16490 results for "sec+and+unspecified+malignant+neoplasm"

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• Sex chromosome aneuploidies give rise to changes in the circular RNA profile

  Purpose The landscape of circular RNAs (circRNAs), an important class of non-coding RNAs that regulate gene expression, has never been described in human disorders of sex chromosome aneuploidies. We profiled circRNAs in Turner syndrome females (45,X;TS) and Klinefelter syndrome males (47,XXY; KS) to investigate how circRNAs respond to a missing or an extra X chromosome. Methods Samples of blood, muscle and fat were collected from individuals with TS (n = 33) and KS (n = 22) and from male (n = 16) and female (n = 44) controls. CircRNAs were identified using a combination of circRNA identification pipelines (CIRI2, CIRCexplorer2 and circRNA_finder). Results Differential expression of circRNAs was observed throughout the genome in TS and KS, in all tissues. The host-genes from which several of these circRNAs were derived, were associated with known phenotypic traits. Furthermore, several differentially expressed circRNAs had the potential to capture micro RNAs that targeted protein-coding genes with altered expression in TS and KS. Conclusion Sex chromosome aneuploidies introduce pervasive changes in the circRNA transcriptome, demonstrating that the genomic changes in these syndromes are more complex than hitherto thought. CircRNAs may help explain some of the genomic and phenotypic traits observed in these syndromes.

  Study EGAS00001006404

• T cell responses of ALS patients

  In this project, we aimed to understand how T cell responses contribute to the disease progression of amyotrophic lateral sclerosis (ALS). The present data is on single-cell sequencing isolated from human cerebrospinal fluid (CSF) cells from both ALS patients (n=5) and controls (n=4). This analysis was conducted as part of a bigger project which is summarized in the section below. We used flow cytometry to define T cell subsets and phenotypes in blood and CSF samples collected at the time of diagnosis on a cohort of 89 newly diagnosed ALS patients in Stockholm, Sweden. High frequency of CD4+FOXP3- effector T cells in blood and CSF was associated with poor survival whereas high frequency of activated regulatory T (Treg) cells and high ratio between activated and resting Treg cells in blood was associated with better survival. T cell profiles also predicted disease progression rate. On an independent cohort of cases and controls, we used single cell transcriptomics data to demonstrate that ALS patients had altered T cell gene expression patterns and clonally expanded CD4+ and CD8+ T cells in CSF. In summary, T cell responses contribute to disease progression of ALS, supporting modulation of adaptive immunity as a viable therapeutic option.

  Study EGAS00001006675

• T cell landscape definition by multi-omics identifies galectin-9 as novel immunotherapy target in chronic lymphocytic leukemia (CLL)

  Failure of immunotherapy after applying checkpoint inhibitors or CAR-T cells is linked to T cell exhaustion. Here, we explored the T cell landscape in chronic lymphocytic leukemia (CLL) by single-cell omics analyses of blood, bone marrow and lymph node samples of patients and spleen samples of a CLL mouse model. By single-cell RNA- sequencing, mass cytometry (CyTOF), and multiplex image analysis of tissue microarrays, we defined the spectrum of phenotypes and transcriptional programs of T cells and and their differentiation state trajectories. We identified disease-specific accumulation of distinct regulatory T cell subsets and T cells harboring an exhausted phenotype exclusively in the CLL lymph node tissue. Integration of TCR data revealed a clonal expansion of CD8+ precursor exhausted T cells, suggesting their reactivity for CLL cells. Interactome analyses identified the TIM3 ligand Galectin-9 as novel immunoregulatory molecule in CLL. Blocking of Galectin-9 in CLL-bearing mice slowed down disease development and reduced the number of TIM3 expressing T cells. Galectin-9 expression correlated with shorter survival of CLL patients. Thus, Galectin-9 contributes to immune escape in CLL and represents a novel target for immunotherapy.

  Study EGAS00001006864

• CIP: Differential Response to Hydroxyurea and Incidence of Stroke in Sickle Cell Disease

  Sickle cell disease (SCD) is a severe debilitating hematological disorder associated with a high degree of morbidity and mortality. There are approximately 200,000 babies born with sickle cell disease each year, with the disease predominately affecting individuals in Africa. The overall global burden of the disease is tremendous, with more than 100,000 patients currently in the US and further millions worldwide. The governing bodies of the World Health Organization have recently adopted a resolution to strengthen the response to sickle disease in all affected countries and there is a definite need for high quality sickle cell disease research that has the potential to improve the treatment and prognosis of patients with this devastating disease. The clinical manifestations of SCD arise from a complex pathophysiology that includes hemolysis, acute vaso-occlusion, endothelial dysfunction, inflammation, and chronic organ damage. While the individual clinical course of this disease is highly variable, many of the associated complications demonstrate some degree of heritability. Intensive research into identifying genetic modifiers that can affect the pathophysiology of SCD has been limited to date and there is an urgent need to improve of our knowledge the molecular mechanisms underlying the clinical complications of SCD. The Sickle cell CIP project is investigating complication of stroke and pharmacogenomics of hydroxyurea response in patients with sickle cell anemia. The major benefit of hydroxyurea comes from its ability to induce fetal hemoglobin (HbF) and higher HbF levels are associated with reduced morbidity and mortality in SCA patients. We will perform whole exome and whole genome sequencing of SCA patients in order to identify genome variants associated with incidences of stroke and HbF response to hydroxyurea.

  Study phs000691

• Genetic Aberrations and Subclonal Structure Impact Chronic Lymphocytic Leukemia

  Large-scale whole-exome sequencing (WES) of primary tumor samples enables the unbiased discovery of recurrent putative driver events and patterns of clonal evolution. We report the identification of 44 recurrently mutated genes and 11 recurrent CNVs through the WES of 538 chronic lymphocytic leukemia (CLL) and matched germline DNAs. These include previously unrecognized cancer drivers (e.g., RPS15, IKZF3), and collectively identify nuclear export, MYC activity and MAPK signaling as central pathways affected by somatic mutation in CLL. A clonality analysis of this large dataset further enabled the reconstruction of temporal relationships between these driver events. Several drivers were associated with shorter progression-free survival (PFS) in 280 samples that were collected prior to uniform treatment with front line chemo-immunotherapy, with mature follow up of greater than 10 years. Direct comparison between matched pretreatment and relapse CLL from 59 samples demonstrated marked clonal evolution occurring in more than 95% of these patients. Distinct patterns of clonal evolution in relationship to specific gene alteration were observed, suggesting a hierarchy of fitness amongst mutations. Thus, large WES datasets of clinically informative samples enable the discovery of novel driver genes as well as the network of relationships between the drivers and their impact on disease relapse and clinical outcome.Additionally, we performed RNA-seq for 268 CLL samples (including 26 follow-up samples) and used them to identify expression subtypes of CLL. RRBS for 30 of these samples was also generated. In an integrative analysis of genetic, transcriptomic, and epigenetic data, incorporating known and newly identified subtypes of CLL, we built new models to improve patient prognostication.

  Study phs000922

• CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

  GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

  Study phs000930

• A Multifactorial Tumor and Immune Cell Profile Determines Response to Immune Checkpoint blockade in Melanoma

  The complex crosstalk between tumor and immune cells during immune checkpoint blockade mandates the development of integrated models that interpret the anti-tumor immune response and predict clinical outcome. We have integrated genome-wide sequence and structural alterations with pre and on-therapy transcriptomic and T cell repertoire features for a cohort of 64 immunotherapy-naïve melanomas treated with anti-PD1 monotherapy or combined anti-PD1 and anti-CTLA4 therapy. While tumor mutation burden (TMB) was associated with improved response to therapy, expressed mutation burden was superior to TMB in predicting outcome. An increased pre-existing T cell density differentiated responding from non-responding tumors independent of therapy. Importantly, T cell repertoire reshaping determined by T cell receptor (TCR) clonotypic regressions and expansions reflected response to therapy such that a more dynamic repertoire predicted improved clinical outcome. Through whole-transcriptome analyses, we discovered differential abundance of B cell subsets in responding tumors, which highlights the importance of the interplay between pre-existing T and B cell immunity in shaping therapeutic response. Tumor temporal trajectories during therapy revealed distinct patterns of molecular response related to expressed mutation elimination or retention that accurately interpreted clinical response. High-dimensional genomic, transcriptomic and immune repertoire data were integrated by both a machine learning and a censored regression approach, resulting in a harmonized multi-modal predictor of response to immune checkpoint blockade. B cell abundance, expressed mutation load and tumor aneuploidy were combined to identify patients at high risk for recurrence, such that high risk patients had a significantly shorter progression-free survival (HR=9.18, 95% CI: 3.14-26.85, p=3.4e-06) especially in the anti-PD1/anti-CTLA4 group (HR=20.34, 95% CI: 4.08-101.32, p=1.68e-06).

  Study EGAS00001004548

• Mutational Landscape and Tumor Burden Assessed by Cell-Free DNA in Diffuse Large B-Cell Lymphoma: a Population-based Study

  Purpose: We analyzed the utility of cfDNA in a prospective population-based cohort to determine the mutational profile, assess tumor burden, and estimate its impact in response rate and outcome in patients with DLBCL. Experimental Design: One-hundred patients were diagnosed with DLBCL during the study period. Mutational status of 112 genes was studied in cfDNA by targeted next-generation sequencing. Paired formalin-fixed paraffin-embedded samples and volumetric PET/CT were assessed when available. Results: Appropriate cfDNA to perform the analyses was obtained in 79/100 cases. At least one mutation could be detected in 69/79 cases (87%). The sensitivity of cfDNA to detect the mutations was 68% (95% CI: 56.2-78.7). The mutational landscape found in cfDNA samples was highly consistent with that shown in the tissue and allowed genetic classification in 43% of the cases. A higher amount of ctDNA significantly correlated with clinical parameters related to tumor burden (elevated LDH and β2-microglobulin serum levels, advanced stage, and high-risk IPI) and total metabolic tumor volume assessed by PET/CT. In patients treated with curative intent, high ctDNA levels (>2.5 log hGE/mL) were associated with lower complete response (65% vs. 96%, P<0.004), shorter progression-free survival (65% vs. 85%, P=0.038) and overall survival (73% vs. 100%, P=0.007) at 2 years, although it did not maintain prognostic value in multivariate analyses. Conclusions: In a population-based prospective DLBCL series, cfDNA resulted an alternative source to estimate tumor burden and to determine the tumor mutational profile and genetic classification, which have prognostic implications and may contribute to a future tailored

  Study EGAS00001004733

• Deep single-cell RNA sequencing data for 12346 T cells from tumour, adjacent normal tissue and peripheral blood of treatment-naive NSCLC patients

  Cancer immunotherapies have shown sustained clinical responses in treating non-small cell lung cancer (NSCLC), but efficacy varies between patients and is believed to depend in part on the amount and properties of tumor infiltrating lymphocytes (TILs). To comprehensively depict and dissect the baseline landscape of the composition, lineage and functional states of TILs in lung cancer, here we generated deep single-cell RNA sequencing data for 12,346 T cells from the primary tumour, adjacent normal tissues and peripheral blood of 14 treatment-naive NSCLC patients. Combined expression and TCR-based lineage tracking revealed a significant proportion of effector T cells with common origins and similar functional states across peripheral blood and tumours pointing towards a highly migratory nature of these T cells. We also observed tumour-infiltrating CD8+ T cells undergoing extensive clonal expansion and exhaustion, with two clusters of cells exhibiting states preceding exhaustion. Survival analysis on independent datasets suggested that high ratio of pre-exhausted to exhausted T cells is associated with better prognosis of lung adenocarcinoma (LUAD). In addition, we observed further heterogeneity within the tumour regulatory T cells (Tregs), characterized by the bimodal distribution of TNFRSF9, an activation marker for antigen-specific Tregs. The gene signature of this group of activated tumour Tregs, which included IL1R2, correlated with poor prognosis in LUAD. The T cell clusters revealed by our single cell analyses provide a new approach for patient stratification, and the accompanying compendium of data will help the research community to gain further insight into the functional states and dynamics of T cell responses in lung cancer.

  Study EGAS00001002430

• Evaluation of somatic mutations in urine samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Purpose: Current diagnostic methods for endometrial cancer lack specificity, leading to many women undergoing invasive procedures. The aim of this study was to evaluate somatic mutations in urine to accurately discriminate endometrial cancer patients from controls. Experimental Design: Overall, 72 samples were analyzed using next-generation sequencing with molecular identifiers targeting 47 genes. We evaluated urine supernatant samples from women with endometrial cancer (n=19) and age-matched controls (n=20). Cell pellets from urine and plasma samples from seven cases were sequenced; further, we also evaluated paired tumor samples from all cases. Finally, immunohistochemical markers for molecular profiling were evaluated in all tumor samples. Results: Overall, we were able to identify mutations in DNA from urine supernatant samples in 100% of endometrial cancers. In contrast, only one control (5%) showed variants at a variant allele frequency (VAF)≥2% in the urine supernatant samples. The molecular classification obtained by using tumor samples and urine samples showed good agreement. Analyses in paired samples revealed a higher number of mutations and VAFs in urine supernatants than in urine cell pellets and blood samples. Conclusions: Evaluation of somatic mutations using urine samples may offer a user-friendly and reliable tool for endometrial cancer detection and molecular classification. The diagnostic performance for endometrial cancer detection was very high, and cases could be molecularly classified using these noninvasive and self-collected samples. Additional multi-center evaluations using larger sample sizes are needed to validate the results and understand the potential of urine samples for the early detection and prognosis of endometrial cancer.

  Study EGAS00001007396