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• RNA-seq of Glioblastoma stem cells

  Chromatin accessibility discriminates stem from mature cell populations, enabling the identification of primitive stem-like cells in primary tumors, such as Glioblastoma (GBM) where self-renewing cells driving cancer progression and recurrence are prime targets for therapeutic intervention. We show, using single-cell chromatin accessibility, that primary GBMs harbor a heterogeneous self-renewing population whose diversity is captured in patient-derived glioblastoma stem cells (GSCs). In depth characterization of chromatin accessibility in GSCs identifies three GSC states: Reactive, Constructive, and Invasive, each governed by uniquely essential transcription factors and present within GBMs in varying proportions. Orthotopic xenografts reveal that GSC states associate with survival, and identify an invasive GSC signature predictive of low patient survival. Our chromatin-driven characterization of GSC states improves prognostic precision and identifies dependencies to guide combination therapies.

  Study EGAS00001003070

• Transcriptome sequencing across a prostate cancer cohort identifies PCAT-1, an unannotated lincRNA implicated in disease progression

  Noncoding RNAs (ncRNAs) are emerging as key molecules in human cancer, with the potential to serve as novel markers of disease and to reveal uncharacterized aspects of tumor biology. Here we discover 121 unannotated prostate cancer-associated ncRNA transcripts (PCATs) by ab initio assembly of high-throughput sequencing of polyA+ RNA (RNA-Seq) from a cohort of 102 prostate tissues and cells lines. We characterized one ncRNA, PCAT-1, as a prostate-specific regulator of cell proliferation and show that it is a target of the polycomb repressive complex 2 (PRC2). We further found that patterns of PCAT-1 and PRC2 expression stratified patient tissues into molecular subtypes distinguished by expression signatures of PCAT-1-repressed target genes. Taken together, our findings suggest that PCAT-1 is a transcriptional repressor implicated in a subset of prostate cancer patients. These findings establish the utility of RNA-Seq to identify disease-associated ncRNAs that may improve the stratification of cancer subtypes.

  Study phs000443

• Extracellular vesicles from TGF-β-activated cancer-associated fibroblasts remodel the tumor microenvironment through EV surface-associated proteins.

  In this study, we explored the function of extracellular vesicles (EVs) derived from non-activated cancer-associated fibroblasts (CAFs) and TGF-β-activated CAFs. We tested these two types of EVs on other cell types in the tumor environment, including cancer cells, CD8+ T cells, and CAFs. We further explored the protein cargo in EVs altered by TGF-β treatment using quantitative proteomics, and selected several highly upregulated proteins for further analysis. We found that the majority of these proteins were presented on the EV surface, and they regulated the target cells in an EV-cell contact dependent manner.

  Study EGAS50000000922

• AC-ICAM: An Atlas and Compass of Immune-CAncer-Microbiome Interactions in Colon Cancer

  Fresh frozen tumor samples and matched normal colon specimens from chemotherapy naïve, consecutive patients with a histological diagnosis of colon adenocarcinoma at Leiden University Medical Center (LUMC) were subjected to multi-omics profiling at Sidra Integrated Genomics Services, part of Sidra Medicine, Doha, Qatar. This resulted in a high-quality dataset of samples collected between 2001 and 2015. Multi-step QC was performed, including assessment of the quality of the nucleic acid extraction, sequencing, and genetic concordance between DNA/RNA sequences from the same patient. After QC, this resulted in RNA sequencing on 348 tumor samples, whole exome sequencing (WES) on 281 tumor-normal sample pairs (n=562 samples), TCR sequencing of the TCR β locus (TRB) for 114 tumor and 10 matched normal samples, and 16S rDNA sequencing on 246 tumor-normal sample pairs (n=492 samples) and 42 tumor only samples, and 167 WGS non human-aligned reads of the tumor samples. Extensive clinicopathological and survival data of the cohort are available. The median follow-up time for this cohort is 4.6 years, and the distribution of gender and pathological stage are within expected ranges for this patient population with a mean age of 68. We refer to this resource as the Sidra-LUMC (SILU) colon adenocarcinoma (COAD) Atlas and Compass of Immune-Colon cancer-Microbiome interactions (AC-ICAM)."Reprinted from Nature Medicine,Roelands, J., Kuppen, P.J.K., Ahmed, E.I. et al. An integrated tumor, immune and microbiome atlas of colon cancer. Nat Med (2023). https://doi.org/10.1038/s41591-023-02324-5, with permission from Nature."

  Study phs002978

• cfDNA dataset from the urine supernatant of ovarian cancer patients and healthy controls

  Background Ovarian cancer is the deadliest gynecological malignancy worldwide, due to frequent diagnosis at advanced stage. Simple and non-invasive methods for earlier and accurate detection are urgently needed. Here, the presence of tumor-derived DNA in home-collected urine, cervicovaginal self-samples and clinician-taken cervical scrapes of ovarian cancer patients was explored by DNA methylation and copy number analysis. Methods A total of 428 samples (urine, cervicovaginal self-samples, and clinician-taken cervical scrapes) of 110 healthy controls and 54 patients with benign (n=25) or malignant (n=29) ovarian masses were analyzed. Different urine fractions were examined (full void urine, urine supernatant, and urine sediment). All samples were tested for 12 methylation markers by quantitative methylation-specific PCR. Shallow whole-genome sequencing was performed to detect copy number aberrations and verify the presence of tumor-derived DNA. Results Full void urine was most discriminatory between healthy controls and ovarian cancer patients (C2CD4D, p=0.008; CDO1, p=0.022; MAL, p=0.008), followed by cervical scrapes (C2CD4D, p=0.001; CDO1, p=0.004). A significant difference between benign and malignant ovarian masses was only observed for GHSR in the urine sediment (p=0.024). Methylation levels in cervicovaginal self-samples did not discriminate between healthy controls, benign and malignant ovarian masses. Copy number changes were identified in 17% of urine supernatant samples and smaller fragment sizes were seen in urine supernatant samples with a high tumor fraction. Conclusions This study demonstrates the presence of ovarian cancer-derived DNA in home-collected urine. Additional studies are warranted to further explore the clinical applicability of this approach.

  Study EGAS00001007238

• Temptation Resistance Failures: Transdiagnostic Features and Influences

  Multiple forms of psychopathology involve problems with resisting temptations and urges. This study utilizes experience sampling (ES) methodology to assess temptation resistance across different classes of temptations and urges including both common everyday temptations and more disorder-specific temptation classes. The study tests the hypothesis that the broad ability to successfully resist temptations and urges across temptation classes is a common features of the externalizing superspectrum (factor) of psychopathology, particularly the disinhibition spectra as defined by the Hierarchical Taxonomy of Psychopathology (HiTOP). Additional associations are expected to arise between reduced temptation resistance success for specific temptation classes and narrower symptom domains associated with the externalizing and internalizing spectra (e.g., binge eating, and nonsuicidal self-harm among internalizing symptoms). The study further tests genetic and environmental influences on temptation strength and resistance ability with a focus on polygenic scores, adverse childhood experiences and childhood neighborhood deprivation variables that have previously been related to externalizing. To address these issues, we will study up to 1200 subjects (minimum 1000) selected with enrichment for psychopathology. Subjects will be recruited from a combination of ResearchMatch, and targeted contact with Reddit groups, and targeted social media/online advertisements, with targeted recruitment of at least 150 subjects who indicate problems with SUD, alcohol use disorder (AUD) or nicotine dependence, 70 who indicate problems with gambling or other impulse control problems, 70 subjects with criminal/legal problems, and 70 subjects based on binge eating episodes 70 with self-injurious behavior, and 70 with obsessive-compulsive disorder. Subjects will complete the (Externalizing Spectrum Inventory-BF and HiTOP-SR) to measure externalizing and internalizing spectra. Diagnoses in key categories will be confirmed with structured diagnostic interviews. Subjects also complete information on childhood adversity and geocoding is used to assess environment during development. The two-week ES regimen collects data on the strongest types of temptations and urges experienced by the subject, their subjective strength, the goal of the urge (pleasure/relief from negative feelings), the level of conflict with other goals, whether the person attempted to resist the temptation, the resistance strategy, and resistance success, to allow assessment of the extent to which differences in each of these facets (and calculated temptation resistance efficacy) are related to narrow or broad dimensions of psychopathology. Whole genome sequencing with .5x coverage and imputation will be performed to allow generation of polygenic scores for externalizing and addiction in order to test the hypothesis that externalizing polygenic scores are related to poor temptation resistance efficacy across temptation classes.

  Study phs004064

• Genomic Sequencing of Ewing Sarcoma

  Pediatric Ewing sarcoma is a pediatric cancer that primarily arises from the bone. It is characterized by chimeric fusions of the EWS gene and an ETS family transcription factor. In this study, we performed massively parallel sequencing of a larger collection of Ewing sarcoma tumors to define the genomic landscape of this disease. We found that these tumors are among of the most genetically normal cancers currently characterized. There was also a marked absence of recurrent mutations in immediately targetable signaling transduction pathway genes. In this study we answer outstanding questions about ETS transcription factor expression, effects of treatment on mutational burden in Ewing sarcoma tumors, and describe patterns of tumor evolution. We also found that loss-of-function mutations in STAG2 were present in approximately 15% of Ewing sarcoma tumors and loss of STAG2 expression was associated with disease metastasis in this patient cohort.

  Study phs000804

• Comprehensive characterization of pre- and post-treatment samples of breast cancer reveal potential mechanisms of chemotherapy resistance

  When locally advanced breast cancer is treated with neoadjuvant chemotherapy, the recurrence risk is significantly higher if no complete pathologic response is achieved. Identification of the underlying resistance mechanisms is essential to select treatments with maximal efficacy and minimal toxicity. Here we employed gene expression profiles derived from 317 HER2-negative treatment-naïve breast cancer biopsies of patients who underwent neoadjuvant chemotherapy, deep whole exome and RNA-sequencing profiles of 22 matched pre- and post-treatment tumors, and treatment outcome data to identify biomarkers of response and resistance mechanisms. Molecular profiling of treatment-naïve breast cancer samples revealed that expression levels of proliferation, immune response and extracellular matrix (ECM) organization combined predict response to chemotherapy. Triple negative patients with high proliferation, high immune response and low ECM expression had a significantly better treatment response and survival benefit (HR 0.29, 95% CI 0.10-0.85; p=0.02), while in ER+ patients the opposite was seen (HR 4.73, 95% CI 1.51-14.8; 0=0.008). The characterization of paired pre-and post-treatment samples revealed that aberrations of known cancer genes were either only present in the pre-treatment sample (CDKN1B) or in the post-treatment sample(TP53, APC, CTNNB1). Proliferation-associated genes were frequently down-regulated in post-treatment ER+ tumors, but not in triple negative tumors. Genes involved in ECM were upregulated in the majority of post-chemotherapy samples. Genomic and transcriptomic differences between pre- and post-chemotherapy samples are common and may reveal potential mechanisms of therapy resistance. Our results show a wide range of distinct, but related mechanisms, with a prominent role for proliferation- and ECM-related genes.

  Study EGAS00001005876

• Add Health: Longitudinal Study of a Nationally Representative Sample of Adolescents in Grades 7-12 in the United States during the 1994-95 School Year, Followed into Adulthood with Five Interviews/Surveys in 1995, 1996, 2001-02, 2008, and 2016-18

  The National Longitudinal Study of Adolescent to Adult Health [Add Health] is an ongoing longitudinal study of a nationally representative U.S. cohort of more than 20,000 adolescents in grades 7-12 (aged 12-19 years) in 1994 followed into adulthood with five interviews/surveys in 1995, 1996, 2001-02, 2008, and 2016-18. Add Health was designed to understand how social environments and behaviors in adolescence are linked to health and achievement outcomes in young adulthood. Add Health contains unprecedented environmental, behavioral, psychosocial, biological, and genetic data from early adolescence and into adulthood on a large, nationally representative cohort with unprecedented racial, ethnic, socioeconomic, and geographic diversity. Add Health has a large, multidisciplinary user base of over 50,000 researchers around the world who have published over 3,400 research articles. Add Health is housed at the Carolina Population Center of the University of North Carolina at Chapel Hill. Add Health datasets are distributed according to a tiered data disclosure plan designed to protect the data from the risk of direct and indirect disclosure of respondent identity. Add Health's large sample size, population diversity and rich longitudinal database of psychosocial, physical, and contextual data will permit investigation of an exceptionally broad range of phenotypes with known genetic variation. Prospective longitudinal measures are available to document change over time in each of these phenotypes, as well as change in the social environment and life experiences, making the Add Health sample ideal for understanding genetic linkages with health and behavior across the life course. The original design of Add Health included important features for understanding biological processes in health and developmental trajectories across the life course of young people, including an embedded genetic sample with more than 3,000 pairs of adolescents with varying biological resemblance (e.g., twins, full sibs, half sibs, and adolescents who grew up in the same household but have no biological relationship), testing of saliva and urine for sexually transmitted infections and HIV, and biomarkers of cardiovascular health, metabolic processes, immune function, renal function, and inflammation. Add Health therefore has critical objective indicators of health status and disease markers in young adulthood, well before chronic illness or its complications emerge in later adulthood. Because DNA has been collected on the full sample at Wave IV, it is possible to link genetic profiles with social, behavioral, and biological measures over time from adolescence into adulthood. Add Health sampled the multiple environments in which young people live their lives, including the family, peers, school, neighborhood, community, and relationship dyads, and provides independent and direct measurement of these environments over time. Add Health contains extensive longitudinal information on health-related behavior, including life histories of physical activity, involvement in risk behavior, substance use, sexual behavior, civic engagement, education, and multiple indicators of health status based on self-report (e.g., general health, chronic illness), direct measurement (e.g., overweight status and obesity), and biomarkers. No other data resource with this expanse of genotype and phenotype data on a large nationally representative longitudinal sample with race, ethnic, socioeconomic, and geographic diversity exists. A complete reference guide on study design and accomplishments can be found on the Add Health website: https://cdr.lib.unc.edu/concern/articles/6t053j27s.

  Study phs001367

• Bayesian-Based Noninvasive Prenatal Diagnosis of Single-Gene Disorders

  In the last decade, non-invasive prenatal diagnosis (NIPD) has emerged as an effective procedure for early detection of inherited diseases during pregnancy. This technique is based on using cell-free DNA (cfDNA) and fetal cfDNA (cffDNA) in maternal blood, and hence, has minimal risk for the mother and fetus compared with invasive techniques. NIPD is used today for identifying chromosomal abnormalities (in some instances) and for single-gene disorders (SGDs) of paternal origin. However, for SGDs of maternal origin, sensitivity poses a challenge that limits the testing to one genetic disorder at a time. Here we present a Bayesian method for the NIPD of monogenic diseases that is independent of the mode of inheritance and parental origin. Furthermore, we show that accounting for differences in the fragment length distribution of fetal- and maternal-derived cfDNA results in increased accuracy. Our model is the first to predict inherited insertions-deletions (indels). The method described can serve as a general framework for the NIPD of SGDs; this will facilitate easy integration of further improvements. One such improvement that is presented in the current study is a machine learning model that corrects errors based on patterns found in previously processed data. Overall, we show that next generation sequencing (NGS) can be used for the NIPD of a wide range of monogenic diseases, simultaneously. We believe that our study will lead to the achievement of a comprehensive NIPD for monogenic diseases. (Reprinted from Bayesian-based noninvasive prenatal diagnosis of single-gene disorders, with permission from Genome Research)

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