7297 results for "canc*"

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• SCLC MeDIP-seq

  Methylation profile of 33 patients with small cell lung cancer (SCLC) for both, tumour and normal lung samples using MeDIP-seq.

  Dataset EGAD50000000724

• Luminal progenitor cell line iHBEC(CD117)

  Basal-like breast cancer originates in luminal progenitors, frequently with an altered PI3K pathway, and focally in close association with genetically altered myoepithelial cells at the site of tumor initiation. The exact trajectory behind this bi-lineage phenomenon remains poorly understood. Here we used a breast cancer relevant transduction protocol including hTERT, shp16, shp53, and PIK3CA(H1047R) to immortalize FACS isolated luminal cells, and we identified a candidate multipotent progenitor. We found that the apparent luminal phenotype of these oncogene transduced progenitors was metastable giving rise to basal-like cells dependent on culture conditions. After culturing the cells for more than 60 passages, cells were subjected to scRNA-seq as well as bulk RNA sequencing of two subpopulations (CD271+ and CD271-).

  Dataset EGAD50000000723

• Whole genome sequencing of pancreatic cystic fluid for early detection and diagnosis of pancreatic cancer

  Pancreatic cancer (PC) is a leading cause of cancer-related deaths globally. Accurate PC detection at early or premalignant stage, when surgery is effective, would increase survival rates and prevent unnecessary surgery or surveillance. Molecular diagnostic attempts using PCy fluid (PCyF), as a liquid biopsy, to analyze common mutations associated with PC development are yet to contribute to early diagnosis. Whole genome sequencing (WGS) is utilized in various cancers, PC inclusive, for detecting genetic changes associated with carcinogenesis, but not in PCyF due to technical limitations, including isolated DNA purity. The goal of the study was to achieve high quality of WGS from PCyF from 9 patients to enable development of signatures of malignancy. The WGS was performed using Illumina sequencing. Experimental design was at a 50x depth.

  Dataset EGAD50000000869

• Rare germline variants in patients with personal and family history of colorectal cancer

  A double primary colorectal cancer (CRC) in a familial setting signals a high risk of CRC. In order to find novel high/moderate penetrance CRC susceptibility genes, we performed whole-exome sequencing on germline blood samples of seven familial cases from Poland with a double primary CRC.

  Dataset EGAD50000000861

• Dataset for early breast cancer samples

  This dataset contains WGS data for 27 tumor, control and patient derived culture samples of patients with breast cancer. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X using TruSeq Nano DNA Kit. The sequencing was always paired

  Dataset EGAD50000000860

• scRNA-seq from lung cancer organoids and immune cells

  15 scRNA-seq samples were multiplexed, and 5' 10X Chromium scRNA-seq was performed. This dataset provides the FASTQ files for the multiplexed data, as well as the BAM files for the demultiplexed samples.

  Dataset EGAD50000000845

• PDiamond Korean Lung Cancer Data

  WES and RNA-seq data of PDiamond Korean lung cancer data

  Dataset EGAD50000000844

• Single cell RNA sequencing of PBMC samples from CRC patients

  This data contains scRNA-seq on 14 PBMC samples from colorectal cancer patients.

  Dataset EGAD50000000841

• Pilot data of PDiamond Lung Cancer Data

  RNAseq pilot data of PDiamond Korean lung cancer data

  Dataset EGAD50000000843

• RNAseq data of metastatic breast cancer samples

  Paired-end RNA sequencing data from 28 metastatic breast cancer samples. Sequencing was performed on the Illumina NovSeq 6000 and HiSeq 4000 using TruSeq Stranded mRNA Kit.

  Dataset EGAD50000000818

• WGS and WES data of metastatic breast cancer tissues and organoids

  Paired-end WGS (x25) and WES data (x2) from metastatic breast cancer organoids, tissues and germline controls. WGS was performed on Illumina NovSeq 6000 and HiSeq X, using Illumina TruSeq Nano DNA kit. WES was performed on Illumina NovSeq 6000 and HiSeq 2000, using Agilent SureSelect XT HS + Human All Exon V7 and SureSelect Human All Exon V6+UTR (hg19).

  Dataset EGAD50000000817

• Whole-genome sequencing of tumour, germline and plasma samples from a BRCA1-mutant breast cancer patient

  This data set contains the fastq files from whole-genome sequencing of temporally matched tumour (fresh frozen biopsies), blood germline and plasma samples collected from a BRCA1-mutant breast cancer patient to directly compare mutation signature analysis using gold-standard tumour-germline paired variant calling with a novel ctDNA-based method (MisMatchFinder).

  Dataset EGAD50000000811

• Low-coverage whole genome sequencing of plasma from BRCA-mutant breast cancer patients

  Plasma samples from patients with breast cancer (stage IV) who had confirmed BRCA mutations were subjected to low-coverage whole-genome sequencing This dataset contains raw fastq files from 6 breast cancer plasma samples.

  Dataset EGAD50000000810

• BELLINI clinical trial bulk WES data: cohorts A & B

  WES data of 30 breast cancer primary tumors obtained from 30 unique patients from BELLINI clinical trial (cohorts A & B) and 30 matched blood samples. The data includes pretreatment samples. The included raw WES sequencing data in fastq format was generated using Illumina NovaSeq 6000.

  Dataset EGAD50000000809

• scRNAseq data from metastatic breast cancer samples

  Paired-end SMARTseq2 data of EpCAM+ sorted cells from liquid biopsies from 3 patients. Sequencing was performed on Illumina HiSeq 2500.

  Dataset EGAD50000000816

• BELLINI clinical trial bulk RNA-Seq data: cohorts A, B & С

  RNA-Seq data of 78 breast cancer primary tumors obtained from 45 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (15 patients, 25 samples) received nivolumab for 4 weeks, patients in cohort B (15 patients, 28 samples) received nivolumab + ipilimumab for 4 weeks, and patients in cohort C (15 patients, 25 samples) received nivolumab + ipilimumab for 6 weeks. The included raw transcriptome sequencing data in fastq format was generated using Illumina NovaSeq 6000.

  Dataset EGAD50000000808

• Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

  Targeted cfDNA and WBC sequencing data from patients profiled in the study "Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer". Note that 'Exome sequencing' is listed under Dataset Type since there is no option for targeted panel sequencing.

  Dataset EGAD50000000303

• WGS of human colorectal cancer organoid exposed to genotoxic pks+ E. coli

  Organoid cultures were exposed to different E.Coli strains and a dye control. In total 25 organoid cultures were whole-genome sequenced using the Novaseq6000 platforms. The data is deposited as .bam format.

  Dataset EGAD50000000304

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 11)

  The dataset contains whole genome sequencing data of 23 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 89 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000313

• Homopolymer switches WES dataset

  This project used NGS (next generation sequencing) in mismatch repair deficient colorectal cancer samples. The project investigated the role of secondary MMR (mismatch repair) gene mutations in tumor evolution. This dataset includes BAM files from multi-region Whole Exome Sequencing of 49 samples from 22 patient tumors.

  Dataset EGAD50000000319

• INVADE bulk RNAseq

  Fastq files of bulk RNAseq data from DCIS, invasive and microinvasive breast cancer at diagnosis. This dataset covers 18 DCIS cases, 17 microinvasive and 20 primary invasive breast cancer.

  Dataset EGAD50000000320

• scRNAseq data of CAP

  Fastq files from scRNAseq data of cancer associated pericytes-like from 3 patients. CAP were isolated from a total of 3 primary BC (surgical residues prior to any treatment) by using BDFACS ARIA III sorter (BD Biosciences). BC were collected directly from the operating room after surgical specimen macroscopic examination and selection of areas of interest by a pathologist. Samples were cut into small pieces (around 1 mm3) and digested in CO2-independent medium (Gibco #18045-054) supplemented with 150 μg/mL liberase (Roche #05401020001) and Dnase I (Roche #11284932001) for 40 min at 37°C with shaking (180 rpm). After digestion, cells were processed and stained as described above (#Flow Cytometry analysis of BC samples). CAP fibroblasts were then gated on the Live/Dead negative fraction and defined as EPCAM- CD45- CD31- CD235a- FAPMed CD29High. CAP scRNA-seq: Upon isolation, CAP cells were directly collected into RNase-free tubes (Thermo Fisher Scientific, #AM12450) precoated with DMEM (GE Life Sciences, #SH30243.01) supplemented with 10% FBS (Biosera, #1003/500). Single-cell capture, lysis, and cDNA library construction were performed using Chromium system from 10X Genomics, with the following kits: Chromium Single Cell 3′ Library & Gel Bead Kit v2 kit (10X Genomics, #120237) and Chromium Single Cell A Chip Kits (10X Genomics, #1000009). Generation of gel beads in Emulsion (GEM), barcoding, post GEM-reverse transcription cleanup and cDNA amplification were performed according to the manufacturer’s instructions. Cells were loaded accordingly on the Chromium Single cell A chips, and 12 cycles were performed for cDNA amplification. cDNA quality and quantity were checked on Agilent 2100 Bioanalyzer using Agilent High Sensitivity DNA Kit (Agilent, #5067-4626) and library construction followed according to 10X Genomics protocol. Libraries were next run on the Illumina HiSeq (for patients P1) and NovaSeq (for patients P2–3) with a depth of sequencing of 50,000 reads per cell.

  Dataset EGAD50000000321

• Spatial transcriptomic data of breast cancer

  Fastq files from spatial transcriptomic of breast cancer coming from 8 Breast cancer sections. Sample preparation: frozen BC samples were chosen based on tissue structure and RNA quality (RIN > 8). The “Visium Spatial Tissue Optimization Slide and Reagent Kit” (10X Genomics; #PN-1000193) was then used to optimize permeabilization conditions for BC tissues. Briefly, sections were fixed, stained and then permeabilized at different time points to capture mRNA, and the reverse transcription was performed to generate fluorescently labeled cDNA. The permeabilization time that resulted in the highest fluorescence signal with the lowest background diffusion was chosen. The best permeabilization time for BC tissue was 18 min. Cryostat sections of 10 μm of thickness were cut and placed on Visium Spatial Gene Expression slides (10X Genomics, PN-1000184). The slide was incubated for 1 min at 37°C, then fixed with methanol for 30 min at -20°C followed by Hematoxylin and Eosin (H&E) staining and images were taken under a high-resolution microscope. After imaging, the coverslip was detached by holding the slide in water and the slide was mounted in a plastic slide cassette. The spatial gene expression process, including tissue permeabilization, second strand synthesis and cDNA amplification, was performed according to the manufacturer’s instructions (10X Genomics; #CG000239). cDNA quality was next assessed using Agilent High sensitivity DNA Kit (Agilent, #5067-4626). The spatial gene libraries were constructed using Visium Spatial Library Construction Kit (10X Genomics, PN-1000184).

  Dataset EGAD50000000322

• Transcriptomic characterization of the histopathological growth patterns in breast cancer liver metastases

  20 fastq files of RNA-sequencing of the 2 main histopathological grow patterns observed in liver metastases.

  Dataset EGAD50000000331

• RNA-seq data for study 'Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.'

  RNA-seq data from nasal and bronchial tissues in 649 subjects, many with lung cancer. Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dataset EGAD50000000333