Safeguard function of PU.1 shapes the inflammatory epigenome of neutrophils.

Neutrophils are essential first-line defense cells against invading pathogens, yet when inappropriately activated, their strong immune response can cause collateral tissue damage and contributes to immunological diseases. However, whether neutrophils can intrinsically titrate their immune response remains unknown. Here we conditionally deleted the Spi1 gene, which encodes the myeloid transcription factor PU.1, from neutrophils of mice undergoing fungal infection and then performed comprehensive epigenomic profiling. We found that as well as providing the transcriptional prerequisite for eradicating pathogens, the predominant function of PU.1 was to restrain the neutrophil defense by broadly inhibiting the accessibility of enhancers via the recruitment of histone deacetylase 1. Such epigenetic modifications impeded the immunostimulatory AP-1 transcription factor JUNB from entering chromatin and activating its targets. Thus, neutrophils rely on a PU.1-installed inhibitor program to safeguard their epigenome from undergoing uncontrolled activation, protecting the host against an exorbitant innate immune response.

Sustained PU.1 levels balance cell-cycle regulators to prevent exhaustion of adult hematopoietic stem cells.

To provide a lifelong supply of blood cells, hematopoietic stem cells (HSCs) need to carefully balance both self-renewing cell divisions and quiescence. Although several regulators that control this mechanism have been identified, we demonstrate that the transcription factor PU.1 acts upstream of these regulators. So far, attempts to uncover PU.1's role in HSC biology have failed because of the technical limitations of complete loss-of-function models. With the use of hypomorphic mice with decreased PU.1 levels specifically in phenotypic HSCs, we found reduced HSC long-term repopulation potential that could be rescued completely by restoring PU.1 levels. PU.1 prevented excessive HSC division and exhaustion by controlling the transcription of multiple cell-cycle regulators. Levels of PU.1 were sustained through autoregulatory PU.1 binding to an upstream enhancer that formed an active looped chromosome architecture in HSCs. These results establish that PU.1 mediates chromosome looping and functions as a master regulator of HSC proliferation.

CAFE: an R package for the detection of gross chromosomal abnormalities from gene expression microarray data.

SUMMARY: The current methods available to detect chromosomal abnormalities from DNA microarray expression data are cumbersome and inflexible. CAFE has been developed to alleviate these issues. It is implemented as an R package that analyzes Affymetrix *.CEL files and comes with flexible plotting functions, easing visualization of chromosomal abnormalities. AVAILABILITY AND IMPLEMENTATION: CAFE is available from https://bitbucket.org/cob87icW6z/cafe/ as both source and compiled packages for Linux and Windows. It is released under the GPL version 3 license. CAFE will also be freely available from Bioconductor. CONTACT: sander.h.bollen@gmail.com or nancy.mah@mdc-berlin.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Patient listening on social media for patient-focused drug development: a synthesis of considerations from patients, industry and regulators.

Patients, life science industry and regulatory authorities are united in their goal to reduce the disease burden of patients by closing remaining unmet needs. Patients have, however, not always been systematically and consistently involved in the drug development process. Recognizing this gap, regulatory bodies worldwide have initiated patient-focused drug development (PFDD) initiatives to foster a more systematic involvement of patients in the drug development process and to ensure that outcomes measured in clinical trials are truly relevant to patients and represent significant improvements to their quality of life. As a source of real-world evidence (RWE), social media has been consistently shown to capture the first-hand, spontaneous and unfiltered disease and treatment experience of patients and is acknowledged as a valid method for generating patient experience data by the Food and Drug Administration (FDA). While social media listening (SML) methods are increasingly applied to many diseases and use cases, a significant piece of uncertainty remains on how evidence derived from social media can be used in the drug development process and how it can impact regulatory decision making, including legal and ethical aspects. In this policy paper, we review the perspectives of three key stakeholder groups on the role of SML in drug development, namely patients, life science companies and regulators. We also carry out a systematic review of current practices and use cases for SML and, in particular, highlight benefits and drawbacks for the use of SML as a way to identify unmet needs of patients. While we find that the stakeholders are strongly aligned regarding the potential of social media for PFDD, we identify key areas in which regulatory guidance is needed to reduce uncertainty regarding the impact of SML as a source of patient experience data that has impact on regulatory decision making.

Two distinct auto-regulatory loops operate at the PU.1 locus in B cells and myeloid cells.

The transcription factor PU.1 occupies a central role in controlling myeloid and early B-cell development, and its correct lineage-specific expression is critical for the differentiation choice of hematopoietic progenitors. However, little is known of how this tissue-specific pattern is established. We previously identified an upstream regulatory cis element whose targeted deletion in mice decreases PU.1 expression and causes leukemia. We show here that the upstream regulatory cis element alone is insufficient to confer physiologic PU.1 expression in mice but requires the cooperation with other, previously unidentified elements. Using a combination of transgenic studies, global chromatin assays, and detailed molecular analyses we present evidence that PU.1 is regulated by a novel mechanism involving cross talk between different cis elements together with lineage-restricted autoregulation. In this model, PU.1 regulates its expression in B cells and macrophages by differentially associating with cell type-specific transcription factors at one of its cis-regulatory elements to establish differential activity patterns at other elements.

Applications of quantitative social media listening to patient-centric drug development.

Social media listening has been increasingly acknowledged as a tool with applications in many stages of the drug development process. These applications were created to meet the need for patient-centric therapies that are fit-for-purpose and meaningful to patients. Such applications, however, require the leverage of new quantitative approaches and analytical methods that draw from developments in artificial intelligence and real-world data (RWD) analysis. Here, we review the state-of-the-art in quantitative social media listening (QSML) methods applied to drug discovery from the perspective of the pharmaceutical industry.

A Patient-Centered Conceptual Model of Symptoms and Their Impact in Early Parkinson's Disease: A Qualitative Study.

BACKGROUND: Individuals with Parkinson's disease (PD) develop a significant disease burden over time that contributes to a progressive decline in health-related quality of life. There is a paucity of qualitative research to understand symptoms and impacts in individuals with early-stage PD (i.e., Hoehn and Yahr stage 1-2 and ≤2 years since diagnosis). OBJECTIVE: The collection of qualitative data to inform the selection of clinical outcome assessments for clinical trials is advocated by regulators. This patient-centered, multistage study sought to create a conceptual model of symptoms and their impact for individuals with early-stage PD. METHODS: Symptoms and impacts of PD were gathered from a literature review of qualitative research, a quantitative social media listening analysis, and qualitative patient concept elicitation interviews (n = 35). Clinical experts provided input to validate and finalize the concepts. RESULTS: The final conceptual model consisted of 27 symptoms categorized into 'motor' or 'non-motor' domains, and 39 impacts divided into five domains. Most frequently reported symptoms in early-stage PD were 'tremors' (89%), 'stiffness and rigidity', and 'fatigue' (69%, both). Most frequently reported impacts included 'anxiety' (74%), 'eating and drinking' (71%), followed by 'exercise/sport' and 'relationship with family/family life' (66%, both). CONCLUSION: This study provides initial insights relating to the symptom and impact burden of early-stage PD patients. The conceptual model can be used to help researchers to develop and select optimal patient-centered outcomes to measure treatment benefit in clinical trials. These findings could inform future qualitative research and the development of outcomes specifically for early-stage PD patients.

A Neural Network Approach for Understanding Patient Experiences of Chronic Obstructive Pulmonary Disease (COPD): Retrospective, Cross-sectional Study of Social Media Content.

BACKGROUND: The abundance of online content contributed by patients is a rich source of insight about the lived experience of disease. Patients share disease experiences with other members of the patient and caregiver community and do so using their own lexicon of words and phrases. This lexicon and the topics that are communicated using words and phrases belonging to the lexicon help us better understand disease burden. Insights from social media may ultimately guide clinical development in ways that ensure that future treatments are fit for purpose from the patient's perspective. OBJECTIVE: We sought insights into the patient experience of chronic obstructive pulmonary disease (COPD) by analyzing a substantial corpus of social media content. The corpus was sufficiently large to make manual review and manual coding all but impossible to perform in a consistent and systematic fashion. Advanced analytics were applied to the corpus content in the search for associations between symptoms and impacts across the entire text corpus. METHODS: We conducted a retrospective, cross-sectional study of 5663 posts sourced from open blogs and online forum posts published by COPD patients between February 2016 and August 2019. We applied a novel neural network approach to identify a lexicon of community words and phrases used by patients to describe their symptoms. We used this lexicon to explore the relationship between COPD symptoms and disease-related impacts. RESULTS: We identified a diverse lexicon of community words and phrases for COPD symptoms, including gasping, wheezy, mucus-y, and muck. These symptoms were mentioned in association with specific words and phrases for disease impact such as frightening, breathing discomfort, and difficulty exercising. Furthermore, we found an association between mucus hypersecretion and moderate disease severity, which distinguished mucus from the other main COPD symptoms, namely breathlessness and cough. CONCLUSIONS: We demonstrated the potential of neural networks and advanced analytics to gain patient-focused insights about how each distinct COPD symptom contributes to the burden of chronic and acute respiratory illness. Using a neural network approach, we identified words and phrases for COPD symptoms that were specific to the patient community. Identifying patterns in the association between symptoms and impacts deepened our understanding of the patient experience of COPD. This approach can be readily applied to other disease areas.

Mesenchymal stromal cell characteristics vary depending on their origin.

Mesenchymal stromal cells (MSCs) are rare progenitor cells that can be isolated from various tissues. They exhibit multilineage differentiation potential, support regenerative processes, and interact with various immune cells. Therefore, MSCs represent a promising tool for regenerative medicine. However, source-dependent and donor-dependent differences of MSC properties, including implications on their clinical application are still largely unknown. We evaluated MSCs derived from perinatal tissues umbilical cord (UC) and amniotic membrane (AM) in comparison to adult MSCs from bone marrow (BM), which were used as gold standard. We found genetic background-independent differences between MSCs from UC and AM. While AM- and UC-MSCs were closer to each other than to BM-MSCs, they also exhibited differences between each other. AM-MSCs from different donors but not UC-MSCs displayed high interdonor variability. In addition, we show that although all MSCs expressed similar surface markers, MSC populations from UC and AM showed differential profiles of gene expression and paracrine factor secretion to BM-derived MSCs. Notably, pathway analysis of gene expression data revealed intriguing differences between MSCs suggesting that MSCs from UC and AM possess in general a higher potential of immunomodulatory capacity, whereas BM-MSCs showed a higher potential of supporting regenerative processes as exemplified by neuronal differentiation and development. These differences between perinatal and BM-derived MSCs may be relevant for clinical applications.