5624 results for "canc*"

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• Single Cell Genome Sequence for DLP+ library A95632C

  Single Cell Genome Sequence for triple negative breast cancer patient-derived xenograft SA609 passage 6 on DLP+ library A95632C

  Dataset EGAD00001009322

• Normal sample for patient SA291

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA291

  Dataset EGAD00001009368

• Widespread hypertranscription in aggressive human cancers

  Data used to validate RNAmp tool.

  Dataset EGAD00001009285

• Clinical cancer panel sequencing (UCSF500) analysis of TERT promoter duplication in GBM.

  Dataset contains paired-end clinical cancer panel sequencing (UCSF500) data from 2 samples of an initial tumor and one sample of a recurrence from one GBM patient and one sample from a second GBM patient.

  Dataset EGAD00001009286

• WTS and WES of Renal Cell Carcinoma Tumors From a Phase III Anti-Angiogenic Adjuvant Therapy Trial

  Archival de-identified formalin-fixed paraffin-embedded RCC tumor tissue blocks from nephrectomy or tumor biopsy were processed as per below and the same sections were used for both DNA and RNA extractions. For WES (ACE version 3; Illumina NovaSeq), samples were profiled using Personalis ACE Cancer Exome (Personalis, Inc, Menlo Park, CA) Whole-transcriptome profiles were generated by RNA-seq (Accuracy and Content Enhanced (ACE) version 3; Illumina NovaSeq) using Personalis ACE Cancer Transcriptome (Personalis, Inc, Menlo Park, CA ) Of the 615 patients in the intent-to-treat population in S-TRAC trial, 193 individual specimens were available for molecular profiling, of which 171 (27.8%) (sunitinib, n = 91; placebo, n = 80) returned results for the WES analysis, and 133 (21.6%) (sunitinib, n = 72; placebo, n = 61) returned results for the GES analysis. Of the 138 WTS samples with data, replicates for two patients were summarized by median expression, and three samples were excluded from the final analysis due to low counts.

  Dataset EGAD00001009294

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia - RNA

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009305

• Normal sample for patient SA289

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA289

  Dataset EGAD00001009367

• Diagnostic utility of whole genome sequencing in adults with B-other acute lymphoblastic leukemia

  Genomic profiling at diagnosis of B-cell precursor Acute Lymphoblastic Leukemia (BCP-ALL) in adults is used to guide disease classification, risk stratification and treatment decisions. Patients for which diagnostic screening fails to identify disease defining or risk stratifying lesions are classified as B-other ALL. We screened a cohort of 652 BCP-ALL cases enrolled in UKALL14 to identify and perform whole genome sequencing (WGS) on paired tumor-normal samples. For 52 B-other patients we compared WGS findings to data from clinical and research cytogenetics. WGS identifies a cancer associated event in 51/52 cases, this includes an established subtype defining genetic alteration in 5/52 that were previously missed by standard-of-care genetics. Of the 47 true B-other ALL we identified a recurrent driver in 87% (41).  Complex karyotype by cytogenetics emerges as a heterogeneous group, underlied by distinct genetic alterations associated with either favorable (DUX4-r) or poor outcomes (MEF2D-r, IGK::BCL2). For a subset of 31 cases, we integrate findings from RNA-sequencing (RNA-seq) analysis to include fusion gene detection, and classification by gene expression. Compared to RNA-seq, WGS was sufficient to detect and resolve recurrent genetic subtypes, however RNA-seq can provide orthogonal validation of findings. In conclusion, we demonstrate that WGS can identify clinically relevant genetic abnormalities missed by standard-of-care testing and identify leukemia driver events in virtually all cases of B-other ALL.

  Dataset EGAD00001009304

• WGS of cell-free DNA derived from plasma of CRC patients and healthy controls, and WGS of matched tumor tissue and saliva

  This dataset contains: 1.) Whole-genome sequencing (WGS) data (~6x) of 259 cfDNA samples obtained from 50 colorectal cancer (CRC) patients and 61 healthy controls. Paired-end sequencing was performed with 2x101 bp reads on the NovaSeq 6000 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38). 2.) WGS data (~1x) of 50 tumor biopsy and 45 saliva samples from CRC patients. Paired-end sequencing was performed with 2x101 bp reads on the NovaSeq 6000 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38).

  Dataset EGAD00001009309

• WES and RNA-seq of triple-negative breast cancers from the MyBrCa cohort

  The dataset contains a genomics characterization of 35 triple-negative Asian breast tumours from the Malaysian Breast Cancer cohort. This includes whole-exome sequencing of tumour tissue at 80X, whole-exome sequencing of matched normal (blood) tissue at 40X, and RNA-seq of tumour tissue at 40X coverage (>15 million reads). Whole-exome libraries were prepared using the Nextera Rapid Capture Exome Kit; exome capture was performed in pools of 3 and subjected to paired end 75 sequencing on a NovaSeq 6000 platform. RNA libraries were prepared using the TruSeq Stranded Total RNA HT kit with Ribo-Zero Gold as per manufacturer’s instructions and also subjected to paired end 75 sequencing on a NovaSeq 6000 platform. Uploaded bam files have been mapped to the hs37d5 human genome and processed using the standard GATK pipelines. Paired clinical, demographic, genotyping, and overall survival data for these patients are available from the associated publications or by request.

  Dataset EGAD00001009311

• Single Cell Genome Sequence for DLP+ library A95618B

  Single Cell Genome Sequence for Triple negative breast cancer patient-derived xenograft SA609 passage 3 on DLP+ library A95618B

  Dataset EGAD00001009316

• Single Cell Genome Sequence for DLP+ library A95628A

  Single Cell Genome Sequence for triple negative breast cancer patient SA1162SB on DLP+ library A95628A

  Dataset EGAD00001009319

• Normal sample for patient SA280

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA280

  Dataset EGAD00001009365

• NLG-LBC-05 ctDNA project sequencing data

  Low-pass whole-genome sequencing of pretherapy lymphoma cfDNA and targeted sequencing of cfDNA, tumor tissue and whole-blood samples of NLG-LBC-05 patient samples and cfDNA of nine subjects with no known cancer. Hybrid capture target enrichment; panel target and sequencing information provided in PMID:34932792. FASTQ files provided for targeted sequencing, separate sequencing runs per sample noted with prefix "run" if applicable. Sequences from DTX1 and KLHL6 targets are advised to be excluded from analyses due to PCR/plasmid contaminants of in-house origin.

  Dataset EGAD00001009337

• Normal sample for patient SA495

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA495

  Dataset EGAD00001009372

• Normal sample for patient SA425

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA425

  Dataset EGAD00001009371

• Normal sample for patient SA423

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA423

  Dataset EGAD00001009370

• Normal sample for patient SA300

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA300

  Dataset EGAD00001009369

• Normal sample for patient SA239

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA239

  Dataset EGAD00001009364

• Normal sample for patient SA238

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA238

  Dataset EGAD00001009363

• Normal sample for patient SA221

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA221

  Dataset EGAD00001009362

• Tumour sample for patient SA280

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA280

  Dataset EGAD00001009361

• Tumour sample for patient SA291

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA291

  Dataset EGAD00001009360

• Tumour sample for patient SA289

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA289

  Dataset EGAD00001009359

• Tumour sample for patient SA286

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA286

  Dataset EGAD00001009358

• Tumour sample for patient SA495

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA495

  Dataset EGAD00001009357

• Tumour sample for patient SA683

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA683

  Dataset EGAD00001009350

• Tumour sample for patient SA682

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA682

  Dataset EGAD00001009349

• Tumour sample for patient SA681

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA681

  Dataset EGAD00001009348

• Tumour sample for patient SA680

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA680

  Dataset EGAD00001009347

• Tumour sample for patient SA679

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA679

  Dataset EGAD00001009346

• Tumour sample for patient SA678

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA678

  Dataset EGAD00001009345

• Tumour sample for patient SA677

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA677

  Dataset EGAD00001009344

• Tumour sample for patient SA676

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA676

  Dataset EGAD00001009343

• Tumour sample for patient SA675

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA675

  Dataset EGAD00001009342

• Tumour sample for patient SA674

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA674

  Dataset EGAD00001009341

• Tumour sample for patient SA673

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA673

  Dataset EGAD00001009340

• Normal sample for patient SA679

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA679

  Dataset EGAD00001009379

• Normal sample for patient SA680

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA680

  Dataset EGAD00001009380

• Normal sample for patient SA681

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA681

  Dataset EGAD00001009381

• Normal sample for patient SA682

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA682

  Dataset EGAD00001009382

• Normal sample for patient SA683

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA683

  Dataset EGAD00001009383

• Normal sample for patient SA678

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA678

  Dataset EGAD00001009378

• Normal sample for patient SA677

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA677

  Dataset EGAD00001009377

• Normal sample for patient SA673

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA673

  Dataset EGAD00001009373

• Normal sample for patient SA676

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA676

  Dataset EGAD00001009376

• Normal sample for patient SA674

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA674

  Dataset EGAD00001009374

• Normal sample for patient SA675

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA675

  Dataset EGAD00001009375

• Targeted DNA sequencing dataset for the study "Molecular profiling of EBV associated diffuse large B-cell lymphoma"

  We performed deep targeted DNA sequencing with a panel of 74 selected cancer-related genes previously identified to be recurrently mutated in EBV associated DLBCL. Sequencing was performed on a HiSeq platform (Illumina) with 250 bp paired-end reads. There are 68 FFPE samples in this targetedDNAseq-dataset with 46 unpaired tumors and 22 normals used as a panel of normals.

  Dataset EGAD00001009396

• Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors.

  Whole-genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from long-term survivors performed as part of the Multidisciplinary Ovarian Cancer Outcomes Group (MOCOG) study. The dataset includes fastq files from 58 HGSC tumours (53 primary tumours and 5 recurrent tumours) and 53 matched normals from 53 long-term survivor patients. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche) according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

  Dataset EGAD00001009398