Understanding Human Autoimmunity and Autoinflammation Through Transcriptomics.

Transcriptomics, the high-throughput characterization of RNAs, has been instrumental in defining pathogenic signatures in human autoimmunity and autoinflammation. It enabled the identification of new therapeutic targets in IFN-, IL-1- and IL-17-mediated diseases. Applied to immunomonitoring, transcriptomics is starting to unravel diagnostic and prognostic signatures that stratify patients, track molecular changes associated with disease activity, define personalized treatment strategies, and generally inform clinical practice. Herein, we review the use of transcriptomics to define mechanistic, diagnostic, and predictive signatures in human autoimmunity and autoinflammation. We discuss some of the analytical approaches applied to extract biological knowledge from high-dimensional data sets. Finally, we touch upon emerging applications of transcriptomics to study eQTLs, B and T cell repertoire diversity, and isoform usage.

Pan-cancer proteogenomics expands the landscape of therapeutic targets.

Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomics data from 1,043 patients across 10 cancer types with additional public datasets to identify potential therapeutic targets. Pan-cancer analysis of 2,863 druggable proteins reveals a wide abundance range and identifies biological factors that affect mRNA-protein correlation. Integration of proteomic data from tumors and genetic screen data from cell lines identifies protein overexpression- or hyperactivation-driven druggable dependencies, enabling accurate predictions of effective drug targets. Proteogenomic identification of synthetic lethality provides a strategy to target tumor suppressor gene loss. Combining proteogenomic analysis and MHC binding prediction prioritizes mutant KRAS peptides as promising public neoantigens. Computational identification of shared tumor-associated antigens followed by experimental confirmation nominates peptides as immunotherapy targets. These analyses, summarized at https://targets.linkedomics.org, form a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development.

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations.

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis) and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants and identify differences in genetic effects between weight-bearing and non-weight-bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone, and osteophytic cartilage) and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.

Proteogenomic Analysis of Human Colon Cancer Reveals New Therapeutic Opportunities.

We performed the first proteogenomic study on a prospectively collected colon cancer cohort. Comparative proteomic and phosphoproteomic analysis of paired tumor and normal adjacent tissues produced a catalog of colon cancer-associated proteins and phosphosites, including known and putative new biomarkers, drug targets, and cancer/testis antigens. Proteogenomic integration not only prioritized genomically inferred targets, such as copy-number drivers and mutation-derived neoantigens, but also yielded novel findings. Phosphoproteomics data associated Rb phosphorylation with increased proliferation and decreased apoptosis in colon cancer, which explains why this classical tumor suppressor is amplified in colon tumors and suggests a rationale for targeting Rb phosphorylation in colon cancer. Proteomics identified an association between decreased CD8 T cell infiltration and increased glycolysis in microsatellite instability-high (MSI-H) tumors, suggesting glycolysis as a potential target to overcome the resistance of MSI-H tumors to immune checkpoint blockade. Proteogenomics presents new avenues for biological discoveries and therapeutic development.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

A Bright Future for Antibiotics?

Multidrug resistance is a global threat as the clinically available potent antibiotic drugs are becoming exceedingly scarce. For example, increasing drug resistance among gram-positive bacteria is responsible for approximately one-third of nosocomial infections. As ribosomes are a major target for these drugs, they may serve as suitable objects for novel development of next-generation antibiotics. Three-dimensional structures of ribosomal particles from Staphylococcus aureus obtained by X-ray crystallography have shed light on fine details of drug binding sites and have revealed unique structural motifs specific for this pathogenic strain, which may be used for the design of novel degradable pathogen-specific, and hence, environmentally friendly drugs.

Defining a Cancer Dependency Map.

Most human epithelial tumors harbor numerous alterations, making it difficult to predict which genes are required for tumor survival. To systematically identify cancer dependencies, we analyzed 501 genome-scale loss-of-function screens performed in diverse human cancer cell lines. We developed DEMETER, an analytical framework that segregates on- from off-target effects of RNAi. 769 genes were differentially required in subsets of these cell lines at a threshold of six SDs from the mean. We found predictive models for 426 dependencies (55%) by nonlinear regression modeling considering 66,646 molecular features. Many dependencies fall into a limited number of classes, and unexpectedly, in 82% of models, the top biomarkers were expression based. We demonstrated the basis behind one such predictive model linking hypermethylation of the UBB ubiquitin gene to a dependency on UBC. Together, these observations provide a foundation for a cancer dependency map that facilitates the prioritization of therapeutic targets.

Negative DNA supercoiling induces genome-wide Cas9 off-target activity.

CRISPR-Cas9 is a powerful gene-editing technology; however, off-target activity remains an important consideration for therapeutic applications. We have previously shown that force-stretching DNA induces off-target activity and hypothesized that distortions of the DNA topology in vivo, such as negative DNA supercoiling, could reduce Cas9 specificity. Using single-molecule optical-tweezers, we demonstrate that negative supercoiling λ-DNA induces sequence-specific Cas9 off-target binding at multiple sites, even at low forces. Using an adapted CIRCLE-seq approach, we detect over 10,000 negative-supercoiling-induced Cas9 off-target double-strand breaks genome-wide caused by increased mismatch tolerance. We further demonstrate in vivo that directed local DNA distortion increases off-target activity in cells and that induced off-target events can be detected during Cas9 genome editing. These data demonstrate that Cas9 off-target activity is regulated by DNA topology in vitro and in vivo, suggesting that cellular processes, such as transcription and replication, could induce off-target activity at previously overlooked sites.

Immunometabolism in atherosclerosis: a new understanding of an old disease.

Atherosclerosis, a chronic inflammatory condition, remains a leading cause of death globally, necessitating innovative approaches to target pro-atherogenic pathways. Recent advancements in the field of immunometabolism have highlighted the crucial interplay between metabolic pathways and immune cell function in atherogenic milieus. Macrophages and T cells undergo dynamic metabolic reprogramming to meet the demands of activation and differentiation, influencing plaque progression. Furthermore, metabolic intermediates intricately regulate immune cell responses and atherosclerosis development. Understanding the metabolic control of immune responses in atherosclerosis, known as athero-immunometabolism, offers new avenues for preventive and therapeutic interventions. This review elucidates the emerging intricate interplay between metabolism and immunity in atherosclerosis, underscoring the significance of metabolic enzymes and metabolites as key regulators of disease pathogenesis and therapeutic targets.

Moving Immune Therapy Forward Targeting TME.

The host immune system shapes the fate of tumor progression. Hence, manipulating patients' immune system to activate host immune responses against cancer pathogenesis is a promising strategy to develop effective therapeutic interventions for metastatic and drug-resistant cancers. Understanding the dynamic mechanisms within the tumor microenvironment (TME) that contribute to heterogeneity and metabolic plasticity is essential to enhance the patients' responsiveness to immune targeted therapies. Riera-Domingo et al. (Riera-Domingo C, Audige A, Granja S, Cheng WC, Ho PC, Baltazar F, Stockmann C, Mazzone, M. Physiol Rev 100: 1-102, 2020) describe the immune landscape within the TME and highlight the significance of metabolic and hypoxic signatures that impact immune function and response to immunotherapy strategies. Current literature in this field confirms that targeting tumor metabolism and the acidic microenvironment commonly associated with tumors may present viable strategies to modulate the host immune system in favor of response to immune targeted therapies. However, development of better tools to understand tumor-immune interactions and identify mechanisms driving nonresponders, more innovative clinical trial design, and new therapies will need to be identified to move the field forward. Personalized immune therapies incorporating metabolic and microbiome-based gene signatures to influence the therapeutic response and novel methods to generate immunologically "hot" tumors are at the forefront of immunotherapy currently. The combination of these approaches with clinically approved immunotherapies will be valuable moving forward.

High-Resolution In Vivo Identification of miRNA Targets by Halo-Enhanced Ago2 Pull-Down.

The identification of microRNA (miRNA) targets by Ago2 crosslinking-immunoprecipitation (CLIP) methods has provided major insights into the biology of this important class of non-coding RNAs. However, these methods are technically challenging and not easily applicable to an in vivo setting. To overcome these limitations and facilitate the investigation of miRNA functions in vivo, we have developed a method based on a genetically engineered mouse harboring a conditional Halo-Ago2 allele expressed from the endogenous Ago2 locus. By using a resin conjugated to the HaloTag ligand, Ago2-miRNA-mRNA complexes can be purified from cells and tissues expressing the endogenous Halo-Ago2 allele. We demonstrate the reproducibility and sensitivity of this method in mouse embryonic stem cells, developing embryos, adult tissues, and autochthonous mouse models of human brain and lung cancers. This method and the datasets we have generated will facilitate the characterization of miRNA-mRNA networks in vivo under physiological and pathological conditions.

In vivo CRISPR screening for phenotypic targets of the mir-35-42 family in C. elegans.

Identifying miRNA target genes is difficult, and delineating which targets are the most biologically important is even more difficult. We devised a novel strategy to test the phenotypic impact of individual microRNA-target interactions by disrupting each predicted miRNA-binding site by CRISPR-Cas9 genome editing in C. elegans We developed a multiplexed negative selection screening approach in which edited loci are deep sequenced, and candidate sites are prioritized based on apparent selection pressure against mutations that disrupt miRNA binding. Importantly, our screen was conducted in vivo on mutant animals, allowing us to interrogate organism-level phenotypes. We used this approach to screen for phenotypic targets of the essential mir-35-42 family. By generating 1130 novel 3'UTR alleles across all predicted targets, we identified egl-1 as a phenotypic target whose derepression partially phenocopies the mir-35-42 mutant phenotype by inducing embryonic lethality and low fecundity. These phenotypes can be rescued by compensatory CRISPR mutations that retarget mir-35 to the mutant egl-1 3'UTR. This study demonstrates that the application of in vivo whole organismal CRISPR screening has great potential to accelerate the discovery of phenotypic negative regulatory elements in the noncoding genome.

cCMP and cUMP phosphodiesterases in viral infections.

In bacteria, cCMP and cUMP have a key role in defense against infection with bacterial viruses. Bacteriophages encode phosphodiesterases (PDEs; 'nucleases'; Apyc1), which cleave cCMP/cUMP, counteracting this defense. We propose that PDEs are of broader biological relevance, including cCMP/cUMP-cleaving PDEs of eukaryotic viruses, which may constitute new drug targets.

How to drug a cloud? Targeting intrinsically disordered proteins.

Biologically active proteins/regions without stable structure (i.e., intrinsically disordered proteins and regions (IDPs and IDRs)) are commonly found in all proteomes. They have a unique functional repertoire that complements the functionalities of ordered proteins and domains. IDPs/IDRs are multifunctional promiscuous binders capable of folding at interaction with specific binding partners on a template- or context-dependent manner, many of which undergo liquid-liquid phase separation, leading to the formation of membrane-less organelles and biomolecular condensates. Many of them are frequently related to the pathogenesis of various human diseases. All this defines IDPs/IDRs as attractive targets for the development of novel drugs. However, their lack of unique structures, multifunctionality, binding promiscuity, and involvement in unusual modes of action preclude direct use of traditional structure-based drug design approaches for targeting IDPs/IDRs, and make disorder-based drug discovery for these "protein clouds" challenging. Despite all these complexities there is continuing progress in the design of small molecules affecting IDPs/IDRs. This article describes the major structural features of IDPs/IDRs and the peculiarities of the disorder-based functionality. It also discusses the roles of IDPs/IDRs in various pathologies, and shows why the approaches elaborated for finding drugs targeting ordered proteins cannot be directly used for the intrinsic disorder-based drug design, and introduces some novel methodologies suitable for these purposes. Finally, it emphasizes that regardless of their multifunctionality, binding promiscuity, lack of unique structures, and highly dynamic nature, "protein clouds" are principally druggable. Significance Statement Intrinsically disordered proteins and regions are highly abundant in nature, have multiple important biological functions, are commonly involved in the pathogenesis of a multitude of human diseases, and are therefore considered as very attractive drug targets. Although dealing with these unstructured multifunctional protein/regions is a challenging task, multiple innovative approaches have been designed to target them by small molecules.

Harnessing the Power of Electronic Health Records and Genomics for Drug Discovery.

A long-standing recognition that information from human genetics studies has the potential to accelerate drug discovery has led to decades of research on how to leverage genetic and phenotypic information for drug discovery. Established simple and advanced statistical methods that allow the simultaneous analysis of genotype and clinical phenotype data by genome- and phenome-wide analyses, colocalization analyses with quantitative trait loci data from transcriptomics and proteomics data sets from different tissues, and Mendelian randomization are essential tools for drug development in the postgenomic era. Numerous studies have demonstrated how genomic data provide opportunities for the identification of new drug targets, the repurposing of drugs, and drug safety analyses. With an increase in the number of biobanks that enable linking in-depth omics data with rich repositories of phenotypic traits via electronic health records, more powerful ways for the evaluation and validation of drug targets will continue to expand across different disciplines of clinical research.

Integration of genetic fine-mapping and multi-omics data reveals candidate effector genes for hypertension.

Genome-wide association studies of blood pressure (BP) have identified >1,000 loci, but the effector genes and biological pathways at these loci are mostly unknown. Using published association summary statistics, we conducted annotation-informed fine-mapping incorporating tissue-specific chromatin segmentation and colocalization to identify causal variants and candidate effector genes for systolic BP, diastolic BP, and pulse pressure. We observed 532 distinct signals associated with ≥2 BP traits and 84 with all three. For >20% of signals, a single variant accounted for >75% posterior probability, 65 were missense variants in known (SLC39A8, ADRB2, and DBH) and previously unreported BP candidate genes (NRIP1 and MMP14). In disease-relevant tissues, we colocalized >80 and >400 distinct signals for each BP trait with cis-eQTLs and regulatory regions from promoter capture Hi-C, respectively. Integrating mouse, human disorder, gene expression and tissue abundance data, and literature review, we provide consolidated evidence for 436 BP candidate genes for future functional validation and discover several potential drug targets.

Homeostatic chemokines as putative therapeutic targets in idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a fatal chronic interstitial lung disease (ILD) that affects lung mechanical functions and gas exchange. IPF is caused by increased fibroblast activity and collagen deposition that compromise the alveolar-capillary barrier. Identifying an effective therapy for IPF remains a clinical challenge. Chemokines are key proteins in cell communication that have functions in immunity as well as in tissue homeostasis, damage, and repair. Chemokine receptor signaling induces the activation and proliferation of lung-resident cells, including alveolar macrophages (AMs) and fibroblasts. AMs are an important source of chemokines and cytokines during IPF. We highlight the complexity of this system and, based on insights from genetic and transcriptomic studies, propose a new role for homeostatic chemokine imbalance in IPF, with implications for putative therapeutic targets.

Multiomic prediction of therapeutic targets for human diseases associated with protein phase separation.

The phenomenon of protein phase separation (PPS) underlies a wide range of cellular functions. Correspondingly, the dysregulation of the PPS process has been associated with numerous human diseases. To enable therapeutic interventions based on the regulation of this association, possible targets should be identified. For this purpose, we present an approach that combines the multiomic PandaOmics platform with the FuzDrop method to identify PPS-prone disease-associated proteins. Using this approach, we prioritize candidates with high PandaOmics and FuzDrop scores using a profiling method that accounts for a wide range of parameters relevant for disease mechanism and pharmacological intervention. We validate the differential phase separation behaviors of three predicted Alzheimer's disease targets (MARCKS, CAMKK2, and p62) in two cell models of this disease. Overall, the approach that we present generates a list of possible therapeutic targets for human diseases associated with the dysregulation of the PPS process.

Discovery of antibodies and cognate surface targets for ovarian cancer by surface profiling.

Although antibodies targeting specific tumor-expressed antigens are the standard of care for some cancers, the identification of cancer-specific targets amenable to antibody binding has remained a bottleneck in development of new therapeutics. To overcome this challenge, we developed a high-throughput platform that allows for the unbiased, simultaneous discovery of antibodies and targets based on phenotypic binding profiles. Applying this platform to ovarian cancer, we identified a wide diversity of cancer targets including receptor tyrosine kinases, adhesion and migration proteins, proteases and proteins regulating angiogenesis in a single round of screening using genomics, flow cytometry, and mass spectrometry. In particular, we identified BCAM as a promising candidate for targeted therapy in high-grade serous ovarian cancers. More generally, this approach provides a rapid and flexible framework to identify cancer targets and antibodies.

Challenges for global antibiotic regimen planning and establishing antimicrobial resistance targets: implications for the WHO Essential Medicines List and AWaRe antibiotic book dosing.

SUMMARYThe World Health Organisation's 2022 AWaRe Book provides guidance for the use of 39 antibiotics to treat 35 infections in primary healthcare and hospital facilities. We review the evidence underpinning suggested dosing regimens. Few (n = 18) population pharmacokinetic studies exist for key oral AWaRe antibiotics, largely conducted in homogenous and unrepresentative populations hindering robust estimates of drug exposures. Databases of minimum inhibitory concentration distributions are limited, especially for community pathogen-antibiotic combinations. Minimum inhibitory concentration data sources are not routinely reported and lack regional diversity and community representation. Of studies defining a pharmacodynamic target for ß-lactams (n = 80), 42 (52.5%) differed from traditionally accepted 30%-50% time above minimum inhibitory concentration targets. Heterogeneity in model systems and pharmacodynamic endpoints is common, and models generally use intravenous ß-lactams. One-size-fits-all pharmacodynamic targets are used for regimen planning despite complexity in drug-pathogen-disease combinations. We present solutions to enable the development of global evidence-based antibiotic dosing guidance that provides adequate treatment in the context of the increasing prevalence of antimicrobial resistance and, moreover, minimizes the emergence of resistance.