12069 results for "cancer rna-seq"

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• ChIIP-seq and RNA-seq

  epigenome profiling in tumor tissues and paired normal tissues of LUAD patients and transcriptome profiling in tumor tissues of LUAD patients.

  Dataset EGAD00001007066

• mRNA capture sequencing and RT-qPCR for the detection of pathognomonic, novel and secondary fusion transcripts in formalin-fixed paraffin-embedded tissue: a sarcoma showcase

  RNA sequencing is widely used to study gene abundance patterns, but less frequently to assess structural alterations such as fusion transcripts. In this study, we assess the performance of messenger RNA (mRNA) capture sequencing to identify fusion transcripts in formalin-fixed paraffin-embedded (FFPE) tissue of different types of sarcoma, followed by orthogonal confirmation using RT-qPCR. To validate our workflow, we used the TruSight RNA Pan-Cancer Panel to analyze a first cohort of 6 positive control tumors for which the diagnostic workup demonstrated the presence of a specific chromosomal rearrangement. Fusion transcript calling by FusionCatcher confirmed all known aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole transcriptome TruSeq RNA Exome sequencing was applied to a second cohort of 17 patients, diagnosed with fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS), for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. Remarkably, for 6 out of 17 patients, mRNA capture sequencing readily detected a pathognomonic fusion transcript, i.e. PAX3-FOXO1 in 2 ARMS patients, and EWSR1-FLI1, EWSR1-ERG or EWSR1-NFATC2 in 4 URCS patients. These data show that RNA capture sequencing may enhance the detection rate of pathognomonic fusion genes in sarcoma. For the 11 patients with no known pathognomonic fusion transcript, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2 and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in two patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53 and UBE2F-ALS2). Our results provide new insights into the underlying genetic causes of these malignancies.

  Study EGAS00001005202

• Interactions between the tumor and the systemic response of breast cancer patients

  Breast cancer (BC) research has largely focused on the molecular properties of the tumor proper. However, to understand how cancer progresses and ultimately modulates patient outcome, we also require an understanding of the molecular changes in the patient systemic response (SR). Toward this end, we generated and analyzed RNA profiles from tumor and matched blood samples in 173 BC patients. We designed a system (MIxT) to explore and link tightly co-expressed gene sets (modules) across matched tissues. The gene composition of modules, and their expression, largely vary across tissues. Distinct patterns of expression in the SR are predominantly detected in highly immunogenic BC subtypes. We also find that the expression pattern of a module in one tissue is correlated to the expression pattern of a module in the other tissue in a fashion that depends on subtype. For example, systemic immunosuppression is detected in basalL patients in a fashion that is proportional to the level of expression of several tumor modules highlighting immune evasion mechanisms active in these particular cancers.

  Study EGAS00001001804

• MethCORR: DNA Methylation-based Characterization, Classification and Prognostication of Colorectal Cancer using Archival Formalin-fixed, Paraffin-embedded Tissue

  Transcriptional characterization and classification has potential to resolve the inter-tumor heterogeneity of colorectal cancer (CRC) and improve patient management. Yet, robust transcriptional profiling is difficult using formalin-fixed, paraffin-embedded (FFPE) samples, which complicates testing in clinical and archival material. We present MethCORR, an approach that allows uniform molecular characterization and classification of fresh-frozen and FFPE samples. MethCORR identifies genome-wide correlations between RNA expression and DNA methylation in fresh-frozen samples. This information is used to infer gene expression information in FFPE samples from their DNA methylation profiles. MethCORR was applied to methylation profiles from 877 fresh-frozen and FFPE samples and comparative analysis identified the same two major subtypes in four independent cohorts. Furthermore, subtype-specific prognostic biomarkers that better predicted relapse-free survival (HR=2.66, 95% CI [1.67-4.22], P<0.001) than TNM staging and MSI status were identified and validated using DNA methylation-specific PCR assays. The MethCORR approach is general, and may be similarly successful for other cancer types.

  Study EGAS00001004293

• Endocrine therapy reprogramming of breast cancer facilitates metastatic escape via upregulation of P-Rex1/Rac1 signalling

  The estrogen receptor (ER) drives growth in ~70% of breast cancers, and endocrine therapies prevent recurrence. However, 30% of patients recur, with many fatal cases occurring late (after >5 years), presenting a challenge due to their often non-proliferative nature and limited options. To study this, we generated slow-growing resistant cells that form small primary tumours but readily metastasize. Single-cell RNA sequencing (scRNAseq) revealed that endocrine therapy reprograms these cells, notably upregulating the Rac1 signalling component P-Rex1. We found in clinical cohorts that P-Rex1 in high in ER+ breast cancer. Intravital imaging demonstrated that Rac1 signalling is active in ER+ cells following endocrine therapy. Targeting the Rac1 pathway with small molecule inhibitors (NSC23766, R-ketorolac) reduced survival and motility in resistant cells, inhibited in vivo Rac1 activity, and reduced tumour burden when combined with tamoxifen in a drug-refractory patient-derived xenograft. This work identifies the P-Rex1/Rac1 axis, as a potential therapeutic target for late recurring ER+ breast cancer.

  Study EGAS00001008353

• Differential expression in clear cell renal cell carcinoma

  To investigate the levels of gene expression in clear cell renal cell carcinoma (ccRCC), we performed an RNA-seq analysis in 786-O, A-498, UM-RC-2 clear cell renal carcinoma cell lines, as well as HK-2 normal renal epithelium cell line, cultured under normoxic (20% O2) and hypoxic (0.05% O2) conditions. Data are provided in raw fastq files and csv files with the differential expression results. Differential expression was calculated by the RNAflow pipeline (DEseq2), and log fold changes are calculated with respect to the normal cell line (HK-2), with separate results between normoxic and hypoxic datasets.

  Dataset EGAD50000001883

• ICARUS-LUNG01 dataset

  A total of 46 frozen tumor biopsies underwent WES analysis, while 41 blood samples were used as germline controls.Tumor samples qualified for whole exome sequencing (WES) if they contained ≥10% tumor cells. For bulk RNA-seq, 20 paired baseline and on-treatment frozen tumor biopsies were analyzed. Tumor samples qualified if they contained ≥30% tumor cells. For GeoMx spatial transcriptomic study we used 7 patients from the ICARUS LUNG01 trial focusing on tumour and immune cell compartments. We selected 7 paired baseline and on-treatment patient samples for analysis. We selected up to 4 regions of interest (ROI) per sample tissue. We identified tumour and immune cell areas of illumination (AOI) using CK and CD45 antibodies respectively

  Dataset EGAD50000001014

• ATAC-seq dataset of Single cell RNA sequencing reveals induced bifurcated differentiation after RUNX1::RUNX1T1 depletion in patient-derived leukemic blasts

  In this study, we demonstrate that primary AML cells harboring the chromosomal translocation t(8;21) are critically dependent on the corresponding fusion gene, RUNX1::RUNX1T1, to suppress differentiation and maintain stemness. Silencing RUNX1::RUNX1T1 expression using siRNA-loaded lipid nanoparticles induces significant changes in chromatin accessibility, redirecting the leukemia-associated transcriptional network towards a myeloid differentiation program. Single-cell analyses reveal that this transcriptional reprogramming is associated with the depletion of immature stem and progenitor-like cell populations, accompanied by an expansion of granulocytic and eosinophilic/mast cell-like populations with impaired self-renewal capacity.

  Dataset EGAD00001015509

• ScRNA-seq of PBMC and whole blood samples reveales a dysregulated myeloid cell compartment in severe COVID-19

  In a dual-center, two-cohort study, we performed single-cell RNA-sequencing of whole blood and peripheral blood mononuclear cells to determine changes in immune cell composition and activation in mild vs. severe COVID-19 over time. This study provides detailed insights into the systemic immune response to SARS-CoV-2 infection and reveals profound alterations in the myeloid cell compartment associated with severe COVID-19.

  Dataset EGAD00001006550

• Unravelling the contribution of HIF pathway and its therapeutic potential in human AML leukemia-initiating cells

  We performed single cell RNA sequencing (scRNA-seq) from bone marrow on 11 pediatric (0-14 years-old) and adolescent and young adult (AYA) (15-39 years-old) de novo AML samples (Dx) (4 inv(16), 3 t(8;21) and 4 rMLL). In addition, for some patients also relapse sample was sequenced (2 inv(16), 2 t(8;21) and 3 rMLL). Cells were sorted into CD34+/CD38- and CD34-/CD38+ and sequenced separately.

  Dataset EGAD00001008514