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Prostate Specific Membrane Antigen (PSMA) is a prominent biomarker in Prostate Cancer (PC) and has evolved into a useful target for both imaging and therapy. But how PSMA becomes overexpressed upon PC development, its modulation by androgen deprivation therapy (ADT), and its absence in neuroendocrine-differentiated PC is not well understood. The exact mechanism by which PSMA is regulated has not been defined. Understanding PSMA regulation in PC patients for diagnostic, prognostic, and treatment purposes would be extremely valuable and could be exploited for PSMA-targeted therapies. To address this, we sought to characterize the epigenetic landscape of FOLH1 (the gene for PSMA) and determine the regulatory factors involved in FOLH1 transcription. Based on histone marker and protein ChIP-Seq data sets alongside ATAC-seq, we found that FOLH1 is a Super Enhancer (SE) and is collectively bound by an array of transcription factors (TFs), including AR, FOXA1, and HOXB13. We developed a hidden Markov model (HMM) with seven chromatin states built on average TF binding in the FOLH1 landscape and trained on the FOLH1 gene and known enhancer regions. Chromatin states were annotated based on features in the FOLH1 gene. With a simple regression model and k-fold cross-validation, mean occupancy of the three TFs and H3K27Ac in each state accurately predicts FOLH1 expression (ρ > 0.9) across PC samples. To assess the functionality of the enhancer regions predicted by our computational HMM, we performed a CRISPR interference (CRISPRi) screen with a nuclease dead-Cas9 protein conjugated to the KRAB transcriptional repressor and directed by a pool of gRNAs that tile across the AR protein-bound regions within the FOLH1 landscape. A sliding window analysis of our CRISPRi screen revealed that the top scoring gRNAs delineate 5 Regulatory Regions (RRs) found within the SE region of FOLH1 that control FOLH1/PSMA expression. Motif identification in these RRs have provided a list of potential TF candidates involved in regulating FOLH1, and knockdown experiments are currently being conducted to evaluate individual and combinations of TF contribution to FOLH1 expression. There is evidence for a constellation of TFs responsible for regulating FOLH1, and context-specific modifications in FOLH1 regulation will need to be evaluated in various models and conditions. These results suggest FOLH1 is regulated by epigenetic control in the SE region and may be altered in progression or with ADT. Characterizing the regulation of FOLH1/PSMA will result in a deeper understanding of the meaning of alterations in uptake on PSMA imaging and may enable some degree of control over expression, thus aiding in PSMA-directed treatments. Citation Format: Margaret E. White, Thomas Pranzatelli, Xavier Moore, Joel Bowman, Jay Chiorini, Peter Choyke, Kathy Kelly. The regulation of FOLH1/PSMA in prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 976.

ObjectivesSjögren’s syndrome (SS) is an autoimmune sialadenitis with unknown aetiology. Although extensive research implicated an abnormal immune response associated with lymphocytes, an initiating event mediated by salivary gland epithelial cell (SGEC) abnormalities causing activation is poorly characterised. Transcriptome studies have suggested alternations in lysosomal function are associated with SS, but a cause and effect linkage has not been established. In this study, we demonstrated that altered lysosome activity in SGECs by expression of lysosome-associated membrane protein 3 (LAMP3) can initiate an autoimmune response with autoantibody production and salivary dysfunction similar to SS.MethodsRetroductal cannulation of the submandibular salivary glands with an adeno-associated virus serotype 2 vector encoding LAMP3 was used to establish a model system. Pilocarpine-stimulated salivary flow and the presence of autoantibodies were assessed at several time points post-cannulation. Salivary glands from the mice were evaluated using RNAseq and histologically.ResultsFollowing LAMP3 expression, saliva flow was significantly decreased and serum anti-Ro/SSA and La/SSB antibodies could be detected in the treated mice. Mechanistically, LAMP3 expression increased apoptosis in SGECs and decreased protein expression related to saliva secretion. Analysis of RNAseq data suggested altered lysosomal function in the transduced SGECs, and that the cellular changes can chemoattract immune cells into the salivary glands. Immune cells were activated via toll-like receptors by damage-associated molecular patterns released from LAMP3-expressing SGECs.ConclusionsThese results show a critical role for lysosomal trafficking in the development of SS and establish a causal relationship between LAMP3 misexpression and the development of SS.

PurposeTo develop a novel method to quantify the amount of fibrosis in the salivary gland and to investigate the relationship between fibrosis and specific symptoms associated with Sjögren’s syndrome (SS) using this method.Materials and MethodsParaffin-embedded labial salivary gland (LSG) slides from 20 female SS patients and their clinical and LSG pathology data were obtained from the Sjögren’s International Collaborative Clinical Alliance. Relative interstitial fibrosis area (RIFA) in Masson’s trichrome-stained LSG sections was quantified from digitally scanned slides and used for correlation analysis. Gene expression levels were assessed by microarray analysis. Core promoter accessibility for RIFA-correlated genes was determined using DNase I hypersensitive sites sequencing analysis.ResultsRIFA was significantly correlated with unstimulated whole saliva flow rate in SS patients. Sixteen genes were significantly and positively correlated with RIFA. In a separate analysis, a group of differentially expressed genes was identified by comparing severe and moderate fibrosis groups. This combined set of genes was distinct from differentially expressed genes identified in lung epithelium from idiopathic pulmonary fibrosis patients compared with controls. Single-cell RNA sequencing analysis of salivary glands suggested most of the RIFA-correlated genes are expressed by fibroblasts in the gland and are in a permissive chromatin state.ConclusionRIFA quantification is a novel method for assessing interstitial fibrosis and the impact of fibrosis on SS symptoms. Loss of gland function may be associated with salivary gland fibrosis, which is likely to be driven by a unique set of genes that are mainly expressed by fibroblasts.

Despite signs of infection, the involvement of the oral cavity in COVID-19 is poorly understood. To address this, single-cell RNA sequencing data-sets were integrated from human minor salivary glands and gingiva to identify 11 epithelial, 7 mesenchymal, and 15 immune cell clusters. Analysis of SARS-CoV-2 viral entry factor expression showed enrichment in epithelia including the ducts and acini of the salivary glands and the suprabasal cells of the mucosae. COVID-19 autopsy tissues confirmed in vivo SARS-CoV-2 infection in the salivary glands and mucosa. Saliva from SARS-CoV-2-infected individuals harbored epithelial cells exhibitingACE2expression and SARS-CoV-2 RNA. Matched nasopharyngeal and saliva samples found distinct viral shedding dynamics and viral burden in saliva correlated with COVID-19 symptoms including taste loss. Upon recovery, this cohort exhibited salivary antibodies against SARS-CoV-2 proteins. Collectively, the oral cavity represents a robust site for COVID-19 infection and implicates saliva in viral transmission.

Background: Prostate-specific membrane antigen (PSMA) has emerged as a promising target for developing radionuclide therapy (RNT) in prostate cancer; however, accumulation of PSMA-RNT in salivary glands can result in irreversible xerostomia. Methods to prevent PSMA-RNT-related xerostomia could be clinically useful; however, little is known about PSMA expression in salivary glands of preclinical animal models. Using [(18)F]DCFPyL autoradiography/biodistribution, PSMA expression levels were determined in salivary glands of various preclinical monkey and rodent species and compared with humans. Methods: Binding affinities (K(d)) and PSMA levels (B(max)) were determined by in vitro [(18)F]DCFPyL autoradiography studies. In vivo rodent tissue uptakes (%ID/g) were determined from [(18)F]DCFPyL biodistributions. Results: [(18)F]DCFPyL exhibited low nanomolar K(d) for submandibular gland (SMG) PSMA across all the species. PSMA levels in human SMG (B(max) = 60.91 nM) were approximately two-fold lower compared with baboon SMG but were two- to three-fold higher than SMG PSMA levels of cynomolgus and rhesus. Rodents had the lowest SMG PSMA levels, with the mouse being 10-fold higher than the rat. In vivo rodent biodistribution studies confirmed these results. Conclusions: SMG of monkeys exhibited comparable PSMA expression to human SMG whereas rodents were lower. However, the results suggest that mice are relatively a better small animal preclinical model than rats for PSMA salivary gland studies.

Significant effort has been applied to identify the genome-wide gene expression profiles associated with salivary gland development and pathophysiology. However, relatively little is known about the regulators that control salivary gland gene expression. We integrated data from DNase1 digital genomic footprinting, RNA-seq, and gene expression microarrays to comprehensively characterize the cis- and trans-regulatory components controlling gene expression of the healthy submandibular salivary gland. Analysis of 32 human tissues and 87 mouse tissues was performed to identify the highly expressed and tissue-enriched transcription factors driving salivary gland gene expression. Following RNA analysis, protein expression levels and subcellular localization of 39 salivary transcription factors were confirmed by immunohistochemistry. These expression analyses revealed that the salivary gland highly expresses transcription factors associated with endoplasmic reticulum stress, human T-cell lymphotrophic virus 1 expression, and Epstein-Barr virus reactivation. DNase1 digital genomic footprinting to a depth of 333,426,353 reads was performed and utilized to generate a salivary gland gene regulatory network describing the genome-wide chromatin accessibility and transcription factor binding of the salivary gland at a single-nucleotide resolution. Analysis of the DNase1 gene regulatory network identified dense interconnectivity among PLAG1, MYB, and 13 other transcription factors associated with balanced chromosomal translocations and salivary gland tumors. Collectively, these analyses provide a comprehensive atlas of the cis- and trans-regulators of the salivary gland and highlight known aberrantly regulated pathways of diseases affecting the salivary glands.

Background Chromatin accessibility profiling assays such as ATAC-seq and DNase1-seq offer the opportunity to rapidly characterize the regulatory state of the genome at a single nucleotide resolution. Optimization of molecular protocols has enabled the molecular biologist to produce next-generation sequencing libraries in several hours, leaving the analysis of sequencing data as the primary obstacle to wide-scale deployment of accessibility profiling assays. To address this obstacle we have developed an optimized and efficient pipeline for the analysis of ATAC-seq and DNase1-seq data. Results We executed a multi-dimensional grid-search on the NIH Biowulf supercomputing cluster to assess the impact of parameter selection on biological reproducibility and ChIP-seq recovery by analyzing 4560 pipeline configurations. Our analysis improved ChIP-seq recovery by 15% for ATAC-seq and 3% for DNase1-seq and determined that PCR duplicate removal improves biological reproducibility by 36% without significant costs in footprinting transcription factors. Our analyses of down sampled reads identified a point of diminishing returns for increased library sequencing depth, with 95% of the ChIP-seq data of a 200 million read footprinting library recovered by 160 million reads. Conclusions We present optimized ATAC-seq and DNase-seq pipelines in both Snakemake and bash formats as well as optimal sequencing depths for ATAC-seq and DNase-seq projects. The optimized ATAC-seq and DNase1-seq analysis pipelines, parameters, and ground-truth ChIP-seq datasets have been made available for deployment and future algorithmic profiling. Electronic supplementary material The online version of this article (10.1186/s12864-018-4943-z) contains supplementary material, which is available to authorized users.

Background Chromatin accessibility profiling assays such as ATAC-seq and DNase1-seq offer the opportunity to rapidly characterize the regulatory state of the genome at a single nucleotide resolution. Optimization of molecular protocols has enabled the molecular biologist to produce next-generation sequencing libraries in several hours, leaving the analysis of sequencing data as the primary obstacle to wide-scale deployment of accessibility profiling assays. To address this obstacle we have developed an optimized and efficient pipeline for the analysis of ATAC-seq and DNase1-seq data. Results We executed a multi-dimensional grid-search on the NIH Biowulf supercomputing cluster to assess the impact of parameter selection on biological reproducibility and ChIP-seq recovery by analyzing 4560 pipeline configurations. Our analysis improved ChIP-seq recovery by 15% for ATAC-seq and 3% for DNase1-seq and determined that PCR duplicate removal improves biological reproducibility by 36% without significant costs in footprinting transcription factors. Our analyses of down sampled reads identified a point of diminishing returns for increased library sequencing depth, with 95% of the ChIP-seq data of a 200 million read footprinting library recovered by 160 million reads. Conclusions We present optimized ATAC-seq and DNase-seq pipelines in both Snakemake and bash formats as well as optimal sequencing depths for ATAC-seq and DNase-seq projects. The optimized ATAC-seq and DNase1-seq analysis pipelines, parameters, and ground-truth ChIP-seq datasets have been made available for deployment and future algorithmic profiling.