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• Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS)

  Advances in antiretroviral therapies (ART) and patient management have improved survival of people living with HIV (PLWH). However, with exposure to ART and associated side effects and toxicities as well as to the virus itself, PLWH are at an increased risk of several chronic diseases. The Centers for AIDS Research (CFAR) Network of Integrated Clinical Systems (CNICS) research network integrates longitudinal clinical data and treatment management of PLWH and provides research infrastructure to support HIV-associated clinical, social, and behavioral outcomes and comparative effectiveness research using data collected from 8 Centers for AIDS Research clinical sites across United States. For detailed study description, see Kitahata et al. (2008, PMID:18263650).

  Study phs001788

• Proteomic Characterization of Intrahepatic Cholangiocarcinoma Identifies Risk-Stratifying Subgroups, Proteins Associated with Time-To-Recurrence, and mTOR Effector Molecule EIF4A1 as a Druggable Therapeutic Target

  Using mass spectrometry-based proteomics, we analyzed two independent cohorts comprising 80 and 62 treatment-naive ICC tumors, 67 adjacent non-malignant tissues, and 9 patient-derived xenografts (PDX). In the first cohort, we identifed two subclusters with distinct times-to-recurrence (TTR). A 4-protein classifier trained on our data cohort accurately stratifies these ICC clusters in the Dong et al. dataset (2022) and in our independent second cohort, revealing similar associations between proteomic motifs and clinical outcomes. The Translation regulator EIF4A1 emerges as a therapeutic target, as its inhibition with novel drug eFT226 significantly reduces tumor growth in an ICC PDX model.

  Study EGAS50000001343

• scRNA-seq of HSPC treated with gemcitabine and carboplatin

  4 samples of 2000000 HSPCs in 2 ml media each were then prepared and treated for 24 hours: carboplatin-high: 150 µg/ml carboplatin carboplatin-low: 18.75 µg/ml carboplatin gemcitabine: 25 ng/ml gemcitabine control: no drug Single-cells were subsequently extracted using the ddSEQ™ Single-Cell Isolator (Bio-Rad) and later sequenced using the SureCell™ Whole Transcriptome Analysis 3' Library Prep Kit (Illumina) on the NextSeq 500 System (Illumina) using the NextSeq 500/550 High Output Kit v2.5 150 Cycles (Illumina) all following the manufacturer's instructions. The raw FASTQ-files are available as read 1 and read 2 files from 4 lanes for each sample giving a total of 16 FASTQ-files. The FASTQ-files were also processed following the ddSeeker (Romagnoli, D., et al., BMC Genomics 2018, doi:10.1186/s12864-018-5249-x) and Drop-seq (Macosko, E.Z., et al., Cell 2015, doi:10.1016/j.cell.2015.05.002) protocols for processing scRNA-seq data to yield the final digital gene expression (dge) for each cell of each sample. This has resulted in one dge text file and one dge summary text file per sample. These 8 text-files with dge data are found in the zip-compressed analysis data-file.

  Dataset EGAD00001006080

• Deep amplicon sequencing to infer malignant clonal populations for The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

  A total of 192 positions per patient were deeply sequenced in each corresponding tumor sample (including 4 experimental controls and SNVs predicted to originate at each node of the sample phylogeny, see Zhang et al. for details). Genomic DNA templates were used as starting material to generate PCR products. PCR was set up using Phusion DNA polymerase according to the manufacturer’s specifications. The standard PCR conditions used were an initial denaturation at 98C for 30 seconds, followed by 35 cycles of 98C for 10 seconds, 60C for 15 seconds and 72C for 8 seconds, and a final extension at 72C for 10 minutes. PCR products were cleaned up using PCRClean DX beads. Amplicons were pooled by template for sequencing sample preparation. Sample preparation involved a second round of amplification using Phusion DNA polymerase with 6 PCR cycles, with primers specified in Zhang et al. DNA quality was assessed using the Caliper LabChip GX HighSensitivity Assay and DNA quantity was measured using a Qubit dsDNA HS assay kit on a Qubit fluorometer. The indexed libraries were pooled together and sequenced on the Illumina NextSeq500 platform with paired-end 150bp reads using v2 chemistry reagents.

  Dataset EGAD00001003986

• HTAN MCL Pre-Cancer Atlas Pilot Project - Targeted Sequencing Development Study

  The HTAN-MCL Pre-Cancer Atlas Pilot Project (PCAPP) is the result of a collaboration between the seven members of the MCL consortium. Across four organ types, PCAPP's goal is to collect and profile pre-malignant lesions for gene expression, DNA mutations, single-cell gene expression and immune-environment. Most PML are small in size and only available come from formalin fixed paraffin embedded archived tissue. The primary goal of PCAPP is to 1) understand the logistical challenges of PML specimen collection, 2) document technical limitations of the assays that are specific to the PML and 3) overcome them to support the generation of a more comprehensive Pre-Cancer Atlas in the future. The current upload provides RNA and DNA sequencing from participants with DCIS who were studied at the University of San Diego and the University of Vermont. Description of the overall study: A. Background/Significance One of the critical barriers to developing new approaches for cancer detection and prevention is the lack of understanding of the key molecular and cellular changes that cause cancer initiation and progression. Unlike the extensive work that has been done profiling advanced stage tumors, few studies have comprehensively profiled the molecular alterations found in precancerous tissues. Premalignant lesions are currently characterized by histologic changes that precede the development of invasive carcinoma1,2.These lesions can often be identified in regions surrounding an invasive tumor or in biopsies taken from patients undergoing diagnostic evaluation for suspicion of cancer. Currently, limited metrics exist to identify lesions that will likely progress to carcinoma and require intervention from those that will naturally regress or remain stable3,4. Characterization of the molecular alterations in premalignant lesions and the corresponding changes in the microenvironment would hasten the development of biomarkers for early detection and risk stratification as well as suggest preventive interventions to reverse or delay the development of cancer. Our pilot study will establish the feasibility of transcriptomic, genomic and immune profiling of FFPE premalignant lesions from multiple organ sites, collected and profiled with uniform SOPs across multiple institutions within the MCL consortium. We will characterize the molecular alterations in precancerous lesions and the corresponding microenvironment in four major organ sites, in order to uncover the molecular and cellular determinants of premalignancy, and establish standardized sequencing and immunohistochemistry protocols on FFPE precancerous tissue. We will also evaluate the technical feasibility of single nuclei sequencing of small FFPE pre-cancer lesions. Successful completion of the proposed pilot study will set the stage for expansion and development of a comprehensive Pre-Cancer Atlas (PCA) as part of the NCI's moonshot.B. Specific Aims Aim 1: Collect premalignant lesions (PML) and their associated microenvironment via LCM from FFPE tissue across four organ sites (breast, lung, pancreas & prostate). Aim 2: Perform bulk RNA and DNA seq on premalignant FFPE samples (and flash frozen tissue where available) and compare the genomic/transcriptomic alterations within and across organ sites. C. ApproachAim 1: Collect premalignant lesions (PML) and their associated microenvironment via LCM from FFPE tissue across four organ sites (breast, lung, pancreas & prostate). MethodsI. Patient Population/Sample Collection: Overview of the sites collecting PML tissue from the respective organs is provided in Table 1 and a full description of the biospecimens to be obtained is described in detail for each organ type below. Table 1. Breakdown of cohort by tissue type and collection site.Organ siteBreastLungPancreasProstateType of PMLDCISAAH, Squamous Dysplasia/CISIPMNsPINCollection of PatientsUCSF/UCSDUVMBU*/UCLAVanderbilt/MoffittMDACC*JHUStanford*# of Patients201920 (10 of each type)20 (10 of each type)242020Total patients per Organ39402440Note: single nuclei/cell RNA-Seq will be performed on 4-5 FFPE samples from each of the organ types 1. DCIS lesions from breast tissue: DCIS lesions will be collected from 39 patients (20 from UCSF/UCSD & 19 from UVM) with primary low or high-grade DCIS diagnosed from a breast core biopsy. Subsequent resected lumpectomy or mastectomy tissues will be prospectively sampled in the vicinity of the prior biopsy site using multiple approaches: 1) Live cells (heterogeneous mix) will be obtained as a cell scrape slurry from the lesion surface or by fine needle aspirate (FNA); 2) For a subset of specimens where size is sufficient, a block of breast tissue with DCIS will be fresh-frozen; 3) The remainder of the specimen will be taken for routine formalin-fixation and paraffin-embedding (FFPE). The FFPE sample will be annotated to identify the matched FFPE tissue block adjacent to the fresh-frozen sample and will be sectioned for use in bulk and single nuclei sequencing . We will dissect DCIS, adjacent normal and when available, associated carcinoma. In addition, when possible, normal tissue will be collected from a tissue block lacking lesions as well as collection of blood. A subset of patients (n = 5 | FFPE, flash frozen and fresh) will be sent to the Broad Institute for single nuclei/cell sequencing.2. AAH and squamous dysplastic/CIS lesions from airway and lung tissue: For squamous cell lung cancer, we will collect endobronchial biopsies from abnormal airway regions identified on autofluroscence bronchoscopy or identify PMLs in the margins of resected lung tissue. We will study 20 patients (5 each from BU/UCLA/Vanderbilt/Moffitt) with pre-invasive squamous lesions (moderate-severe dysplasia or carcinoma in situ (CIS)) identified on pathologic examination. LCM of the premalignant region and adjacent normal epithelium will be performed as well as the invasive tumor for those collected from the resection margin (n=5 from UCLA). On a subset of lesions collected at bronchoscopy (n=5), we will collect additional biopsies that will be flash frozen and fresh for single nuclei and cell sequencing, respectively, performed at the Broad Institute. In parallel to the work at the Broad, BU will perform single cell RNA-seq on these freshly cell sorted tissues (n = 5). Blood will be collected on all patients for genomic studies. For lung adenocarcinoma, we will collect resected FFPE lung tissues from 20 patients (10 from UCLA and 10 from Vanderbilt/Moffitt) with early stage lung adenocarcinoma that harbor atypical adenomatous (AAH) premalignant lesions in the resection margin. We will LCM multiple AAH regions (3-5 per patient) as well as adjacent regions of normal epithelium and invasive adenocarcinoma. In addition, blood will be collected on all patients for genomic studies. 3. IPMNs from pancreatic tissue: For pancreatic cancer PML, we will collect low and high grade lesions from 24 patients representing macroscopic Intraductal Papillary Mucinous Neoplasms (IPMN) (n=24) from surgically resected specimens along with blood samples. Archival FFPE specimens of microscopic PanIN lesions, occurring multi-focally adjacent to invasive PDAC, and archival IPMN lesions (with or without associated invasive cancer), along with the adjacent normal tissue, will undergo LCM and utilized for bulk DNA and RNA sequencing. If matched frozen tissues are available for a subset of these FFPE samples, we will bank for comparison of profiles. Because IPMNs are macroscopic lesions, they provide an opportunity for obtaining the samples fresh and therefore can be used for single cell sequencing (in contrast to PanINs). Therefore, 5 freshly obtained IPMNs will be used for the single cell RNA sequencing studies performed at both the Broad Institute and MDACC, and the matched FFPE and/or frozen sections from these lesions (obtained from the adjacent PML) will be sent to Broad Institute as a pilot to assess "single nuclei" RNA sequencing.4. PINs from prostate tissue: For prostate cancer PML, there will be 40 samples of Prostatic Intraepithelial Neoplasia (PIN) collected between the Stanford and JHU sites (20 cases per site). At the Stanford site, 20 prostate specimens detected by PSA screening who have/will undergo surgery (radical prostatectomy) for clinically localized disease will make up the final cohort. The age range of the participants would be 40-75, and we anticipate that 18 will be Caucasian, 1 Asian and 1 Latino or African American based on the practice demographics practice at Stanford. Clinical and MRI data will also be collected for these samples. We will collect low grade (e.g. Gleason score of 6/Grade group 1; n=10) and high grade (Gleason score 4+3=7 or higher/Grade group 3 or higher; n=10) PINs from FFPE samples that have prostate carcinoma. In addition to obtaining LCM archival samples of low and high grade PIN, we will also obtain normal prostatic epithelial from the peripheral, central and transition zones as well as multiple samples of prostate carcinoma in order to obtain the spectrum of Gleason grades in the carcinoma as needed. LCM samples will be used for bulk DNA and RNA sequencing. In addition, single cells will be dissected from FFPE samples to prepare single cell RNA seq libraries using techniques developed at Stanford, and FFPE tissue will be sent to the Broad for single nuclei sequencing. When available, flash frozen and fresh samples from these prostates will be archived and prepared for single nuclei and cell sequencing, respectively, at the Broad Institute and at Stanford (single cell only). JHU will also capture 10 cases (5 grade group 1 and 5 grade group 2) of high grade PIN, normal and invasive adenocarcinoma using frozen sections from fresh frozen tissues. When possible these will be from the same patients as the FFPE samples. Since frozen sections can be quite challenging to morphologically determine high grade PIN from normal epithelium, for these samples we will perform a number of additional tissue-based characterizations. These will include a multicolor combined basal cells (p63 and CK903) and PIN/carcinoma markers (AMACR) referred to in the cocktail as "PIN4", c-MYC (referred to as MYC) protein5, by IHC and mRNA by in situ hybridization (AM De Marzo, Q Zheng unpublished observations), telomere length by in situ hybridization6 and the 5'ETS/45S rRNA7. For these slides, the whole slides will be scanned with a Hammamatsu Nanozoomer with a 40x objective and regions of interest will be annotated as a guide for LCM.II. Laser-capture microdissection (LCM): FFPE tissue blocks will be sectioned at 7μm thickness and serial sections will be stained with H&E. LCM will be performed utilizing standard LCM systems, such as Leica LMD7000 and ArcturusXT at each site. Regions of premalignancy will be dissected and RNA/DNA will be extracted from microdissected cells using the Qiagen All Prep DNA/RNA FFPE Kit. Aim 2: Perform bulk RNA and DNA seq on premalignant FFPE samples and compare the genomic/transcriptomic alterations within and across organ sites. Rationale: There have been limited studies characterizing the genomic and transcriptomic landscape of premalignant lesions associated with breast, pancreatic, lung or prostate cancers. Characterizing the molecular determinants of premalignant disease that are unique and shared across multiple organs will enable new candidate biomarkers for early detection and novel therapeutic strategies for early intervention. MethodsBulk RNA-seq of LCM FFPE tissue: All participating sites will perform bulk RNA-seq in accordance with SOPs developed at BU. In brief, total RNA will be isolated from LCM'd lesion and associated microenvironment tissue using the Qiagen All Prep DNA/RNA FFPE Kit and quality will be assessed with the Agilent Bioanalyzer. Libraries will be generated with the Illumina TruSeq Access kit (for FFPE samples). They will be sequenced on the Illumina HiSeq2500 with 75base-pair paired-end reads. Quality of FASTQ files will be assessed with FastQC. Reads will be aligned to the human genome with STAR and gene-level and isoform-level expression will be quantified with RSEM. Splice junction saturation, transcript integrity, and biotype distributions will be calculated for each sample with RSeQC. DESeq2 and EdgeR will be used to identify associations between gene expression profiles and clinical variables while controlling for confounding covariates. BU will serve as an RNA-seq Core to assess reproducibility of FFPE RNA-seq methods across sites. We will perform RNA-seq according to the SOP listed above on a subset of samples for each organ type (total n ~ 20). Bulk seq of DNA from FFPE tissue: All participating sites will perform targeted or whole exome-seq (WES) in accordance with SOPs. In brief, DNA from laser captured material will be isolated using the Qiagen All Prep DNA/RNA FFPE Kit and undergo stringent quality control to ensure high quality input material for genomic profiling. Purified DNA (ideally 100-200 ng) will be used for library preparation and amplification, followed by next generation sequencing using standard protocols distributed by CDMG. Exome-seq methods are considered standardized, thus we will not need a DNA-seq Core to assess reproducibility across sites. We anticipate local centers will use Illumina paired end reads, following the following general approach. 1) DNA library preparation: Paired-end libraries will be prepared following the manufacturer's protocols (Illumina and Agilent), fragmented to 150-200 bp 2) Capture of targeted exome: Whole exome capture will be carried out using the protocol for Agilent's SureSelect Human All Exon kit. Purified capture products will be amplified using the SureSelect GA PCR primers (Agilent) for 12 cycles. 3) Sequencing will be carried out for the captured libraries using at least 100 bp paired-end reads. To achieve high level sensitivity and accuracy for detecting all the mutations in the whole exome, each sample will be sequenced at 200X mean depth. 4) Read mapping and alignment and variant analysis: Sequence short reads will be aligned to a reference genome (NCBI human genome assembly build 38) using BWA-MEM. Local realignment of aligned reads will be performed using Genome Analysis Toolkit (GATK).Data QC: To ensure scientific rigor and consistency among sites in RNA and DNA processing we will include a preliminary analysis of steps in processing and analysis. Protocols for extraction of high quality RNA and DNA from formalin fixed paraffin embedded (FFPE) tissues, which will be used extensively in these studies continue to improve and may have variable implementation among the sites participating in this study. To evaluate consistency of preliminary steps in processing and downstream analyses, we will initially distribute slides from one large FFPE fixed cancer of origin from prostate, breast, lung and pancreatic cancer. Analysis of these samples will allow us to review the DNA and RNA characteristics (yield, purity and strand length) among sites. Downstream analysis of these same samples will also allow us to compare among sites the consistency of variant calls among centers. We will be able to identify if there are some times of calls (such as small insertion deletions) that are more variable among centers versus other types of calls (such as relative gene expression or single base pair substitutions) that we expect to be less variable and to characterize the reliability of findings across sites. We are also including a 5% blind duplicate analysis of RNA sequencing. Samples will be analysed by the participating genomics cores without knowledge of the phenotype. RNA seq and CNA analyses are normalized for batch effects. We will also compare the observed sex to the self-reported sex as based on RNA profiles and exome sequencing of X chromosome genes as another check for processing accuracy and sample management. D. References 1. Wacholder, S. Precursors in Cancer Epidemiology: Aligning Definition and Function. Cancer Epidemiol. Prev. Biomark. 22, 521-527 (2013). PMID: 23549395.2. Berman, J. J. Precancer: The Beginning and the End of Cancer. (Jones & Bartlett Learning, 2011).3. Nasiell, K., Nasiell, M. & Vaćlavinková, V. Behavior of moderate cervical dysplasia during long-term follow-up. Obstet. Gynecol. 61, 609-614 (1983). PMID: 6835614.4. Merrick, D. T. et al. Persistence of Bronchial Dysplasia Is Associated with Development of Invasive Squamous Cell Carcinoma. Cancer Prev. Res. (Phila. Pa.) 9, 96-104 (2016). PMID: 26542061.5. Gurel, B. et al. Nuclear MYC protein overexpression is an early alteration in human prostate carcinogenesis. Mod. Pathol. Off. J. U. S. Can. Acad. Pathol. Inc 21, 1156-1167 (2008). PMID: 18567993.6. Meeker, A. K. et al. Telomere shortening is an early somatic DNA alteration in human prostate tumorigenesis. Cancer Res. 62, 6405-6409 (2002). PMID: 12438224.7. Guner, G. et al. Novel Assay to Detect RNA Polymerase I Activity In Vivo. Mol. Cancer Res. MCR 15, 577-584 (2017). PMID: 28119429.

  Study phs002225

• Effects of Metformin on Transcriptomic and Metabolomic Profiles in Breast Cancer Survivors Enrolled in the Randomized Placebo-Controlled MetBreCS Trial

  RNA from snap-frozen breast tissue biopsies were purified after lysing by tissuelyser (Qiagen) and using RNA Purification Plus Kit (Norgen biotek CORP, 47700) with additional on-column DNase-I treatment (Qiagen, 79254) at 27 °C. RNA purity and integrity (RIN) were quantified using RNA 6000 Nano kit (Agilent Technologies, 5067-1511) on the 4200 TapeStation (Agilent, Santa Clara, USA). Library preparation and 2x75bp paired-end of 160 ng total RNA input was performed using Illumina Stranded Total RNA Prep Ligation kit and Illumina HiSeq4000 system (Illumina, Sand Diego, CA, USA). RNA sequencing data from HiSeq4000 were quality checked and aligned to GRCh38 (GCA_000001405.15) reference genome using HISAT2 2.0.5 and submitted to subread v.1.5.2 for feature counts calculation. Finally, 36 paired biopsies samples (metformin n=26 and placebo n=12) were sequenced and included in the final analyses.

  Dataset EGAD50000001274

• National Cancer Institute (NCI) Adding Hispanics to Ongoing GWAS in Colorectal Cancer

  Genome-wide association studies (GWAS) of colorectal cancer (CRC) have been instrumental in identifying a number of common susceptibility loci in Non Hispanic (NH)-White populations, and a NCI priority is to extend GWAS findings to other populations to address racial/ethnic disparities in cancer susceptibility. Currently, GWA studies of CRC in NH-Whites, Japanese and African-Americans are ongoing. We propose a complementary study to address this critical research area in Hispanics. Hispanics represent the fastest growing ethnic population in the U.S. and have been largely understudied in terms of genetic susceptibility to cancer. There are noted differences in incidence, survival and mortality in CRC by ethnic/racial groups. Hispanics often present with CRC at a younger age and have a significantly greater incidence of stage IV tumors or metastatic disease compared to NH-Whites. We propose to conduct a large, cost-efficient, population-based GWAS in Hispanics by building upon existing NIH-funded resources, the Colon Cancer Family Registry (Colon CFR) and the Multiethnic Cohort Study (MEC). We plan to recruit 2,500 Hispanic men and women diagnosed with CRC between 01/2008 to present using cancer registries in California, physican referrals and familial referrals. Risk factor/diet questionnaires, pathology reports, Oragene saliva samples (for genotyping), optional blood samples (for genotyping and biometric analysis) and tumor blocks (for MSI testing) will be collected using methodologies developed in the Colon CFR/MEC. Cases of CRC in the MEC (currently 473; anticipated 600 at end) will also be included. Population-based Hispanic individuals without a diagnosis of CRC participating in other GWA studies in the MEC (n=3,900, U01HG004726, Haiman) will be used as controls. We will genotype all 3,100 cases using the Illumina 1M array and use available genotype and epidemiologic data collected on 3,900 controls. Our statistical analyses will include: single-SNP and haplotype effects, gene-environment interactions and heterogeneity by MSI, tumor subtype and family history of CRC. We will replicate findings in a second-stage using CRC cases and controls from Mexico (1,000 cases and 1,000 controls, EU FP7 funding, CHIBCHA, Carvajal-Carmona/Tomlinson). We will also examine heterogeneity of the risk estimates by ethnicity/race by leveraging GWA data on NH-Whites (2,142 cases, 1,909 controls, U01 CA122839, Casey), (4,000 cases, 6,000 NH-White controls, UK-CHIBCHA, Tomlinson), Colombians (2,000 cases and 2,000 controls, CHIBCHA), Japanese (1,000 cases and 1,000 controls) and African-Americans (1,500 cases and 1,500 controls, R01CA126895, Le Marchand). We will genotype replicated significant SNPs in our main and combined analysis in several Hispanic populations (note: studies funded by EU or NIH for data collection but not GWAS), including 800 Puerto Ricans, 2,000 Brazilians, 2,000 Argentineans and 3,000 Spanish/Portuguese, to assess generalizability of findings. We will examine the differences in inflammatory gene transcription dynamics in leukocytes (from blood sample collection) by fatigue level (as assessed from study questionnaire data). This study will have a high impact by addressing the key question of racial/ethnic disparities related to genetic susceptibility to CRC, will provide translational guidelines on biological mechanisms during the cancer survivorship period to increase quality of life among cancer survivors, and will enable further growth and investment into research among Hispanics by providing a resource of genetic data and biospecimens, which is lacking.

  Study phs001193

• cfMeDIP-seq for 18 patients with pleural mesothelioma

  The dataset contains cfMeDIP-sequencing data (bam files) for 18 plasma samples from pleural mesothelioma patients. The libraries were prepared according to the published protocol (Shen, S. Y., Burgener, J. M., Bratman, S. V. & De Carvalho, D. D. Preparation of cfMeDIP- seq libraries for methylome profiling of plasma cell-free DNA. Nat. Protoc. 14, 2749–2780 (2019)). Whole genome sequencing (WGS) was performed for pre-made libraries on NovaSeq X Plus with a 150 paired-end strategy. Low-quality reads and adapters were removed with Trim Galore version 0.6.6 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore). The trimmed reads were aligned to hg38 with Bowtie2 version 2.3.4.3. SAMTools version 1.9 was used to convert the SAM alignment files to BAM files, sort and index reads, and remove duplicates.

  Dataset EGAD50000002126

• Gabriella Miller Kids First Pediatric Research Program in Germline and Somatic Variants in Myeloid Malignancies in Children

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource).All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed.This project aims to sequence an unparalleled number of cases of de novo Acute Myeloid Leukemia (AML) and Down Syndrome AML (DS-AML), to establish a database comprised of genomic and transcriptome information which can be interrogated for both somatic and germline variants. Identification of the somatic variants will provide valuable data on the potential genes and pathways that can be targeted for therapeutic purposes. In addition, interrogation of the host’s constitutional genome may yield valuable information about potential germline variants that, in combination with the somatic data, might provide a more informed approach to patient care. For those patients with predisposition mutations, chemotherapy alone might not be adequate for cure, and stem cell transplantation might be required. Also, those who might be at high risk of adverse secondary events (cardiac complications, secondary malignancies, etc.) can be identified early and their therapy can be tailored to minimize anticipated complications. Thus, we propose that the optimum outcome can only be obtained through comprehensive interrogation of the somatic and germline genomes to fully annotate the genomic makeup of the leukemia and its host. Knowing the genomic and transcriptomic makeup of these patients, along with a full complement of clinical characteristics for this cohort, will be critical for making strong correlations which may aid in therapeutic development for future patients. The de novo AML, DS-AML, and Acute Promyelocytic Leukemia (APL) cases were all collected through clinical protocols conducted by the Children’s Oncology Group (COG). In addition to funding from the Gabriella Miller Kids First Pediatric Research Program, the DS-AML cohort was specifically funded by the Lifespan to Understand Down syndrome (INCLUDE) Project.

  Study phs002187

• Are children born after medical assisted reproduction at greater risk of having an increased de novo mutation rate?

  Introduction: De novo mutations (DNMs) play a prominent role in sporadic disorders with reduced fitness such as infertility and intellectual disability. Advanced paternal age is known to increase disease risk in offspring by increasing the number of DNMs in their genome. Less is known about the effect of assisted reproduction techniques (ART) on the number of DNMs in offspring. With the on-going trend of delayed parenthood more children are now born both from older fathers and through ART. Materials and Methods: We investigated 49 trios (mother, father and child) and 2 quartets (mother, father and 2 siblings) divided into children born after spontaneous conception (n=18); born after in vitro fertilisation (IVF) (n=17) and born after intracytoplasmic sperm injection combined with testicular sperm extraction (ICSI-TESE) (n=18). Groups further divided by paternal age, young (<35) or old (>45 years of age at conception). Whole-genome sequencing was performed twice to independently detect and validate all DNMs in children. Results: A clear paternal age effect was observed, with 70 DNMs detected on average in children born to young fathers and 94 DNMs in those born to older fathers (p = 0.001). No significant differences were observed between different methods of conception (p = 1) with paternal age affecting all methods equally. Conclusions: Paternal age, not method of conception, had a major effect on the observed number of DNMs in offspring. Given the role DNMs in disease risk, this negative result is good news for IVF and ICSI-TESE born children, if replicated in larger cohorts.

  Study EGAS00001005569