11935 results for "cancer rna-seq"

in 13.67 milliseconds.

• Molecular Determinants of Tumor Behavior in Early Lung Adenocarcinoma

  Lung adenocarcinoma is the leading cause of cancer death worldwide and a heterogeneous disease with poor survival in the advanced stage. Given that the frequency of early diagnosis is increasing, the investigation of the molecular determinants of disease progression is paramount. Prediction of whether the tumor is indolent or aggressive has been the subject of recent investigations. Yet, the molecular underpinnings explaining the difference in tumor behavior remains largely unknown and is directly relevant to the efficacy and cost-effectiveness of lung cancer screening, including the risks of over-diagnosis and overtreatment. To gain insights into the molecular pathogenesis and the underlying molecular determinants of clinical behavior of early adenocarcinoma, we investigated genetic alterations in 102 surgically resected early adenocarcinomas. We hypothesized that the behavior of early adenocarcinoma can be predicted based on genomic underpinnings. To identify the type of genomic alterations associated with resected indolent and aggressive early lung ADC, the DNA samples from 21 adenocarcinoma in situ (AIS), 27 minimally invasive adenocarcinoma (MIA) and 54 fully invasive adenocarcinoma were collected and subjected to a deep next generation sequencing, targeting a custom 347 cancer gene panel. Our study provides new insights into cancer genomic evolution, helps to elucidate the interplay of somatic mutation and the adaptation of clones, and brings new insights into the key distinction between indolent and aggressive tumor behavior.

  Study phs001811

• This study generated Oxford Nanopore long read sequencing data of cancer cell line mixtures for validating long-read variant calls in cancer genomics

  Long-read sequencing (LRS) improves genome alignment and facilitates resolving variants in complex genomic regions, making it a promising approach for cancer variant detection and biomarker discovery. Here, we evaluate the performance of LRS to detect somatic variants across different tumour purities and sequencing depths by comparing to somatic variants from short-read sequencing. We generated experimental mixtures of cancer cell lines and matched normal cell lines to simulate 10 tumour purities (ranging from 0 to 100% tumour content). This resulted in 22 samples which were sequenced using whole genome LRS to a targeted depth of 60x and somatic variants were identified. We downsampled sequencing data to explore the optimal read depth for somatic variant detection. Our results show that long-read variant calling tools achieve recall rates comparable to short-read gold standards. While a tumour sequencing depth of 30x to 60× is generally sufficient for detecting common variants, particularly structural variants (SVs), sequencing the matched normal sample at adequate depth is crucial for accuracy. Notably, we found variants unique to LRS that may represent real and previously undetected events. This study highlights key factors for optimising cancer genome sequencing with LRS and provides a comprehensive dataset of cell line mixtures for future research and tool development.

  Study EGAS00001008107

• EGAD00000000054

  NCI-H209 is an immortal cell line derived from a bone marrow metastasis of a patient with small cell lung cancer, taken before chemotherapy. The specimen showed histologically typical small cells with classic neuroendocrine features. NCI-BL209 is an EBV-transformed B-cell line derived from the same patient as the small cell lung cancer cell line, NCI-H209

  Dataset EGAD00000000054

• Colorectal cancer GWAS on the Spanish population

  Data on Affymetrix 6.0 arrays for Genome-Wide Association Study of colorectal cancer in the Spanish population. Additionally, geographical origin for each sample is provided, which constitutes the largest to-date Spanish genomic sample population

  Dataset EGAD00010001715

• NSCCG_CRC_GWAS

  Genotype data of 7,281 individuals with colorectal cancer from the National Study of Colorectal Cancer Genetics (NSCCG) study. Individuals genotyped on the Illumina OncoArray. Data provided in plink format and has not been quality controlled. Control samples used were obtained from the PRACTICAL and BCAC consortia, and are available through the respective Data Access Coordination Committees (http://practical.icr.ac.uk and http://bcac.ccge.medschl.cam.ac.uk/)

  Dataset EGAD00010002184

• Heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer

  A mutation accumulation experiment in colorectal cancer (CRC) derived tumoroids. A sequential single-cell cloning approach was adopted to measure the mutation rate in eight tumoroids obtained from five patients. WGS was also performed on their matched normal tissue and on standard tumoroids cultures without any cloning step.

  Dataset EGAD50000000411

• A Pilot Study Using Next Generation Sequencing in Advanced Cancers: Feasibility and Challenges

  In this study, we used NGS to identify somatic events in advanced stage cancer patients to demonstrate the feasibility for using this approach to improve patient treatment.

  Study phs000657

• GIST Comprehensive Cancer Panel

  DNA Sequencing of 864 genes from KiCS cancer panel. Multiple family members affected with multifocal GIST who underwent whole genome sequencing of the germline and tumor. Affected individuals with GIST harbored a germline variant found within exon 13 of the KIT gene, (c.1965T>G; p.Asn655Lys, p.N655K) and a variant in the MSR1 gene (c.877C>T; p.Arg293*, pR293X).

  Dataset EGAD50000000548

• WES for CNV-verified CTCs from 2 patients with metastatic prostate cancer

  This dataset contains 4 paired fastq files sequenced by illumina Novoseq 6000. WES analysis (illumina platform, PE150, 100x coverage) was performed on a pool of CNV-verified CTCs that were enriched using high-throughout microfluidic device from entire leukopak from patients with metastatic prostate cancer (GU-1 and GU-2).

  Dataset EGAD50000001005

• DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy"

  DAC for "Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy" with Florian Janke (f.janke@dkfz-heidelberg.de) and Holger Sültmann (h.sueltmann@dkfz-heidelberg.de)

  Dac EGAC50000000308