14989 results for "cancer studies using rna-seq"

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• Somatic cancer gene mutation screening

  Sequencing of colorectal tumors and normal tissue using Ion AmpliSeq Cancer Hotspot Panel V2

  Dataset EGAD00001001010

• Transcriptomic intra-tumor heterogeneity of colorectal cancer varies depending on tumor location within the colorectum

  Background; Intra-tumor heterogeneity (ITH) of colorectal cancer (CRC) complicates molecular tumor classification, such as transcriptional subtyping. Differences in cellular states, biopsy cell composition, and tumor microenvironment may all lead to ITH. Here we analyze ITH at the transcriptomic and proteomic levels to ascertain whether subtype discordance between multiregional biopsies reflects relevant biological ITH or lack of classifier robustness. Further, we study the impact of tumor location on ITH.MethodsMultiregional biopsies from stage II and III CRC tumors were analyzed by RNA sequencing (41 biopsies, 14 tumors) and multiplex immune protein analysis (89 biopsies, 29 tumors). CRC subtyping were performed using consensus molecular subtypes (CMS), CRC intrinsic subtypes (CRIS), and TUMOR types. ITH-scores and network maps were defined to determine the origin of heterogeneity. A validation cohort was used with one biopsy per tumor (162 tumors).ResultsOverall, inter-tumor transcriptional variation exceeded ITH, and subtyping calls were frequently concordant between multiregional biopsies. Still, some tumors had high ITH and were classified discordantly. Proximal tumors showed ITH related to differences in the microenvironment, while ITH within distal tumors were cancer-cell related. This subtype discordancy reflected actual molecular ITH within the tumors. The relevance of the subtypes was reflected at protein level where several inflammation markers were significantly increased in immune related transcriptional subtypes, which was verified in an independent cohort (Wilcoxon rank sum test; p<0.05).ConclusionOur transcriptomic and proteomic analyses show that the tumor location along the colorectum influence the ITH of CRC, which again influence the concordance of subtyping.

  Study EGAS00001004668

• Luminal Androgen Receptor-Enriched Triple Negative Breast Cancer

  This is a study to determine the efficacy of androgen receptor (AR) inhibitors in LAR (luminal androgen receptor)-enriched triple-negative breast cancer (TNBC) in the neoadjuvant setting. Twenty-four patients were treated with neoadjuvant AR inhibitor enzalutamide and paclitaxel for 12 weeks. Whole exome sequencing and RNA-sequencing was performed prior to treatment. The data for only two patients are consented for release through dbGaP. The remaining data are available under a Materials Transfer Agreement with the University of Texas MD Anderson Cancer Center.

  Study phs003586

• Single cell atlas of large B-cell lymphoma

  The dataset comprises multi-omics profiles from 232 biopsies, including 217 from patients with large B-cell lymphoma (114 newly diagnosed and 103 relapsed/refractory) and 15 benign control samples. Specifically: single-nucleus RNA sequencing (snRNA-seq) was performed on all 232 biopsies; single-nucleus ATAC sequencing was conducted on 96 biopsies; bulk RNA sequencing was generated for 208 biopsies; whole-exome sequencing (WES) was performed on 174 tumor biopsies with 118 matched germline samples; Low-pass whole-genome sequencing (lpWGS) was performed on 174 tumor biopsies with 41 matched germline samples. All raw data files are provided in FASTQ format.

  Dataset EGAD50000001491

• RNA seq of intestinal biopsies and blood cells from patients with celiac disease and controls

  This study presents RNA sequenced from several intestinal phenotypes such as from patients with damaged intestinal mucosa as well as from those without a damaged intestine but still an autoantibody response to tissue transglutaminase (“potential celiac disease”) or those with treated celiac disease. By combining phenotypes in a much larger number of tissue samples from both peripheral blood and mucosal biopsies, we found highly differentially expressed genes, but also identify genes involved in controlling and triggering celiac disease associated changes. This study identifies molecular mechanisms involved in celiac disease and new possible targets for treatment and for identification of individuals at risk.

  Dataset EGAD50000001597

• noninvasive lung cancer subtyping

  Accurate diagnosis of lung cancer is important for treatment decision-making. Currently, the gold standard for diagnosing histological subtypes of lung cancer relies on tumor biopsies. Recently, liquid biopsy, particularly cell-free DNA (cfDNA), has shown promising results in cancer detection and classification. In this study, we investigated the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. Specifically, we focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcription activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in the cross-validation and an AUC of 0.747 in the independent validation. Additionally, tumor copy number variations inferred from cfDNA methylome analysis revealed potential implications for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasively lung cancer subtyping, offering insights for cancer monitoring and early detection.

  Study EGAS00001007717

• Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

  Molecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), were missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we used Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis revealed genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells (MDCs). Importantly, we detected heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observed remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

  Study EGAS00001004943

• Cell-Free DNA Genomic Profiling and its Clinical Implementation in Advanced Prostate Cancer

  Sixty-eight patients with advanced prostate cancer in castration-resistant or castration-sensitive settings undergoing treatment at the University Hospital Basel or the St. Claraspital Basel (Switzerland) were selected for targeted parallel sequencing analysis on liquid biopsy (plasma cfDNA) and matched formalin-fixed, paraffin-embedded (FFPE) tumor tissue samples. The liquid biopsy sequencing (plasma cfDNA) was performed using a custom-designed targeted AmpliSeq HD Prostate Cancer cfDNA panel on all 68 patients. The sequencing on 42 matched FFPE tumor biopsy samples was performed using a custom-designed or an alternative commercial panel (ThermoFisher). Raw data underwent automated processing on the Ion Torrent Server v5.16.1 (ThermoFIsher) and were aligned to a hg19 reference genome using the Torrent Alignment Software (ThermoFihser).

  Dataset EGAD50000000348

• TRACERx 100: RNAseq data from the first 100 TRACERx tumours

  TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). This study looks at the multi-region RNAseq data from the TRACERx100 cohort with high enough quality RNA available. There is RNAseq data from 164 regions (64 patients).

  Study EGAS00001003458

• RNA-seq of uncultured CD112high and CD112low long-term(LT) human hematopoietic stem cells (HSC) and cultured and lentiviral transduced (CTRL, INKA1-OE) LT- and short-term HSC from umbilical cord blood

  We performed RNA-sequencing to elucidate the biological pathways (1) altered by INKA1 overexpression in LT-HSC and ST-HSC that may contribute to the induced transient restraint in generating proliferative hematopoietic output in vivo and in vitro; and (2) that underlie the differential in vitro priming and regeneration phenotypes of CD112high and CD112low LT-HSC. Therefore, we prospectively isolated indicated subpopulations from 3 independent human umbilical cord blood pools and subjected them either to RNA-sequencing directly or following culture, lentiviral transduction and purification of the transduced cell fractions.

  Study EGAS00001004768

• ANGIOPREDICT - an FP7-funded project enabling personalised medicine for patients with metastatic colorectal cancer.

  In ANGIOPREDICT, academic cancer biologists and industry-based biotechnology researchers will work together with clinicians to identify biomarkers to predict whether individual metastatic colorectal cancer patients will respond positively to Avastin® combination therapy. Diagnostic tests using these biomarkers will also be developed to provide clinicians with the means to predict patient treatment responses in the future.

  Study EGAS00001005423

• Characterization of High-Grade Serous Ovarian Cancer Subtypes via Single-Cell and Spatial-Transcriptomics Profiling

  We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors. The initial dataset (added October, 2020) contains 3 samples (3 individuals). The next dataset (added November, 2022) contains 34 samples from 8 individuals. The samples in the second dataset were sequenced in five different ways: 1) rRNA depletion and bulk RNA sequencing of tumor chunks, 2) rRNA depletion and bulk RNA sequencing of dissociated cells, 3) poly-A capture and bulk RNA sequencing of dissociated cells, 4) poly-A capture and scRNA sequencing of dissociated cells, 5) barcoding and pooling cells and scRNA sequencing (2 pools of 4 samples each). The third dataset (added June, 2024) contains data from one spatially resolved transcriptomics experiment (4 samples, one per Visium capture area, describing one tumor from one individual) and scRNA sequencing on 5 samples (5 individuals).

  Study phs002262

• Exome sequencing of a novel cervical cancer cell line

  Human cancer cell lines are largely used in the searching for new antineoplastic agents. However, due to the artifacts of a long-term in culture, cell lines do not always represent the realistic tumor cell behavior. This has motivated the development of models that better mimetics the tumor tissue, among them, the establishment of primary cell cultures. In this work, we establish and characterized a low-passage cervix cancer cell line from a Brazilian patient with squamous cell carcinoma. The phenotype confirms the epithelial and tumor origin, through cytokeratins, EpCAM, and p16 staining. Whole exome sequencing showed relevant somatic mutations in several genes including BRCA2, TGFBR1, and IRX2 genes. CNV analysis by nanostring and WGS revealed amplification in genes related mainly with kinases proteins, involved in proliferation, migration and cell differentiation, such as EGFR, PIK3CA, and MAPK7. Overexpression of EGFR was confirmed by phospho RTK-array and western blot analysis. Furthermore, the cell was sensitivity to cisplatin, with IC50 13 times lower than SiHa cell line. In conclusion, this cervical cancer cell line presents molecular alterations that are an important tool for leading pre-clinical studies of new drugs that target one or more of the altered pathways.

  Study EGAS00001003343

• Single cell transcriptomic landscape of pediatric B-cell acute lymphoblastic leukemia: dissection of transcriptional heterogeneity and B-cell developmental state

  Introduction: Genomic analyses of bulk ALL samples have improved our understanding of the genetic basis and risk stratification of B-ALL, but do not directly examine intratumor heterogeneity or enable inference of leukemia developmental state and cell of origin. Methods: We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) (10X Genomics 5’v2) and compared them to a scRNA-seq reference map of normal human B-cell development. Results: Analysis of heterogeneity of inferred DNA copy number alterations at single cell level showed that aneuploid ALL with near haploidy and hyperdiploid harbor chromosomal losses or gains in all blasts, consistent with early, synchronous origin rather than sequential accumulation. Intra-sample heterogeneity was driven by five gene expression signatures: cell cycle, metabolism, differentiation, inflammation, refining leukemic subtyping. An atlas of B cell development was established to map B-ALL samples to specific developmental states. Hyperdiploid samples resembled pro-B cells, while MEF2D-r and TCF3::PBX1 showed high pre-B abundance. Patients with high early lymphoid abundance had poorer outcomes. Conclusions: Understanding variation in transcriptional programs and developmental states of B-ALL blasts by sc transcriptome refines existing clinical and genomic classifications and provides novel prognostic markers.

  Study EGAS00001007512

• RnaSeq data from 414 tumor samples with non muscle invasive bladder cancer

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). This dataset contains 414 BAM files corresponding to the full total RNA-sequencing dataset.

  Dataset EGAD50000000733

• Multi-omic dataset utilized in the analysis of a phase II study of epigenetic priming followed by nivolumab in lung cancer

  This dataset includes sequence files from whole exome sequencing and bulk RNA sequencing of tissue and blood biospecimens from a phase II clinical trial investigating epigenetic priming followed by immune checkpoint blockade in non-small cell lung cancer (NSCLC; NCT01928576). There are 78 whole exome sequencing files and 36 bulk RNA sequencing files included in this dataset.

  Dataset EGAD50000001336