2638 results

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• Blood RNA-seq from Mexican DMD patients and healthy controls

  These data are part of a study that aimed to assess the potential of blood RNA-seq to track non-invasively disease progression for DMD. In particular, here we focus on a study designed to compare gene expression in blood from DMD patients to that of healthy controls. These data are analysed in the following manuscript: Signorelli, M., Ebrahimpoor, M. et al. (accepted). Peripheral blood transcriptome profiling enables monitoring disease progression in dystrophic mice and patients. To appear in EMBO Molecular Medicine.

  Study EGAS00001004907

• ABCB1 expression in HCC biopsies

  We analyzed the ABCB1 expression in RNA-seq data of 134 HCCs (120 of these were previously published), including the biopsies from which the 3 doxorubicin-sensitive and 3 doxorubicin-resistant HCCOs were derived.

  Study EGAS50000000041

• Novel genome editing strategies to uncover genotype-phenotype correlations in Polycystic Kidney Disease: a proof-of-concept

  Bulk RNA-seq of genome-edited HEK293T cell lines engineered to model specific PKD1 variants. This dataset enables the exploration of genotype-phenotype correlations in Polycystic Kidney Disease (PKD)

  Study EGAS50000001188

• Dopaminergic neuron differentiation of human embryonic stem cells

  2 replicates of dopaminergic neuron differentiation of human embryonic stem cells from timepoints day 17 and day 28, performed with 10X Genomics single cell RNA-seq. Part of the Ásgrimsdottir et al. (Arenas Lab).

  Study EGAS50000001099

• Arriba: accurate and efficient detection of gene fusions from RNA-Seq (H021)

  The identification of gene fusions from RNA sequencing data is a routine task in cancer research and precision oncology. However, despite the availability of many computational tools, fusion detection remains challenging. Existing methods suffer from poor prediction accuracy and are computationally demanding. We developed Arriba, a novel fusion detection algorithm with high sensitivity and short runtime. When applied to a large collection of published pancreatic cancer samples (n=803), Arriba identified a variety of driver fusions, many of which affected druggable proteins, including ALK, BRAF, FGFR2, NRG1, NTRK1, NTRK3, RET, and ROS1. The fusions were significantly associated with KRAS wild-type tumors and involved proteins stimulating the MAPK signaling pathway, suggesting that they substitute for activating mutations in KRAS. In addition, we confirmed the transforming potential of two novel fusions, RRBP1-RAF1 and RASGRP1-ATP1A1, in cellular assays. These results demonstrate Arriba’s utility in both basic cancer research and clinical translation.

  Study EGAS00001003554

• Single-cell RNA-seq of cervix and placenta

  Placental trophoblasts have been detected in cervical smears early in gestation, creating opportunities for non-invasive prenatal diagnosis. However, trophoblast isolation is limited by the lack of a cell catalogue and molecular profile of cervical smears. To establish an atlas and to explore the potential of single-cell RNA-sequencing to detect cervical trophoblasts, 10,539 single-cell transcriptomes from 12 non-invasive exocervical smears from pregnant women were profiled. In addition, we characterized 34,565 cells from six placental biopsies. We uncovered a novel extravillous trophoblast cell subtype characterized by epithelial marker genes and reduced HLA-G expression. Integration of both cell atlases demonstrated surprisingly similar expression profiles between maternal epithelial cells and placental extravillous trophoblasts, indicating that these trophoblasts retained epithelial properties without an invasive mesenchymal phenotype. Additionally, differential expression analysis identified novel markers discriminating cervical and placental cell types. Those analyses may contribute to trophoblast discovery and isolation from cervical smears.

  Study EGAS00001007044

• Idiosyncratic and generic single nuclei and spatial transcriptional patterns in papillary and anaplastic thyroid cancers

  Thyroid cancer is the most common endocrine malignancy. This dataset encompasses two types of thyroid cancer : anaplastic which is the most de-differentiated and aggressive one, and papillary which is the most common one. We profiled 14 patients, including 10 papillary and 4 anaplastic thyroid carcinomas, using both single nuclei RNA sequencing and spatial transcriptomics to link single cell resolution RNA sequencing with tissue morphology and better understand inter and intratumoral thyroid cancer heterogeneity.

  Study EGAS00001007574

• Single cell RNA sequencing of CD19 CAR T-cell infusion products

  We performed single cell RNA sequencing of remnants from CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma. Libraries were prepared using 10X 5’ GEX chemistry and sequenced on an Illumina HiSeq 4000 to obtain >50,000 reads per cell.

  Study EGAS00001004576

• Multiregion Whole Exome and Smart-Seq3 single cell RNA sequencing of Breast Tumors

  Multiple regions were cut out of each tumor extracted form breast cancer patients and two experiments were run: - Whole exome sequencing on each of the regions plus an adjacent normal tissue sample - Smart-Seq3 Single cell RNA sequencing on EPCAM+ CD45- sorted cells from different tumor regions

  Study EGAS00001006851

• Total RNA sequencing from the TNT trial (NCT00532727)

  Primary tumours from 186 TNT participants (13 matched recurrences) were profiled using total RNA-sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective-response-rate (ORR) and progression-free-survival (PFS) and performed conditional inference forest clustering to integrate multi-modal data.

  Study EGAS00001007398