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• NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

  T-cell lymphoblastic lymphoma (T-LBL) is a common pediatric malignancy accounting for approximately 20% of the non-Hodgkin lymphomas during childhood. Survival rates of T-LBL are ~80%, but outcome after relapse is dismal, with salvage rates reaching only ~15. Considering the extremely poor prognosis after relapse and absence of clinically relevant high-risk genetics, there is an urgent need for the identification of molecular risk factors and new prognostic biomarkers in T-LBL, as well as identification of new therapeutic strategies. In this study we present a novel entity of high-risk pediatric T-LBL patients characterized by previously unknown NOTCH1 gene fusions and highly elevated blood TARC levels

  Dataset EGAD00001015255

• Genetic_mechanisms_of_resistance_to_chemotherapy_in_breast_cancer

  Resistance towards chemotherapy is one of the main causes of treatment failure and deathamong breast cancer patients.The main objective of this project is to identify genetic mechanisms causing some breastcancer patients not to respond to a particluar type of chemotherapy (epirubicin) while otherpatients respond very well to the same treatment.In the project we will perform genome / exome sequencing of a selection of breast cancerpatients (n=30). These patients are drawn from a cohort where all patients have recievedtreatment with epirubicin monotherapy before surgical removal of a locally advanced breasttumour, and where all patients have been subjected to objective evaluation of the response tothe therapy.Subsequent to sequencing, we will analyse the data and compare with the clinical data foreach patient (object response to therapy). The main aim being to identify mutations that areassociated with resistance to epirubicin.Identification of mutations with strong predictive value, may have a direct impact on cancertreatment since it opens the possibility for genetic testing of a tumour, and desicion on whichdrug is likely to work best, prior to treatment start.

  Study EGAS00001000276

• Clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancers defined by genomic analysis

  Ductal Carcinoma In Situ (DCIS) is the most common form of pre-invasive breast cancer and despite treatment a small fraction (5-10%) of DCIS patients present with invasive disease many years later. A fundamental biologic question is whether the invasive disease recurring in the same breast is established by tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial pure DCIS lesion and paired invasive recurrent tumors in 95 patients together with single cell DNA sequencing in a subset of cases. Our data shows that in 75% the invasive recurrence was clonally related to the initial DCIS, suggesting that the tumor cells were not eliminated during the initial treatment with surgery +/- radiotherapy. Surprisingly however, 18% were clonally unrelated to the DCIS, representing new independent lineages, and 7% of cases were ambiguous. Our findings show that although DCIS is often the precursor of invasive recurrence, a significant fraction of invasive recurrences are unrelated to the initial DCIS. This knowledge is essential for accurate risk evaluation of DCIS treatment de-escalation strategies and the identification of predictive biomarkers.

  Study EGAS00001005784

• Clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancers defined by genomic analysis

  Ductal Carcinoma In Situ (DCIS) is the most common form of pre-invasive breast cancer and despite treatment a small fraction (5-10%) of DCIS patients present with invasive disease many years later. A fundamental biologic question is whether the invasive disease recurring in the same breast is established by tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial pure DCIS lesion and paired invasive recurrent tumors in 95 patients together with single cell DNA sequencing in a subset of cases. Our data shows that in 75% the invasive recurrence was clonally related to the initial DCIS, suggesting that the tumor cells were not eliminated during the initial treatment with surgery +/- radiotherapy. Surprisingly however, 18% were clonally unrelated to the DCIS, representing new independent lineages, and 7% of cases were ambiguous. Our findings show that although DCIS is often the precursor of invasive recurrence, a significant fraction of invasive recurrences are unrelated to the initial DCIS. This knowledge is essential for accurate risk evaluation of DCIS treatment de-escalation strategies and the identification of predictive biomarkers.

  Study EGAS00001006306

• Polycystic Ovary Syndrome (PCOS) Genetics

  PCOS is a complex genetic disease reflecting the interplay of susceptibility genes and environmental factors. The cardinal reproductive feature of the syndrome, hyperandrogenemia, appears to play a direct role in the pathogenesis of the associated metabolic abnormalities. Male as well as female first-degree relatives have reproductive and metabolic phenotypes including increased prevalence rates of type 2 diabetes (T2D), metabolic syndrome (MBS) and other risk factors for cardiovascular disease (CVD). Northwestern University (NU) investigators lead a team that has extensive experience in phenotyping PCOS and in the genetic analysis of complex diseases including genome-wide association study (GWAS). Together with an expert group of collaborators from the Hershey Medical Center, and The University of Chicago, we have conducted a GWAS to identify PCOS susceptibility alleles using a large cohort of extensively and consistently phenotyped PCOS cases. Population controls for this study come from the NUgene project described below. NUgene project: In 2002, Northwestern committed to the development of a DNA repository to serve as a platform for the identification and validation of genotype-phenotype associations that will impact healthcare. The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators.

  Study phs000368

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005584

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_oncoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005586

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005587

• RNA sequencing of untreated head and neck cancer patient-derived xenografts (PDXs) and matched patient tumor tissue.

  RNA sequencing was performed on untreated patient tumor tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC). The aim of this analysis was to characterize the transcriptional landscape of the tumors in the in vivo setting. 117 total samples were sequenced with paired reads on 10 lanes from different flowcells. They were loaded as 2400 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002278

• Whole-exome sequencing (WES) analysis of untreated head and neck cancer patient-derived xenografts (PDXs) matched patient tumor tissue and normal mucosa tissue.

  WES analysis was performed on untreated patient tumor/normal mucosa tissue and matched patient-derived xenograft (PDX) models of primary head and neck squamous cell carcinoma (HNSCC) to investigate the preservation of tumor-specific genomic alterations in the in vivo context. 183 total samples were sequenced with paired reads on 8-10 lanes from different flowcells. They were loaded as 3538 separate files to maintain the data as it was received from BGI - each sample is therefore composed of 5 separate EGAN with 2-4 files each, adding a 0.1 - .. - 0.5 to each BioSample ID to generate sample aliases. All R1 (and R2, separately) files referring to a BioSample ID should be concatenated to obtain fastq files corresponding to single patients or PDXs.

  Dataset EGAD50000002325