14980 results for "cancer studies using rna-seq"

in 13.29 milliseconds.

• FOXM1 is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer that is detectable using metabolic imaging (RNA-seq data)

  PIK3CA, encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires novel predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. Since the transcription factor drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II), changes in FOXM1 expression can be detected using magnetic resonance imaging of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by PET measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-[18F]fluorodeoxyglucose.

  Study EGAS00001004452

• The characterization of gene expression pattern of anticancer agent-resistant cancer stem cells using RNA sequencing analysis.

  Slow cycling cancer stem cells persist and contribute to tumor regrowth after chemotherapy.To investigate this mechanism, we developed stemness- and cell cycle-visualized colon cancer organoids from patient tissues, and perfomed comparative transcriptome analysis using sorted rapid cycling stem cells (LGR5+p27-) and slow cycling stem cells (LGR5+p27+). In addition, we analyzed the changes in the gene expression patterns in the slow cycling stem cells and all of tumor cells after chemotherapy (camptothecin) treatment. Gene ontology analysis and gene set enrichment analysis using these transcriptome data revealed cell adhesion signal and YAP siganling pathway were important to maintain the dormancy and resume propagation after chemotherapy. In each experiments, total RNA was extracted from organoids and sequenced with HiSeq X Ten (Illumina).

  Study JGAS000350

• Dataset for cancer_of_unknown_primary-RNA

  Rare cancer sequencing data of 58 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008857

• Raw RNA-seq data for clinical efficacy and biomarker analysis of neoadjuvant atezolizumab in operable urothelial carcinoma in the ABACUS trial

  ABACUS is a single arm phase 2 study that investigated 2 cycles of atezolizumab (1200mg Q3) prior to cystectomy in 95 patients with muscle invasive transitional cell cancer (T2-4N0M0). Pathological complete response (pCR) occurring in ≥20% of patients was the primary endpoint. Biomarker analysis on sequential tissue was a co-primary endpoint. This dataset includes the raw RNA-seq data.

  Dataset EGAD00001006205

• Covacta RNAseq counts

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes read counts per gene. Read counts were generated for the Gencode v27 annotation using the summarize Overlaps method from bioC in mode “IntersectionStrict”

  Dataset EGAD00001011164

• SYSCOL Human colorectal cancer project pilot RNA-seq and germline genotyping

  Genotyping by array and Transcriptome profiling by high-throughput sequencing

  Dataset EGAD00001000880

• RNA-Seq of kidney cancer organoid biobank

  Dataset EGAD00001005318

• SU2C-MARK Lung Cancer Consortium - Checkpoint Blockade Response Project

  Immune checkpoint inhibitors have become a critical part of the armamentarium against advanced Non-Small Cell Lung Cancer (NSCLC). While early studies have identified Tumor Mutation Burden (TMB) and PD-L1 staining as important biomarkers of response, they remain imperfect predictors. Here we describe a multi-institutional effort as part of the SU2C-MARK Lung Cancer Consortium in which Whole Exome Sequencing (WES) - and in select cases, RNA sequencing – was performed on a large collection of NSCLC samples prior to immune checkpoint blockade therapy, along with matched clinical response data following therapy. (Profiling of a small number of on- or post-treatment samples was also performed.) We anticipate this dataset to be of high value for the development of a deep understanding of the molecular determinants of immune checkpoint blockade response as well as the discovery of novel biomarkers.

  Study phs002822

• 99 Cases of Small Cell Lung Cancer Study

  Small cell lung cancer (SCLC) is an aggressive disease with poor survival. A few sequencing studies performed on limited number of samples have revealed potential disease-driving genes in SCLC, however, much still remains unknown, particularly in the Asian patient population. Here we conducted whole exome sequencing (WES) and transcriptomic sequencing of primary tumors from 99 Chinese SCLC patients. Dysregulation of tumor suppressor genes TP53 and RB1 was observed in 82% and 62% of SCLC patients, respectively, and more than half of the SCLC patients (62%) harbored TP53 and RB1 mutation and/or copy number loss. Additionally, Serine/Arginine Splicing Factor 1 (SRSF1) DNA copy number gain and mRNA over-expression was strongly associated with poor survival using both discovery and validation patient cohorts. Functional studies in vitro and in vivo demonstrate that SRSF1 is important for tumorigenicity of SCLC and may play a key role in DNA repair and chemo-sensitivity. These results strongly support SRSF1 as a prognostic biomarker in SCLC and provide a rationale for personalized therapy in SCLC. The manuscript has been accepted by Plos Genetics.

  Study phs001083

• Assessment of candidate high-grade serous ovarian carcinoma predisposition genes through integrated germline and tumour sequencing

  High-grade serous ovarian carcinoma (HGSOC) has a significant hereditary component, only half of which is explained. Previously, we performed germline exome sequencing on BRCA1 and BRCA2-negative HGSOC patients, revealing three proposed and 43 novel candidate genes enriched with rare loss-of-function variants. For validation, we undertook case-control analyses using genomic data from disease-free controls. This confirms enrichment for nearly all previously identified genes. Additionally, one-hundred-and-eleven HGSOC tumours from variant carriers were sequenced alongside other complementary studies, seeking evidence of biallelic inactivation as supportive evidence. PALB2 and ATM validate as HGSOC predisposition genes, with 6/8 germline carrier tumours exhibiting biallelic inactivation accompanied by characteristic mutational signatures. Among candidate genes, only LLGL2 consistently shows biallelic inactivation and protein expression loss, supporting it as a novel HGSOC susceptibility gene. The remaining candidate genes fail to validate. Integrating case-control analyses with tumour sequencing is thus crucial for accurate gene discovery in familial cancer studies.

  Study EGAS50000000770

• Genomic and Transcriptomic Data from Advanced Rare Cancer Patients Treated with Pembrolizumab

  This dataset comprises whole exome sequencing data and RNA-seq data of advanced rare cancer patients.

  Dataset EGAD50000002182

• Proteogenomic Landscape of Curable Prostate Cancer

  Aligned RNA-seq sequences in this dataset are from the Proteogenomic Landscape of Curable Prostate Cancer study

  Dataset EGAD00001004875

• Effects of Metformin on Transcriptomic and Metabolomic Profiles in Breast Cancer Survivors Enrolled in the Randomized Placebo-Controlled MetBreCS Trial

  RNA from snap-frozen breast tissue biopsies were purified after lysing by tissuelyser (Qiagen) and using RNA Purification Plus Kit (Norgen biotek CORP, 47700) with additional on-column DNase-I treatment (Qiagen, 79254) at 27 °C. RNA purity and integrity (RIN) were quantified using RNA 6000 Nano kit (Agilent Technologies, 5067-1511) on the 4200 TapeStation (Agilent, Santa Clara, USA). Library preparation and 2x75bp paired-end of 160 ng total RNA input was performed using Illumina Stranded Total RNA Prep Ligation kit and Illumina HiSeq4000 system (Illumina, Sand Diego, CA, USA). RNA sequencing data from HiSeq4000 were quality checked and aligned to GRCh38 (GCA_000001405.15) reference genome using HISAT2 2.0.5 and submitted to subread v.1.5.2 for feature counts calculation. Finally, 36 paired biopsies samples (metformin n=26 and placebo n=12) were sequenced and included in the final analyses.

  Dataset EGAD50000001274

• RNA-seq data from the MESOMICS project (French project of molecular characterization of malignant pleural mesothelioma)

  The dataset includes fastq files from 109 tumor samples as well as RNA-seq gene expression R data, RNA-seq transcript expression R data, RNA-seq gene counts matrix, RNA-seq transcript counts matrix, RNA-seq gene FPKM matrix RNA-seq transcript FPKM matrix for the 109 samples. The sequencing was done with HiSeq 2000 instrument.

  Dataset EGAD00001007024