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• GILD_ExomeSeq_PTNHL

  This study is meant to gain further knowledge in haematological cancers. Patients samples (mainly DNAs or PCR products) from haematolocical cancer patients will be sequenced, and the outputs will be correlated to their diagnosis and/or prognosis; the findings may also add more insight into the understanding of biology in this type of tumour. We will be sequencing Primary Testicular Lymphomas (PTL) to identify genetic drivers of this rare cancer

  Study EGAS00001001613

• Genomic Heterogeneity and the Small Renal Mass

  Tumor heterogeneity is believed to represent a barrier to pre-operative genomic characterization in kidney cancer. Previous studies of heterogeneity in clear cell renal cell carcinoma (ccRCC) evaluated only large and metastatic tumors. In small renal tumors in which multiple biopsies are not feasible, the extent of heterogeneity remains unknown. In this study, we evaluated how the extent of genomic heterogeneity in small and large ccRCC. A total of 23 small (<4cm ) and 24 large (>7cm ) ccRCC had 3 regions sampled for evaluation of copy number, clear-cell A/clear-cell B (ccA/ccB) classification, and cell cycle progression (CCP) score. Small tumors have less genomic complexity and significantly fewer subclonal events. Pre-treatment genomic characterization based on a single biopsy in small ccRCC can provide insight into biologic potential to make clinical decisions.

  Study EGAS00001002919

• Timing the landmark events in the evolution of clear cell renal cell cancer

  Clear cell renal cancer is characterized by near-universal loss of the short arm of chromosome 3 (3p). This event arises through unknown mechanisms, but critically results in the loss of several tumor suppressor genes. We analyzed whole genomes from 95 biopsies across 33 patients with clear cell renal cancer (ccRCC) recruited into the Renal TRACERx study. We find novel hotspots of point mutations in the 5'-UTR of TERT, targeting a MYC-MAX repressor, that result in telomere lengthening. The most common structural abnormality generates simultaneous 3p loss and 5q gain (36% patients), typically through chromothripsis. Using molecular clocks, we estimate this occurs in childhood or adolescence, generally preceding emergence of the most recent common ancestor by years to decades. Similar genomic changes recent common ancestor by years to decades. Similar genomic changes are seen in inherited kidney cancers. Modeling differences in age-incidence between inherited and sporadic cancers suggests that the number of cells with 3p loss capable of initiating sporadic tumors is no more than a few hundred. Targeting essential genes in deleted regions of chromosome 3p could represent a potential preventative strategy for renal cancer.

  Dataset EGAD00001003445

• Evaluating potential drug candidates for the treament of Henamgiopericytoma on patient derived cell line models

  Solitary fibrous tumor/Hemangiopericytoma (SFT/HPC) is a rare subtype of soft tissue sarcoma associated with NAB2-STAT6 gene fusions. This study established and characterized a novel SFT/HPC patient-derived cell line called SFT-S1. Potential drug candidates that could be repurposed for the treatment of SFT/HPC were screened. Screening was performed through RNA-Seq

  Dataset EGAD50000000039

• Whole-genome and transcriptome sequencing of primary cutaneous CD8+ aggressive epidermotropic cytotoxic T-cell lymphoma

  Primary cutaneous CD8+ aggressive epidermotropic cytotoxic T-cell lymphoma (pcAECyTCL) is a rare variant of cutaneous T-cell lymphoma with an aggressive clinical course and a very poor prognosis. We subjected tumor biopsies from patients with pcAECyTCL to whole-genome sequencing and RNA-sequencing to investigate genomic alterations and deregulated gene expression in the disease.

  Study EGAS00001004332

• Kidney_tumour_RNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002487

• Tumor Fraction Guided Cell-Free DNA Profiling in Metastatic Cancer Patients

  Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth. Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. The results show that cfDNA tumor fraction can inform the interpretation of negative cfDNA results and guide the selection of subsequent sequencing platforms that are most likely to identify clinically-relevant genomic alterations.

  Study phs002290

• Determination of the molecular nature of the Vel blood group by exome sequencing

  The genetic basis of the Vel group is yet to be determined. We have collected DNA samples from about 90 Vel negative blood donors by phenotyping 270,000 donors. Understanding the genetic basis of the Vel group could have clinical significance as transfusion of Vel positive blood to Vel negative recipients with anti-Vel can cause severe and acute haemolytic transfusion reactions.

  Study EGAS00001000069

• Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer

  Chromosomal instability is a major challenge to patient stratification and targeted drug development for high-grade serous ovarian carcinoma (HGSOC). Here we show that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and methylation status. We identified five prevalent clonal driver SCNAs (chromosomal amplifications encompassing MYC, PIK3CA, CCNE1, KRAS and TERT) from multi-regional HGSOC data and reasoned that their strong selection should prioritise them as key biomarkers for targeted therapies. We used primary HGSOC spheroid models to test interactions between in vitro targeted therapy and SCNAs. MYC chromosomal copy number was associated with in-vitro and clinical response to paclitaxel and in-vitro response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context of MYC-amplified HGSOC was statistically associated with increased prevalence of SCNAs in genes from the PI3K pathway. Co-occurrence of amplifications in MYC and genes from the PI3K pathway was independently observed in squamous lung cancer and triple negative breast cancer. These results suggest that identifying co-occurrence of clonal driver SCNA genes could be used to tailor therapeutics for precision medicine.

  Study EGAS00001006200

• Multi-Ethnic Study of Atherosclerosis (BioLINCC)

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics).

  Study phs003288