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• Autism Post-Mortem Brain RNA-Sequencing: SRRM4 Splicing Study

  Purpose: The goal of this study was to assess the status of splicing changes in microexons in the cortex of individuals with autism. Methods: We performed RiboZero Gold (rRNA depleted) 50bp PE RNA-seq in a larger set of case and control samples to define 12 autism and 12 control samples showing the greatest global differential gene expression change. These samples, which show differential expression of the splicing regulator SRRM4, were used to evaluate global splicing changes. Results: Within these samples, 126 of 504 (30%) detected alternative microexons display, a mean ΔPSI > 10 between ASD and control subjects of which 113 (90%) also display neural-differential regulation. By contrast, only 825 of 15,405 (5.4%) longer (i.e. > 27 nt) exons show such misregulation, of which 285 (35%) correspond to neural-regulated exons. Notably, we also observe significantly higher correlations between microexon inclusion and nSR100 mRNA expression levels across the stratified ASD samples and controls, for those microexons regulated by nSR100 relative to those microexons that are not regulated by this factor (p=1.4x10-7, Wilcoxon Sum Rank test). Conclusions: These data suggest microexon regulation is a potentially important mechanism underlying ASD and likely other neurodevelopmental disorders.

  Study phs000872

• Molecular classification improves risk assessment in adult B-lineage ALL: Patients on the international UKALLXII-ECOG2993 trial.

  Acute lymphoblastic leukemia (ALL) in adults is a rare disease with outcomes that remain significantly inferior to those of children with ALL. While genomic classification of pediatric B-lineage ALL (B-ALL) has led to improved risk assignment and therapeutic paradigms, similar advances in adults have been lacking. The international UKALLXII/E2993 (NCT00002514) trial accrued over 2000 adult (17-64 years old) patients over 13 years, including 1229 BCR/ABL negative B-ALLs. While 93% of B-ALL achieved a remission, 41% relapsed at a median time of 13 months (Range) and overall survival (OS) at 5 years was 42% (CI). Older age and higher white blood cell (WBC) count at presentation negatively affected OS. Patients with a sibling donor assigned to allogeneic transplantation had superior OS compared to patients without donor. Randomization of patients without a donor showed an advantage of chemotherapy over autologous transplantation in first remission. Transcriptome sequencing of 94% of E2993 patients enabled genomic subtyping. We found that one-third of patients belonged to favorable genotypes (DUX4-rearranged, ETV6-RUNX1, TCF3-PBX1, PAX5 P80R, high hyperdiploidy). Of 63.4% of patients classified as high-risk based age and WBC count at diagnosis, almost 40% harbored subtype-defining genetic associations associated with favorable- or intermediate outcomes. These patients did significantly better than expected from their protocol-defined risk assignment. Our data in a large adult B-ALL cohort treated on a single international trial show the important prognostic value of genomic analysis and the potential benefit for many of the novel genotypes.

  Study EGAS00001004638

• Identification and Molecular Characterization of Somatic Mutations in Malformations of Cortical Development

  Genetic mutations causing disease may be inherited, newly acquired in parental gametes and present in the zygote or acquired as somatic events at some point in development after fertilization. The burden and localization of an acquired mutation depend on when the mutation arises. As is the case for inherited genetic variation, there is accumulating evidence that somatic mutations can lead to severe tissue-specific disease. Malformations of cortical development (MCD) represent a group of disorders characterized by a range of morphological and structural abnormalities of the cerebral cortex reflecting errors in embryonic cortical development. MCD are associated with intellectual disability, as well as refractory epilepsy, and may require the surgical removal of the affected tissue. Inherited gene mutations involved in neuronal development explain only a fraction of MCD cases. In this project we sought to evaluate the hypothesis that somatic mutations disrupt embryonic cortical development and are responsible for a substantial fraction of MCD. Using high coverage next generation sequencing of protein-coding regions in DNA extracted from abnormal brain tissue and unaffected tissue (leukocytes) from patients with three forms of MCD, we sought to identify somatic mutations within each patient with MCD. Exome sequence data from study participants are provided to facilitate research into the genetic underpinnings of MCD.

  Study phs002128

• bulk TCR-seq data IMCISION

  We performed bulk TCR sequencing (Adaptive Biotechnologies, Seattle, WA) on peripheral blood monocytic cells (PBMCs) from 9 HNSCC patients enrolled in the IMCISION trial (Vos et al. 2021) that responded to anti-PD-1 and anti-CTLA4 combination immunotherapy. DNA was extracted from PBMCs that were isolated from pre-treatment and on-treatment blood.

  Study EGAS00001007367

• Germline MBD4 Mutations and Predisposition to Uveal Melanoma

  Uveal melanoma (UM) arises from malignant transformation of melanocytes from the uveal tract. This rare tumor has a poor outcome with frequent liver metastases and primary resistance to treatment1. The only strong predisposing condition for UM is the BAP1 tumor predisposition syndrome due to germline BAP1 deleterious mutations. UMs are generally characterized by a very low tumor mutation burden (TMB). However, some UMs display a high level of CpG to TpG mutations associated with MBD4 inactivation. Here, we explored the incidence of germline MBD4 variants in a consecutive series of 1, 099 primary UMs, and identified 8 deleterious MBD4 mutations, an aprox 10-fold increased incidence compared with the general population. These mutations were associated with a high TMB in tested UMs. We thus demonstrated that MBD4 is the second major predisposing gene for UM.

  Study EGAS00001003941

• Effects of busulfan, fludarabine and clofarabine treatment on human small intestinal organoids generated from healthy donors

  The intestine is vulnerable to chemotherapy-induced toxicity due to its high epithelial proliferative rate, making gut toxicity an off-target effect in several cancer treatments, including conditioning regimens for allogeneic hematopoietic cell transplantation (HSCT). In HSCT, intestinal damage is an important factor in the development of Graft-versus-Host Disease (GVHD), an immune complication in which donor immune cells attack the recipient's tissues. Here, we developed a novel human intestinal organoid-based 3D model system to study the effects of chemotherapy-induced intestinal epithelial damage at the RNA level. We show that chemotherapy conditioning specifically reprograms the intestinal epithelial transcriptome after treatment with either busulfan (3.5μM), fludarabine (15μM) or clofarabine (0.5μM) for 24h. This knowledge can potentially enable us to understand which changes undergo in healthy tissues upon conditioning and how those are related with immune activation typical in GVHD.

  Study EGAS00001007550

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073

• Summary Statistics GWAS SSNS

  Column 1 rsid: SNP identifier;Column 2 chromosome: name of chromosome on which the SNP is located;Column 3: position: base pair position on the chromosome;Column 4 minor_test_allele: the base that constitutes the minor allele;Column 5 major_allele: the base that constitutes the major allele;Column 6 maf: the frequency of the minor allele, indicated as a fraction of 1;Column 7 allele_freq_cases: the minor allele frequency in cases;Column 8 allele_freq_controls: the minor allele frequency in controls;Column 9 regression_pvalue: the p-value for the difference in allele frequency between cases and controls;Column 10 odds_ratio: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00010002316

• Summary Statistics GWAS SSNS

  Column 1 “rsid”: SNP identifier Column 2 “chromosome”: name of chromosome on which the SNP is located Column 3: “position”: base pair position on the chromosome Column 4 “minor_test_allele”: the base that constitutes the minor allele Column 5 “major_allele”: the base that constitutes the major allele Column 6 “maf”: the frequency of the minor allele, indicated as a fraction of 1 Column 7 “allele_freq_cases”: the minor allele frequency in cases Column 8 “allele_freq_controls”: the minor allele frequency in controls Column 9 “regression_pvalue”: the p-value for the difference in allele frequency between cases and controls Column 10 “odds_ratio”: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00001008782

• Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is the leading cause of death from gynecological cancers worldwide. No effective screening methods exist, and tumors are commonly detected at advanced stages where treatment is much less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we detected ovarian cancer with high specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach distinguished benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Study EGAS50000000484