Background:Pathological diagnosis of melanocytic tumors can be difficult and prone to error. More accurate and reliable ancillary investigations than those currently available are required to improve diagnostic accuracy. Goals: (1) to generate a genomic model for distinguishing benign (nevi) from malignant (melanoma) melanocytic skin tumors, developed from a customized gene panel evaluated on a cohort of 250 nevi and melanomas. (2) To evaluate the performance of the genomic model in melanocytic tumors of uncertain diagnosis/behavior. Details: The cohort of 250 melanomas and naevi was split into a discovery set and a validation set. Our genomic model obtained an area under the curve of 95% in the discovery cohort and 96% for the validation cohort. Based on a Youden index threshold, the resulting classifier shows high specificity (>95% in the discovery and validation cohorts), with sensitivities >80% in the discovery and validation cohorts. Evaluation of the genomic model on a cohort of 110 melanocytic tumors identifies key driver mutations in agreement with the likely pathway of origin of the tumors. The probability of melanoma (p=0.02) from the genomic model was significantly associated with pathology-based estimates of malignancy for melanocytic tumors lacking pathway-defining genomic aberrations (conventional tumors). The genomic model identified 8/36 (22%) conventional tumors with unresolved malignancy to have a high probability of melanoma, with 7/8 of these cases showing negative/non-aberrant results with either fluorescent in-situ hybridization, PRAME and/or p16 immunostains. Furthermore, no evidence of malignant behavior based on the genomic model was seen in 4 conventional borderline tumors with more than 1 year follow-up. Conclusion: This genomic model can become a clinically useful ancillary tool that is highly specific for differentiating melanomas from nevi.
Homologous recombination deficiency (HRD)-induced genomic scars are an FDA-approved biomarker for identifying cancers likely to respond to PARP inhibitors. However, detecting HRD scars from blood biopsies has been challenging due to the low tumor content in blood samples. To address this limitation, we developed DirectHRD, a genomic scar-based HRD classifier leveraging whole-genome sequencing (WGS) data for non-invasive blood biopsy testing. DirectHRD was applied to 90 cell-free DNA (cfDNA) samples across four cancer types: breast, ovarian, prostate, and pancreatic. The method achieved an AUC of 0.87 and demonstrated the ability to detect HRD at tumor fractions as low as 1%, offering a tenfold increase in sensitivity compared to state-of-the-art methods.
This experiment is to validate putative somatic substitutions and indels identified in an exome screen of ~50 osteosarcoma tumour/normal pairs. It is the first stage in our ICGC commitment to study osteosarcoma. The validation process is an important component of our analysis to clarify the data prior to looking for evidence of new cancer genes, or subverted pathways important in the development of cancer. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/
The Clinical Trial of COVID-19 Convalescent Plasma in Outpatients (C3PO) is a multicenter, randomized, single blind, two-arm, placebo controlled Phase III trial with blinded outcome assessments to establish the safety and efficacy of single dose of convalescent plasma for preventing the progression from mild to severe COVID-19 illness.
Acute Myeloid Leukemia (AML) remains a clinical challenge since most patients diagnosed with AML will die from the disease. Some patients harbor treatment-refractory disease and many others relapse with disease that in many cases is resistant to treatments. Our study was designed to understand the molecular basis of disease progression in AML through assessing genomics signatures in patient specimens collected through an international collaboration which assembled samples from 138 AML patients which experienced disease relapse and normal hematopoietic cells (n=15). It is hoped that this resource will help researchers understand mechanisms of disease relapse in AML and contribute to the general pool of data available for analyses for this disease and general research use.
Oncogenic mutations confer aberrant replicative capacity to cells with little or no replicative capacity, generating cancer stem cells that perpetuate the tumor through extensive self-replication and differentiation blockade. However, whether oncogenes disrupt the cellular identity ofcancer stem cell by altering the developmental potential is unknown. Fate conversion has been demonstrated by ectopic expression of master transcriptional regulators, such as PU.1 and C/EBP alpha that confers myeloid cell fate to other cell types, and PRDM16 that confers brown adipose fate to white adipocytes or myoblasts. Here we show that a transcriptional regulator overexpressed in human myeloid malignancies, PRDM16s, causes oncogenic fate conversion, by transforming cells fated to form platelets and erythrocytes into myeloid leukemia-initiating cells (LICs). Prdm16s expression in hematopoietic progenitor cells caused a myelodysplastic syndrome (MDS)-like disease that progressed to acute myelogenous leukemia (AML). The myeloid diseases caused by Prdm16s exhibited expansion of megakaryocyte-erythroid progenitors (MEPs) but not granulocyte-macrophage progenitors. MEPs from Prdm16s-induced leukemia possessed LIC potential, and expression of Prdm16s in normal MEPs was sufficient to convert them to myeloid LICs and blocked megakaryocytic/erythroid potential. Prdm16s induced the expression of myeloid master regulators, including PU.1 and C/EBP alpha, by interacting with their super enhancers. Ablation of myeloid master regulators attenuated the myeloid potential and reinstalled the megakaryocytic/erythroid potential of leukemic-MEPs in mouse models and in human AML with PRDM16 rearrangement. Our study demonstrates that oncogenic Prdm16 expression converts the fate of MEPs to a malignant myeloid fate by activating myeloid master transcription factors.
We performed whole genome sequencing to detect possible off-target mutations induced by prime editing. Liver organoids, derived from a healthy control, were transfected with either control (GFP) plasmids or prime editing plasmids (GFP+PE2+pegRNA+nickRNA) to induce a 6-bp deletion in CTNNB1. One control and two prime-edited organoid lines were clonally expanded from single cells. High-throughput sequencing was performed on the complete genomic DNA isolated from these clonal lines, as well as the starting culture (bulk). After correction for germline mutations in the starting culture, new mutations in the control and prime-edited lines were compared. The same approach was followed in small intestinal organoids, derived from a patient with disease-causing 3-bp deletion in DGAT1. In these small intestinal organoids, prime editing was used to insert the 3 missing nucleotides. Two corrected clones were compared to one control clone.
We sequenced the coding and untranslated regions of 72 prostate cancer driver genes in 712 plasma cell free DNA samples from 428 men with metastatic prostate cancer, in an effort to understand the role of untranslated region mutations in late stage prostate cancer.
Study Overview The Environmental Determinants of Diabetes in the Young (TEDDY) Study is a longitudinal study that investigates genetic and genetic-environmental interactions, including gestational events, childhood infections, dietary exposures, and other environmental factors after birth, in relation to the development of islet autoimmunity and type 1 diabetes (T1D). A consortium of six clinical centers assembled to participate in the development and implementation of the study to identify environmental triggers for the development of islet autoimmunity and T1D in genetically susceptible individuals. Beginning in 2004, the TEDDY study screened over 400,000 newborns for high-risk HLA-DR, DQ genotypes from both the general population and families already affected by T1D. The TEDDY study enrolled around 8,676 participants across six clinical centers worldwide (Finland, Germany, Sweden and three in the United States) in the 15-year prospective follow-up. Participants are followed every three months for islet autoantibody (IA) measurements with blood sampling until four years of age and then at least every six months until the age of 15. After the age of four, autoantibody positive participants continue to be followed at three month intervals and autoantibody negative participants are followed at six-month intervals. In addition to the analysis of autoantibodies, additional data and sample collection are performed at each visit. Parents collect monthly stool samples in early childhood. The parents also fill out questionnaires at regular intervals in connection with study visits and record information about diet and health status in the child's TEDDY Book between visits. Continued long-term follow-up of the currently active TEDDY participants will provide important scientific information on early childhood diet, reported and measured infections, vaccinations, and psychosocial stressors that may contribute to the development of type 1 diabetes and islet autoimmunity. Additional information on the TEDDY study is available in the following articles: Rewers et al., 2008, PMID: 19120261 and Hagopian et al., 2006, PMID: 17130573. Details of the TEDDY protocol can be found in Hagopian et al., 2011, PMID: 21564455. TEDDY data currently available in dbGaP include: gene expression, SNPs, exome, microbiome (gut, nasal, and plasma), RNA sequencing, and whole genome sequencing. For more information on TEDDY Study version history please refer to TEDDY Study dbGaP README File. ImmunoChip SNP DNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for SNP genotyping. Genotyping was performed by the Center for Public Health Genomics at the University of Virginia using the Illumina ImmunoChip SNP array, which contains around 196,000 SNPs from 186 regions associated with 12 autoimmune diseases (Hadley et al., 2015, PMID: 26010309). Data cleaning and validation included the removal of subjects with a low call rate (< 5% SNPs missing) and differences in reported sex and prior genotyping at the TEDDY HLA laboratory. Additionally, SNPs with a low call rate or Hardy-Weinberg equilibrium P value < 10-6, except for chromosome 6 due to HLA eligibility requirements, were removed from the final dataset (Törn et al., 2015, PMID: 25422107).TEDDY-T1DExome ArrayDNA from whole blood samples on study participants and their family members (mothers, fathers, and siblings) was obtained and used for genotyping. Genotyping was performed by the University of Virginia using the Illumina TEDDY-T1DExome array. The TEDDY-T1DExome array is a custom chip that contains 550,601 markers from the Infinium CoreExome-24 v1.1 BeadChip and an additional 90,214 tagSNPs specifically selected by the TEDDY investigators based on their associations with nutrients, vitamins, type 2 diabetes, autoimmune diseases, body-mass index, or other exposures and phenotypes measured by TEDDY study.The Illumina GenTrain2 algorithm was used for genotype calling. Sample quality control metrics included sample call rate, heterozygosity rate and concordance of gender between the information reported and genotyped. Gene Expression The TEDDY study collected peripheral blood for the extraction of total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA (200 ng) was further used for cRNA amplification and labeling with biotin using Target Amp cDNA synthesis kit (Epicenter catalog no. TAB1R6924). Labeled cRNA was hybridized to the Illumina HumanHT-12 Expression BeadChips based on the manufacturer's instructions. The HumanHT-12 Expression BeadChip provides coverage for more than 47,000 transcripts and known splice variants across the human transcriptome. Microbiome The TEDDY microbiome study aimed to characterize the longitudinal development of the microbiome, including bacteria, viruses and other microorganisms in the gut, plasma, and nasal cavity of prediabetic and diabetic subjects compared to autoantibody negative non-diabetic subjects. Stool samples used were collected monthly from 3 to 48 months, after which stool samples were collected every 3 months. Nasal swab samples were collected every 3 months starting at 9 months of age until 48 months, after which nasal swabs were collected every 6 months. Plasma samples were collected every 3 months starting at 3 months of age until 48 months, after which plasma samples were collected every 6 months. If the subject was autoantibody positive at 48 months then they remained on the 3 month collection interval for nasal swab and plasma samples. Samples underwent 16s rRNA gene sequencing, DNA and viral RNA metagenomics shotgun sequencing, and sequencing of the internal transcribed spacer (ITS) regions. Additional information on the TEDDY microbiome data is available in the following articles: Vatanen et al., 2018, PMID: 30356183, Stewart et al., 2018, PMID: 30356187, and Vehik et al., 2020, PMID: 31792456. RNA Sequencing The TEDDY study aimed to characterize the transcriptome in subjects with islet autoimmunity and type 1 diabetes compared to matched control subjects. Peripheral blood was collected to extract total RNA from enrolled children starting at 3 months of age, and then at 3 month intervals up to 48 months and then biannually. Total RNA was extracted using a high throughput (96-well format) extraction protocol using magnetic (MagMax) beads technology at the TEDDY RNA Laboratory, Jinfiniti Biosciences in Augusta, GA. Purified RNA was then sent to the Broad Institute for the generation of the TEDDY RNA sequencing (RNA-Seq) data. The RNA samples were prepped using Superscript III reverse transcriptase and Illumina's TruSeq Stranded mRNA Sample Prep Kit. The TruSeq libraries were run on the Illumina HiSeq2500 platform. Whole Genome Sequencing The TEDDY study aimed to conduct deep whole genome sequencing and examine the genomic variations in subjects with islet autoimmunity and type 1 diabetes compared to matched autoantibody negative and non-diabetic children. DNA from whole blood was obtained from TEDDY children for whole genome sequencing. The WGS data were generated on the Illumina HiSeq X Ten system.
We revealed a large population of long cell-free DNA molecules (up to 23,635 bp in length) in maternal plasma and developed an approach which leveraged the abundance of CpG sites on long molecules to deduce the tissue of origin of individual plasma DNA molecules based on single-molecule methylation analysis. We illustrated how such an approach may be utilized to achieve noninvasive prenatal testing of monogenic diseases. We also revealed a reduction in amounts of such long cell-free DNA molecules and a different end motif profile in maternal plasma DNA from pregnancies with preeclampsia.
