Project description:250k Sty, 250k Nsp, 250k Hind and 250k Xba Affymetrix SNP arrays for 50 leukemia remission samples used as controls for copy number analysis for GSE9109 and GSE9112. Keywords: Acute leukemia, BCR-ABL1, chronic myeloid leukemia, copy number analysis, loss-of-heterozygosity, genomics *** Due to privacy concerns, the primary SNP array data is no longer available with unrestricted access. Individuals wishing to obtain this data for research purposes may request access using the Web links below. ***
Project description:This single cell RNA-seq experiment was performed to quantify DLL3 expression in tumor cells in small cell lung cancer patients.Tumors were rapidly dissociated after the surgical procedure using the Miltenyi Biotec Human Tumor Dissociation kit (cat# 130-095-929). Libraries were constructed using the VDJ NextGEM v1.1 10x Genomics Chromium kit according to the manufacturer's instructions. Samples were sequenced on a NextSeq 550 sequencer (Illumina). Corresponding EGA study number: EGAS50000001400, EGA dataset number: EGAD50000002034.
Project description:High-resolution genomic microarrays provides simultaneous detection of copy-number aberrations such as the known recurrent aberrations in Chronic Lymphocytic Leukemia_diagnostic sample_patient (del(11q), del(13q), del(17p) and trisomy 12), and copy-number neutral loss of heterozygosity. We screened 369 newly diagnosed Chronic Lymphocytic Leukemia_diagnostic sample_patient patient samples from a population-based cohort using 250K single nucleotide polymorphism-arrays.
Project description:A novel method for detecting genome-wide ASM (allele-specific methylation) was developed by modification of the Affymetrix 250K StyI SNP arrays. Using this method, and the above mentioned samples, we consistently detected ASM in non-imprinted regions of the genome. Interestingly, ASM appears to be strongly correlated with the SNP sequences in cis.
Project description:This dataset was applied to evaluate the performance of a deep learning framework, FFPERescuer, specifically designed to reconstruct gene expression profiles from RNA sequencing data derived from FFPE (formalin-fixed, paraffin-embedded) tumor tissues. The dataset includes a total of 12 RNA-Seq samples, comprising 10 FFPE tumor tissue samples from colorectal cancer (CRC) cases collected in Amsterdam, the Netherlands, with 2 duplicate samples included for reproducibility assessment. The corresponding gene expression profiles from fresh-frozen tumor tissues for these 10 cases are available in the dataset GSE33113, generated using microarray technology.
Project description:Canine mammary gland tumors (CMTs) have been suggested as promising cancer models to human breast cancer due to their many biological and clinical similarities. Here, we collected 222 samples consist of 158 tumor samples and 64 matched normal samples of CMTs. Fresh tissue samples were transferred in to RNAlater, and refrigerated overnight at 4°C and then stored at -80°C. Total RNA was extracted from tissues using RNeasy mini kit. We aligned RNA-Seq raw data from 222 samples to canine reference genome CanFam3.1 using Tophat. We assembled transcript and calculated FPKM values using Cufflinks. All tumor samples were evaluated by histopathological characteristics including histopathological subtype, grade, and lymphatic invasion, and annotated with corresponding sequencing data. The histopathological classification and the histological grading system of CMTs were adopted from those of human breast cancer. In addition, immunohistochemical evaluation was performed in samples for estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status. DISCLAIMER: Using this dataset became freely available on Jul 22, 2019. On the other hand, we are now preparing a key paper about comparative analysis of canine and human breast cancer based on this dataset. If you plan to submit a similar paper using this dataset before the main paper is published, please feel free to contact the submitter (swkim@yuhs.ac) to coordinate submission.
Project description:This single cell RNA-seq experiment was performed to quantify DLL3 expression in circulating tumor cells in small cell lung cancer patients to predict response to tarlatamab treatment. CTCs enriched from the blood of three SCLC patients prior or post tarlatamab treatment using the CTC-iChip followed by magnetic depletion of RBCs were processed with the 10x Genomics Chromium platform (Chromium GEM-X Single Cell 3' Kit v4) and sequenced on a NextSeq 2000 system. Corresponding EGA study number: EGAS50000001401, EGA dataset number: EGAD50000002035
