancer cells in 143 samples from 21 patients using whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T- and B-cell receptor sequencing. We identify 3 immunologic response categories, which frequently co-exist within individual patients. Furthermore, epithelial CD8+ TIL were inversely associated with malignant cell diversity, evidenced by subclonal neoepitope elimination and spatial tracking between tumor and T-cell clones. Intersecting mutational signatures and immune analysis showed that foldback inversion genomic aberrations lead to worse outcomes even in the presence of cytotoxic TIL (n=433). Thus, regional variation in immune contexture mirrors the pattern of intraperitoneal malignant spread, provoking new perspectives for treatment of this challenging disease.

  Study EGAS00001002839

• Molecular Subtype-specific Biomarkers Improves Colorectal Cancer Prognostication

  Colorectal cancer (CRC) is characterized by major inter-tumor diversity that complicates the prediction of disease and treatment outcomes. Recent efforts help resolve this by sub-classification of CRC according to natural molecular subtypes, however, this strategy is not yet able to provide clinicians with improved tools for decision-making. We here present an extended framework for CRC stratification that specifically aims to improve patient prognostication. Using transcriptional profiles from 1,100 CRCs, including a novel set of >300 samples, we identify novel cancer cell and tumor archetypes and suggest the tumor microenvironment as a major prognostic determinant that can be influenced by the microbiome. Notably, our subtyping strategy allowed identification of novel archetype-specific prognostic biomarkers that provided information beyond and independent of UICC-TNM staging, MSI-status and consensus molecular subtyping. The results illustrate that our extended subtyping framework, combining subtyping and subtype-specific biomarkers, could contribute to improved patient prognostication and may form a strong basis for future studies.

  Study EGAS00001002376

• Clinical Implications of Genomic Alterations in the Tumor and Circulation of Pancreatic Cancer Patients

  Pancreatic adenocarcinoma has the worst mortality of any solid cancer. To evaluate the clinical implications of genomic alterations in this tumor type, we performed whole-exome analyses of 24 tumors, targeted genomic analyses of 77 tumors, and used non-invasive approaches to examine tumor-specific mutations in the circulation of these patients. These analyses reveal somatic mutations in chromatin regulating genes MLL, MLL2, MLL3, and ARID1A in 20% of patients that were associated with improved survival. We observe alterations in genes with potential clinical utility in over a third of cases. Liquid biopsy analyses demonstrate that 43% of patients with localized disease have detectable circulating tumor DNA (ctDNA) at diagnosis. Detection of ctDNA after resection predicts clinical relapse and poor outcome, and recurrence by ctDNA is detected 6.5 months earlier than with CT imaging. These observations provide genetic predictors of outcome in pancreatic cancer and have implications for new avenues of therapeutic intervention.

  Study EGAS00001001257

• Data from the paper Context-specific Effects of TGFβ/SMAD3 in Cancer Are Modulated by the Epigenome. Tufegdzic et al, Cell Reports 2015

  The transforming growth factor beta (TGFβ) signalling pathway exerts opposing effects on cancer cells, acting either as a tumor-promoter or as a tumor-suppressor. Here we show these opposing effects are a result of the synergy between SMAD3, a downstream effector of TGFβ signalling, and the distinct epigenomes of breast tumor initiating cells (BTICs). These effects of TGFβ are associated with distinct gene expression programs, but genomic SMAD3 binding patterns are highly similar in the BTIC-promoting and BTIC- suppressing contexts. Our data show cell type-specific epigenetic configurations provide a modulatory layer by determining accessibility of genes to regulation by TGFβ/SMAD3. LBH, one such context-specific target gene, is regulated according to its DNA methylation status, and is crucial for TGFβ-dependent promotion of BTICs. Overall, these results reveal that the epigenome plays a central and previously overlooked role in shaping the context-specific effects of TGFβ in cancer.

  Study EGAS00001001570

• Contribution of allelic imbalance to colorectal cancer

  Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge, and unbiased CRISPR-Cas9 knockout and activation screens identified altogether 79 genes within AI peaks regulating cell growth. Genetic and functional data implicates loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers.

  Study EGAS00001002966