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• Epigenomics of Neurocognitive Function in Breast Cancer

  This study harnessed the data and biospecimens from the Exercise Program in Cancer and Cognition (EPICC) study (parent study) that collected data on cognitive function, demographics, other symptoms and biospecimens at two time points (T1: enrollment, T2: six months later) within the context of a six-month randomized controlled trial of a moderate intensity aerobic exercise intervention. This study collected genome wide DNA methylation data from T1 and T2 and conducted epigenome-wide association-based analyses to find genes and biological pathways explaining variability in cognitive function and explaining how exercise mitigates cognitive decline. Our initial findings identified cg10331779 near CTNND2 (p-value=9.65×10-9) associated with processing speed and cg25906741 in MLIP (p-value=2.01×10-8) associated with subjectively measured cognitive function. Additionally, differentially methylated regions were identified near SLC6A11, PRKG1/CSTF2T, and FAM3B for processing speed and near PI4KB and SGCE/PEG10 for mental flexibility.

  Study phs003959

• Estimating the Efficacy of Pharmacogenomics Over a Lifetime

  The goal was to evaluate the potential impact of pharmacogenomic testing on drug prescribing over a lifetime. To address this goal, 300 random patients enrolled in Marshfield Clinic's PMRP biobank with life-long medical records were whole genome sequenced and evaluated for known clinically actionable pharmacogenomic variants as defined by CPIC and FDA. This genomic data was evaluated in the context of extensive longitudinal prescription record data from patient EHR. Results show nearly all (93%) carry a clinically actionable pharmacogenomic variant and 80% with a variant were prescribed approximately three medications on average that may have been impacted because of their variants, the optimal age for pharmacogenomic testing was prior to age 50, but most patients well past their 50s can still benefit from pharmacogenomic testing. Results available include genotype and drug prescribing data.

  Study phs003454

• Disease-Linked Regulatory DNA Variants and Homeostatic Transcription Factors in Epidermis

  The role of non-coding variants in polygenic skin disease and their connection to homeostatic transcription factors (TFs) in epidermis was investigated. Homeostatic TFs were identified by perturb-seq in differentiating keratinocytes, using either 10x or split-pool approaches to sequencing, with follow-up validation by siRNA and RNA-seq. TF binding events were profiled by population sampling Cleavage Under Targets & Release Using Nuclease (CUT&RUN), in which a random population of neonatal foreskin keratinocytes were assayed by CUT&RUN for homeostatic TFs under progenitor growth and differentiation conditions. Heterozygous alleles were identified from the TF binding data and examined for allele specific binding events (ASBs). ASBs were then compared with non-coding variants linked to skin disease. Variants with potentially pathogenic effects were identified. Promoters and high TF occupancy genomic regions were found to be "buffered" against variants causing ASBs.

  Study phs003977

• Detection of brain cancer using genome-wide cell-free DNA fragmentomes

  Diagnostic delays in patients with brain cancer are common and can impact patient outcome. Development of a blood-based assay for detection of brain cancers could accelerate brain cancer detection. In this study, we analyzed genome-wide cell-free (cfDNA) fragmentomes, including fragmentation profiles and repeat landscapes, from the plasma of individuals with (n=148) and without (n=357) brain cancer. Machine learning analyses of cfDNA fragmentome features detected brain cancer across all grade gliomas (AUC=0.90, 95% CI: 0.87-0.93) and these results were validated in an independent prospectively collected cohort. cfDNA fragmentome changes in patients with gliomas represented a combination of fragmentation profiles from glioma cells and altered white blood cell populations in the circulation. These analyses reveal the properties of cfDNA in patients with brain cancer and open new avenues for noninvasive detection of these individuals.

  Study EGAS50000000986

• ProstOmics: spatial and bulk multi-omics of prostate cancer

  In this ERC-funded ProstOmics project we have used spatial and bulk multi-omics on fresh frozen prostate cancer samples to investigate cancer biology and find for biomarkers to improve patient treatment. All tissue material were collected from prostate cancer patients undergoing radical prostatectomy who had not received any prior cancer-specific treatment.Of the 498 prostate tissue samples (114 patients) included in our project, 176 samples (N=37 patients) have been analyzed with bulk transcriptomics (RNA-seq). Some of these 176 samples were also analyzed with spatial transcriptomics (n=32, N=8, Visium 10x RNA-seq) and DNA methylomics (n=96, N=24, array). All datasets include metadata for histopathological evaluation. Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Study EGAS50000000413

• Dynamic Evolution of Fibroblasts Revealed by Single Cell RNA Sequencing of Human Pancreatic Cancer

  Understanding the constituents of the pancreatic ductal adenocarcinoma (PDAC) microenvironment may illuminate more efficacious targets for treating this aggressive malignancy. However, the compositional changes occurring in untreated and treated PDAC relative to both normal and inflamed pancreas have not been well characterized. To provide a more comprehensive understanding of the PDAC tumor microenvironment relative to the non-cancerous pancreas, we performed single-cell expression profiling (10X Genomics Chromium) on samples of upfront resectable PDAC, FOLFIRINOX-based treated PDAC, chronic pancreatitis, and normal pancreas specimens from 19 patients. Spatial gene expression profiling (10X Genomics Visium) was performed to gain additional insight into cell populations. Our analysis revealed that fibroblasts are central mediators of cell-cell communication in both inflamed and malignant settings and defined unique roles for these cell populations in different disease contexts.

  Study phs003751

• Highly prevalent NF-kappa B signaling pathway-activating somatic mutations in intracranial aneurysms

  Intracranial aneurysms (IAs) are a high-risk factor for life-threatening subarachnoid hemorrhage. Their etiology, however, remains mostly unknown. We conducted screening for somatic mutations in 65 IA tissues and identified 16 genes that were mutated with a high prevalence (92%). In particular, six genes, including PDGFRB, were mutated commonly in fusiform and saccular IAs and are linked to the NF-kappa B signaling pathway. Mutant PDGFRBs constitutively activate NF-kappa B signaling and induce inflammation-related gene expression in vitro. Spatial transcriptomics also detected similar changes in IA tissues. Virus-mediated expression of a mutant PDGFRB induces a fusiform-like dilatation of the basilar artery in mice. This study reveals a high prevalence of somatic mutations in NF-kappa B signaling genes in IAs and opens a new avenue of research toward development of its pharmacological interventions.

  Study JGAS000591

• Mutational anysis of breast cancer stem cells

  Exome sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations��� (clones���) mutations will be detected. Based on cancer stem theory, each populations��� cells are derived from each cancer stem cells, which their numbers are not so different among different clones. Here, we separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. By comping two groups��� mutation, we identified mutations, which were only detected in stem cell population. These mutations could be the mutations in cells of small size populations, and maybe the important mutations to understand the heterogeneity of tumor tissues, progression, and/or prediction for the outcome to therapies.

  Study JGAS000304

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Study EGAS50000001328

• BLUEPRINT Hematopoietic Stem/Progenitor Cell Methylomes

  An optimized whole genome bisulfite sequencing protocol (µWGBS, Farlik et al. 2015 Cell Reports) was used to establish DNA methylation profiles of FACS-purified stem and progenitor cells types of the human blood lineage. Most cell types were sorted from the peripheral blood of three donors with eight pools of ten cells, two pools of 50 cells, and one pool of 1000 cells. HSCs and MPPs were also sorted from fetal liver (HSCs only), cord blood, and bone marrow. Single-cell methylomes using the scWGBS protocol (Farlik et al. 2015 Cell Reports) were established for six cell types (HSC, MPP, CMP, GMP, CLP, MLP0). Gene expression profiling using the Smart-seq2 protocol (Picelli et al. 2013 Nature Methods) was done for nine stem/progenitor cell types (HSC, MPP, CMP, GMP, CLP, MLP0, MLP1, MLP2, MLP3).

  Study EGAS00001002070