12143 results for "cancer rna-seq"

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• OT2_Solid_WXS_T

  Whole-exome sequencing on AB 5500xl Genetic Analyzer of colorectal cancer primary tumor sample (OT2_cohort)

  Dataset EGAD00001003386

• Prostate cancer datasets WES

  WES: 48 samples (5 blood samples from 6 patient data): 22 Tumour cores and 26 normal/benign cores (HiSeq)

  Dataset EGAD00001004467

• OT2_Illumina_WGS_MET

  Whole-genome sequencing on Illumina HiSeq2000/2500 of colorectal cancer metastasis sample (OT2_cohort)

  Dataset EGAD00001003372

• Illumina_WGS_T

  Whole-genome sequencing on Illumina HiSeq2000/2500 of colorectal cancer primary tumor sample

  Dataset EGAD00001002088

• Hipo-032 Metastasome of Colorectal Cancer

  Whole genome sequencing of Control (blood), Tumor and metastasis triplets for 12 samples.

  Dataset EGAD00001003965

• pilot

  Pilot study for genome-wide sequencing of cell-free DNA from nipple aspirate fluid and plasma of breast cancer patient

  Dataset EGAD00001010836

• BASIS Genome Validation Study

  Bespoke validation experiments will be performed on ER+ Breast Cancer cases to confirm the presence of mutations found in whole genome sequencing.

  Dataset EGAD00001000661

• Molecular characterization of invasive lobular carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer accounting for 10-15% of cases. ILC differs from invasive ductal carcinoma (IDC)with respect to epidemiology, histology, and clinical presentation. Moreover, ILC is lesssensitive to chemotherapy, more frequently bilateral, and more prone to form gastrointestinal, peritoneal, and ovarian metastases than IDCs. In contrast to IDC, the prognostic value ofhistological grade (HG) in ILC is controversial. One of the three major components of histological grading (tubule formation) is missing in ILC which hinders the process of gradingin this histological subtype and results in the classification of approximately two thirds of ILC as HG 2.Over the last decade, a number of gene expression signatures have shed light onto breast cancer classification, allowing breast cancer care to become more personalized. Withrespect to the management of estrogen receptor (ER)-positive breast cancer, several gene expression signatures provide prognostic and/or predictive information beyond what is possible with current classical clinico-pathological parameters alone. Nevertheless, most studies using gene expression signature have not considered different histologic subtypesseparately. Recently, a comprehensive research program has elucidated some of the biological underpinnings of invasive lobular carcinoma. Genetic material extracted from 200 ILC tumor samples were studied using gene expression profiling and identified ILCmolecular subtypes. These proliferation-driven gene signatures of ILC appear to have prognostic significance. In particular, the Genomic Grade (GG) gene signature improved upon HG in ILC and added prognostic value to classic clinico-pathologic factors. In addition this study demonstrated that most ILC are molecularly characterized as luminal-A (~75%)followed by luminal-B (~20%) and HER2-positve tumors (~5%). Moreover, we investigated the prognostic value of known gene signatures/ gene modules in the same cohort of ILC. As a second step within the scope of this project, we aim to investigate the interactionsbetween somatic ILC tumor mutations to observed transcriptome findings. To this end, we aim to perform somatic mutation analysis for the ILC tumors for which Affymetrix gene expression profiling is available. To this end, we will use a gene screen assay, which specifically interrogates the mutational status of a few hundreds of cancer genes. We believe that this pioneering effort will be fundamental for a tailored treatment of ILC withimprovement in patients' outcome.

  Dataset EGAD00001000288

• Nivolumab and Tumor Infiltrating Lymphocytes (TIL) in Advanced Non-Small Cell Lung Cancer

  We performed a trial of adoptive cell therapy using tumor infiltrating lymphocytes (TIL) in metastatic non-small cell lung cancer (NSCLC). We conducted a single-arm open- label phase 1 trial (NCT03215810) of TIL administered with nivolumab in 20 patients with advanced NSCLC. Patients had tumor metastases resected for TIL, and the sequencing data from these tumors is included herein. The primary endpoint was safety, and secondary endpoints included objective response rate, duration of response, and T-cell persistence. Autologous TIL was expanded ex vivo from minced tumors cultured with IL-2. Patients received initial nivolumab for 4 cycles. If they had subsequent evidence of progression, then they proceeded to receive cyclophosphamide and fludarabine lymphodepletion, TIL infusion, and interleukin-2, followed by maintenance nivolumab. The endpoint of safety was met according to pre-specified criteria. Of 13 evaluable patients, 3 had confirmed responses and 11 had reduction in tumor burden, with a median best change of 35%. Two patients achieved complete responses ongoing 1.5 years later. In exploratory analyses, we found T cells recognizing multiple types of cancer mutations were detected after TIL treatment, and were enriched in responding patients.

  Study phs002486

• Detecting and Subtyping Lung Cancer Through Analysis of Circulating Tumor DNA

  Small cell lung cancer (SCLC) is among the most aggressive tumors with poor clinical outcomes. Tumors are rarely resected, which is a major barrier to molecular profiling of tumor tissue; therefore, non-invasive approaches using circulating tumor DNA (ctDNA) from liquid biopsies are needed to help advance research and clinical care for patients with SCLC. We developed a targeted capture panel that profiles SCLC genes and transcriptional regulation sites, including transcription start sites (TSS) and transcription factor binding sites (TFBS). This is a single assay that detects genomic mutations and transcriptional regulation activity based on ctDNA fragment patterns reflecting epigenetic nucleosomal positions. We applied this assay to sequence patient-derived xenograft (PDX) and patient plasma samples. We also performed whole genome sequencing (WGS) for a subset of the PDX plasma samples to validate the capture data. We developed new algorithms to quantify activity of key SCLC marker genes of ASCL1, NEUROD1, POU2F3, and ATOH1 and to classify SCLC subtypes based on activity of these markers. Furthermore, we developed a model to classify SCLC from non-small cell lung cancer (NSCLC), which has potential important applications for monitoring transdifferentiation and tumor plasticity.

  Study phs003570