Locus specific endogenous retroviral expression associated with Alzheimer's disease.

Introduction: Human endogenous retroviruses (HERVs) are transcriptionally-active remnants of ancient retroviral infections that may play a role in Alzheimer's disease. Methods: We combined two, publicly available RNA-Seq datasets with a third, novel dataset for a total cohort of 103 patients with Alzheimer's disease and 45 healthy controls. We use telescope to perform HERV quantification for these samples and simultaneously perform gene expression analysis. Results: We identify differentially expressed genes and differentially expressed HERVs in Alzheimer's disease patients. Differentially expressed HERVs are scattered throughout the genome; many of them are members of the HERV-K superfamily. A number of HERVs are correlated with the expression of dysregulated genes in Alzheimer's and are physically proximal to genes which drive disease pathways. Discussion: Dysregulated expression of ancient retroviral insertions in the human genome are present in Alzheimer's disease and show localization patterns that may explain how these elements drive pathogenic gene expression.

Oncogenic Transformation Drives DNA Methylation Loss and Transcriptional Activation at Transposable Element Loci.

Transposable elements (TE) are typically silenced by DNA methylation and repressive histone modifications in differentiated healthy human tissues. However, TE expression increases in a wide range of cancers and is correlated with global hypomethylation of cancer genomes. We assessed expression and DNA methylation of TEs in fibroblast cells that were serially transduced with hTERT, SV40, and HRASR24C to immortalize and then transform them, modeling the different steps of the tumorigenesis process. RNA sequencing and whole-genome bisulfite sequencing were performed at each stage of transformation. TE expression significantly increased as cells progressed through transformation, with the largest increase in expression after the final stage of transformation, consistent with data from human tumors. The upregulated TEs were dominated by endogenous retroviruses [long terminal repeats (LTR)]. Most differentially methylated regions (DMR) in all stages were hypomethylated, with the greatest hypomethylation in the final stage of transformation. A majority of the DMRs overlapped TEs from the RepeatMasker database, indicating that TEs are preferentially demethylated. Many hypomethylated TEs displayed a concordant increase in expression. Demethylation began during immortalization and continued into transformation, while upregulation of TE transcription occurred in transformation. Numerous LTR elements upregulated in the model were also identified in The Cancer Genome Atlas datasets of breast, colon, and prostate cancer. Overall, these findings indicate that TEs, specifically endogenous retroviruses, are demethylated and transcribed during transformation. SIGNIFICANCE: Analysis of epigenetic and transcriptional changes in a transformation model reveals that transposable element expression and methylation are dysregulated during oncogenic transformation.

Inhibiting DNA methylation and RNA editing upregulates immunogenic RNA to transform the tumor microenvironment and prolong survival in ovarian cancer.

BACKGROUND: Novel therapies are urgently needed for ovarian cancer (OC), the fifth deadliest cancer in women. Preclinical work has shown that DNA methyltransferase inhibitors (DNMTis) can reverse the immunosuppressive tumor microenvironment in OC. Inhibiting DNA methyltransferases activate transcription of double-stranded (ds)RNA, including transposable elements. These dsRNAs activate sensors in the cytoplasm and trigger type I interferon (IFN) signaling, recruiting host immune cells to kill the tumor cells. Adenosine deaminase 1 (ADAR1) is induced by IFN signaling and edits mammalian dsRNA with an A-to-I nucleotide change, which is read as an A-to-G change in sequencing data. These edited dsRNAs cannot be sensed by dsRNA sensors, and thus ADAR1 inhibits the type I IFN response in a negative feedback loop. We hypothesized that decreasing ADAR1 editing would enhance the DNMTi-induced immune response. METHODS: Human OC cell lines were treated in vitro with DNMTi and then RNA-sequenced to measure RNA editing. Adar1 was stably knocked down in ID8 Trp53-/- mouse OC cells. Control cells (shGFP) or shAdar1 cells were tested with mock or DNMTi treatment. Tumor-infiltrating immune cells were immunophenotyped using flow cytometry and cell culture supernatants were analyzed for secreted chemokines/cytokines. Mice were injected with syngeneic shAdar1 ID8 Trp53-/- cells and treated with tetrahydrouridine/DNMTi while given anti-interferon alpha and beta receptor 1, anti-CD8, or anti-NK1.1 antibodies every 3 days. RESULTS: We show that ADAR1 edits transposable elements in human OC cell lines after DNMTi treatment in vitro. Combining ADAR1 knockdown with DNMTi significantly increases pro-inflammatory cytokine/chemokine production and sensitivity to IFN-ß compared with either perturbation alone. Furthermore, DNMTi treatment and Adar1 loss reduces tumor burden and prolongs survival in an immunocompetent mouse model of OC. Combining Adar1 loss and DNMTi elicited the most robust antitumor response and transformed the immune microenvironment with increased recruitment and activation of CD8+ T cells. CONCLUSION: In summary, we showed that the survival benefit from DNMTi plus ADAR1 inhibition is dependent on type I IFN signaling. Thus, epigenetically inducing transposable element transcription combined with inhibition of RNA editing is a novel therapeutic strategy to reverse immune evasion in OC, a disease that does not respond to current immunotherapies.

Epigenetic Therapies in Ovarian Cancer Alter Repetitive Element Expression in a TP53-Dependent Manner.

Epithelial ovarian carcinomas are particularly deadly due to intratumoral heterogeneity, resistance to standard-of-care therapies, and poor response to alternative treatments such as immunotherapy. Targeting the ovarian carcinoma epigenome with DNA methyltransferase inhibitors (DNMTi) or histone deacetylase inhibitors (HDACi) increases immune signaling and recruits CD8+ T cells and natural killer cells to fight ovarian carcinoma in murine models. This increased immune activity is caused by increased transcription of repetitive elements (RE) that form double-stranded RNA (dsRNA) and trigger an IFN response. To understand which REs are affected by epigenetic therapies in ovarian carcinoma, we assessed the effect of DNMTi and HDACi on ovarian carcinoma cell lines and patient samples. Subfamily-level (TEtranscripts) and individual locus-level (Telescope) analysis of REs showed that DNMTi treatment upregulated more REs than HDACi treatment. Upregulated REs were predominantly LTR and SINE subfamilies, and SINEs exhibited the greatest loss of DNA methylation upon DNMTi treatment. Cell lines with TP53 mutations exhibited significantly fewer upregulated REs with epigenetic therapy than wild-type TP53 cell lines. This observation was validated using isogenic cell lines; the TP53-mutant cell line had significantly higher baseline expression of REs but upregulated fewer upon epigenetic treatment. In addition, p53 activation increased expression of REs in wild-type but not mutant cell lines. These data give a comprehensive, genome-wide picture of RE chromatin and transcription-related changes in ovarian carcinoma after epigenetic treatment and implicate p53 in RE transcriptional regulation. SIGNIFICANCE: This study identifies the repetitive element targets of epigenetic therapies in ovarian carcinoma and indicates a role for p53 in this process.

HAPHPIPE: Haplotype Reconstruction and Phylodynamics for Deep Sequencing of Intrahost Viral Populations.

Deep sequencing of viral populations using next-generation sequencing (NGS) offers opportunities to understand and investigate evolution, transmission dynamics, and population genetics. Currently, the standard practice for processing NGS data to study viral populations is to summarize all the observed sequences from a sample as a single consensus sequence, thus discarding valuable information about the intrahost viral molecular epidemiology. Furthermore, existing analytical pipelines may only analyze genomic regions involved in drug resistance, thus are not suited for full viral genome analysis. Here, we present HAPHPIPE, a HAplotype and PHylodynamics PIPEline for genome-wide assembly of viral consensus sequences and haplotypes. The HAPHPIPE protocol includes modules for quality trimming, error correction, de novo assembly, alignment, and haplotype reconstruction. The resulting consensus sequences, haplotypes, and alignments can be further analyzed using a variety of phylogenetic and population genetic software. HAPHPIPE is designed to provide users with a single pipeline to rapidly analyze sequences from viral populations generated from NGS platforms and provide quality output properly formatted for downstream evolutionary analyses.

Validation of Variant Assembly Using HAPHPIPE with Next-Generation Sequence Data from Viruses.

Next-generation sequencing (NGS) offers a powerful opportunity to identify low-abundance, intra-host viral sequence variants, yet the focus of many bioinformatic tools on consensus sequence construction has precluded a thorough analysis of intra-host diversity. To take full advantage of the resolution of NGS data, we developed HAplotype PHylodynamics PIPEline (HAPHPIPE), an open-source tool for the de novo and reference-based assembly of viral NGS data, with both consensus sequence assembly and a focus on the quantification of intra-host variation through haplotype reconstruction. We validate and compare the consensus sequence assembly methods of HAPHPIPE to those of two alternative software packages, HyDRA and Geneious, using simulated HIV and empirical HIV, HCV, and SARS-CoV-2 datasets. Our validation methods included read mapping, genetic distance, and genetic diversity metrics. In simulated NGS data, HAPHPIPE generated pol consensus sequences significantly closer to the true consensus sequence than those produced by HyDRA and Geneious and performed comparably to Geneious for HIV gp120 sequences. Furthermore, using empirical data from multiple viruses, we demonstrate that HAPHPIPE can analyze larger sequence datasets due to its greater computational speed. Therefore, we contend that HAPHPIPE provides a more user-friendly platform for users with and without bioinformatics experience to implement current best practices for viral NGS assembly than other currently available options.