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The coronavirus disease of 2019 (COVID-19) pandemic declared by the World Health Organization on March 11, 2020 impacted healthcare services with provider and patient cancellations, delays, and patient avoidance or delay of emergency department or urgent care. Limited data exist on the population proportion affected by delayed healthcare, which is important for future healthcare planning efforts. Our objective was to evaluate the impact of the COVID-19 pandemic on healthcare service cancellations or delays and delays/avoidance of emergency/urgent care overall and by population characteristics.This was a cross-sectional study.Our sample (n = 2314) was assembled through a phone survey from 8/12/2020-10/27/2020 among non-institutionalized St. Louis County, Missouri, USA residents ≥18 years. We asked about provider and patient-initiated cancellations or delays of appointments and pandemic-associated delays/avoidance of emergency/urgent care overall and by participant characteristics. We calculated weighted prevalence estimates by select resident characteristics.Healthcare services cancellations or delays affected ∼54% (95% CI 50.6%-57.1%) of residents with dental (31.1%, 95% CI 28.1%-34.0%) and primary care (22.1%, 95% CI 19.5%-24.6%) being most common. The highest prevalences were among those who were White, ≥65 years old, female, in fair/poor health, who had health insurance, and who had ≥1 medical condition. Delayed or avoided emergency/urgent care impacted ∼23% (95% CI 19.9%-25.4%) of residents with a higher prevalence in females than males.Healthcare use disruptions impacted a substantial proportion of residents. Future healthcare planning efforts should consider these data to minimize potential morbidity and mortality from delayed care.

The true prevalence of COVID-19 is difficult to estimate due to the absence of random population-based testing. To estimate current and past COVID-19 infection prevalence in a large urban area, we conducted a population-based survey in St. Louis County, Missouri.The population-based survey of active infection (PCR) and seroprevalence (IgG antibodies) of adults (≥18 years) was conducted through random-digit dialing and targeted sampling of St. Louis County residents with oversampling of Black residents. Infection prevalence of residents was estimated using design-based and raking weighting.Between August 17 and October 24, 2020, 1245 residents completed a survey and underwent PCR testing; 1073 residents completed a survey and underwent PCR and IgG testing or self-reported results. Weighted prevalence estimates of residents with active infection were 1.9% (95% CI, 0.4%-3.3%) and 5.6% were ever infected (95% CI, 3.3%-8.0%). Overall infection hospitalization and fatality ratios were 4.9% and 1.4%, respectively.Through October 2020, the percentage of residents that had ever been infected was relatively low. A markedly higher percentage of Black and other minorities compared to White residents were infected with COVID-19. The St. Louis region remained highly vulnerable to widespread infection in late 2020.

Transcription factors are proteins that flip genetic switches; their role is to control when and where genes are active. They do this by binding to short stretches of DNA called cis-regulatory sequences. Each sequence can have several binding sites for different transcription factors, but it is largely unclear whether the transcription factors binding to the same regulatory sequence actually work together. It is possible that each transcription factor may work independently and there only needs to be critical mass of transcription factors bound to throw the genetic switch. If this is the case, the most important features of a cis-regulatory sequence should be the number of binding sites it contains, and how tightly the transcription factors bind to those sites. The more transcription factors and the more strongly they bind, the more active the gene should be. An alternative option is that certain transcription factors may work better together, enhancing each other's effects such that the total effect is more than the sum of its parts. If this is true, the order, orientation and spacing of the binding sites within a sequence should matter more than the number. One way to investigate to distinguish between these possibilities is to study mouse embryonic stem cells, which have a core set of four transcription factors. Looking directly at a real genome, however, can be confusing and it is difficult to measure the effects of different cis-regulatory sequences because genes differ in so many other ways. To tackle this problem, King et al. created a synthetic set of cis-regulatory sequences based on the four core transcription factors found in mouse stem cells. The synthetic set had every combination of two, three or four of the binding sites, with each site either facing forwards or backwards along the DNA strand. King et al. attached each of the synthetic cis-regulatory sequences to a reporter gene to find out how well each sequence performed. This revealed that the cis-regulatory sequences with the most binding sites and the tightest binding affinities work best, suggesting that transcription factors mainly work independently. There was evidence of some interaction between some transcription factors, because, of the synthetic sequences with four binding sites, some worked better than others, and there were patterns in the most effective binding site combinations. However, these effects were small and when King et al. went on to test sequences from the real mouse genome, the most important factor by far was the number of binding sites. Synthetic libraries of DNA sequences allow researchers to examine gene regulation more clearly than is possible in real genomes. Yet this approach does have its limitations and it is impossible to capture every type of cis-regulatory sequence in one library. The next step to extend this work is to combine the two approaches, taking sequences from the real genome and manipulating them one by one. This could help to unravel the rules that govern how cis-regulatory sequences work in real cells.

Cis-regulatory modules contain multiple transcription factor (TF)-binding sites and integrate the effects of each TF to control gene expression in specific cellular contexts. Transposable elements (TEs) are uniquely equipped to deposit their regulatory sequences across a genome, which could also contain cis-regulatory modules that coordinate the control of multiple genes with the same regulatory logic. We provide the first evidence of mouse-specific TEs that encode a module of TF-binding sites in mouse embryonic stem cells (ESCs). The majority (77%) of the individual TEs tested exhibited enhancer activity in mouse ESCs. By mutating individual TF-binding sites within the TE, we identified a module of TF-binding motifs that cooperatively enhanced gene expression. Interestingly, we also observed the same motif module in the in silico constructed ancestral TE that also acted cooperatively to enhance gene expression. Our results suggest that ancestral TE insertions might have brought in cis-regulatory modules into the mouse genome., The gene-battery model posits transposable elements (TEs) may be cis-regulatory elements to control gene expression. Here, mouse-specific TEs are shown as binding sites for multiple collaborating transcription factors in embryonic stem cells, and act as cis-regulatory modules in synergistic fashion.

In embryonic stem cells (ESCs), a core network of transcription factors establish and maintain the gene expression program necessary to grow indefinitely in cell culture and generate all three primary germ layers. To understand how interactions between four key pluripotency transcription factors (TFs), SOX2, POU5F1 (OCT4), KLF4, and ESRRB, contribute to cis-regulation in mouse ESCs, we assayed two massively parallel reporter assay (MPRA) libraries composed of different combinations of binding sites for these TFs. One library was an exhaustive set of synthetic cis-regulatory elements and the second was a set of genomic sequences with comparable configurations of binding sites. Comparisons between the libraries allowed us to determine the regulatory grammar requirements for these binding sites in constrained synthetic contexts versus genomic sequence contexts. We found that binding site quality is a common attribute for active elements in both the synthetic and genomic contexts. For synthetic regulatory elements, the level of expression is mostly determined by the number of binding sites but is tuned by a grammar that includes position effects. Surprisingly, this grammar appears to only play a small role in setting the output levels of genomic sequences. The relative activity of genomic sequences is best explained by the predicted affinity of binding sites, regardless of identity, and optimized spacing between sites. Our findings highlight the need for detailed examinations of complex sequence space when trying to understand cis-regulatory grammar in the genome.

In embryonic stem cells (ESCs), a core transcription factor (TF) network establishes the gene expression program necessary for pluripotency. To address how interactions between four key TFs contribute to cis-regulation in mouse ESCs, we assayed two massively parallel reporter assay (MPRA) libraries composed of binding sites for SOX2, POU5F1 (OCT4), KLF4, and ESRRB. Comparisons between synthetic cis-regulatory elements and genomic sequences with comparable binding site configurations revealed some aspects of a regulatory grammar. The expression of synthetic elements is influenced by both the number and arrangement of binding sites. This grammar plays only a small role for genomic sequences, as the relative activities of genomic sequences are best explained by the predicted occupancy of binding sites, regardless of binding site identity and positioning. Our results suggest that the effects of transcription factor binding sites (TFBS) are influenced by the order and orientation of sites, but that in the genome the overall occupancy of TFs is the primary determinant of activity., eLife digest Transcription factors are proteins that flip genetic switches; their role is to control when and where genes are active. They do this by binding to short stretches of DNA called cis-regulatory sequences. Each sequence can have several binding sites for different transcription factors, but it is largely unclear whether the transcription factors binding to the same regulatory sequence actually work together. It is possible that each transcription factor may work independently and there only needs to be critical mass of transcription factors bound to throw the genetic switch. If this is the case, the most important features of a cis-regulatory sequence should be the number of binding sites it contains, and how tightly the transcription factors bind to those sites. The more transcription factors and the more strongly they bind, the more active the gene should be. An alternative option is that certain transcription factors may work better together, enhancing each other's effects such that the total effect is more than the sum of its parts. If this is true, the order, orientation and spacing of the binding sites within a sequence should matter more than the number. One way to investigate to distinguish between these possibilities is to study mouse embryonic stem cells, which have a core set of four transcription factors. Looking directly at a real genome, however, can be confusing and it is difficult to measure the effects of different cis-regulatory sequences because genes differ in so many other ways. To tackle this problem, King et al. created a synthetic set of cis-regulatory sequences based on the four core transcription factors found in mouse stem cells. The synthetic set had every combination of two, three or four of the binding sites, with each site either facing forwards or backwards along the DNA strand. King et al. attached each of the synthetic cis-regulatory sequences to a reporter gene to find out how well each sequence performed. This revealed that the cis-regulatory sequences with the most binding sites and the tightest binding affinities work best, suggesting that transcription factors mainly work independently. There was evidence of some interaction between some transcription factors, because, of the synthetic sequences with four binding sites, some worked better than others, and there were patterns in the most effective binding site combinations. However, these effects were small and when King et al. went on to test sequences from the real mouse genome, the most important factor by far was the number of binding sites. Synthetic libraries of DNA sequences allow researchers to examine gene regulation more clearly than is possible in real genomes. Yet this approach does have its limitations and it is impossible to capture every type of cis-regulatory sequence in one library. The next step to extend this work is to combine the two approaches, taking sequences from the real genome and manipulating them one by one. This could help to unravel the rules that govern how cis-regulatory sequences work in real cells.

DNA vaccines have demonstrated antitumor efficacy in multiple preclinical models, but low immunogenicity has been observed in several human clinical trials. This has led to many approaches seeking to improve the immunogenicity of DNA vaccines. We previously reported that a DNA vaccine encoding the cancer–testis antigen SSX2, modified to encode altered epitopes with increased MHC class I affinity, elicited a greater frequency of cytolytic, multifunctional CD8+ T cells in non–tumor-bearing mice. We sought to test whether this optimized vaccine resulted in increased antitumor activity in mice bearing an HLA-A2–expressing tumor engineered to express SSX2. We found that immunization of tumor-bearing mice with the optimized vaccine elicited a surprisingly inferior antitumor effect relative to the native vaccine. Both native and optimized vaccines led to increased expression of PD-L1 on tumor cells, but antigen-specific CD8+ T cells from mice immunized with the optimized construct expressed higher PD-1. Splenocytes from immunized animals induced PD-L1 expression on tumor cells in vitro. Antitumor activity of the optimized vaccine could be increased when combined with antibodies blocking PD-1 or PD-L1, or by targeting a tumor line not expressing PD-L1. These findings suggest that vaccines aimed at eliciting effector CD8+ T cells, and DNA vaccines in particular, might best be combined with PD-1 pathway inhibitors in clinical trials. This strategy may be particularly advantageous for vaccines targeting prostate cancer, a disease for which antitumor vaccines have demonstrated clinical benefit and yet PD-1 pathway inhibitors alone have shown little efficacy to date. Cancer Immunol Res; 3(8); 946–55. ©2015 AACR.

A genome-wide assay defines the relationship of cis-regulatory sequences and chromatin structure in regulating gene expression. A gene's position in the genome can profoundly affect its expression because regional differences in chromatin modulate the activity of locally acting cis-regulatory sequences (CRSs). Here we study how CRSs and regional chromatin act in concert on a genome-wide scale. We present a massively parallel reporter gene assay that measures the activities of hundreds of different CRSs, each integrated at many specific genomic locations. Although genome location strongly affected CRS activity, the relative strengths of CRSs were maintained at all chromosomal locations. The intrinsic activities of CRSs also correlated with their activities in plasmid-based assays. We explain our data with a quantitative model in which expression levels are set by independent contributions from local CRSs and the regional chromatin environment, rather than by more complex sequence- or protein-specific interactions between these two factors. The methods we present will help investigators determine when regulatory information is integrated in a modular fashion and when regulatory sequences interact in more complex ways.

BACKGROUND An important focus of tumor immunotherapy has been the identification of appropriate antigenic targets. Serum-based screening approaches have led to the discovery of hundreds of tumor-associated antigens recognized by IgG. Our efforts to identify immunologically recognized proteins in prostate cancer have yielded a multitude of antigens; however, prioritizing these antigens as targets for evaluation in immunotherapies has been challenging. In this report, we set out to determine whether the evaluation of multiple antigenic targets would allow the identification of a subset of antigens that are common immunologic targets in patients with prostate cancer. METHODS Using a phage immunoblot approach, we evaluated IgG responses in patients with prostate cancer (n = 126), patients with chronic prostatitis (n = 45), and men without prostate disease (n = 53). RESULTS We found that patients with prostate cancer or prostatitis have IgG specific for multiple common antigens. A subset of 23 proteins was identified to which IgG were detected in 38% of patients with prostate cancer and 33% patients with prostatitis versus 6% of controls (P

DNA methylation undergoes dynamic changes during development and cell differentiation. Recent genome-wide studies discovered that tissue-specific differentially methylated regions (DMRs) often overlap tissue-specific distal cis-regulatory elements. However, developmental DNA methylation dynamics of the majority of the genomic CpGs outside gene promoters and CpG islands has not been extensively characterized. Here, we generate and compare comprehensive DNA methylome maps of zebrafish developing embryos. From these maps, we identify thousands of developmental stage-specific DMRs (dsDMRs) across zebrafish developmental stages. The dsDMRs contain evolutionarily conserved sequences, are associated with developmental genes and are marked with active enhancer histone posttranslational modifications. Their methylation pattern correlates much stronger than promoter methylation with expression of putative target genes. When tested in vivo using a transgenic zebrafish assay, 20 out of 20 selected candidate dsDMRs exhibit functional enhancer activities. Our data suggest that developmental enhancers are a major target of DNA methylation changes during embryogenesis.

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Recent large-scale genomics efforts to characterize the cis-regulatory sequences that orchestrate genome-wide expression patterns have produced impressive catalogues of putative regulatory elements. Most of these sequences have not been functionally tested, and our limited understanding of the non-coding genome prevents us from predicting which sequences are bona fide cis-regulatory elements. Recently, massively parallel reporter assays (MPRAs) have been deployed to measure the activity of putative cis-regulatory sequences in several biological contexts, each with specific advantages and distinct limitations. We developed LV-MPRA, a novel lentiviral-based, massively parallel reporter gene assay, to study the function of genome-integrated regulatory elements in any mammalian cell type; thus, making it possible to apply MPRAs in more biologically relevant contexts. We measured the activity of 2,600 sequences in U87 glioblastoma cells and human neural progenitor cells (hNPCs) and explored how regulatory activity is encoded in DNA sequence. We demonstrate that LV-MPRA can be applied to estimate the effects of local DNA sequence and regional chromatin on regulatory activity. Our data reveal that primary DNA sequence features, such as GC content and dinucleotide composition, accurately distinguish sequences with high activity from sequences with low activity in a full chromosomal context, and may also function in combination with different transcription factor binding sites to determine cell type specificity. We conclude that LV-MPRA will be an important tool for identifying cis-regulatory elements and stimulating new understanding about how the non-coding genome encodes information.

Over the last decade, immunotherapies have been developed for the treatment of prostate cancer with the goal of generating anti-tumor immune responses. Vaccine-based treatments target the immune system to a specific antigen, or set of antigens, expressed by the tumor. Other therapeutic modalities, including androgen deprivation therapy, can result in tissue damage and have been demonstrated to elicit prostate antigen-specific immune responses. The evaluation of immune responses to individual tumor antigens in the context of these non-antigen-specific immunomodulatory treatments has been notoriously difficult and time-consuming. We have previously reported a panel of 125 commonly recognized prostate cancer-associated antigens identified from multiple IgG screening approaches. This panel included multiple cancer-testis antigens and antigenic proteins recognized by IgG in patients with chronic prostatitis or prostate cancer. In the current study we questioned whether this panel could be used to identify antigen-specific immune responses elicited in patients with prostate cancer following androgen deprivation. 125 lambda phage encoding these unique antigens were spotted in triplicate using a high-throughput, high-density SEREX methodology. Sera were obtained from 33 patients with prostate cancer collected pretreatment and three months post-androgen deprivation therapy. These sera were used to probe this panel and IgG antibody responses were detected and objectively quantified by densitometry. 31 sera sets met pre-specified criteria as adequate for analysis. Results demonstrated that autoantibodies were induced to 62 of the 125 antigens. IgG responses were elicited to 21 of the antigens in multiple patients, including MAD-Pro-34, MAD-CT-1, and LAGE-1, each of which have previously been demonstrated to be the targets of autoantibody responses in prostate cancer patients. IgG responses were detected to at least one protein in 18 of 31 patients, and to multiple antigens in 11 of 31 patients. These data demonstrate that androgen deprivation elicits IgG responses to prostate-associated proteins, and that responses can be detected using a panel of commonly recognized prostate antigens. Further studies will aim to characterize this panel and autoantibody profiles in patients treated with other non-antigen-specific immunotherapies or anti-prostate tumor vaccines. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 5591.