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• CPTAC: Proteogenomic Studies of Ovarian Tumor Responses to Agents Targeting the DNA Damage Response

  There is a critical unmet need for predictors of chemo-refractory High-grade serous ovarian cancer (HGSOC). Despite over 3 decades of research on platinum responses in cancer, no predictive biomarker has been translated into clinical use. Predictors of refractory disease could spare these patients the unnecessary toxicity of a platinum-based regimen and provide a means to triage these patients to clinical trials to identify effective therapies for refractory disease. This study has approached the development of a predictor in a novel way enabling detection of a multi-analyte panel biomarker capable of detecting a subset of refractory HGSOCs with high specificity and implicating potential treatment vulnerabilities for refractory disease. We reported the first proteogenomic analysis of platinum refractoriness in HGSOC and made the novel dataset available as a resource to the community, including a ProTrack portal: http://ptrc.cptac-data-view.org/. Detailed proteogenomic profiles were generated for this study from a retrospective cohort of 242 treatment-naive HGSOCs with enriched representation of "exceptional non-responders" (i.e., patients with chemo-refractory disease). Whole genome sequence (WGS) and RNA seq FASTQ files are available through dbGaP. Proteomic data are available through the NCI Proteomic Data Commons (PDC): https://pdc.cancer.gov/pdc/.

  Study phs003152

• Genetic Epidemiology of Lung Cancer Consortium GWAS of Familial Lung Cancer

  Familial lung cancer cases were collected by the Genetic Epidemiology of Lung Cancer Consortium (GELCC) recruitment sites: University of Cincinnati, Karmanos Cancer Institute at Wayne State University, Louisiana State University Health Sciences Center-New Orleans, Mayo Clinic, and Medical College of Ohio. Familial cases for this study came from three sources: 1) one case each from families (at least 3 affected lung cancer cases in the family) included in the linkage analysis; 2) one case from linkage-eligible families (at least 3 affected lung cancer cases in the family) but where there were insufficient biospecimens available to make them informative for linkage analysis; and 3) one case from families not eligible for the linkage study with a family history of at least one first or second degree relative affected with lung cancer. Unrelated controls were selected from 1) among the spouses of family members, thus matching on socio-economic status (SES) and ethnicity (typically) of the cases or 2) from case-control studies of lung cancer conducted in the same location in which the linkage families were collected and matched on age, sex, and race. All cases and controls self-reported as European American. Biospecimens used for normal DNA extraction included blood, saliva or mouthwash. Some samples underwent whole genome amplication.

  Study phs000629

• Longitudinal Study of Bone and Endocrine Disease in Children with MPS I, II, and VI: A Multicenter Study of the Lysosomal Disease Network

  Mucopolysaccharidoses (MPS) I, II, and VI are a group of rare, lysosomal storage diseases in which certain enzymes are missing that are normally required for breaking down specific complex carbohydrates. Deficiencies in these enzymes result in the build-up of toxic substances in various tissues and cause damage to the body's organs. In the past, children diagnosed with MPS I, II, or VI frequently died in early to late childhood. Recent advances in treatments including hematopoietic cell transplantation (HCT) and enzyme replacement therapy (ERT) have been helping children with these disorders live into adulthood. The long term-course of the disease is now unknown. Unfortunately, severe skeletal disease persists for most individuals despite current therapies. This is a longitudinal study of 50 children and adults with MPS I, II, and VI. Study participants will be evaluated every year for up to 3 years. The purpose of this study is to document the progression of skeletal disease and identify biomarkers that either predict disease severity or could be used as therapeutic targets. This information is needed to: determine long-term benefits and limitations of current treatments including HCT or ERT direct development of further treatment options improve clinical care for children affected by the disorder

  Study phs001576

• Orofacial Pain: Prospective Evaluation and Risk Assessment (OPPERA)

  The OPPERA project has two sub-studies investigating effects of genetic, physiological, psychological and clinical factors on the risk of developing painful temporomandibular disorder (TMD). OPPERA I baseline case-control study of chronic TMJD (dbGaP study accession phs000762). This sub-study uses a case-control study design to investigate characteristics associated with chronic TMD. The parent OPPERA phenotype file contains an indicator variable (PHASE1CASECONTROL) identifying participants in this sub-study. Data users should use the relevant case-classification variable (CHRNONICTMDCASE) and apply statistical methods appropriate for case-control studies when analyzing TMJD in this sub-study. OPPERA I prospective cohort for first onset of TMJD (dbGaP study accession phs000850). This sub-study uses a prospective cohort study design to investigate characteristics that predict risk of developing first-onset TMD. The parent OPPERA phenotype file contains an indicator variable (PROSPECTIVECOHORT) identifying participants in this sub-study. Data users should use the relevant case-classification variable (INCIDENTCASE) and the relevant time-in-study variable (FOLLOWUPYEARS) when analyzing TMJD in this sub-study. It is recommended that data users apply statistical methods appropriate for cohort studies of a dynamic population (for example, Cox regression models, where INCIDENTCASE is the censoring variable and FOLLOWUPYEARS is time in study).

  Study phs000761

• PIEZO1 Loss of Function Compound Heterozygous Mutation in the Rare Congenital Human Disorder Prune Belly Syndrome

  Prune Belly Syndrome (PBS) is a rare congenital myopathy that is incompletely understood genetically. In this IRB approved study, one white Non-Hispanic 35 year-old male PBS proband was prospectively enrolled and phenotyped. Blood lymphocyte DNA from the proband underwent paired-end Whole Exome Sequencing using the Illumina SureSelect kit and HiSeq2500 sequencer with data pipeline analysis. We aligned the subject's sequence against the GRCh38/hg19 assembly and variant calling was performed using data training sets from the 1000 Genomes Project, Omni 2.5 M SNP microarray, and HapMap phase 3.3. These variants were filtered for rare minor allele frequency ( 0.9, CADD score > 20, GERP > 4, MutationTaster = “DC”, Mutation Assessor = “M” or “NE”, and Vest > 3.00. Rare and novel candidate functional variants were screened in the ClinVar database for prior association with smooth muscle myopathy (SMM). Only variants that met these criteria were included for further analysis. Confirmed variants had inheritance analysis performed on available samples. Our WES analysis identified novel compound heterozygous variants in the PIEZO1 gene. We conducted an extensive functional analysis of the PIEZO1 PBS variants that revealed loss-of-function characteristics. Thus, PIEZO1 mutations may be causal for PBS. Our WES data will be available through dbGaP.

  Study phs003475

• Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA

  Aberrant DNA methylation plays a critical role in tumorigenesis. While DNA methylation has been used for cancer detection and classification, DNA hemi-methylation, a novel epigenetic mark has not been analyzed extensively in cancer epigenomes. Here we report a strand-specific (ss) sequencing method (MeDIP-Seq) for plasma cell free (cf) DNA (sscf-MeDIP-Seq), which can analyze both symmetrically methylated DNA regions (DMRs) as well as hemi-methylated regions (DHMRs). Using the sscf-MeDIP-Seq method, we analyzed plasma cfDNA methylomes of 271 samples from subjects with liver cancer and brain cancer and from individuals without cancer (controls). Among them, 215 samples were chosen as the discovery cohort for the identification of DMRs and DHMRs specific in each subject group and for the training of machine learning models of multi-cancer detection (MCD) using DMRs, DHMRs and DMRs+DHMRs as inputs. These models were then used to predict the 56 samples in the validation cohort. We found that models trained with DMRs+DHMRs as inputs in general outperformed models trained with DMRs or DHMRs alone, with AUROC being 0.971, 0.981, and 0.99 in predicting control, liver and brain cancer samples in the validation cohort, respectively, by the DMR+DHMR-trained models.

  Study phs003462

• IMPRESS: Improved methylation profiling using restriction enzymes and smMIP sequencing, combined with a new biomarker panel, creating a multi-cancer detection assay

  Background Despite the worldwide progress in cancer diagnostics, more sensitive diagnostic biomarkers are needed. The methylome has been extensively investigated in the last decades, but a low-cost, bisulfite-free detection method for multiplex analysis is still lacking. Methods We developed a methylation detection technique called IMPRESS, which combines methylation-sensitive restriction enzymes and single-molecule Molecular Inversion Probes. We used this technique for the development of a multi-cancer detection assay for eight of the most lethal cancer types worldwide. We selected 1791 CpG sites that can distinguish tumor from normal tissue based on DNA methylation. These sites were analysed with IMPRESS in 35 blood, 111 tumor and 114 normal samples. Finally, a classifier model was built. Results We present the successful development of IMPRESS and validated it with ddPCR. The final classifier model discriminating tumor from normal samples was built with 358 CpG target sites and reached a sensitivity of 0.95 and a specificity of 0.91. Moreover, we provide data that highlight IMPRESS’s potential for liquid biopsies. Conclusions We successfully created an innovative DNA methylation detection technique. By combining this method with a new multi-cancer biomarker panel, we developed a sensitive and specific multi-cancer assay, with potential use in liquid biopsies.

  Study EGAS50000000624

• Single-Cell Genomic and Transcriptomic Analysis of the Aging Human Brain

  We studied human brain aging using single-cell whole genome sequencing and single-nucleus RNA sequencing of the pre-frontal cortex from 19 donors ranging in age from 0.4 years to 104 years. All donors were free of neuropathology and none received a clinical neurological diagnosis prior to death. snRNA-seq libraries were prepared in batches that always included old and young donors to mitigate batch effects in the preparations. Neurons for single-cell WGS were collected from the same tissue region as the snRNA-seq for each donor but represent independent cells. Multiplexed error-robust fluorescent in-situ hybridization (MERFISH) data was also collected from pre-frontal cortex samples of a subset of the 19 donors. Transcriptomic results identified infant-specific cell clusters, and common-down regulation of cell-essential genes involved in ribosomes, transport, homeostasis and metabolism during aging, across all cell types. scWGS identified two-age associated mutational signatures, as well as gene-length and expression-level dependent somatic mutation rates in neurons. Raw sequencing data in fastq format for single-nucleus RNA-seq and single-cell DNA-seq, as well as cell and gene count matrix, transcript metadata, and cell metadata for MERFISH will be available in dbGaP.

  Study phs003445

• BHD-associated kidney cancer

  Background Birt-Hogg-Dub? (BHD) syndrome is a hereditary kidney cancer syndrome, which predisposes patients to develop kidney cancer, cutaneous fibrofolliculomas and pulmonary cysts. The responsible gene, FLCN is a tumor suppressor for kidney cancer which plays an important role for energy homeostasis through the regulation of mitochondrial oxidative metabolism. However, how FLCN-deficiency leads to renal tumorigenesis is unclear. Results Whole-exome sequencing analysis of BHD-associated kidney cancer revealed that copy number variations (CNV) of BHD-associated kidney cancer are considerably different from those already reported in sporadic cases. Somatic mutation analysis revealed BHD-associated kidney cancer has quite few common mutations in specific genes; however, chromatin remodeling genes in total were frequently mutated in BHD-associated kidney cancer (17/29 tumors, 59%). Metabolite analysis revealed that glycolysis, pentose phosphate pathway and lipid metabolism were upregulated whereas the rate of beta oxydation and TCA cycle is decreased in BHD-associated kidney cancer compared to normal adjacent kidney. Conclusions BHD-associated kidney cancer displays a unique molecular characteristics which is totally different from that of sporadic kidney cancer, providing the mechanistic insight into tumorigenesis under FLCN deficiency as well as the foundation for the development of novel therapeutics for kidney cancer.

  Study JGAS000115

• Assessing gene expression profiling from FFPE Patient Samples: A Comparison of Two Library Preparation Approaches and Recommendations

  Next-Generation Sequencing (NGS) has transformed cancer research and clinical practice, with Whole Exome Sequencing (WES) driving advances in mutational profiling and personalized oncology. Yet, transcriptomic signatures remain essential for understanding disease mechanisms, including therapy resistance pathways. RNA sequencing (RNA-seq), however, faces unique challenges when dealing with low-input or degraded RNA, as often found in archival formalin-fixed paraffin-embedded (FFPE) tissues. Although previous studies have compared library preparation protocols, rapidly evolving technologies call for updated evaluations. Here, we present a direct comparison of two FFPE-compatible stranded RNA-seq library preparation kits: TaKaRa™ SMARTer® Stranded Total RNA-Seq Kit v2 (Kit A) and Illumina Stranded Total RNA Prep Ligation with Ribo-Zero Plus (Kit B). Both kits generated high-quality RNA-seq data, yet important differences emerged. Notably, Kit A achieved comparable gene expression quantification to Kit B while requiring 20-fold less RNA input, a crucial advantage for limited samples, albeit with increased sequencing depth. We critically discuss these results in relation to RNA availability, technical performance, cost-effectiveness, processing time, and automation potential, offering practical guidance for selecting optimal RNA-seq strategies in clinical and translational research settings

  Study EGAS50000001066