Biology subjects

Davis, B. D.

Publications and source records attributed to Davis, B. D..

3 recordsLinked to original sources

bioRxiv2020

DNA methylation landscapes of matched primary and recurrent high grade serous ovarian cancers are preserved throughout disease progression and chemoresistance.

Little is known about the role of global DNA methylation in recurrence and chemoresistance of high grade serous ovarian cancer (HGSOC). We performed whole genome bisulfite sequencing (WGBS) and whole transcriptome sequencing (RNA-seq) to establish methylation and gene expression signatures in 62 primary and recurrent tumors from 28 patients diagnosed with stage III/IV HGSOC. Eleven of these patients carried pathogenic germline BRCA1/BRCA2 mutations. Genome-wide methylation and transcriptomic features identified in primary tumors were largely preserved in matched recurrent tumors from the same patient (P-value = 7.16 x 10-7 and 1.41 x 10-3 in BRCA1/2 and non-BRCA1/2 cases respectively). Tumors from BRCA1/2 carriers displayed high levels of heterogeneity, with significantly more shared methylation changes identified between primary and recurrent tumors from non-BRCA1/2 patients, which may be related to the poorer survival we observe in HGSOCs from non-BRCA1/2 carriers (P-value = 0.0056). Partially methylated domains (PMDs) dominated the epigenetic variation across all tumors, and were more hypomethylated in BRCA1/2 than non-BRCA1/2 cases. Differential gene expression analysis identified upregulation of genes from immune pathways including antigen processing and presentation in tumors from BRCA1/2 carriers, implicating increased immune response in the improved survival observed in these patients. In summary, this study shows a previously unreported conservation of methylation and gene expression in recurrent HGSOCs. These data have implications for the possible effectiveness of epigenetic based therapies to treat both primary and recurrent ovarian cancers.

genomics↗

bioRxiv2020

Ovarian Cancer Risk Variants are Enriched in Histotype-Specific Enhancers that Disrupt Transcription Factor Binding Sites

Quantifying the functional effects of complex disease risk variants can provide insights into mechanisms underlying disease biology. Genome wide association studies (GWAS) have identified 39 regions associated with risk of epithelial ovarian cancer (EOC). The vast majority of these variants lie in the non-coding genome, suggesting they mediate their function through the regulation of gene expression by their interaction with tissue specific regulatory elements (REs). In this study, by intersecting germline genetic risk data with regulatory landscapes of active chromatin in ovarian cancers and their precursor cell types, we first estimated the heritability explained by known common low penetrance risk alleles. The narrow sense heritability [Formula] of both EOC overall and high grade serous ovarian cancer (HGSOCs) was estimated to be 5-6%. Partitioned SNP-heritability across broad functional categories indicated a significant contribution of regulatory elements to EOC heritability. We collated epigenomic profiling data for 77 cell and tissue types from public resources (Roadmap Epigenomics and ENCODE), and H3K27Ac ChIP-Seq data generated in 26 ovarian cancer-relevant cell types. We identified significant enrichment of risk SNPs in active REs marked by H3K27Ac in HGSOCs. To further investigate how risk SNPs in active REs influence predisposition to ovarian cancer, we used motifbreakR to predict the disruption of transcription factor binding sites. We identified 469 candidate causal risk variants in H3K27Ac peaks that break TF motifs (enrichment P-Value < 1x10-5 compared to control variants). The most frequently broken motif was REST (P-Value = 0.0028), which has been reported as both a tumor suppressor and an oncogene. These systematic functional annotations with epigenomic data highlight the specificity of the regulatory landscape and demonstrate functional annotation of germline risk variants is most informative when performed in highly relevant cell types.

genetics↗

bioRxiv2019

Exautomate: A user-friendly tool for region-based rare variant association analysis (RVAA)

Region-based rare variant association analysis (RVAA) is a popular method to study rare genetic variation in large datasets, especially in the context of complex traits and diseases. Although this method shows great promise in increasing our understanding of the genetic architecture of complex phenotypes, performing a region-based RVAA can be challenging. The sequence kernel association test (SKAT) can be used to perform this analysis, but its inputs and modifiable parameters can be extremely overwhelming and may lead to results that are difficult to reproduce. We have developed a software package called \"Exautomate\" that contains the tools necessary to run a region-based RVAA using SKAT and is easy-to-use for any researcher, regardless of their previous bioinformatic experiences. In this report, we discuss the utilities of Exautomate and provide detailed examples of implementing our package. Importantly, we demonstrate a proof-of-principle analysis using a previously studied cohort of 313 familial hypercholesterolemia (FH) patients. Our results show an increased burden of rare variants in genes known to cause FH, thereby demonstrating a successful region-based RVAA using Exautomate. With our easy-to-use package, we hope researchers will be able to perform reproducible region-based RVAA to further our collective understanding behind the genetics of complex traits and diseases.

bioinformatics↗