Translational Drug Development Research Articles

Spatially resolved metabolomics: From metabolite mapping to function visualising.

Mass spectrometry imaging (MSI)-based spatially resolved metabolomics addresses the limitations inherent in traditional liquid chromatography-tandem mass spectrometry (LC-MS)-based metabolomics, particularly the loss of spatial context within heterogeneous tissues. MSI not only enhances our understanding of disease aetiology but also aids in the identification of biomarkers and the assessment of drug toxicity and therapeutic efficacy by converting invisible metabolites and biological networks into visually rendered image data. In this comprehensive review, we illuminate the key advancements in MSI-driven spatially resolved metabolomics over the past few years. We first outline recent innovations in preprocessing methodologies and MSI instrumentation that improve the sensitivity and comprehensiveness of metabolite detection. We then delve into the progress made in functional visualization techniques, which enhance the precision of metabolite identification and annotation. Ultimately, we discuss the significant potential applications of spatially resolved metabolomics technology in translational medicine and drug development, offering new perspectives for future research and clinical translation. HIGHLIGHTS: MSI-driven spatial metabolomics preserves metabolite spatial information, enhancing disease analysis and biomarker discovery. Advances in MSI technology improve detection sensitivity and accuracy, expanding bioanalytical applications. Enhanced visualization techniques refine metabolite identification and spatial distribution analysis. Integration of MSI with AI promises to advance precision medicine and accelerate drug development.

Drug-Drug Interactions and Synergy: From Pharmacological Models to Clinical Application.

This review explores the concept of synergy in pharmacology, emphasizing its importance in optimizing treatment outcomes through the combination of drugs with different mechanisms of action. Synergy, defined as an effect greater than the expected additive effect elicited by individual agents according to specific predictive models, offers a promising approach to enhance therapeutic efficacy while minimizing adverse events. The historical evolution of synergy research, from ancient civilizations to modern pharmacology, highlights the ongoing quest to understand and harness synergistic interactions. Key concepts, such as concentration-response curves, additive effects, and predictive models, are discussed in detail, emphasizing the need for accurate assessment methods throughout translational drug development. Although various mathematical models exist for synergy analysis, selecting the appropriate model and software tools remains a challenge, necessitating careful consideration of experimental design and data interpretation. Furthermore, this review addresses practical considerations in synergy assessment, including preclinical and clinical approaches, mechanism of action, and statistical analysis. Optimizing synergy requires attention to concentration/dose ratios, target site localization, and timing of drug administration, ensuring that the benefits of combination therapy detected bench-side are translatable into clinical practice. Overall, the review advocates for a systematic approach to synergy assessment, incorporating robust statistical analysis, effective and simplified predictive models, and collaborative efforts across pivotal sectors, such as academic institutions, pharmaceutical companies, and regulatory agencies. By overcoming critical challenges and maximizing therapeutic potential, effective synergy assessment in drug development holds promise for advancing patient care. SIGNIFICANCE STATEMENT: Combining drugs with different mechanisms of action for synergistic interactions optimizes treatment efficacy and safety. Accurate interpretation of synergy requires the identification of the expected additive effect. Despite innovative models to predict the additive effect, consensus in drug-drug interactions research is lacking, hindering the bench-to-bedside development of combination therapies. Collaboration among science, industry, and regulation is crucial for advancing combination therapy development, ensuring rigorous application of predictive models in clinical settings.

Looking for a Beam of Light to Heal Chronic Pain.

Chronic pain (CP) is a leading cause of disability and a potential factor that affects biological processes, family relationships, and self-esteem of patients. However, the need for treatment of CP is presently unmet. Current methods of pain management involve the use of drugs, but there are different degrees of concerning side effects. At present, the potential mechanisms underlying CP are not completely clear. As research progresses and novel therapeutic approaches are developed, the shortcomings of current pain treatment methods may be overcome. In this review, we discuss the retinal photoreceptors and brain regions associated with photoanalgesia, as well as the targets involved in photoanalgesia, shedding light on its potential underlying mechanisms. Our aim is to provide a foundation to understand the mechanisms underlying CP and develop light as a novel analgesic treatment has its biological regulation principle for CP. This approach may provide an opportunity to drive the field towards future translational, clinical studies and support pain drug development.

Advancements in high-resolution 3D microscopy analysis of endosomal morphology in postmortem Alzheimer's disease brains.

Abnormal endo-lysosomal morphology is an early cytopathological feature of Alzheimer's disease (AD) and genome-wide association studies (GWAS) have implicated genes involved in the endo-lysosomal network (ELN) as conferring increased risk for developing sporadic, late-onset AD (LOAD). Characterization of ELN pathology and the underlying pathophysiology is a promising area of translational AD research and drug development. However, rigorous study of ELN vesicles in AD and aged control brains poses a unique constellation of methodological challenges due in part to the small size of these structures and subsequent requirements for high-resolution imaging. Here we provide a detailed protocol for high-resolution 3D morphological quantification of neuronal endosomes in postmortem AD brain tissue, using immunofluorescent staining, confocal imaging with image deconvolution, and Imaris software analysis pipelines. To demonstrate these methods, we present neuronal endosome morphology data from 23 sporadic LOAD donors and one aged non-AD control donor. The techniques described here were developed across a range of AD neuropathology to best optimize these methods for future studies with large cohorts. Application of these methods in research cohorts will help advance understanding of ELN dysfunction and cytopathology in sporadic AD.

Brachytherapy on-a-chip: a clinically-relevant approach for radiotherapy testing in 3d biology.

We describe the first microfluidic device for in vitro testing of brachytherapy (BT), with applications in translational cancer research. Our PDMS-made BT-on-chip system allows highly precise manual insertion of clinical BT seeds, reliable dose calculation using standard clinically-used TG-43 formalism and easy culture of naturally hypoxic spheroids in less than 3 days, thereby increasing the translational potential of the device. As the BT-on-chip platform is designed to be versatile, we showcase three different gold-standard post-irradiation bioassays and recapitulate, for the first time on-chip, key clinical observations such as dose rate effect and hypoxia-induced radioresistance. Our results suggest that BT-on-chip can be used to safely and efficiently integrate BT and radiotherapy to translational research and drug development pipelines, without expensive equipment or complex workflows.

Patient-Derived Xenograft Models for Translational Prostate Cancer Research and Drug Development.

Patient-derived xenografts (PDXs) are a valuable preclinical research platform generated through transplantation of a patient's resected tumor into an immunodeficient or humanized mouse. PDXs serve as a high-fidelity avatar for both precision medicine and therapeutic testing against the cancer patient's disease state. While PDXs show mixed response to initial establishment, those that successfully engraft and can be sustained with serial passaging form a useful tool for basic and translational prostate cancer (PCa) research. While genetically engineered mouse (GEM) models and human cancer cell lines, and their xenografts, each play beneficial roles in discovery science and initial drug screening, PDX tumors are emerging as the gold standard approach for therapeutic proof-of-concept prior to entering clinical trial. PDXs are a powerful platform, with PCa PDXs shown to represent the original patient tumor cell population and architecture, histopathology, genomic and transcriptomic landscape, and heterogeneity. Furthermore, PDX response to anticancer drugs in mice has been closely correlated to the original patient's susceptibility to these treatments in the clinic. Several PDXs have been established and have undergone critical in-depth characterization at the cellular and molecular level across multiple PCa tumor subtypes representing both primary and metastatic patient tumors and their inherent levels of androgen responsiveness and/or treatment resistance, including androgen-sensitive, castration resistant, and neuroendocrine PCa. Multiple PDX networks and repositories have been generated for the collaborative and shared use of these vital translational cancer tools. Here we describe the creation of a PDX maintenance colony from an established well-characterized PDX, best practice for PDX maintenance in mice, and their subsequent application in preclinical drug testing. This chapter aims to serve as a go to resource for the preparation and adoption of PCa PDX models in the research laboratory and for their use as a valuable preclinical platform for translational research and therapeutic agent development.

Uptake Transporters at the Blood-Brain Barrier and Their Role in Brain Drug Disposition.

Uptake drug transporters play a significant role in the pharmacokinetic of drugs within the brain, facilitating their entry into the central nervous system (CNS). Understanding brain drug disposition is always challenging, especially with respect to preclinical to clinical translation. These transporters are members of the solute carrier (SLC) superfamily, which includes organic anion transporter polypeptides (OATPs), organic anion transporters (OATs), organic cation transporters (OCTs), and amino acid transporters. In this systematic review, we provide an overview of the current knowledge of uptake drug transporters in the brain and their contribution to drug disposition. Here, we also assemble currently available proteomics-based expression levels of uptake transporters in the human brain and their application in translational drug development. Proteomics data suggest that in association with efflux transporters, uptake drug transporters present at the BBB play a significant role in brain drug disposition. It is noteworthy that a significant level of species differences in uptake drug transporters activity exists, and this may contribute toward a disconnect in inter-species scaling. Taken together, uptake drug transporters at the BBB could play a significant role in pharmacokinetics (PK) and pharmacodynamics (PD). Continuous research is crucial for advancing our understanding of active uptake across the BBB.

Abstract 4299: Gene expression based machine learning classifier to predict and validate cancer type in patient derived xenograft (PDX) models

Abstract Patient derived xenografts (PDX) are increasingly utilized in translational research and drug development. Characterizing the genomic features of PDX is essential to establishing reliable models for cancer research. Despite great interest, problems remain in PDX tumor data banks including improper cancer type diagnosis and sample mix-ups. In an effort to improve annotation and quality of PDX models, we developed a machine learning model trained on gene expression data from The Cancer Genome Atlas (TCGA). We then applied the model to corresponding data collected from nearly 300 Certis PDX models plus publicly available data from NCI’s Patient-Derived Models Repository (PDMR). The model shows high precision and variable recall and provides a fast and accurate method for cancer type diagnosis. Citation Format: Warren Andrews, Long Do, Jonathan Nakashima. Gene expression based machine learning classifier to predict and validate cancer type in patient derived xenograft (PDX) models. [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 4299.

Role of allopregnanolone-mediated γ-aminobutyric acid A receptor sensitivity in the pathogenesis of premenstrual dysphoric disorder: Toward precise targets for translational medicine and drug development.

Premenstrual dysphoric disorder (PMDD) can be conceptualized as a disorder of suboptimal sensitivity to neuroactive steroid hormones. Its core symptoms (emotional instability, irritability, depression, and anxiety) are related to the increase of stress sensitivity due to the fluctuation of hormone level in luteal phase of the menstrual cycle. In this review, we describe the emotional regulatory effect of allopregnanolone (ALLO), and summarize the relationship between ALLO and γ-aminobutyric acid A (GABAA) receptor subunits based on rodent experiments and clinical observations. A rapid decrease in ALLO reduces the sensitivity of GABAA receptor, and reduces the chloride influx, hindered the inhibitory effect of GABAergic neurons on pyramidal neurons, and then increased the excitability of pyramidal neurons, resulting in PMDD-like behavior. Finally, we discuss in depth the treatment of PMDD with targeted GABAA receptors, hoping to find a precise target for drug development and subsequent clinical application. In conclusion, PMDD pathophysiology is rooted in GABAA receptor sensitivity changes caused by rapid changes in ALLO levels. Targeting GABAA receptors may alleviate the occurrence of PMDD.

Data sharing to advance gene-targeted therapies in rare diseases.

Recent advancements in gene-targeted therapies have highlighted the critical role data sharing plays in successful translational drug development for people with rare diseases. To scale these efforts, we need to systematize these sharing principles, creating opportunities for more rapid, efficient, and scalable drug discovery/testing including long-term and transparent assessment of clinical safety and efficacy. A number of challenges will need to be addressed, including the logistical difficulties of studying rare diseases affecting individuals who may be scattered across the globe, scientific, technical, regulatory, and ethical complexities of data collection, and harmonization and integration across multiple platforms and contexts. The NCATS/NIH Gene-Targeted Therapies: Early Diagnosis and Equitable Delivery meeting series held during June 2021 included data sharing models that address these issues and framed discussions of areas that require improvement. This article describes these discussions and provides a series of considerations for future data sharing.

Biological Mechanism-based Neurology and Psychiatry: A BACE1/2 and Downstream Pathway Model.

In oncology, comprehensive omics and functional enrichment studies have led to an extensive profiling of (epi)genetic and neurobiological alterations that can be mapped onto a single tumor's clinical phenotype and divergent clinical phenotypes expressing common pathophysiological pathways. Consequently, molecular pathway-based therapeutic interventions for different cancer typologies, namely tumor type- and site-agnostic treatments, have been developed, encouraging the real-world implementation of a paradigm shift in medicine. Given the breakthrough nature of the new-generation translational research and drug development in oncology, there is an increasing rationale to transfertilize this blueprint to other medical fields, including psychiatry and neurology. In order to illustrate the emerging paradigm shift in neuroscience, we provide a state-of-the-art review of translational studies on the β-site amyloid precursor protein cleaving enzyme (BACE) and its most studied downstream effector, neuregulin, which are molecular orchestrators of distinct biological pathways involved in several neurological and psychiatric diseases. This body of data aligns with the evidence of a shared genetic/biological architecture among Alzheimer's disease, schizoaffective disorder, and autism spectrum disorders. To facilitate a forward-looking discussion about a potential first step towards the adoption of biological pathway-based, clinical symptom-agnostic, categorization models in clinical neurology and psychiatry for precision medicine solutions, we engage in a speculative intellectual exercise gravitating around BACE-related science, which is used as a paradigmatic case here. We draw a perspective whereby pathway-based therapeutic strategies could be catalyzed by highthroughput techniques embedded in systems-scaled biology, neuroscience, and pharmacology approaches that will help overcome the constraints of traditional descriptive clinical symptom and syndrome-focused constructs in neurology and psychiatry.

Animal Models of Osteoarthritis Part 1–Preclinical Small Animal Models: Challenges and Opportunities for Drug Development

Osteoarthritis (OA) is the most common form of arthritis and a major source of pain and disability in the adult population. There is a significant unmet medical need for the development of effective pharmacological therapies for the treatment of OA. In addition to spontaneously occurring animal models of OA, many experimental animal models have been developed to provide insights into mechanisms of pathogenesis and progression. Many of these animal models are also being used in the drug development pipeline. Here, we provide an overview of commonly used and emerging preclinical small animal models of OA and highlight the strengths and limitations of small animal models in the context of translational drug development. There is limited information in the published literature regarding the technical reliability of these small animal models and their ability to accurately predict clinical drug development outcomes. The cost and complexity of the available models however is an important consideration for pharmaceutical companies, biotechnology startups, and contract research organizations wishing to incorporate preclinical models in target validation, discovery, and development pipelines. Further considerations relevant to industry include timelines, methods of induction, the key issue of reproducibility, and appropriate outcome measures needed to objectively assess outcomes of experimental therapeutics. Preclinical small animal models are indispensable tools that will shine some light on the pathogenesis of OA and its molecular endotypes in the context of drug development. This paper will focus on small animal models used in preclinical OA research. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

Cognitive Impairment Associated with Schizophrenia: From Pathophysiology to Treatment.

Cognitive impairment is a core feature of schizophrenia and a major contributor to poor functional outcomes. Methods for assessment of cognitive dysfunction in schizophrenia are now well established. In addition, there has been increasing appreciation in recent years of the additional role of social cognitive impairment in driving functional outcomes and of the contributions of sensory-level dysfunction to higher-order impairments. At the neurochemical level, acute administration of N-methyl-d-aspartate receptor (NMDAR) antagonists reproduces the pattern of neurocognitive dysfunction associated with schizophrenia, encouraging the development of treatments targeted at both NMDAR and its interactome. At the local-circuit level, an auditory neurophysiological measure, mismatch negativity, has emerged both as a veridical index of NMDAR dysfunction and excitatory/inhibitory imbalance in schizophrenia and as a critical biomarker for early-stage translational drug development. Although no compounds have yet been approved for treatment of cognitive impairment associated with schizophrenia, several candidates are showing promise in early-phase testing.

Need for a Standardized Translational Drug Development Platform: Lessons Learned from the Repurposing of Drugs for COVID-19.

In the absence of drugs to treat or prevent COVID-19, drug repurposing can be a valuable strategy. Despite a substantial number of clinical trials, drug repurposing did not deliver on its promise. While success was observed with some repurposed drugs (e.g., remdesivir, dexamethasone, tocilizumab, baricitinib), others failed to show clinical efficacy. One reason is the lack of clear translational processes based on adequate preclinical profiling before clinical evaluation. Combined with limitations of existing in vitro and in vivo models, there is a need for a systematic approach to urgent antiviral drug development in the context of a global pandemic. We implemented a methodology to test repurposed and experimental drugs to generate robust preclinical evidence for further clinical development. This translational drug development platform comprises in vitro, ex vivo, and in vivo models of SARS-CoV-2, along with pharmacokinetic modeling and simulation approaches to evaluate exposure levels in plasma and target organs. Here, we provide examples of identified repurposed antiviral drugs tested within our multidisciplinary collaboration to highlight lessons learned in urgent antiviral drug development during the COVID-19 pandemic. Our data confirm the importance of assessing in vitro and in vivo potency in multiple assays to boost the translatability of pre-clinical data. The value of pharmacokinetic modeling and simulations for compound prioritization is also discussed. We advocate the need for a standardized translational drug development platform for mild-to-moderate COVID-19 to generate preclinical evidence in support of clinical trials. We propose clear prerequisites for progression of drug candidates for repurposing into clinical trials. Further research is needed to gain a deeper understanding of the scope and limitations of the presented translational drug development platform.

Optimal Choice of Neoadjuvant Chemotherapy for HER2-Negative Breast Cancer: Clinical Insights.

The neoadjuvant setting provides immense opportunities for translational research and drug development. The acceptance of pathological complete response (pCR) as a surrogate endpoint for clinical benefit has led to the widespread use of neoadjuvant treatment. Optimal neoadjuvant therapies are determined based on their ability to achieve the highest rates of pCR. Predicted rates of pCR for triple negative breast cancer (TNBC) treated with sequential taxane/anthracycline regimens range from 35% to 48%. With the addition of a platinum agent pCR rates of 55% are predicted. Further increases have been observed with the addition of immune checkpoint inhibitors to this standard chemotherapy backbone. In the pivotal KEYNOTE-522 clinical trial pCR rates of 65% and 69% were reported for chemotherapy plus pembrolizumab in the overall and PD-L1-positive subgroup respectively. The role of the neoadjuvant chemotherapy is less clear in hormone receptor (HR)-positive, human epidermal growth factor receptor-2 (HER2)-negative breast cancer. In general, HR–positive cancers have the least chance of achieving a pCR after neoadjuvant chemotherapy, especially if they are low-grade. If neoadjuvant chemotherapy is given for high-risk HR-positive, HER2-negative breast cancer, standard adjuvant anthracycline/taxane regimens are appropriate. Optimum endocrine therapy is the standard-of-care in the adjuvant setting regardless of pCR. There are several genomic signatures available to guide decisions regarding adjuvant chemotherapy use however these assays are not routinely used in the neoadjuvant setting. For high-risk patients meeting the criteria for the monarchE trial adjuvant abemaciclib in addition to endocrine therapy is associated with an improvement in disease free survival (DFS) at 3 years. Based on the OlympiA trial patients with germline BRCA mutations should be considered for adjuvant olaparib therapy. In this article we review neoadjuvant clinical trials that guide optimum treatment options for TNBC and HR-positive, HER2-negative breast cancer.

Comparing the Cytokine Storms of COVID-19 and Pandemic Influenza.

Emerging respiratory viruses are major health threats due to their potential to cause massive outbreaks. Over the past 2 years, the coronavirus disease 2019 (COVID-19) pandemic has caused millions of cases of severe infection and deaths worldwide. Although natural and vaccine-induced protective immune mechanisms against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been increasingly identified, the factors that determine morbimortality are less clear. Comparing the immune signatures of COVID-19 and other severe respiratory infections such as the pandemic influenza might help dissipate current controversies about the origin of their severe manifestations. As such, identifying homologies in the immunopathology of both diseases could provide targets for immunotherapy directed to block shared pathogenic mechanisms. Meanwhile, finding unique characteristics that differentiate each infection could shed light on specific immune alterations exploitable for diagnostic and individualized therapeutics for each case. In this study, we summarize immunopathological aspects of COVID-19 and pandemic influenza from the perspective of cytokine storms as the driving force underlying morbidity. Thereby, we analyze similarities and differences in the cytokine profiles of both infections, aiming to bring forward those molecules more attractive for translational medicine and drug development.

Model-based dose selection to inform translational clinical oncology development of WNT974, a first-in-class Porcupine inhibitor.

WNT974 is a potent, selective, and orally bioavailable first‐in‐class inhibitor of Porcupine, a membrane‐bound O‐acyltransferase required for Wnt secretion, currently under clinical development in oncology. A phase I clinical trial is being conducted in patients with advanced solid tumors. During the dose‐escalation part, various dosing regimens, including once or twice daily continuous and intermittent dosing at a dose range of 5–45 mg WNT974 were studied, however, the protocol‐defined maximum tolerated dose (MTD) was not established based on dose‐limiting toxicity. To assist in the selection of the recommended dose for expansion (RDE), a model‐based approach was utilized. It integrated population pharmacokinetic (PK) modeling and exposure–response analyses of a target‐inhibition biomarker, skin AXIN2 mRNA expression, and the occurrence of the adverse event, dysgeusia. The target exposure range of WNT974 that would provide a balance between target inhibition and tolerability was estimated based on exposure–response analyses. The dose that was predicted to yield an exposure within the target exposure range was selected as RDE. This model‐based approach integrated PK, biomarker, and safety data to determine the RDE and represented an alternative as opposed to the conventional MTD approach for selecting an optimal biological dose. The strategy can be broadly applied to select doses in early oncology trials and inform translational clinical oncology drug development.

Sex-related differences within sleep-wake dynamics, cataplexy, and EEG fast-delta power in a narcolepsy mouse model.

Narcolepsy type 1 (NT1) is a sleep-wake disorder caused by selective loss of hypocretin (HCRT, also called orexin) neurons. Although the prevalence of NT1 is equal in men and women, sex differences in NT1 symptomatology have been reported in humans and other species. Yet, most preclinical studies fail to include females, resulting in gender bias within translational drug development. We used hcrt-tTA;TetO DTA mice (NT1 mice) that lose their HCRT neurons upon dietary doxycycline removal to examine in detail the effect of sex on NT1 symptoms and sleep-wake characteristics. We recorded 24-h electroencephalography (EEG), electromyography (EMG), and video in adult male and female NT1 mice for behavioral state quantification. While conducting this study, we recognized another type of behavioral arrest different from cataplexy: shorter lasting and with high δ power. We termed these delta attacks and propose a set of criteria for quantifying these in future research. Our findings show that both sexes exhibit high behavioral state instability, which was markedly higher in females with more behavioral arrests interrupting the wake episodes. Females exhibited increased wake at the expense of sleep during the dark phase, and decreased rapid eye movement (REM) sleep during the 24-h day. During the dark phase, fast-δ (2.5-4 Hz) in non-rapid eye movement (NREM) sleep and θ (6-10 Hz) EEG spectral power in REM sleep were lower in females compared to males. We demonstrate that biologically driven sex-related differences exist in the symptomatology of NT1 mice which calls for including both sexes in future research.

Fluorogenic RNA aptamers to probe transcription initiation and co-transcriptional RNA folding by multi-subunit RNA polymerases.

Transcription is the first and most highly regulated step in gene expression. Experimental techniques for monitoring transcription are, thus, important for studying gene expression and gene regulation as well as for translational research and drug development. Fluorescence methods are often superior to other techniques for real-time monitoring of biochemical processes. Green fluorescent proteins have long served as valuable tools for studying the process of translation. Here we present two methods that utilize fluorescent light-up RNA aptamers (FLAPs), the RNA mimics of green fluorescent proteins, to monitoring transcription and co-transcriptional RNA folding. FLAPs adopt defined three-dimensional folds that bind low molecular weight compounds called fluorogens with concomitant increase in fluorescence by many folds. FLAPs provide a strong fluorescence signal with low background that allows monitoring of transcription in real time in vitro and in vivo. However, it takes several seconds for RNA polymerase to synthesize FLAPs and the subsequent folding of the fluorogen-binding platform takes additional seconds or minutes. Here we show that Broccoli-FLAP is well suited for monitoring the rate of transcription initiation in a multi-round setup that mitigates the slow rate of the FLAP maturation. Furthermore, we demonstrate that a relatively slow and inefficient folding of iSpinach-FLAP can be taken advantage of for monitoring the action of RNA folding chaperones.

NF-κB signaling in inflammation and cancer.

Since nuclear factor of κ‐light chain of enhancer‐activated B cells (NF‐κB) was discovered in 1986, extraordinary efforts have been made to understand the function and regulating mechanism of NF‐κB for 35 years, which lead to significant progress. Meanwhile, the molecular mechanisms regulating NF‐κB activation have also been illuminated, the cascades of signaling events leading to NF‐κB activity and key components of the NF‐κB pathway are also identified. It has been suggested NF‐κB plays an important role in human diseases, especially inflammation‐related diseases. These studies make the NF‐κB an attractive target for disease treatment. This review aims to summarize the knowledge of the family members of NF‐κB, as well as the basic mechanisms of NF‐κB signaling pathway activation. We will also review the effects of dysregulated NF‐κB on inflammation, tumorigenesis, and tumor microenvironment. The progression of the translational study and drug development targeting NF‐κB for inflammatory diseases and cancer treatment and the potential obstacles will be discussed. Further investigations on the precise functions of NF‐κB in the physiological and pathological settings and underlying mechanisms are in the urgent need to develop drugs targeting NF‐κB for inflammatory diseases and cancer treatment, with minimal side effects.