Evolution of community outreach and engagement at National Cancer Institute-Designated Cancer Centers, an evolving journey.

Cancer mortality rates have declined during the last 28 years, but that process is not equitably shared. Disparities in cancer outcomes by race, ethnicity, socioeconomic status, sexual orientation and gender identity, and geographic location persist across the cancer care continuum. Consequently, community outreach and engagement (COE) efforts within National Cancer Institute-Designated Cancer Center (NCI-DCC) catchment areas have intensified during the last 10 years as has the emphasis on COE and catchment areas in NCI's Cancer Center Support Grant applications. This review article attempts to provide a historic perspective of COE within NCI-DCCs. Improving COE has long been an important initiative for the NCI, but it was not until 2012 and 2016 that NCI-DCCs were required to define their catchment areas rigorously and to provide specific descriptions of COE interventions, respectively. NCI-DCCs had previously lacked adequate focus on the inclusion of historically marginalized patients in cancer innovation efforts. Integrating COE efforts throughout the research and operational aspects of the cancer centers, at both the patient and community levels, will expand the footprint of COE efforts within NCI-DCCs. Achieving this change requires sustained commitment by the centers to adjust their activities and improve access and outcomes for historically marginalized communities.

Unused potential of lipid-lowering therapy in very high-risk patients with atherosclerotic cardiovascular disease. A retrospective data analysis.

BACKGROUND: Atherosclerotic cardiovascular disease (ASCVD) is the most common cause of death in Europe. Although the 2019 European Society of Cardiology/European Atherosclerosis Society Guidelines for the management of dyslipidaemias claim a target low-density lipoprotein cholesterol (LDL-C) value of <55 mg/dL for very high-risk patients by use of lipid-lowering therapy (LLT) and lifestyle adaptations, the target level achievement is not satisfactory. We examined LLT use in ASCVD patients exceeding LDL-C target levels at admission and its adaptations at discharge. METHODS AND RESULTS: Between January 2017 and February 2020, 1091 patients with LDL-C >100 mg/dL and ASCVD defined as diagnosis of angina pectoris (AP, n = 179), acute myocardial infarction (AMI, n = 317), chronic ischemic heart disease (CHD, n = 195), or peripheral artery disease (PAD, n = 400) were extracted from hospital records. LLT use on admission and discharge as well as recommendations on lifestyle and nutrition were analysed. On admission, 51% of the patients were not taking LLT. At discharge, 91% were prescribed statins and 87% were advised on lifestyle adaptation and/or pharmacological treatment. High-intensity statin use at discharge was present in 63% of the AP-group, 92% of the AMI-group, 62% of the CHD-group and 71% of the PAD-group. Ezetimibe was present in 16% and proprotein convertase subtilisin/kexin 9 inhibitors (PCSK9i) in 1%. However, of those on high-intensity statin, 25% remained on insufficient statin dosage. CONCLUSION: Switch to high-intensity statins and use of ezetimibe and PCSK9i was low in chronic ASCVD patients. Even though statin intake was high in high-risk patients, target levels were still not reached.

The Colocation Model in Community Cancer Care: A Description of Patient Clinical and Demographic Attributes and Referral Pathways.

PURPOSE: Cancer disparities are well documented among Black, Indigenous, and People of Color, yet little is known about the characteristics of programs that serve these populations. Integrating specialized cancer care services within community settings is important for addressing the needs of historically marginalized populations. Our National Cancer Institute-Designated Cancer Center initiated a clinical outreach program incorporating cancer diagnostic services and patient navigation within a Federally Qualified Health Center (FQHC) to expedite evaluation and resolution of potential cancer diagnoses with the goal of collaboration between oncology specialists and primary care providers in a historically marginalized community in Boston, MA. MATERIALS AND METHODS: Sociodemographic and clinical characteristics were analyzed from patients who were referred to the program for cancer-related care between January 2012 and July 2018. RESULTS: The majority of patients self-identified as Black (non-Hispanic) followed by Hispanic (Black and White). Twenty-two percent of patients had a cancer diagnosis. Treatment and surveillance plans were established for those with and without cancer at a median time to diagnostic resolution of 12 and 28 days, respectively. The majority of patients presented with comorbid health conditions. There was a high prevalence of self-reported financial distress among patients seeking care through this program. CONCLUSION: These findings highlight the wide spectrum of cancer care concerns in historically marginalized communities. This review of the program suggests that integrating cancer evaluation services within community-based primary health care settings offers promise for enhancing the coordination and delivery of cancer diagnostic services among historically marginalized populations and could be a method to address clinical access disparities.

Parallel evolutionary paths to produce more than one Pseudomonas aeruginosa biofilm phenotype.

Studying parallel evolution of similar traits in independent within-species lineages provides an opportunity to address evolutionary predictability of molecular changes underlying adaptation. In this study, we monitored biofilm forming capabilities, motility, and virulence phenotypes of a plethora of phylogenetically diverse clinical isolates of the opportunistic pathogen Pseudomonas aeruginosa. We also recorded biofilm-specific and planktonic transcriptional responses. We found that P. aeruginosa isolates could be stratified based on the production of distinct organismal traits. Three major biofilm phenotypes, which shared motility and virulence phenotypes, were produced repeatedly in several isolates, indicating that the phenotypes evolved via parallel or convergent evolution. Of note, while we found a restricted general response to the biofilm environment, the individual groups of biofilm phenotypes reproduced biofilm transcriptional profiles that included the expression of well-known biofilm features, such as surface adhesive structures and extracellular matrix components. Our results provide insights into distinct ways to make a biofilm and indicate that genetic adaptations can modulate multiple pathways for biofilm development that are followed by several independent clinical isolates. Uncovering core regulatory pathways that drive biofilm-associated growth and tolerance towards environmental stressors promises to give clues to host and environmental interactions and could provide useful targets for new clinical interventions.

The Core Proteome of Biofilm-Grown Clinical Pseudomonas aeruginosa Isolates.

Comparative genomics has greatly facilitated the identification of shared as well as unique features among individual cells or tissues, and thus offers the potential to find disease markers. While proteomics is recognized for its potential to generate quantitative maps of protein expression, comparative proteomics in bacteria has been largely restricted to the comparison of single cell lines or mutant strains. In this study, we used a data independent acquisition (DIA) technique, which enables global protein quantification of large sample cohorts, to record the proteome profiles of overall 27 whole genome sequenced and transcriptionally profiled clinical isolates of the opportunistic pathogen Pseudomonas aeruginosa. Analysis of the proteome profiles across the 27 clinical isolates grown under planktonic and biofilm growth conditions led to the identification of a core biofilm-associated protein profile. Furthermore, we found that protein-to-mRNA ratios between different P. aeruginosa strains are well correlated, indicating conserved patterns of post-transcriptional regulation. Uncovering core regulatory pathways, which drive biofilm formation and associated antibiotic tolerance in bacterial pathogens, promise to give clues to interactions between bacterial species and their environment and could provide useful targets for new clinical interventions to combat biofilm-associated infections.

BACTOME-a reference database to explore the sequence- and gene expression-variation landscape of Pseudomonas aeruginosa clinical isolates.

Extensive use of next-generation sequencing (NGS) for pathogen profiling has the potential to transform our understanding of how genomic plasticity contributes to phenotypic versatility. However, the storage of large amounts of NGS data and visualization tools need to evolve to offer the scientific community fast and convenient access to these data. We introduce BACTOME as a database system that links aligned DNA- and RNA-sequencing reads of clinical Pseudomonas aeruginosa isolates with clinically relevant pathogen phenotypes. The database allows data extraction for any single isolate, gene or phenotype as well as data filtering and phenotypic grouping for specific research questions. With the integration of statistical tools we illustrate the usefulness of a relational database structure for the identification of phenotype-genotype correlations as an essential part of the discovery pipeline in genomic research. Furthermore, the database provides a compilation of DNA sequences and gene expression values of a plethora of clinical isolates to give a consensus DNA sequence and consensus gene expression signature. Deviations from the consensus thereby describe the genomic landscape and the transcriptional plasticity of the species P. aeruginosa. The database is available at https://bactome.helmholtz-hzi.de.

Unravelling post-transcriptional PrmC-dependent regulatory mechanisms in Pseudomonas aeruginosa.

Transcriptional regulation has a central role in cellular adaptation processes and is well investigated. In contrast, the importance of the post-transcriptional regulation on these processes is less well defined. The technological advancements have been critical to precisely quantify protein and mRNA level changes and hold promise to provide more insights into how post-transcriptional regulation determines phenotypes. In Pseudomonas aeruginosa the methyltransferase PrmC methylates peptide chain release factors to facilitate translation termination. Loss of PrmC activity abolishes anaerobic growth and leads to reduced production of quorum sensing-associated virulence factors. Here, by applying SILAC technology in combination with mRNA-sequencing, they provide evidence that the P. aeruginosa phenotype can be attributed to a change in protein to mRNA ratios of selected protein groups. The UAG-dependent translation termination was more dependent on PrmC activity than the UAA- and UGA-dependent translation termination. Additionally, a bias toward UAG stop codons in global transcriptional regulators was found. The finding that this bias in stop codon usage determines the P. aeruginosa phenotype is unexpected and adds complexity to regulatory circuits. Via modulation of PrmC activity the bacterial cell can cross-regulate targets independently of transcriptional signals, a process with an underestimated impact on the bacterial phenotype.

Transcriptome Profiling of Antimicrobial Resistance in Pseudomonas aeruginosa.

Emerging resistance to antimicrobials and the lack of new antibiotic drug candidates underscore the need for optimization of current diagnostics and therapies to diminish the evolution and spread of multidrug resistance. As the antibiotic resistance status of a bacterial pathogen is defined by its genome, resistance profiling by applying next-generation sequencing (NGS) technologies may in the future accomplish pathogen identification, prompt initiation of targeted individualized treatment, and the implementation of optimized infection control measures. In this study, qualitative RNA sequencing was used to identify key genetic determinants of antibiotic resistance in 135 clinical Pseudomonas aeruginosa isolates from diverse geographic and infection site origins. By applying transcriptome-wide association studies, adaptive variations associated with resistance to the antibiotic classes fluoroquinolones, aminoglycosides, and ß-lactams were identified. Besides potential novel biomarkers with a direct correlation to resistance, global patterns of phenotype-associated gene expression and sequence variations were identified by predictive machine learning approaches. Our research serves to establish genotype-based molecular diagnostic tools for the identification of the current resistance profiles of bacterial pathogens and paves the way for faster diagnostics for more efficient, targeted treatment strategies to also mitigate the future potential for resistance evolution.

Deep transcriptome profiling of clinical Klebsiella pneumoniae isolates reveals strain and sequence type-specific adaptation.

Health-care-associated infections by multi-drug-resistant bacteria constitute one of the greatest challenges to modern medicine. Bacterial pathogens devise various mechanisms to withstand the activity of a wide range of antimicrobial compounds, among which the acquisition of carbapenemases is one of the most concerning. In Klebsiella pneumoniae, the dissemination of the K. pneumoniae carbapenemase is tightly connected to the global spread of certain clonal lineages. Although antibiotic resistance is a key driver for the global distribution of epidemic high-risk clones, there seem to be other adaptive traits that may explain their success. Here, we exploited the power of deep transcriptome profiling (RNA-seq) to shed light on the transcriptomic landscape of 37 clinical K. pneumoniae isolates of diverse phylogenetic origins. We identified a large set of 3346 genes which was expressed in all isolates. While the core-transcriptome profiles varied substantially between groups of different sequence types, they were more homogenous among isolates of the same sequence type. We furthermore linked the detailed information on differentially expressed genes with the clinically relevant phenotypes of biofilm formation and bacterial virulence. This allowed for the identification of a diminished expression of biofilm-specific genes within the low biofilm producing ST258 isolates as a sequence type-specific trait.

The Pseudomonas aeruginosa Transcriptional Landscape Is Shaped by Environmental Heterogeneity and Genetic Variation.

UNLABELLED: Phenotypic variability among bacteria depends on gene expression in response to different environments, and it also reflects differences in genomic structure. In this study, we analyzed transcriptome sequencing (RNA-seq) profiles of 151 Pseudomonas aeruginosa clinical isolates under standard laboratory conditions and of one P. aeruginosa type strain under 14 different environmental conditions. Our approach allowed dissection of the impact of the genetic background versus environmental cues on P. aeruginosa gene expression profiles and revealed that phenotypic variation was larger in response to changing environments than between genomically different isolates. We demonstrate that mutations within the global regulator LasR affect more than one trait (pleiotropy) and that the interaction between mutations (epistasis) shapes the P. aeruginosa phenotypic plasticity landscape. Because of pleiotropic and epistatic effects, average genotype and phenotype measures appeared to be uncorrelated in P. aeruginosa. IMPORTANCE: This work links experimental data of unprecedented complexity with evolution theory and delineates the transcriptional landscape of the opportunistic pathogen Pseudomonas aeruginosa. We found that gene expression profiles are most strongly influenced by environmental cues, while at the same time the transcriptional profiles were also shaped considerably by genetic variation within global regulators. The comprehensive set of transcriptomic and genomic data of more than 150 clinical P. aeruginosa isolates will be made publically accessible to all researchers via a dedicated web interface. Both Pseudomonas specialists interested in expression and regulation of specific genes and researchers from other fields with more global interest in the phenotypic and genotypic variation of this important model species can access all information on various levels of detail.

In vivo mRNA profiling of uropathogenic Escherichia coli from diverse phylogroups reveals common and group-specific gene expression profiles.

mRNA profiling of pathogens during the course of human infections gives detailed information on the expression levels of relevant genes that drive pathogenicity and adaptation and at the same time allows for the delineation of phylogenetic relatedness of pathogens that cause specific diseases. In this study, we used mRNA sequencing to acquire information on the expression of Escherichia coli pathogenicity genes during urinary tract infections (UTI) in humans and to assign the UTI-associated E. coli isolates to different phylogenetic groups. Whereas the in vivo gene expression profiles of the majority of genes were conserved among 21 E. coli strains in the urine of elderly patients suffering from an acute UTI, the specific gene expression profiles of the flexible genomes was diverse and reflected phylogenetic relationships. Furthermore, genes transcribed in vivo relative to laboratory media included well-described virulence factors, small regulatory RNAs, as well as genes not previously linked to bacterial virulence. Knowledge on relevant transcriptional responses that drive pathogenicity and adaptation of isolates to the human host might lead to the introduction of a virulence typing strategy into clinical microbiology, potentially facilitating management and prevention of the disease. Importance: Urinary tract infections (UTI) are very common; at least half of all women experience UTI, most of which are caused by pathogenic Escherichia coli strains. In this study, we applied massive parallel cDNA sequencing (RNA-seq) to provide unbiased, deep, and accurate insight into the nature and the dimension of the uropathogenic E. coli gene expression profile during an acute UTI within the human host. This work was undertaken to identify key players in physiological adaptation processes and, hence, potential targets for new infection prevention and therapy interventions specifically aimed at sabotaging bacterial adaptation to the human host.

The extensive set of accessory Pseudomonas aeruginosa genomic components.

Up to 20% of the chromosomal Pseudomonas aeruginosa DNA belong to the so-called accessory genome. Its elements are specific for subgroups or even single strains and are likely acquired by horizontal gene transfer (HGT). Similarities of the accessory genomic elements to DNA from other bacterial species, mainly the DNA of γ- and ß-proteobacteria, indicate a role of interspecies HGT. In this study, we analysed the expression of the accessory genome in 150 clinical P. aeruginosa isolates as uncovered by transcriptome sequencing and the presence of accessory genes in eleven additional isolates. Remarkably, despite the large number of P. aeruginosa strains that have been sequenced to date, we found new strain-specific compositions of accessory genomic elements and a high portion (10-20%) of genes without P. aeruginosa homologues. Although some genes were detected to be expressed/present in several isolates, individual patterns regarding the genes, their functions and the possible origin of the DNA were widespread among the tested strains. Our results demonstrate the unaltered potential to discover new traits within the P. aeruginosa population and underline that the P. aeruginosa pangenome is likely to increase with increasing sequence information.