Canopy2: tumor phylogeny inference by bulk DNA and single-cell RNA sequencing.

Tumors are comprised of a mixture of distinct cell populations that differ in terms of genetic makeup and function. Such heterogeneity plays a role in the development of drug resistance and the ineffectiveness of targeted cancer therapies. Insight into this complexity can be obtained through the construction of a phylogenetic tree, which illustrates the evolutionary lineage of tumor cells as they acquire mutations over time. We propose Canopy2, a Bayesian framework that uses single nucleotide variants derived from bulk DNA and single-cell RNA sequencing to infer tumor phylogeny and conduct mutational profiling of tumor subpopulations. Canopy2 uses Markov chain Monte Carlo methods to sample from a joint probability distribution involving a mixture of binomial and beta-binomial distributions, specifically chosen to account for the sparsity and stochasticity of the single-cell data. Canopy2 demystifies the sources of zeros in the single-cell data and separates zeros categorized as non-cancerous (cells without mutations), stochastic (mutations not expressed due to bursting), and technical (expressed mutations not picked up by sequencing). Simulations demonstrate that Canopy2 consistently outperforms competing methods and reconstructs the clonal tree with high fidelity, even in situations involving low sequencing depth, poor single-cell yield, and highly-advanced and polyclonal tumors. We further assess the performance of Canopy2 through application to breast cancer and glioblastoma data, benchmarking against existing methods. Canopy2 is an open-source R package available at https://github.com/annweideman/canopy2.

A large meta-analysis identifies genes associated with anterior uveitis.

Anterior Uveitis (AU) is the inflammation of the anterior part of the eye, the iris and ciliary body and is strongly associated with HLA-B*27. We report AU exome sequencing results from eight independent cohorts consisting of 3,850 cases and 916,549 controls. We identify common genome-wide significant loci in HLA-B (OR = 3.37, p = 1.03e-196) and ERAP1 (OR = 0.86, p = 1.1e-08), and find IPMK (OR = 9.4, p = 4.42e-09) and IDO2 (OR = 3.61, p = 6.16e-08) as genome-wide significant genes based on the burden of rare coding variants. Dividing the cohort into HLA-B*27 positive and negative individuals, we find ERAP1 haplotype is strongly protective only for B*27-positive AU (OR = 0.73, p = 5.2e-10). Investigation of B*27-negative AU identifies a common signal near HLA-DPB1 (rs3117230, OR = 1.26, p = 2.7e-08), risk genes IPMK and IDO2, and several additional candidate risk genes, including ADGFR5, STXBP2, and ACHE. Taken together, we decipher the genetics underlying B*27-positive and -negative AU and identify rare and common genetic signals for both subtypes of disease.

Liposome-Based Carbohydrate Vaccine for Simultaneously Eliciting Humoral and Cellular Antitumor Immunity.

Tumor-associated carbohydrate antigen (TACA)-based cancer vaccines achieved promising results, whereas missing the T cell-mediated cellular immune response is still a crucial problem to be solved. Here, we have developed Tn antigen (GalNAc)-modified liposome-encapsulated TLR9 agonist CpG ODN adjuvant as a cancer vaccine. The glyco-liposome vaccines exhibit strong binding ability with an anti-Tn specific antibody and enhance antigen presentation of both bone marrow-derived dendritic cells (BMDCs) and spleen B cells. In vivo immunogenicity studies have demonstrated that the glyco-liposome vaccines can significantly enhance the generation of high anti-Tn antigen antibody titers and further induce a Th1-dependent cellular immune response, evidenced by IFN-γ secretion in an immune coculture of immunized T cells with Tn-expression 4T1 cancer cells. Collectively, our results highlight a liposome-based carbohydrate vaccine as a promising platform, which can simultaneously elicit both humoral and cellular antitumor immunity.

EPIC: Inferring relevant cell types for complex traits by integrating genome-wide association studies and single-cell RNA sequencing.

More than a decade of genome-wide association studies (GWASs) have identified genetic risk variants that are significantly associated with complex traits. Emerging evidence suggests that the function of trait-associated variants likely acts in a tissue- or cell-type-specific fashion. Yet, it remains challenging to prioritize trait-relevant tissues or cell types to elucidate disease etiology. Here, we present EPIC (cEll tyPe enrIChment), a statistical framework that relates large-scale GWAS summary statistics to cell-type-specific gene expression measurements from single-cell RNA sequencing (scRNA-seq). We derive powerful gene-level test statistics for common and rare variants, separately and jointly, and adopt generalized least squares to prioritize trait-relevant cell types while accounting for the correlation structures both within and between genes. Using enrichment of loci associated with four lipid traits in the liver and enrichment of loci associated with three neurological disorders in the brain as ground truths, we show that EPIC outperforms existing methods. We apply our framework to multiple scRNA-seq datasets from different platforms and identify cell types underlying type 2 diabetes and schizophrenia. The enrichment is replicated using independent GWAS and scRNA-seq datasets and further validated using PubMed search and existing bulk case-control testing results.

Copy Number Variation Detection by Single-Cell DNA Sequencing with SCOPE.

Whole-genome single-cell DNA sequencing (scDNA-seq) enables the characterization of copy number profiles at the cellular level. This circumvents the averaging effects associated with bulk-tissue sequencing and has increased resolution yet decreased ambiguity in deconvolving cancer subclones and elucidating cancer evolutionary history. ScDNA-seq data is, however, sparse, noisy, and highly variable even within a homogeneous cell population, due to the biases and artifacts that are introduced during the library preparation and sequencing procedure. Here, we describe SCOPE, a normalization and copy number estimation method for scDNA-seq data. We give an overview of the methodology and illustrate SCOPE with step-by-step demonstrations.

Is Fluorescence Technology a Promising Tool for Detecting Infected Dentin in Deep Carious Lesions?

The purpose of this study was to determine if the degree of fluorescence detected by fluorescence-aided caries excavation (FACE) correlates with dentin bacterial microbiome diversity, as assessed by 16S rRNA gene amplicon sequencing, and with traditional tactile dentin caries assessment. Unidentified human teeth were obtained from a dental facility. The included teeth had a carious lesion two-thirds into the dentin, verified by radiography, and were red-fluorescing (RF) using FACE technology (SIROInspect; Sirona, Bensheim, Germany). Two independent examiners performed visual/tactile assessment of the lesions. RF sites were sampled with a sterile spoon excavator and dentin characteristics were evaluated. Once RF dentin was removed, a second sample of pink-fluorescing (PF) dentin was obtained. After excavation with a sterile round bur to nonfluorescing (NF) dentin, a third sample was collected with a slow-speed round bur. The samples were processed at the UNC (University of North Carolina at Chapel Hill) Microbiome Core Facility. Out of 134 extracted teeth collected, 21 fit the inclusion criteria, yielding 61 dentin samples. RF samples had the highest number of observed operational taxonomic units (n = 154), followed by PF (n = 109) and NF (n = 100). RF carious dentin was primarily "soft," and NF dentin was assessed as "hard" 100% of the time by both examiners (rank correlation χ2: p < 0.001). However, approximately one-third of the tactile assessments of hard dentin still displayed some fluorescence, either pink or red. We concluded that the sampled fluorescing (RF and PF) and NF carious dentin layers displayed diverse bacterial taxa, and tactile assessments of soft, leathery, and hard corresponded with RF, PF, and NF.

SCOPE: A Normalization and Copy-Number Estimation Method for Single-Cell DNA Sequencing.

Whole-genome single-cell DNA sequencing (scDNA-seq) enables characterization of copy-number profiles at the cellular level. We propose SCOPE, a normalization and copy-number estimation method for the noisy scDNA-seq data. SCOPE's main features include the following: (1) a Poisson latent factor model for normalization, which borrows information across cells and regions to estimate bias, using in silico identified negative control cells; (2) an expectation-maximization algorithm embedded in the normalization step, which accounts for the aberrant copy-number changes and allows direct ploidy estimation without the need for post hoc adjustment; and (3) a cross-sample segmentation procedure to identify breakpoints that are shared across cells with the same genetic background. We evaluate SCOPE on a diverse set of scDNA-seq data in cancer genomics and show that SCOPE offers accurate copy-number estimates and successfully reconstructs subclonal structure. A record of this paper's transparent peer review process is included in the Supplemental Information.

Nucleotide excision repair capacity increases during differentiation of human embryonic carcinoma cells into neurons and muscle cells.

Embryonic stem cells can self-renew and differentiate, holding great promise for regenerative medicine. They also employ multiple mechanisms to preserve the integrity of their genomes. Nucleotide excision repair, a versatile repair mechanism, removes bulky DNA adducts from the genome. However, the dynamics of the capacity of nucleotide excision repair during stem cell differentiation remain unclear. Here, using immunoslot blot assay, we measured repair rates of UV-induced DNA damage during differentiation of human embryonic carcinoma (NTERA-2) cells into neurons and muscle cells. Our results revealed that the capacity of nucleotide excision repair increases as cell differentiation progresses. We also found that inhibition of the apoptotic signaling pathway has no effect on nucleotide excision repair capacity. Furthermore, RNA-Seq-based transcriptomic analysis indicated that expression levels of four core repair factors, xeroderma pigmentosum (XP) complementation group A (XPA), XPC, XPG, and XPF-ERCC1, are progressively up-regulated during differentiation, but not those of replication protein A (RPA) and transcription factor IIH (TFIIH). Together, our findings reveal that increase of nucleotide excision repair capacity accompanies cell differentiation, supported by the up-regulated transcription of genes encoding DNA repair enzymes during differentiation of two distinct cell lineages.

CODEX2: full-spectrum copy number variation detection by high-throughput DNA sequencing.

High-throughput DNA sequencing enables detection of copy number variations (CNVs) on the genome-wide scale with finer resolution compared to array-based methods but suffers from biases and artifacts that lead to false discoveries and low sensitivity. We describe CODEX2, as a statistical framework for full-spectrum CNV profiling that is sensitive for variants with both common and rare population frequencies and that is applicable to study designs with and without negative control samples. We demonstrate and evaluate CODEX2 on whole-exome and targeted sequencing data, where biases are the most prominent. CODEX2 outperforms existing methods and, in particular, significantly improves sensitivity for common CNVs.

The effect of single tooth implant restorations on the survival, morbidity, pulpal, and periapical health of adjacent teeth: A chart review.

PURPOSE: To determine whether the placement and restoration of a single tooth posterior implant affects the survival, morbidity, pulpal, and periapical health of adjacent natural teeth. MATERIALS AND METHODS: A retrospective chart review identified patients who received single posterior tooth implants between August 2004 and July 2015 at the UNC SOD and met the study inclusion criteria. Preoperative and postoperative records were reviewed; survival and changes in coronal, pulpal, and periapical status of teeth adjacent to the implant and contralateral tooth were recorded. Dichotomous survival, restoration, and retreatment outcomes were analyzed using conditional logistic regression with patient as strata and implant versus control as the predictor. Exact odds ratio estimates and the 95% confidence intervals were obtained for the relationship of implant versus control side and outcomes. RESULTS: Five hundred and fifty-five sites with follow-up time averaging 5 years ± 30.8 months were reviewed. Teeth adjacent to implants had 1.75 (95% CI: 1.17, 2.64) times the odds of restorative retreatments as compared to controls (P = .005). On the implant side, 48 adjacent teeth (4.5%) were more heavily restored at follow up, while 84 (7.9%) experienced retreatment with comparable number of surfaces restored. On the contralateral side, 54 adjacent teeth (5.0%) were more heavily restored, and 56 (5.2%) experienced comparable levels of retreatment. In addition, 17 (1.7%) implant adjacent teeth required root canal treatment, compared to 12 (1.2%) on the contralateral side; 1 implant adjacent tooth required root canal retreatment. Forty-two teeth (3.8%) adjacent to implants were lost, compared to 35 (3.2%) adjacent to natural teeth. CONCLUSIONS: The incidence for restorative retreatment was significantly higher on teeth adjacent to implant restorations as compared to the contralateral controls. There were no significant differences in the survival, morbidity, pulpal, or periapical health of teeth adjacent to single tooth implants compared to those adjacent to the contralateral natural tooth.