15059 results for "cancer studies using rna-seq"

in 13.85 milliseconds.

• Additional RNAseq data of metastatic breast cancer samples

  Paired-end RNA sequencing data from 33 metastatic breast cancer samples. Sequencing was performed on the Illumina NovSeq 6000 using NEBNext Single Cell and Low Input RNA Library Prep Kit for Illumina.

  Dataset EGAD00001015678

• Paired RNA-Seq of 32 samples of chemo-naïve and post-chemotherapy PDAC tumors

  Paired RNA-Seq of 32 samples of chemo-naïve and post-chemotherapy PDAC tumors (HIPO_015) to define the molecular and cellular impact of neoadjuvant chemotherapy. Transcriptome analysis combined with high resolution mapping of whole tissue sections identified GATA6 (Classical), KRT17 (Basal-like) and Cytochrome P450 3A (CYP3A) co-expressing cells that were preferentially enriched in post-CTX resected samples. The sequencing was done on HiSeq2000/HiSeq2500 using the Takara_SMARTer_Ultra_Low_Input_RNA_and_NEBNext_ChIP-Seq Kit.

  Dataset EGAD00001010884

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  Raw bam file for bulk RNA-seq of checkpoint-blockade treated lung cancer cohorts

  Dataset EGAD50000000469

• Molecular Analysis of Short- Versus Long-Term Survivors of High-Grade Serous Ovarian Carcinoma

  The underlying determinants for long-term survival (LTS, ≥10 years) versus short-term survival (STS, <3 years) of patients diagnosed with high-grade serous ovarian carcinoma (HGSC) are largely unknown. The present study sought to identify molecular predictors of LTS for women with HGSC. A cohort of 24 frozen HGSC samples (12 LTS and 12 STS) were collected and analyzed at DNA and RNA levels. Copy number variation and mutation did not indicate large differences between LTS and STS. From RNA-Seq analysis, 11 genes were found to be differentially expressed between the STS and LTS groups (fold change >2; false discovery rate <0.01). In the validation cohort, transmembrane protein 62 (TMEM62) was found to be related to LTS. Our in vitro and in vivo studies demonstrate that restoring TMEM62 may be a novel approach for treatment of HGSC. These findings may have implications for biomarker and intervention strategies to help improve patient outcomes.

  Study phs003020

• 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

• Multi-Modal Single-Cell, Spatial, and Genomic Analyses of Human Non-Small Cell Lung Cancer Brain Metastases

  We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of 12 treatment-naive non-small cell lung cancer (NSCLC) primary tumors (PTs) and 31 treatment-naive NSCLC brain metastases (BMs). In total, we recovered 277,206 cell transcriptomes in 43 samples. Single-nuclei suspension from frozen NSCLC metastases were generated using methods published in Slyper et al. (Nature Medicine, 2020, PMID:32405060) with modifications. The tissue was first cut in 20 µm sections using a cryostat and stored on dry ice until the next step. Then the tissue was put on wet ice and washed once with 5 ml PBS to remove OCT. After this step nuclei were extracted by vigorous pipetting in salt-tris buffer with Tween-20 (TST) followed by a high-volume wash in salt-tris buffer (ST). Nuclei were counted and 10,000-14,000 and were loaded using a Chromium controller (10X genomics) and Chromium Single Cell 5' Reagents (V1.1 and V2). Complementary DNA libraries were generated according to manufacturer's instructions, with the modification of one additional cycle of amplification. Matched single nuclei T cell receptor (snTCR) sequencing libraries were prepared from amplified cDNA libraries using either Chromium Single Cell V(D)J Enrichment Kit for human T cells Reagent Kit, v1.1, or single cell human TCR amplification kit. Final snTCR sequencing libraries were prepared using Single Index Kit T Set A for V1.1 libraries or Library construction kit and Dual Index Kit TT set A for V2 libraries. Sequencing libraries were quantified using Tapestation D5000 reagents and a 2200 TapeStation and pooled for sequencing. Pool matched low pass whole-genome sequencing (lp-WGS) was performed in addition to snRNA-seq to improve the identification of the malignant and non-malignant cell compartments. Nuclei from snRNA-seq sample preparations were collected by centrifugation (500g, 5 min), snap frozen after removing excess ST buffer, and stored at -200C until further processing. If insufficient nuclei (0C for 9 minutes. Adapters were not diluted, and the optional PCR (5 cycles) and cleanup were performed. After library cleanup with AMPure beads (Beckman Coulter, Brea, CA), libraries were quantified with Tapestation D5000 HS tapes (Agilent) and stored at -200C until sequencing.Using multiplexed immunofluorescence in an independent cohort of treatment-naïve pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features that strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.

  Study phs003865

• Deciphering molecular mechanisms underlying hematological malignancies and development of novel therapeutic approaches

  We aim to identify epigenomic features dysregulated in hematological malignancies through epigenetic analyses of hematological malignant cells. We also perform RNA sequencing to profile tumor cell-specific transcriptomes and target gene sequencing to profile somatic gene mutations in tumor cells. Regarding identified epigenomic abnormalities, we perform further analysis to determine whether they could be good candidates to translate into therapy development. To this end, we will modulate the activity of targets by using their activators and inhibitors in vitro and establish xenograft mouse models of hematological malignancies and manipulate their activity in vivo. Through these studies, we aim to develop new therapeutic agents or modalities that lead to improved patients��� prognosis.

  Study JGAS000603

• Perturb-seq dataset

  We performed a systematic, genome-wide investigation of enhancer regions in colorectal cancer (CRC). We identified 12,117 putative enhancer regions using H3K27ac and H3Kme1 ChIP-seq and ATAC-seq. We performed scRNA-seq in HT29 and SW480 (MSS CRC cell lines) using the Parse Biosciences WT-mega kit with CRISPRi/dCas9 inhibition of these regions (Perturb-seq). The Parse split-pipe pipeline was used to demultiplex the raw fastq files into the processed files (mtx files for genes and gRNA) for each cell line.

  Dataset EGAD50000000375

• EGAD00000000049

  RNA-SEQ data from oestrogen-receptor-alpha-positive metastatic lobular breast cancer sample

  Dataset EGAD00000000049

• RNA-seq data from 7 CAF-S1 primary cell lines isolated from breast Cancer

  Dataset EGAD00001006144