Unbiased Approach Research Articles

Handling of missing component information for common composite score outcomes used in axial spondyloarthritis research when complete-case analysis is unbiased

BackgroundObservational data on composite scores often comes with missing component information. When a complete-case (CC) analysis of composite scores is unbiased, preferable approaches of dealing with missing component information should also be unbiased and provide a more precise estimate. We assessed the performance of several methods compared to CC analysis in estimating the means of common composite scores used in axial spondyloarthritis research.MethodsIndividual mean imputation (IMI), the modified formula method (MF), overall mean imputation (OMI), and multiple imputation of missing component values (MI) were assessed either analytically or by means of simulations from available data collected across Europe. Their performance in estimating the means of the Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), the Bath Ankylosing Spondylitis Functional Index (BASFI), and the Ankylosing Spondylitis Disease Activity Score based on C-reactive protein (ASDAS-CRP) in cases where component information was set missing completely at random was compared to the CC approach based on bias, variance, and coverage.ResultsLike the MF method, IMI uses a modified formula for observations with missing components resulting in modified composite scores. In the case of an unbiased CC approach, these two methods yielded representative samples of the distribution arising from a mixture of the original and modified composite scores, which, however, could not be considered the same as the distribution of the original score. The IMI and MF method are, thus, intrinsically biased. OMI provided an unbiased mean but displayed a complex dependence structure among observations that, if not accounted for, resulted in severe coverage issues. MI improved precision compared to CC and gave unbiased means and proper coverage as long as the extent of missingness was not too large.ConclusionsMI of missing component values was the only method found successful in retaining CC’s unbiasedness and in providing increased precision for estimating the means of BASDAI, BASFI, and ASDAS-CRP. However, since MI is susceptible to incorrect implementation and its performance may become questionable with increasing missingness, we consider the implementation of an error-free CC approach a valid and valuable option.Trial registrationNot applicable as study uses data from patient registries.

Teaching Academic Writing Skills: A Narrative Literature Review of Unifying Academic Values through Academic Integrity

Academic integrity continues to concern educators worldwide. Furthermore, general guidelines for ensuring academic integrity do not seem to encompass all the angles that are required to be taken into consideration when exploring the factors that contribute to multicultural students’ decision to adhere to the norms and values of academic integrity. This literature review focuses on how academic values can be unified through academic integrity, and specifically explores factors and perspectives of utilising academic integrity to unify academic values when teaching academic writing. The dimensions of academic values explored in this paper are: a) beliefs and attitudes of multicultural undergraduate students and the theory of planned behaviour (TPB), b) the value of academic performance in academic writing classes, c) exploring the development of multicultural students’ authorial voice while maintaining academic integrity, and d) using technology to encourage academic integrity in academic writing classes. Over 56 identified sources were chosen carefully to ensure unbiased approaches to the issues of academic integrity and development of academic writing skills. The authors explored the issues from a variety of perspectives. The gap noticed in the review of literature is the disconnection between academic values and academic integrity. The authors make recommendations for future research.

Aortic Valve Calcification Is Induced by the Loss of ALDH1A1 and Can Be Prevented by Agonists of Retinoic Acid Receptor Alpha: Preclinical Evidence for Drug Repositioning.

To date, the only effective treatment of severe aortic stenosis is valve replacement. With the introduction of transcatheter aortic valve replacement and extending indications to younger patients, the use of bioprosthetic valves (BPVs) has considerably increased. The main inconvenience of BPVs is their limited durability because of mechanisms similar as the fibro-calcifying processes observed in native aortic stenosis. One of the major gaps of the field is to identify therapeutic targets to prevent or slow the fibro-calcifying process leading to severe and symptomatic aortic stenosis. The aim was to identify new targets for anticalcification drugs to prevent aortic and BPV calcification using an unbiased translational approach. Explanted valves were collected from patients and organ donor hearts. A comparative transcriptomic analysis was performed on valvular interstitial cells (VIC) obtained from calcified (bicuspid and tricuspid) versus control valves. The mechanisms and consequences of aldehyde dehydrogenase 1 family member A1 (ALDH1A1) downregulation were analyzed in VIC cultures from control human aortic valves. ALDH1A1 was inhibited or silenced and its impact on osteogenic marker expression and calcification processes assessed in VIC. The effect of all-trans retinoic acid on calcification was tested on human VIC cultures and on 2 animal models: the model of subcutaneous implantation of bovine pericardium in rats and the model of xenograft aortic valve replacement in juvenile sheep. Transcriptome analysis of human VIC identified ALDHA1 as the most downregulated gene in VIC from calcified versus control valves. In human VIC, ALDH1A1 expression is downregulated by TGF-β1 in a SMAD2/3-dependent manner. ALDH1A1 inhibition promotes an osteoblast-like VIC phenotype and increases calcium deposition through inhibition of retinoic acid receptor alpha signaling. Conversely, VIC treatment with retinoids decreases calcium deposition and attenuates VIC osteoblast activity. Last, all-trans retinoic acid inhibits calcification development of aortic BPV in both in vivo models and improves aortic valve echocardiographic parameters in the xenograft sheep model. These results show that ALDH1A1 is downregulated in calcified valves, hence promoting VIC transition into an osteoblastic phenotype. Retinoic acid receptor alpha agonists, including all-trans retinoic acid through a drug repositioning strategy, represent a promising and innovative pharmacological approach to prevent calcification of native aortic valves and BPV.

A deficiency screen of the X chromosome for Rap1 GTPase dominant interacting genes in Drosophila border cell migration.

Collective cell migration is critical to embryonic development, wound healing, and the immune response, but also drives tumor dissemination. Understanding how cell collectives coordinate migration in vivo has been a challenge, with potential therapeutic benefits that range from addressing developmental defects to designing targeted cancer treatments. The small GTPase Rap1 has emerged as a regulator of both embryogenesis and cancer cell migration. How active Rap1 coordinates downstream signaling functions required for coordinated collective migration is poorly understood. Drosophila border cells undergo a stereotyped and genetically tractable in vivo migration within the developing egg chamber of the ovary. This group of 6-8 cells migrates through a densely packed tissue microenvironment and serves as an excellent model for collective cell migration during development and disease. Rap1, like all small GTPases, has distinct activity state switches that link extracellular signals to organized cell behaviors. Proper regulation of Rap1 activity is essential for successful border cell migration yet the signaling partners and other downstream effectors are poorly characterized. Using the known requirement for Rap1 in border cell migration, we conducted a dominant suppressor screen for genes whose heterozygous loss modifies the migration defects observed upon constitutively active Rap1V12 expression. Here we identified seven genomic regions on the X chromosome that interact with Rap1V12. We mapped three genomic regions to single Rap1-interacting genes, frizzled 4, Ubiquitin specific protease 16/45, and strawberry notch. Thus, this unbiased screening approach identified multiple new candidate regulators of Rap1 activity with roles in collective border cell migration.

Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour

With the ever-increasing complexity of microscopy modalities, it is imperative to have computational workflows that enable researchers to process and perform in-depth quantitative analysis of the resulting images. However, workflows that allow flexible, interactive and intuitive analysis from raw images to analysed data are lacking for many experimental use-cases. Notably, integrated software solutions for analysis of complex 3D and live cell images are sorely needed. To address this, we present Cecelia, a toolbox that integrates various open-source packages into a coherent data management suite to make quantitative multidimensional image analysis accessible for non-specialists. We describe the application of Cecelia to several immunologically relevant scenarios and the development of an unbiased approach to distinguish dynamic cell behaviours from live imaging data. Cecelia is available as a software package with a Shiny app interface (https://github.com/schienstockd/cecelia). We envision that this framework and its approaches will be of broad use for biological researchers.

Abstract B005: Identification of tumor-reactive TILs from lung cancer organoids co-culture through ruthenium-based proximity labeling

Abstract Tumor-reactive T cells are crucial for the success of tumor-infiltrating lymphocyte (TIL) therapies. Currently, identifying tumor-reactive T cells and their corresponding TCRs typically relies on pre-characterized tumor antigens. Many solid tumors, including lung cancer, exhibit considerable heterogeneity and consequently possess diverse tumor antigenic profiles. Markers such as PD-1 and CD39 are commonly used to identify tumor-reactive TILs, yet these empirically derived markers can produce false positives or fail to capture rare tumor-reactive populations. We here used an unbiased ruthenium-based photocatalytic proximity labeling approach to do co-culture of TILs derived from lung cancer and autologous tumor organoids to identify and validate tumor-specific T cells and their TCRs in six NSCLC samples. We found that labeled TILs were significantly enriched for tumor antigen-reactive T cells, which could be readily separated from bystander T cells via flow cytometry. Single-cell TCR and RNA sequencing revealed that labeled TILs, in contrast to bystander TILs, exhibited a distinct TCR repertoire and transcriptional profile, characterized by effector cytotoxic and activation signatures with partial expression of exhausted T cell markers. We selected the top 10 CD8+ TCR clones with the highest labeling intensity and assessed the reactivity of their corresponding TCR-transduced, CD8-overexpressing Jurkat cells against autologous organoids. We identified 5 novel tumor antigen-reactive TCRs that demonstrated tumor responsiveness and these T cells displayed a mixed transcriptional profile, including hallmark markers of exhaustion. Additionally, we identified clonally expanded, cytotoxic CD4+ T cell states within the labeled TILs that could kill autologous tumors in an MHC class II-dependent and/or Fas-FasL-dependent manner. The ruthenium-based photocatalytic proximity labeling approach, which requires no gene editing, enables identification of tumor-reactive TILs and TCRs independent of specific antigen/HLA contexts. This platform, especially when combined with organoid technology, has the potential to streamline the development of personalized TIL and TCR-T cell therapies. Citation Format: Weilei Hu, Yifei Bian, Zihan Zhao, Shian Ouyang, Jie P. Li, Hongbin Ji. Identification of tumor-reactive TILs from lung cancer organoids co-culture through ruthenium-based proximity labeling [abstract]. In: Proceedings of the AACR IO Conference: Discovery and Innovation in Cancer Immunology: Revolutionizing Treatment through Immunotherapy; 2025 Feb 23-26; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Immunol Res 2025;13(2 Suppl):Abstract nr B005.

Phenotypic clustering in tuberous sclerosis complex reveals four distinct disease trajectories.

Tuberous sclerosis complex (TSC) is a phenotypically heterogeneous autosomal dominant epilepsy, neuropsychiatric, and tumoral predisposition disease, occurring due to germline variants in the TSC1 or TSC2 genes. Despite an improving understanding of the varied phenotypes TSC may present with, there remains an incomplete understanding of the disease trajectory and genotype-phenotype relationship in this disorder. We sought to examine whether an unbiased clustering approach could uncover subgroups of disease trajectories in TSC and enhance understanding of genotype-phenotype correlation. In this observational, prospective, multicentre natural history cohort of patients with confirmed diagnosis of TSC (TSC Alliance Natural History Database), data collected from 2006 - 2022 was used to identify groups of co-occurring phenotypes. This was a multicentre study involving 18 TSC clinical network centres in the US. 947 individuals were included, all of whom had a clinical diagnosis of tuberous sclerosis complex. Each patient was required to have complete characterization of 29 phenotype features associated with TSC. The primary outcomes were consensus clusters of clinical features defining subgroups of patients with TSC and their association with genotype. 947 individuals (50% male) across the TSC Alliance Natural History Database were included in this study, and 29 clinical features were used to define clusters of phenotypes to define disease trajectories. Four reproducible and distinct disease subgroups were identified: angiomyolipoma-predominant TSC (cluster 1), TSC with infantile spasms (cluster 2), neuropsychiatric TSC (cluster 3), and a milder phenotype of TSC (cluster 4). Variants in the rho domain of hamartin and the TSC1 binding domain of tuberin preferentially associated with cluster 1, with increased likelihood of angiomyolipomas, dermatologic findings, and subependymal giant cell astrocytoma. Four distinct disease subgroups exist in TSC and differentially associate with variant location, informing deep genotype-phenotype correlation in TSC with potential impact in personalizing disease surveillance, treatment, and clinical trial endpoint choice. Additional prospective data are needed to confirm these findings.

Extensive location bias of the GPCR-dependent translatome via site-selective activation of mTOR

G protein-coupled receptors (GPCRs) modulate various physiological functions by rewiring cellular gene expression in response to extracellular signals. Control of gene expression by GPCRs has been studied almost exclusively at the transcriptional level, neglecting an extensive amount of regulation that takes place translationally. Hence, little is known about the nature and mechanisms of gene-specific posttranscriptional regulation downstream of receptor activation. Here, we apply an unbiased multiomics approach to delineate an extensive translational regulatory program initiated by the prototypical beta2-adrenergic receptor (β2-AR) and provide mechanistic insights into how these processes are orchestrated. Using ribosome profiling (Ribo-seq), we identify nearly 120 gene targets of adrenergic receptor activity for which expression is exclusively regulated at the level of translation. We next show that all translational changes are induced selectively by endosomal β2-ARs and report that this proceeds through activation of the mammalian target of rapamycin (mTOR) pathway. Specifically, within the set of translational GPCR targets, we find significant enrichment of genes with 5' terminal oligopyrimidine (TOP) motifs, a gene class classically known to be translationally regulated by mTOR. We then demonstrate that endosomal β2-ARs are required for mTOR activation and subsequent mTOR-dependent TOP mRNA translation. This site-selective crosstalk between the pathways is observed in multiple cell models with native β2-ARs, across a range of endogenous and synthetic adrenergic agonists, and for other GPCRs with intracellular activity. Together, this comprehensive analysis of drug-induced translational regulation establishes a critical role for location-biased GPCR signaling in fine-tuning the cellular protein landscape.

Genetic risk variants implicate impaired maintenance and repair of periodontal tissues as causal for periodontitis-A synthesis of recent findings.

Periodontitis is a complex inflammatory disease in which the host genome, in conjunction with extrinsic factors, determines susceptibility and progression. Genetic predisposition is the strongest risk factor in the first decades of life. As people age, chronic exposure to the periodontal microbiome puts a strain on the proper maintenance of barrier function. This review summarizes our current knowledge on genetic risk factors implicated in periodontitis, derived (i) from hypothesis-free systematic whole genome-profiling studies (genome-wide association studies [GWAS] and quantitative trait loci [QTL] mapping studies), and independently validated through further unbiased approaches; (ii) from monogenic and oligogenic forms of periodontitis; and (iii) from syndromic forms of periodontitis. The genes include, but are not limited to, SIGLEC5, PLG, ROBO2, ABCA1, PF4, and CTSC. Notably, CTSC and PLG gene mutations were also identified in non-syndromic and syndromic forms of prepubertal and early-onset periodontitis. The functions of the identified genes in this review suggest that the pathways affected by the periodontitis-associated gene variants converge in functions involved in the maintenance and repair of structural integrity of the periodontal tissues. Particularly, these genes play a role in the healing of inflamed and ulcerated periodontal tissues, including roles in fibrinolysis, extrusion of cellular debris, extracellular matrix remodeling and angiogenesis. Syndromes that include periodontitis in their phenotype indicate that neutrophils play an important role in the regulation of inflammation in the periodontium. The established genetic susceptibility genes therefore collectively provide new insights into the molecular mechanisms and plausible causal factors underlying periodontitis.

Deep Sequencing of Crohn's Disease Lamina Propria Phagocytes Identifies Pathobionts and Correlates With Pro-Inflammatory Gene Expression.

Crohn's disease (CD) is characterized by an inflammatory response to gut microbiota. Macrophages and dendritic cells play an active role in CD inflammation. Specific microbiota have been implicated in the pathogenesis of ileal CD. We investigated the phagocyte-associated microbiome using an unbiased sequencing approach to identify potential pathobionts and elucidate the host response to these microbes. We collected ileal and colonic mucosal biopsies from CD patients and controls without inflammatory bowel disease (IBD), isolated lamina propria phagocytes (CD11b+ cells), and performed deep RNA sequencing (n = 37). Reads were mapped to the human genome for host gene expression analysis and a prokaryotic database for microbiome taxonomic and metatranscriptomic profiling. Results were confirmed in a second IBD cohort (n = 17). Lysed lamina propria cells were plated for bacterial culturing; isolated colonies underwent whole genome sequencing (n = 11). Crohn's disease ileal phagocytes contained higher relative abundances of Escherichia coli, Ruminococcus gnavus, and Enterocloster spp. than those from controls. CD phagocyte-associated microbes had increased expression of lipopolysaccharide (LPS) biosynthesis pathways. Phagocytes with a higher pathobiont burden showed increased expression of pro-inflammatory and antimicrobial genes, including PI3 (antimicrobial peptide) and BPIFB1 (LPS-binding molecule). E. coli isolated from the CD lamina propria had more flagellar motility and antibiotic resistance genes than control-derived strains. Lamina propria resident phagocytes harbor bacterial strains that may act as pathobionts in CD. Our findings shed light on the role of pathobionts and the immune response in CD pathogenesis and suggest new targets for therapies.

Loss of Cathepsin K impairs collagen biogenesis and enhances actin polymerization in trabecular meshwork.

Trabecular meshwork (TM) dysfunction and extracellular matrix (ECM) dysregulation contribute to increased intraocular pressure (IOP) in primary open-angle glaucoma (POAG). Earlier, we provide a proof-of-concept study identifying the regulation and the role of Cathepsin K (CTSK), a potent collagenase, in ECM homeostasis, actin bundling, and IOP regulation. Better understanding of the loss of CTSK function in TM remains unclear. Using siRNA-mediated knockdown of CTSK (siCTSK) in human TM cells, this study investigated the role of CTSK in actin and ECM homeostasis using an unbiased proteomics approach. Loss of CTSK significantly disrupted collagen biogenesis and ECM homeostasis. CTSK depletion also increased intracellular calcium levels, with proteomics data suggesting possible involvement of calcium-regulatory proteins. Additionally, PRKD1 activation enhanced actin polymerization through the LIMK1/SSH1/cofilin pathway, promoting focal adhesion maturation. Despite increased apoptotic markers (CASP3, CASP7, TRADD, PPM1F), caspase 3/7 activation was not induced, suggesting apoptosis-independent cellular remodeling. Notably, RhoQ and myosin motor proteins were significantly downregulated, indicating altered mechanotransduction in TM cells. These findings highlight the role of CTSK in maintaining ECM homeostasis, calcium signaling, and cytoskeletal regulation in TM. Its depletion induces actin polymerization, which may influence aqueous humor outflow. Targeting CTSK-related pathways may provide novel therapeutic strategies for regulating IOP and preventing glaucoma progression.

CD4 + Mucosal-associated Invariant T (MAIT) cells express highly diverse T cell receptors.

Mucosal-associated invariant T cells are highly conserved innate-like T cells in mammals recognized for their high baseline frequency in human blood and cytotoxic effector functions during infectious diseases, autoimmunity, and cancer. While the majority of these cells express a conserved CD8αβ+ TRAV1-2 T cell receptor recognizing microbially-derived Vitamin B2 intermediates presented by the evolutionarily conserved major histocompatibility complex I-related molecule, MR1, there is an emerging appreciation for diverse subsets that may be selected for in humans with distinct functions, including subpopulations that co-express CD4. Prior work has not examined T cell receptor (TCR) heterogeneity in CD4 + MAIT cells, largely due to bias of identifying human MAIT cells as CD8 + TRAV1-2 + cells. In this study, we adopted an unbiased single-cell TCR-sequencing approach of total MR1-5-OP-RU-tetramer-reactive T cells and discovered that CD4 + MAIT cells express highly diverse TRAV1-2 negative TCRs. To specifically characterize this TCR repertoire, we analyzed VDJ sequences of single MR1-5-OP-RU tetramer + MAIT cells across two datasets and identified distinct TCR usage among CD4 + MAIT cells including TRAV21, TRAV8 (TRAV8-1, TRAV8-2, TRAV8-3), and TRAV12 families (TRAV12-2, TRAV12-3), as well as more variable J chain and CDR3 sequences. Non-TRAV1-2 MAIT cell TCRs were also enriched after in vitro expansion, including with Mycobacterial tuberculosis . These results indicate that mature human CD4 + MAIT cells adopt distinct TCR usage from the canonical TRAV1-2 + CD8 + subset and suggest that alternative MR1 ligands in addition to riboflavin intermediates may select them.

Optimized framework for evaluating F3 transgressive segregants in cayenne pepper

Developing F3 transgenic segregants has significant potential to improve cayenne pepper varieties. However, current evaluation methods are often inconsistent and inaccurate, hindering the identification of effective traits. Traditional approaches only focus on a few aspects, thus not covering the full potential performance of the genotype. Utilizing morphometric image processing and categorical parameter assessment can fill the gap of traditional approaches to improving accuracy and objectivity in evaluation. In addition, environmental factors affecting the evaluation process are not adequately considered, making the results unreliable. Therefore, a systematic evaluation framework integrating morphometric analysis, categorical assessment, and environmental correction is essential for optimizing F3 cayenne transgressive segregants. The study aims to develop a synchronized assessment and selection approach based on agronomic, fruit morphometric, and categorical traits in evaluating F3 cayenne transgressive segregants. This research was designed with a randomized completed block design with 16 transgressive segregant genotypes and three check varieties. Each genotype was repeated three times, resulting in 57 experimental units. Based on the results of this study, quantitative and categorical indices could be used to selectively and systematically evaluate potential transgressive segregants in F3 cayenne peppers. The quantitative index is formed from outcome selection criteria, number of productive branches, area, and major axes weighted through an unbiased linear estimation approach, heritability, and best path analysis. Seven genotypes demonstrated superior transgressive performance based on quantitative indices, with G10.9.2, G10.7.1, and G6.8.5 excelling in both agronomic traits and categorical evaluations. These lines can be recommended for yield evaluation and hybrid cross-parents.

Molecular basis of proton sensing by G protein-coupled receptors.

Molecular basis of proton sensing by G protein-coupled receptors.

Generalizable Prediction of Alzheimer Disease Pathologies with a Scalable Annotation Tool and an High-Accuracy Model.

Characterizing the cardinal neuropathologies in Alzheimer disease (AD) can be laborious, time consuming, and susceptible to intra- and inter-observer variability. The lack of high throughput unbiased approaches to reliably assess neuropathology hampers efforts to use pathology as a means to link clinical features of AD to molecular pathogenesis in the ever-growing datasets of persons with AD. To remove this roadblock, we designed an annotation tool in addition to a computational pipeline to analyze digital microscopic images of postmortem tissue from persons with AD in a fully automated and unbiased manner in only a fraction of the time taken with conventional approaches and allows neuropathological analyses and lesion quantification at multiple scales. The pipeline includes a Mask Regional-Convolutional Neural Network (Mask R-CNN) we trained to detect, classify, and segment different types of amyloid. To establish ground truth for training and validation, we utilized an existing open source platform, QuPath, and developed a tool to collect consensus annotations of neuropathology experts. The Mask R-CNN identified amyloid pathology in samples (with accuracy: 94.6%, F1: 87.7%, Dice: 81.8%) unrelated to the training dataset, indicating that it detects generalizable pathology features. Its quantitative measurements of amyloid pathology on 298 samples correlated with the severity of AD neuropathology assessed by experts and neuropathologists (CERAD ratings) and estimates of cognitive compromise (Clinical Dementia Ratings (CDR)). Our computational pipeline should enable rapid, unbiased, inexpensive, quantitative, and comprehensive neuropathological analysis of large tissue collections and integration with orthogonal clinical and multi-omic measurements.

Predicting Who Grade in Meningioma Surgery: Development of an Unbiased Variable Selection and Validation Approach Using Preoperative Clinical and Radiographic Data

Predicting Who Grade in Meningioma Surgery: Development of an Unbiased Variable Selection and Validation Approach Using Preoperative Clinical and Radiographic Data

Comprehensive multi-omics analyses exposes a precision therapy strategy that targets replication stress in hepatocellular carcinoma using WEE1 inhibition.

Comprehensive multi-omics analyses exposes a precision therapy strategy that targets replication stress in hepatocellular carcinoma using WEE1 inhibition.

Proteomics profiling of inflammatory responses to elexacaftor/tezacaftor/ivacaftor in cystic fibrosis.

CFTR modulator therapies have positive clinical outcomes, yet chronic inflammation and bacterial infections persist in people with CF (pwCF). How elexacaftor-tezacaftor-ivacaftor (ETI) fails to improve innate immune signaling responsible for bacterial clearance and inflammation resolution remains unknown. We used an unbiased proteomics approach to measure the effect of ETI on inflammatory proteins. Plasma from 20 pediatric pwCF and 20 non-CF (NCF) was collected during routine examination and 3 months after ETI initiation. Protein screening was performed with an inflammation panel (Target 96, Olink®). Bioinformatics analysis was used to determine changes in protein expression. There were significantly fewer pulmonary exacerbations after ETI initiation, along with sustained improvement in lung function and reduced bacterial colonization. Unpaired analysis of CF pre-ETI and NCF resulted in 34 significantly different proteins. Of these, CCL20, MMP-10, EN-RAGE, and AXIN1 had a log2 fold change of 1.2 or more. There was a modest shift in overall CF protein profiles post-ETI toward the NCF cluster. Unpaired analysis of protein differential expression between NCF and CF post-ETI identified a total of 24 proteins significantly impacted by ETI therapy (p-value ≤ 0.05), with only CCL20 having a log2 fold change higher than 1.2. Paired analysis (CF pre- and CF post-ETI) of differential protein expression demonstrated significant expression changes of MMP-10, EN-RAGE, and IL-17A. Pathway analysis identified significantly impacted pathways such as the NF-κB pathway. This study showed that ETI in a pediatric cohort had a modest effect on several inflammatory proteins with potential as biomarkers. Pathways significantly impacted by ETI can be further studied for future therapies to combat persistent inflammation and dysregulated immunity.

SPT5 regulates RNA polymerase II stability via Cullin 3-ARMC5 recognition.

The stability of RNA polymerase II (Pol II) is tightly regulated during transcriptional elongation for proper control of gene expression. Our recent studies revealed that promoter-proximal Pol II is destabilized via the ubiquitin E3 ligase cullin 3 (CUL3) upon loss of transcription elongation factor SPT5. Here, we investigate how CUL3 recognizes chromatin-bound Pol II as a substrate. Using an unbiased proteomic screening approach, we identify armadillo repeat-containing 5 (ARMC5) as a CUL3 adaptor required for VCP/p97-dependent degradation of SPT5-depleted, chromatin-bound Pol II. Genome-wide analyses indicate that ARMC5 targets promoter-proximal Pol II in a BTB domain-dependent manner. Further biochemical analysis demonstrates that interaction between ARMC5 and Pol II requires the transcriptional cyclin-dependent kinase 9 (CDK9), supporting a phospho-dependent degradation model. We propose that defective, promoter-proximal Pol II that lacks SPT5 is rapidly eliminated from chromatin in a noncanonical early termination pathway that requires CDK9-dependent interaction with the CUL3-ARMC5 ubiquitin ligase complex.

Simulation and quantitative analysis of spatial centromere distribution patterns.

A prominent feature of eukaryotic chromosomes are centromeres, which are specialized regions of repetitive DNA required for faithful chromosome segregation during cell division. In interphase cells centromeres are non-randomly positioned in the three-dimensional space of the nucleus in a cell-type specific manner. The functional relevance and the cellular mechanisms underlying this observation are unknown, and quantitative methods to measure distribution patterns of centromeres in 3D space are needed. Here we have developed an analytical framework that combines robust clustering metrics and advanced modeling techniques for the quantitative analysis of centromere distributions at the single cell level. To identify a robust quantitative measure for centromere clustering, we benchmarked six metrics for their ability to sensitively detect changes in centromere distribution patterns from high-throughput imaging data of human cells, both under normal conditions and upon experimental perturbation of centromere distribution. We find that Ripley's K Score has the highest accuracy with minimal sensitivity to variations in centromeres number, making it the most suitable metric for measuring centromere distributions. As a complementary approach, we also developed and validated spatial models to replicate centromere distribution patterns, and we show that a radially shifted Gaussian distribution best represents the centromere patterns seen in human cells. Our approach creates tools for the quantitative characterization of spatial centromere distributions with applications in both targeted studies of centromere organization as well as in unbiased screening approaches.