12312 results for "cancer rna-seq"

in 12.42 milliseconds.

• 10X whole single cell RNA-seq from pre-frontal cortex biopsy

  The biopsy procedure was performed by a standard operative procedure under general anaesthesia. The placement of burr hole on the frontal lobe, opening of dura and cortex was performed in a routine fashion for VP shunt or VCS surgery. The biopsy was sharp dissected with knife through the leptomeninges, forming a tissue block consisting of cortex and subcortex, and placed in a sterile tube containing CSF. Fresh tissue sample processing was performed within the hours after surgery. The tissue was dissociated followed by red cell and debris removal and counting of the cells to be sequenced with (scRNA-seq; 10x Genomics). After dissociation only non neuronal cells were retrieved.

  Study EGAS50000001058

• Genomic and Genetic Analysis of Brain Tumors and Analysis of Their Clinicopathological Significance

  The treatment outcome of glioma patients remains disappointing, and more studies are needed to improve therapeutic strategies. In particular, it is crucial to understand the mechanisms underlying resistance to treatment and malignant transformation, as well as the intratumoral heterogeneity and interaction of tumor cells and host immunity. Recent advances in omics analysis techniques, such as next-generation sequencing (NGS), have enabled us to obtain omics data more easily and accelerated our ability to integrate this information and precisely characterize cases. In our project, we have already collected more than 100 pairs of human glioma/normal tissue samples, of which some are multiple specimens collected from initial and recurrent tumors, and some include multiple specimens collected from different regions within a single tumor. We used our in-house algorithms, composed of alignment and variant calling programs, to analyze omics data from multiple platforms, such as whole-exome sequencing (WES), RNA sequencing (RNA-seq), and methylation array, with our original cohort of glioma patients. Using several informatics tools, the information about genetic and epigenetic status and expression signatures were analyzed. Those data are expected to provide key information for investigating the mechanisms discussed above. Through this project, we hope to improve strategies for personalized therapy based on comprehensive omics data.

  Study JGAS000004

• Use of new methodologies to achieve a thorough molecular characterization in pediatric acute leukemia

  In childhood leukemia, a better genetic characterization is needed to define new clinic-biological entities, refine the risk-stratification of patients and help to reduce the toxicity by applying a risk-directed therapy. This project aims to obtain information that will allow us to personalize the management of pediatric patients with leukemia as much as possible, so that we can offer a complete diagnosis, a sensitive follow-up and a more targeted treatment to the real risk of each case. The use of massive genome analysis technologies such as transcriptome sequencing (RNA-Sequencing) will allow a comprehensive biological characterization of pediatric leukemia patients, especially those cases that we have not been able to characterize by conventional diagnostic techniques. We believe that the RNA-Seq technique will allow us to identify new biomarkers that will be useful for: 1) defining new biological entities with their own clinical behavior; 2) refining the stratification of patients into risk groups; 3) finding targets for a better follow-up of MRD and 4) identifying therapeutic targets for the application of targeted therapies to reduce toxicity. PI: Camós-Guijosa, Mireia; Vega-García, Nerea Funding: PI21/00213 Instituto de Salud Carlos III (ISCIII)

  Study EGAS50000000701

• Sequencing of Coding and Non-coding Regions in Primary Breast Cancers and Patient-matched Controls

  Genomic analysis of tumor samples has led to the identification of hundreds of cancer genes based on the presence of mutations in protein-coding regions. By contrast, much less is known about cancer-causing mutations in non-coding regions. Here, we performed deep sequencing in 360 primary breast cancers and developed computational methods to identify significantly mutated promoters. Clear signals were found in the promoters of four genes. FOXA1, a known driver of hormone-receptor positive breast cancer, harbors a mutational hotspot in its promoter that leads to overexpression through increased E2F binding. RMRP and NEAT1, two non-coding RNA genes, carry mutations that alter protein binding to the promoter and impact expression levels. Overall, our study shows that recurrent mutations in or near gene promoters in cancers have functional consequences. Power analyses indicate that more such genes remain to be discovered through deep sequencing of adequately sized patient cohorts.

  Study phs001250

• Cellular Dynamics Upon Immune Checkpoint Inhibition

  Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet most patients experience limited or no clinical benefit. To elucidate the mechanisms of response and resistance, we analyzed single-cell RNA-sequencing data from 141 patients across multiple cancer types and ICI treatment modalities, with longitudinally paired samples. Using a robust, integration-free deep phenotyping framework, we annotated 876,410 cells into 80 granular states. We identified consistent compositional changes in 17 cell subtypes following ICI treatment, including enhanced adaptive immune responses and reduced interferon-responsive cells. Co-regulated cell communities within the tumor microenvironment (TME) highlighted coordinated interplay between immune and non-immune components. Importantly, we discovered two distinct patient groups with divergent TME dynamics post-treatment: responders showed expansion of naive lymphocytes, while non-responders exhibited increased immune-experienced/suppressive cells. This dichotomy offers a potential predictive biomarker for patient stratification. Our comprehensive analysis of TME dynamics during ICI treatment advances understanding of response mechanisms and personalized cancer immunotherapy.

  Study EGAS50000000459

• ovarian cancer sample exome seq

  Tissue samples were collected from 18 ovarian cancer patients. After mechanical and enzymatic dissociation, a part of these tissues underwent growth factoromics analysis. For four cases, single-cell sequencing analysis was conducted under conditions with or without estradiol. Additionally, the remains of the tissues were frozen and subsequently subjected to exome sequencing on 16 of these samples. Sixteen cases were diagnosed as HGSOC, while two samples were clear cell or mucinous type (Extended Data Table 1). All cases were grade 3, and none had received neoadjuvant chemotherapy.

  Dataset EGAD50000002057

• Bulk RNASeq of metastatic colorectal cancer organoids with ATOH1 knockout

  Bulk RNA sequencing was performed on mCRC organoids subjected to cetuximab treatment, comparing ATOH1 knockout and control conditions. The dataset is intended to elucidate the contribution of ATOH1-regulated secretory cell population to cetuximab persistence mechanisms.

  Dataset EGAD50000002060

• Korean Advanced Thyroid Cancer Dataset

  Massively-parallel DNA sequencing of 113 advanced thyroid cancers and Massively-parallel RNA sequencing of 25 advanced thyroid cancers

  Dataset EGAD00001004845

• RNAseq of resident memory T cells from human lung tumor

  This dataset includes the RNA sequencing of 14 samples. Samples are FACS sorted CD8+ T cells expressing or not the integrin CD103. The paired samples (TRM and non-TRM) were sorted from the tumor of 7 lung cancer patients.

  Dataset EGAD00001006812

• PROMETEO

  The SOLTI-1503 PROMETEO trial was a single-arm, preoperative, window-of-opportunity phase II study conducted at four sites in Spain between December 2018 and February 2022. It enrolled female patients with operable HER2-negative breast cancer (triple-negative or Luminal B-like) and residual disease after neoadjuvant chemotherapy. Tumor biopsies were collected at five time points (baseline, post-NAC screening, C2D1, C3D1, and surgery) for translational research. This dataset includes raw paired-end RNA sequencing data (~110M reads per library) generated from the 113 biopy samples, archived in FASTQ format.

  Study EGAS50000001499