7147 results for "canc*"

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• Yale Policy for head and neck cancer and HPV clinical trials

  Yale Policy for human controlled access data associated with head and neck cancer and HPV clinical trials

  Dac EGAC50000000403

• RNAseq of pre- and post-5AZA-treated head and neck cancer patients refractory to anti-PD-1 therapy

  RNA sequencing (RNA-seq) was performed on baseline (before low-dose 5-aza treatment) and on-treatment (low-dose 5-aza treatment for 5 or 10 days) tumor samples from eight participants with head and neck cancer who were refractory to anti-PD-1 therapy. RNA library preparations, sequencing reactions, and initial bioinformatics analyses were conducted at GENEWIZ, LLC. In total, 16 150-bp pair-end RNAseq data were generated.

  Dataset EGAD50000001010

• WES of head and neck cancer patients refractory to anti-PD-1 therapy

  Whole exome sequencing (WES) was performed on baseline (before low-dose 5-aza treatment) blood and tumor paired samples from 12 participants with head and neck cancer who were refractory to anti-PD-1 therapy. DNA extractions were performed by the Broad Institute of MIT and Harvard using Qiagen AllPrep DNA/RNA kits (Cat. 80204). In total, 24 150-bp pair-end WES data were generated by Illumina.

  Dataset EGAD50000001011

• RNA sequencing of serial samples from patients enrolled in the NA-PHER2 trial

  Improved outcomes in HER2+ breast cancer have resulted from chemotherapy and anti-HER2 therapies. However, HER2+ER+ cancers exhibit lower response rates. The NA-PHER2 trial investigated chemo-free preoperative HER2 and CDK4/6 blockade with or without endocrine therapy in HER2+ER+ breast cancer. Through RNA sequencing and tumour infiltrating lymphocytes (TIL) assessment in serial biopsies we identified predictive biomarkers of pCR, Day 14 Ki67 response, and unveiled treatment-induced molecular changes.

  Study EGAS50000000248

• Comprehensive molecular portrait reveals genetic diversity and distinct molecular subtypes of small intestinal neuroendocrine tumors

  This study aims to characterize neuroendocrine tumors of the small intestine (siNETs) from genomic, transcriptomic, epigenomic, and clinical perspectives. Involving 122 patients and 219 samples, we generated whole-genome sequencing data, RNA sequencing data, genotyping arrays, and methylation arrays to conduct an integrative analysis of this rare tumor type. Our findings identify distinct molecular subtypes that correlate with siNET clinical features.

  Study EGAS50000000642

• Enabling sensitive and precise detection of ctDNA through somatic copy number aberrations in breast cancer

  Cell-free DNA (cfDNA) extracted from peripheral blood has emerged as a crucial biomarker source in oncology research. To enhance the detection of somatic copy number alterations (SCNAs) and circulating tumor DNA (ctDNA), we developed eSENSES, a 2Mb breast cancer-targeted NGS panel. It includes 15,000 genome-wide SNPs, 500 focal SNPs in breast cancer driver regions, and exons from 81 commonly altered genes, alongside a custom computational approach. eSENSES provides a reliable, powerful and cost-effective tool for monitoring disease progression and guiding therapeutic decisions in breast cancer patients.

  Study EGAS50000000793

• Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin

  Study EGAS00001004660

• MOSAIC - Multi-Omics Spatial Atlas In Cancer

  MOSAIC is a collaborative initiative founded by Owkin, Lausanne University Hospital (CHUV), Charité Universitätsmedizin Berlin, University Hospital Erlangen (UKER), Gustave Roussy Institute in Paris, and University of Pittsburgh. The goal of MOSAIC is to build the largest collection of spatial omics data in cancer. By integrating comprehensive high quality clinical annotations with advanced deep profiling techniques, MOSAIC aims to uncover novel cancer subtypes and identify key drug targets and biomarkers within them.

  Study EGAS50000000689

• NICHE - DNA-seq of MMR proficient early stage colon cancers

  The dataset includes 152 FASTQ files from paired-end WXS sequencing on Illumina HiSeq2500 or Novaseq 6000 for 31 pMMR patients. This includes 31 tumor DNA and 31 blood germline samples.

  Dataset EGAD50000001247

• NICHE - RNA-seq of MMR proficient early stage colon cancers

  The dataset includes 29 FASTQ files from single-end total RNA sequencing on Illumina HiSeq2500 and 66 files from 33 paired-end RNA sequencing samples on Novaseq 6000 for 31 pMMR colon cancer patients.

  Dataset EGAD50000001248

• Gene expression profiling in pregnancy-associated breast cancer

  Study EGAS00001008013

• EMBARCAM BC360 PROJECT

  This dataset is related to the EMBARCAM BC360 PROJECT. A total of 106 breast cancer samples, from Pregnancy-Associated Breast Cancer (PABC) (n=57) and non-PABC (n=49) patients, were analysed using the nCounter Breast Cancer 360 V2 panel on the NanoString platform. All samples were FFPE tumor samples from breast cancer patients, derived from GEICAM/2012-03, GEICAM/2017-07, and EpiGEICAM studies, sponsored by GEICAM.

  Dataset EGAD00010002709

• Longitudinal copy number variation analysis from plasma DNA of head and neck cancer patients under re-radiotherapy

  Recurrent locally advanced head and neck cancer (HNC) patients, receiving re-radiotherapy (re-RT), are presented with short progression-free (PFS) and overall survival. Hence, biomarkers predicting therapy failure are urgently needed. We analyzed copy number variations (CNVs) in blood plasma of HNC patients collected before, during and after re-RT. Detectable CNVs after five and ten fractions of re-irradiation as well as at the end of re-RT were associated with short PFS. Furthermore, we found that CNV kinetics in longitudinally collected plasma reflected therapy response and could detect disease progression in advance of radiographic tumor assessments.

  Study EGAS50000000163

• CANCAP03 single-nuclear RNA sequencing

  CANCAP03 single-nuclear RNA sequencing. Tissue punch cores for six patients, 3 from each of olaparib and olaparib and degarelix cohorts, were processed for nuclear isolation and extraction, prior to single-nuclear RNA sequencing. 10x libraries were constructed. Sequencing on NovaSeq 6000. FASTQ files were processed using CellRanger pipeline. Outputs from the CellRanger pipeline were analysed using the Seurat package in R.

  Dataset EGAD50000001280

• CANCAP03 Data Access Committee

  Dac EGAC50000000508

• Whole genome sequencing of circulating cell-free DNA on Illumina and Ultima platforms

  The dataset includes Illumina (n=1) and Ultima (n=92) sequencing of circulating cell-free DNA. The dataset was generated through standard whole genome sequencing (Illumina n=1 & Ultima n = 15) and using a duplex unique molecular identifier whole genome sequencing workflow (Ultima, n=77). This dataset includes cancer samples and cancer-free control samples.

  Dataset EGAD50000001234

• Constrained hypermutation and absence of TERT promoter mutations in Lynch syndrome-associated urothelial cancer

  Lynch syndrome is a hereditary condition characterized by defective DNA mismatch repair and high incidence of several cancers, including urothelial cancers (UC) of the upper urinary tract and bladder. We set out to study the somatic landscape of LS-associated urothelial cancer (LS-UC) by analyzing 41 surgical tumor samples and 3 urine DNA samples from 34 LS-UC patients.

  Study EGAS50000000831

• Targeted DNA sequencing of 44 urothelial cancer samples from 34 Lynch syndrome patients

  Targeted Illumina sequencing of 41 tumor tissue samples and 3 urine tumor DNA samples from 34 patients with Lynch syndrome associated urothelial cancer. Target capture was performed using the UroScout hybridization capture panel targeting the coding regions of 25 urothelial cancer genes. Sequencing libraries were constructed using the Twist Biosciences Enzymatic Fragmentation DNA Library Prep kit. Sequencing was performed using an Illumina NovaSeq 6000 instrument with 2x150 bp paired sequencing.

  Dataset EGAD50000001220

• Randomized Phase II 2 x 2 Factorial Trial of the Addition of Carboplatin +/- Bevacizumab to Neoadjuvant Weekly Paclitaxel Followed by Dose-Dense AC in Hormone Receptor-Poor/HER2-Negative Resectable Breast Cancer: DNA Sequencing

  This randomized phase II trial studies how well paclitaxel with or without carboplatin and/or bevacizumab followed by doxorubicin and cyclophosphamide works in treating patients with breast cancer that can be removed by surgery. Drugs used in chemotherapy, such as paclitaxel, carboplatin, doxorubicin, and cyclophosphamide, work in different ways to stop the growth of tumor cells, either by killing the cells or by stopping them from dividing. Bevacizumab may stop the growth of tumor cells by blocking blood flow to the tumor. Giving chemotherapy together with bevacizumab before surgery may make the tumor smaller and reduce the amount of normal tissue that needs to be removed. All participants in this study were female. RNA sequencing data from the same patients were published under phs001863. Subject aliases are the same in the two datasets.

  Study phs003801

• SAPCS Blood RNA-seq of prostate cancer patients

  The study aims to quantify the gene expression in blood samples in 20 prostate cancer patients under the Southern African Prostate Cancer Study (SAPCS). The objective is to identify a list of differentially expressed genes.

  Study EGAS50000000702

• Clonal Evolution of PPM1D Mutations in the Spectrum of Myeloid Disorders

  PPM1D, a central regulator of the DNA damage response, is commonly mutated in therapy-related clonal hematopoiesis (CH), acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS). PPM1D mutations have been shown to expand under selective pressure of DNA-damaging chemotherapy. However, whether PPM1D mutations promote the development of hematologic malignancies remains unclear.

  Study EGAS50000000840

• 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

  Anti-PD-(L)1 therapy is routinely used in metastatic NSCLC. However, response rates vary and biomarkers predicting treatment efficacy are lacking. Liquid biopsies allow monitoring of residual disease during therapy. Residual circulating tumor DNA (ctDNA) after therapy represents a predictive marker for adverse outcome. Here, we assessed copy number variations (CNVs) in serial plasma samples of NSCLC patients receiving PD-(L)1 blockade. We profiled CNV and fragmentation features in 118 plasma samples of advanced NSCLC patients by low-coverage whole genome sequencing taken at baseline, after four therapy cycles and at disease progression. CNVs and fragment features (i.e., fragment length, end motifs, position) were significantly altered in patients compared to healthy donors. Furthermore, fragment length changes at baseline and residual CNVs after four therapy cycles correlated with short progression-free survival. Our results highlight the suitability of plasma-based CNV and fragment analysis for disease monitoring and as a predictive marker for response duration in NSCLC patients under anti-PD-(L)1 therapy.

  Study EGAS50000000441

• WGS data of non-small cell lung cancer samples

  Paired-end WGS data from 118 non-small cell lung cancer samples from 49 patients. WGS was performed on Illumina NovaSeq 6000.

  Dataset EGAD50000000639

• 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

• Discovery and validation of an ancillary genomic test of malignancy for primary melanocytic tumors

  Background:Pathological diagnosis of melanocytic tumors can be difficult and prone to error. More accurate and reliable ancillary investigations than those currently available are required to improve diagnostic accuracy. Goals: (1) to generate a genomic model for distinguishing benign (nevi) from malignant (melanoma) melanocytic skin tumors, developed from a customized gene panel evaluated on a cohort of 250 nevi and melanomas. (2) To evaluate the performance of the genomic model in melanocytic tumors of uncertain diagnosis/behavior. Details: The cohort of 250 melanomas and naevi was split into a discovery set and a validation set. Our genomic model obtained an area under the curve of 95% in the discovery cohort and 96% for the validation cohort. Based on a Youden index threshold, the resulting classifier shows high specificity (>95% in the discovery and validation cohorts), with sensitivities >80% in the discovery and validation cohorts. Evaluation of the genomic model on a cohort of 110 melanocytic tumors identifies key driver mutations in agreement with the likely pathway of origin of the tumors. The probability of melanoma (p=0.02) from the genomic model was significantly associated with pathology-based estimates of malignancy for melanocytic tumors lacking pathway-defining genomic aberrations (conventional tumors). The genomic model identified 8/36 (22%) conventional tumors with unresolved malignancy to have a high probability of melanoma, with 7/8 of these cases showing negative/non-aberrant results with either fluorescent in-situ hybridization, PRAME and/or p16 immunostains. Furthermore, no evidence of malignant behavior based on the genomic model was seen in 4 conventional borderline tumors with more than 1 year follow-up. Conclusion: This genomic model can become a clinically useful ancillary tool that is highly specific for differentiating melanomas from nevi.

  Study EGAS50000000887