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• Columbia-Yale-Bilkent Study: Genetics Study of Essential Tremor

  This is a research development/planning grant application to initiate collaborative studies with investigators at Bilkent University in Turkey to study the genetics of Essential Tremor (ET). ET is one of the most common neurological diseases, with an estimated 7 million affected individuals in the United States. The most characteristic clinical feature of ET is a kinetic tremor in the hands or arms, which is mild early in the disease process. As the disease progresses, tremor becomes more severe and more anatomically widespread (e.g., head, trunk). Aside from tremor, patients with ET may also present with other motor features including gait ataxia. Non-motor features can include psychiatric manifestations, cognitive decline and dementia. Despite its extraordinarily high prevalence, the genetic causes of ET are largely unknown. We propose to develop a genetic study of ET focusing on consanguineous families in Turkey. Turkey with a population of about 70 million has a high rate of consanguineous marriages. The rate of consanguinity is estimated to be as much as 20-25% with approximately 70% of all consanguineous marriages involving first cousins. Studying the genetics of ET in the Turkish population, particularly in large consanguineous families, may identify novel genetic causes of ET that are also relevant to ET populations in the United States and worldwide. The proposed research has a high probability of success with our collaborators Drs Ozcelik and Tekinay's expertise in human genetics and functional studies together with an established resource of large consanguineous ET families. The specific aims of this planning grant are to: (1) further develop and solidify collaborations with the team in Bilkent and define the scope of the research that will be the focus of an R01 application, (2) assess the Bilkent team's resources and needs in order to successfully conduct the research, (3) implement cross-training between the United States and Turkish groups in the areas of human genetics, genetic epidemiology and risk factor assessment, genomics, clinical diagnosis, functional studies and personalized genomic medicine, and (4) conduct pilot studies to generate preliminary data necessary for an R01 application.

  Study phs001507

• High-resolution testing of ctDNA dynamics predicts survival in metastatic NSCLC

  One of the great challenges of therapeutic oncology is determining who might achieve survival benefit from a particular therapy. Circulating tumor DNA (ctDNA) provides real-time assessments of patient prognosis and response to treatment using a simple blood draw. While ctDNA positivity is established as a poor prognostic factor, studies on longitudinal ctDNA dynamics have been small and non-randomized, with ctDNA assessments done at disparate time points. To address this, we performed high-sensitivity longitudinal ctDNA testing in 466 patients across 5 time points (1,954 samples total) in a randomized phase III study comparing different chemotherapy-immunotherapy combinations. We leverage machine learning to jointly model multiple ctDNA metrics to predict overall survival in a training/testing framework. _ . Treatment initiation correlated with reductions in ctDNA levels, and training of our machine learning model suggests that assessment of ctDNA dynamics at C3D1 (cycle 3 day 1) of chemo-IO treatment may be optimal to predict OS. The model performs well in the hold-back test data, enabling stratification of patients with Stable Disease (SD) into high-risk vs low-intermediate-risk (HR = 3.2 [2.0-5.3], p <0.001; median 7.1 versus 22.3 months respectively); similarly, the model stratifies patients with a Partial Response (PR) (HR =3.3 [1.7-6.4], p <0.001; median 8.8 versus 28.6 months). Importantly, the model validates well in an external cohort of patients in a different treatment setting and assayed with a different ctDNA technology, in which model predictions similarly identified high-risk patients (OS HR=3.73 [1.83-7.60], logrank p=0.00012). Simulations of clinical trial scenarios employing our ctDNA model further suggest that early ctDNA testing outperforms early radiographic imaging for predicting trial outcomes (increasing the rate of ‘True Go’ decisions by 5.2 - 22.8% depending on the drug combination). Overall, we show that measuring ctDNA dynamics during the course of therapy dramatically improves patient risk stratification, and may provide a means to differentiate between competing therapies at an early time point during clinical trials.

  Study EGAS00001006703

• Peter Van Loo MPNST phase 1

  We comprehensively profile a primary malignant peripheral nerve sheath tumour (MPNST) and its recurrence with a multi-omic and spatial approach at single-cell resolution. Leveraging the extensive heterogeneity in copy number aberrations (CNAs) as a native barcoding system, we fully resolve the evolutionary tree of this tumour revealing multi-furcations suggestive of ongoing chromosomal instability. We show gene dosage effects contribute to phenotypic diversity and are predominantly linear. Using laser capture microdissection, we performed spatial lineage tracing in a human tumour, elucidating the relationship between local expansions and interactions between tumour cells and the microenvironment.

  Dac EGAC50000000904

• Transcriptomic analyisis of 54 samples of AC16 cells exposed to trastuzumab

  Data of 54 samples with their 54 paired fastaq files that were sequenced in a Novaseq 6000 platform. Samples correspond to the three biological replicates of AC16 cells (i.e. AC16, C1, C2). Each biological replicate was edited to carry either of the three different genotypes of the rs1136201 variant (i.e. AA, AG, GG) and each genotype was enriched to express HER2 protein in three levels (i.e. low, medium and high expression) as selected by FACS. Additionally, treatment of each sample was performed and sequenced in duplicates (i.e. 1 and 2)

  Dataset EGAD50000001705

• CITEseq data of Reactive Lymph Nodes

  Mononuclear cells were isolated as cell suspensions by dissociation in a BD Horizon™ Dri Tumor & Tissue Dissociation Reagent (BD Biosciences) using a gentleMACS dissociator (Miltenyi Biotec). A totalseq-C antibody cocktail (Biolegend) was used, and the cell suspensions were diluted to a concentration of 1,000 cells/μL. Library sequencing was performed using the NovaSeq6000 System (Illumina). The FASTQ files were aligned to the 10x provided reference genome using 10x Genomics Cell Ranger software v7.1.0 to create unique molecular identifier count tables of gene expression of the samples.

  Dataset EGAD50000000538

• RNA sequencing of pretreatment, on-treatment and posttreatment gastric and gastroesophageal junction tumors treated with neoadjuvant anti-PD-L1 plus chemotherapy

  This set contains a total of 78 files cram files with RNA sequencing data from 20 patients included in the PANDA study treated with 1 cycle of monotherapy atezolizumab and 4 cycles atezolizumab plus chemotherapy (docetaxel, oxaliplatin and capecitabine). RNA was isolated from fresh frozen material and sequenced at 4 timepoints baseline, after monotherapy atezolizumab, after combination atezolizumab plus chemotherapy and at resection (due to 2 missing samples, there is a total of 78 samples).

  Dataset EGAD50000000241

• ctgap-G-1

  Illumina HumanCoreExome-12v1-1_A chip typing in a Greek adolescent population

  Dataset EGAD00010001005

• RNA sequencing data of pediatric T-cell acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample and from a relapse sample from tonsil of one T-ALL patient (ALLT-317). Data from the relapse sample from bone marrow of this patient is in set 1 of this submission. TruSeq Stranded Total RNA Library Prep (Illumina) kit was used in library preparation, and Novogene's internal method was utilized in rRNA removal. The diagnostic and relapse tumor samples were sequenced using Illumina Novaseq X Plus, and the target sequencing depth was 21 Gb per sample.

  Dataset EGAD50000002585

• cfDNA from fractionated and paired unfractionated plasma samples of lung cancer patients

  Plasma from lung cancer patients from EDTA tubes was fractionated using size exclusion chromatography. Fractions 1-5, 7-11, 12-15, 16-20 were pooled, cfDNA was extracted from the fractions and paired unfractionated samples and PE150bp sequencing was performed on an Illumina Novaseq S4 flowcell. Samples are provided as raw reads without any prior processing.

  Dataset EGAD00001009780

• Population-based analysis of POT1 variants in a cutaneous melanoma case-control cohort

  Pathogenic germline variants in the protection of telomeres 1 gene (POT1) have been associated with predisposition to a range of tumor types, including melanoma, glioma, leukemia and cardioangiosarcoma. We sequenced all coding exons of the POT1 gene in 2,929 European-descent melanoma cases and 3,298 controls, identifying 43 protein-changing genetic variants. We performed functional studies on each of these variants and explored their possible contribution to disease risk.

  Dataset EGAD00001009848