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• South African breast cancer GWAS genotype data in VCF format

  South African breast cancer GWAS genotype data for 2823 female African breast cancer cases. The data was generated using the H3Africa Custom microarray and genotyped on the Illumina HiScan instrument. The dataset is in VCF format.

  Dataset EGAD00010002732

• Gabriella Miller Kids First (GMKF) Pediatric Research Program in Susceptibility to Ewing Sarcoma Based on Germline Risk and Familial History of Cancer

  Ewing sarcoma (EWS) is a deadly bone cancer that occurs in children and adolescents. Mounting evidence suggests that a genetic predisposition exists for this pediatric cancer, although the specific genetic contribution has yet to be identified. EWS has never been linked to a specific cancer predisposition syndrome, although several case reports have been published that describe siblings and cousins with EWS. Furthermore, neuroectodermal tumors appear to occur more commonly in families with EWS. The two consistent epidemiology findings in EWS include a very strong Caucasian predilection and increased rates of hernia in EWS patients and their family members. Finally, the role of genetic microsatellite repeats in EWS tumorigenesis has been recently described, and these GGAA microsatellites are polymorphic in repeat size and location across the genome. The study goals of this Kids First project include (1) To identify cancer predisposition genes in EWS trios increasing disease risk, (2) To identify genome-wide GGAA microsatellite repeats in EWS trios increasing disease risk, and (3) To identity de novo mutation and structural variant rates in EWS trios reflecting underlying DNA repair defects that increase disease risk. As part of the Kids First Common Fund initiative, this study proposal will further elucidate the genetic contribution to pediatric cancer development. Around 375 of these trios were selected for whole genome sequencing as part of the Gabriella Miller Kids First fund. The EWS trios have been collected as part of the Children's Oncology Group's AEPI10N5 Study ("Genetic Epidemiology of Ewing Sarcoma"), and each trio has associated phenotypic data including a detailed family history. We will interrogate the sequence data using our genomic analysis pipeline at the University of Utah and the Utah Science Technology and Research initiative's (USTAR) Center for Genetic Discovery. We will look for the genetic contribution to EWS and the sequence data with be shared in a repository designated by the Kids First Common Fund. The WGS of these ~375 EWS trios will help us to understand the genetic origins of a deadly childhood cancer and may lead to novel strategies for prevention and treatment.

  Study phs001228

• Nala GSI GSAv3 PGx Study

  Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100 % phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

  Study EGAS00001007710

• GCAT Hereditary Cancer Panel Sequencing Dataset

  This dataset comprises targeted sequencing data from 191 participants of the GCAT cohort generated using the I2HCP custom hereditary cancer panel. The panel is based on a custom bait library covering 122 genes associated with hereditary cancer syndromes, including genes related to hereditary colorectal cancer, hereditary breast and ovarian cancer, neurofibromatosis, and related disorders. Target enrichment was performed using a clinically validated design optimized for diagnostic accuracy. The panel and associated bioinformatic pipeline were previously validated, achieving analytical sensitivity and specificity greater than 99%. Sequencing data were processed using standardized alignment and variant calling procedures against the human reference genome. The dataset includes raw sequencing reads (FASTQ format) and processed variant call files (VCF format). All samples were pseudonymized prior to submission in accordance with ethical approvals and participant consent. Data are available under controlled access.

  Dataset EGAD50000002415

• 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

• Natural variation of circulating RNAs in human serum

  The Janus Serum Bank (JSB) is a population-based cancer research biobank. This dataset contains small RNA sequencing (RNA-seq) data of 520 JSB samples from cancer-free individuals. Sequencing libraries were indexed and 12 samples were sequenced per lane on a HiSeq 2500 (Illumina) to an average depth of 18 million reads per sample. The dataset files are raw FASTQ files from the sequencing machine (50bp, single-end sequencing)

  Dataset EGAD00001003968

• Resistance to MAPK-inhibitor induces internal duplication in BRAF_Oscar Krijsman

  2 BRAFV600E cell lines that have been made resistance to 1. the BRAF inhibitor PLX4720 and 2. the combination therapy of dabrafenib and trametinib seem to have a internal duplication in the kinase domain. We would like to know if this is caused by a translocation.

  Dataset EGAD00001001846

• Uncovering RNA Signatures of C9orf72-Linked ALS and Related Disorders

  Substantial clinical and pathological variability has been reported in patients carrying an expanded repeat in C9orf72, who are generally diagnosed with amyotrophic lateral sclerosis (ALS) and/or frontotemporal dementia (FTD). Emerging evidence suggests that C9orf72 expression, RNA foci, and dipeptide-repeat proteins contribute to C9orf72-related diseases; however, the majority of the clinicopathological variability remains unexplained. We hypothesize that RNA sequencing (RNA-Seq) might reveal individual genes or groups of highly correlated genes (modules) that could account for this variability, which may help to identify much-needed druggable targets and/or biomarkers. Our preliminary studies performed in the frontal cortex, where we compared C9orf72 expansion carriers to (disease) controls, demonstrated that the top differentially expressed gene was C9orf72 itself. We also noticed that differentially expressed genes were enriched for the endocytosis pathway, which is consistent with the reported function of the C9orf72 protein in vesicle trafficking. Furthermore, we detected a module enriched for vesicular pathways, and additionally, we discovered an association with survival after onset for several promising candidates involved in vesicular transport. To find new therapeutic targets and biomarkers, here we have completed RNA-Seq on an increased number of samples to examine another relevant region: the cerebellum. As such, we performed RNA-Seq on a well-characterized cohort of C9orf72 expansion carriers, patients without this expansion, and control subjects without neurological diseases. We used multivariable linear regression models for gene-level analysis, weighted correlation network analysis for module-level analysis, and leafcutter for splicing analysis. Using the cerebellar RNA-Seq data, we found a large number (>6,000) of differentially expressed genes, with a notable increase in expression of homeobox genes in C9orf72 expansion carriers, as well as many gene modules that were associated with C9orf72 expansion status. Additionally, using leafcutter, we detected over 1,000 differential splicing events and an increase in the number of cryptic splicing events in C9orf72 expansion carriers.

  Study phs003065

• Initial leukemic epigenomic state determines hypomethylating agent response

  Hypomethylating agents (HMAs) are a mainstay of therapy for myeloid cancers, but genetic biomarkers do not predict who will respond to treatment. Using a variety of single-cell sequencing approaches to define the epigenomic state of responder and nonresponder leukemic cells, we aim to demonstrate that leukemic stem cells (LSC) exist in at least two different epigenomic states: a hematopoietic stem cell (HSC)-or multipotent progenitor (MPP)-like state that is sensitive to HMAs, independent of genetic mutations, or a lymphoid-primed MPP (LMPP)-like nonresponder state. Additionally, we aim to demonstrate that hypomethylation and chromatin accessibility at ZNF143- and CTCF-binding sites result in activation of HOXB4, which defines the HSC/MPP-like state and HMA-sensitivity. Our study aims to provide evidence that the epigenomic state of the LSC is a major determinant of response to HMAs, and demonstrates that a routine clinical assay can identify patients who will respond.

  Study EGAS50000000936

• Tumor inflammation and mutational burden are differentially associated with response to nivolumab or nivolumab plus ipilimumab in metastatic colorectal cancer

  Nivolumab alone and in combination with ipilimumab demonstrated durable clinical benefit in patients with previously treated microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer in the phase 2 CheckMate 142 study. Exploratory biomarker analyses of tumor and microbiome samples from CheckMate 142 were performed to evaluate associations between various biomarkers and the efficacy of nivolumab monotherapy and nivolumab plus ipilimumab combination in these patients. Higher expression of inflammation-related gene expression signatures was associated with improved response per investigator assessment and survival benefit with nivolumab monotherapy. In contrast, higher tumor mutational burden, tumor indel burden and degrees of microsatellite instability were associated with improved response per investigator assessment and survival benefit with nivolumab plus ipilimumab. While interpretation is limited by the exploratory nature of these analyses, they suggest that tumor antigenicity rather than baseline tumor inflammation might be important for the combinatorial efficacy. Validation of these findings in larger, randomized studies is necessary.

  Study EGAS50000000416