Mass Spectrometry-based Technologies Research Articles

Artificial Intelligence and Machine Learning in Hepatocellular Carcinoma Screening, Diagnosis and Treatment - A Comprehensive Systematic Review

Background: Medical image analysis plays a crucial role in the screening, monitoring, diagnosis, and prognosis of diseases. Hepatocellular Carcinoma (HCC) often remain asymptomatic in their early stages. Timely identification and intervention are crucial to prevent the progression to decompensated liver diseases and advanced-stage HCC, minimizing morbidity and mortality. Methodology: This study examined twenty relevant research articles that met the inclusion criteria. Utilizing the PRISMA criteria, a systematic search was conducted on PubMed/MEDLINE and Google Scholar for studies on HCC screening employing Artificial Intelligence (AI) and Machine Learning (ML). The search focused on the keywords "artificial intelligence" and "hepatocellular carcinoma," with inclusion criteria specifying studies in the English language published in and after 2020. Exclusions were made for histology, animal research, and investigations conducted before 2020. Titles and abstracts were thoroughly reviewed, and any discrepancies were discussed. Results: The comprehensive review reveals the transformative impact of AI and ML on HCC screening, diagnosis, and therapy. ML models demonstrated effectiveness in early HCC diagnosis, distinguishing hepatic lesions, predicting treatment responses, and assessing recurrence risks across various techniques. Integration of mass spectrometry-based technologies, advanced imaging, and real-world data significantly improved diagnostic accuracy and clinical decision support. AI models exhibited diagnostic expertise with potential applications in therapy suggestions, personalized surveillance, and prognostic evaluations. However, further validation and seamless integration into clinical practice are essential for realizing their full potential. Conclusion: This systematic study underscores the progress made in the application of AI and ML in HCC screening, diagnosis, and treatment. Numerous studies highlight the capability of AI and ML systems to enhance hepatocellular carcinoma diagnosis, predict outcomes, and optimize therapy. The enduring and versatile nature of these technologies points towards a revolutionary future in personalized and efficient HCC management.

Abstract 3047: Interrogating TEAD protein interactions in cancer

Abstract The Hippo signaling pathway is a major regulator of cellular growth and is frequently deregulated in cancer. The main effectors of the Hippo pathway are the TEAD transcription factors which function by interacting with other co-effector proteins to modulate transcriptional outputs. Notably YAP and TAZ interact with TEAD to mediate oncogenic transcriptional programs, and blocking interaction of TEAD with YAP and TAZ is a sought-after mechanism for small molecule TEAD inhibitors. However, the interaction network of TEAD extends well beyond YAP and TAZ to a variety of additional cofactors, including chromatin remodelers, epigenetic factors, and other transcriptional regulators. Thus, the impact of inhibiting TEAD could extend to unanticipated protein interactions and cellular functions. The purpose of this study is to investigate, define, and interrogate TEAD interaction networks, providing foundational knowledge for interrogating TEAD biological functions and pharmacological effects. We are employing mass spectrometry-based technologies combined with chemical and genetic tools and biochemistry to interrogate TEAD protein interaction networks. We have performed affinity purification coupled with mass spectrometry for TEAD and have identified dozens of significant interacting proteins. TEAD interactions include expected proteins, such as known Hippo pathway members, as well as unexpected protein interactions, such as DNA damage response proteins. Cellular assays probing these DNA damage protein interactions implicate TEAD as a crucial factor for efficient DNA repair mechanisms and maintaining genomic stability. These results raise questions towards a combinatorial effect for TEAD inhibitors and DNA damaging chemotherapeutic agents. Altogether, these ongoing proteomic studies are providing insights into TEAD interaction networks, leading to a deeper understanding of TEAD biology, and providing foundational knowledge that can inform the development of TEAD inhibitors as effective cancer therapies. Citation Format: Alissa Guarnaccia, Jennie Lill, Anwesha Dey. Interrogating TEAD protein interactions in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3047.

Proteomics and Lipidomics to unveil the contribution of PCSK9 beyond cholesterol lowering: a narrative review.

Proprotein convertase subtilisin/kexin type 9 (PCSK9), one of the key regulators of the low-density lipoprotein receptor (LDLR), can play a direct role in atheroma development. Although advances in the understandings of genetic PCSK9 polymorphisms have enabled to reveal the role of PCSK9 in the complex pathophysiology of cardiovascular diseases (CVDs), increasing lines of evidence support non-cholesterol-related processes mediated by PCSK9. Owing to major improvements in mass spectrometry-based technologies, multimarker proteomic and lipidomic panels hold the promise to identify novel lipids and proteins potentially related to PCSK9. Within this context, this narrative review aims to provide an overview of the most significant proteomics and lipidomics studies related to PCSK9 effects beyond cholesterol lowering. These approaches have enabled to unveil non-common targets of PCSK9, potentially leading to the development of novel statistical models for CVD risk prediction. Finally, in the era of precision medicine, we have reported the impact of PCSK9 on extracellular vesicles (EVs) composition, an effect that could contribute to an increased prothrombotic status in CVD patients. The possibility to modulate EVs release and cargo could help counteract the development and progression of the atherosclerotic process.

(Glycan Binding) Activity-Based Protein Profiling in Cells Enabled by Mass Spectrometry-Based Proteomics.

The presence of glycan modifications at the cell surface and other locales positions them as key regulators of cell recognition and function. However, due to the complexity of glycosylation, the annotation of which proteins bear glycan modifications, which glycan patterns are present, and which proteins are capable of binding glycans is incomplete. Inspired by activity-based protein profiling to enrich for proteins in cells based on select characteristics, these endeavors have been greatly advanced by the development of appropriate glycan-binding and glycan-based probes. Here, we provide context for these three problems and describe how the capability of molecules to interact with glycans has enabled the assignment of proteins with specific glycan modifications or of proteins that bind glycans. Furthermore, we discuss how the integration of these probes with high resolution mass spectrometry-based technologies has greatly advanced glycoscience.

Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery.

Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.

Soluble HLA peptidome: A new resource for cancer biomarkers.

Using circulating molecular biomarkers to screen for cancer and other debilitating disorders in a high-throughput and low-cost fashion is becoming increasingly attractive in medicine. One major limitation of investigating protein biomarkers in body fluids is that only one-fourth of the entire proteome can be routinely detected in these fluids. In contrast, Human Leukocyte Antigen (HLA) presents peptides from the entire proteome on the cell surface. While peptide-HLA complexes are predominantly membrane-bound, a fraction of HLA molecules is released into body fluids which is referred to as soluble HLAs (sHLAs). As such peptides bound by sHLA molecules represent the entire proteome of their cells/tissues of origin and more importantly, recent advances in mass spectrometry-based technologies have allowed for accurate determination of these peptides. In this perspective, we discuss the current understanding of sHLA-peptide complexes in the context of cancer, and their potential as a novel, relatively untapped repertoire for cancer biomarkers. We also review the currently available tools to detect and quantify these circulating biomarkers, and we discuss the challenges and future perspectives of implementing sHLA biomarkers in a clinical setting.

Exercise, healthy ageing, and the potential role of small extracellular vesicles.

Extracellular vesicles (EVs) can be released from most cells in the body and act as intercellular messengers transferring information in their cargo to affect cellular function. A growing body of evidence suggests that a subset of EVs, referred to here as 'small extracellular vesicles' (sEVs), can accelerate or slow the processes of ageing and age-related diseases dependent on their molecular cargo and cellular origin. Continued exploration of the vast complexity of the sEV cargo aims to further characterise these systemic vehicles that may be targeted to ameliorate age-related pathologies. Marked progress in the development of mass spectrometry-based technologies means that it is now possible to characterise a significant proportion of the proteome of sEVs (surface and cargo) via unbiased proteomics. This information is vital for identifying biomarkers and the development of sEV-based therapeutics in the context of ageing. Although exercise and physical activity are prominent features in maintaining health in advancing years, the mechanisms responsible are unclear. A potential mechanism by which plasma sEVs released during exercise could influence ageing and senescence is via the increased delivery of cargo proteins that function as antioxidant enzymes or inhibitors of senescence. These have been observed to increase in sEVs following acute and chronic exercise, as identified via independent interrogation of high coverage, publicly available proteomic datasets. Establishing tropism and exchange of functionally active proteins by these processes represents a promising line of enquiry in implicating sEVs as biologically relevant mediators of the ageing process.

Mass spectrometry-based technologies for probing the 3D world of plant proteins.

Over the past two decades, mass spectrometric (MS)-based proteomics technologies have facilitated the study of signaling pathways throughout biology. Nowhere is this needed more than in plants, where an evolutionary history of genome duplications has resulted in large gene families involved in posttranslational modifications and regulatory pathways. For example, at least 5% of the Arabidopsis thaliana genome (ca. 1,200 genes) encodes protein kinases and protein phosphatases that regulate nearly all aspects of plant growth and development. MS-based technologies that quantify covalent changes in the side-chain of amino acids are critically important, but they only address one piece of the puzzle. A more crucially important mechanistic question is how noncovalent interactions-which are more difficult to study-dynamically regulate the proteome's 3D structure. The advent of improvements in protein 3D technologies such as cryo-electron microscopy, nuclear magnetic resonance, and X-ray crystallography has allowed considerable progress to be made at this level, but these methods are typically limited to analyzing proteins, which can be expressed and purified in milligram quantities. Newly emerging MS-based technologies have recently been developed for studying the 3D structure of proteins. Importantly, these methods do not require protein samples to be purified and require smaller amounts of sample, opening the wider proteome for structural analysis in complex mixtures, crude lysates, and even in intact cells. These MS-based methods include covalent labeling, crosslinking, thermal proteome profiling, and limited proteolysis, all of which can be leveraged by established MS workflows, as well as newly emerging methods capable of analyzing intact macromolecules and the complexes they form. In this review, we discuss these recent innovations in MS-based "structural" proteomics to provide readers with an understanding of the opportunities they offer and the remaining challenges for understanding the molecular underpinnings of plant structure and function.

Functional analysis of the stable phosphoproteome reveals cancer vulnerabilities.

MotivationThe advance of mass spectrometry-based technologies enabled the profiling of the phosphoproteomes of a multitude of cell and tissue types. However, current research primarily focused on investigating the phosphorylation dynamics in specific cell types and experimental conditions, whereas the phosphorylation events that are common across cell/tissue types and stable regardless of experimental conditions are, so far, mostly ignored.ResultsHere, we developed a statistical framework to identify the stable phosphoproteome across 53 human phosphoproteomics datasets, covering 40 cell/tissue types and 194 conditions/treatments. We demonstrate that the stably phosphorylated sites (SPSs) identified from our statistical framework are evolutionarily conserved, functionally important and enriched in a range of core signaling and gene pathways. Particularly, we show that SPSs are highly enriched in the RNA splicing pathway, an essential cellular process in mammalian cells, and frequently disrupted by cancer mutations, suggesting a link between the dysregulation of RNA splicing and cancer development through mutations on SPSs.Availability and implementationThe source code for data analysis in this study is available from Github repository https://github.com/PYangLab/SPSs under the open-source license of GPL-3. The data used in this study are publicly available (see Section 2.8).Supplementary information Supplementary data are available at Bioinformatics online.

Proteomics in Deaths by Drowning: Diagnostic Efficacy of Apolipoprotein A1 and α-1Antitrypsin, Pilot Study.

Drowning is one of the leading causes of death worldwide. The pathophysiology of drowning is complex and, sometimes, interpretation of the circumstances of death in the autopsy becomes the main source of information in its diagnosis. New advances in medical research, such as proteomics, especially in forensic pathology, are still in the development. We proposed to investigate the application of Mass Spectrometry-based technologies, to identify differentially expressed proteins that may act as potential biomarkers in the postmortem diagnosis of drowning. We performed a pilot proteomic experiment with the inclusion of two drowned and two control forensic cases. After applying restrictive parameters, we identified apolipoprotein A1 (ApoA1) and α-1 antitrypsin as differentially expressed between the two diagnostic groups. A validation experiment, with the determination of both proteins in 25 forensic cases (16 drowned and 9 controls) was performed, and we corroborated ApoA1 higher values in the drowning group, whereas α-1 antitrypsin showed lower levels. After adjusting by confounder factors, both remained as predictive independent factors for diagnosis of drowning (p = 0.010 and p = 0.022, respectively). We constructed ROC curves for biomarkers’ levels attending at the origin of death and established an ApoA1 cut-off point of 100 mg/dL. Correct classification based on the diagnosis criteria was reached for 73.9% of the cases in a discriminant analysis. We propose apolipoprotein A1 (with our cutoff value for correct classification) and α-1 antitrypsin as valuable biomarkers of drowning. Our study, based on forensic cases, reveals our proteomic approach as a new complementary tool in the forensic diagnosis of drowning and, perhaps, in clinical future implications in drowned patients. However, this is a pilot approach, and future studies are necessary to consolidate our promising preliminary data.

MULTIOMIC PATTERNS IN BODY FLUIDS: TECHNOLOGICAL CHALLENGE WITH A GREAT POTENTIAL TO IMPLEMENT THE ADVANCED PARADIGM OF 3P MEDICINE.

Liquid biopsy (LB) is defined as a sample of any of body fluids (blood, saliva, tear fluid, urine, sweat, amniotic, cerebrospinal and pleural fluids, cervicovaginal secretion, and wound efflux, amongst others), which can be ex vivo analysed to detect and quantity the target(s) of interest. LB represents diagnostic approach relevant for organ-specific changes and systemic health conditions including both manifested diseases and their prestages such as suboptimal health. Further, experts emphasise that DNA-based analysis alone does not provide sufficient information for optimal diagnostics and effective treatments. Consequently, of great scientific and clinical utility are molecular patterns detected by hybrid technologies such as metabolomic tools and molecular imaging. Future proposed strategies utilise multiomic pillars (generally genome, tanscriptome, proteome, metabolome, epigenome, radiome, and microbiome), system-biological approach, and multivariable algorithms for diagnostic, prognostic, and therapeutic purposes. Current article analyses pros and cons of the mass spectrometry-based technologies, provides eminent examples of a success story "from discovery to clinical application," and demonstrates a "road-map" for the technology-driven paradigm change from reactive to predictive, preventive and personalised medical services as the medicine of the future benefiting the patient and healthcare at large. © 2019 The Authors. Mass Spectrometry Reviews published by John Wiley & Sons Ltd. Mass Spec Rev.

Mass spectrometry-applications in pathology

Currently, more complex and extensive diagnostic pathology work-up of sometimes only limited sample material is necessary to ensure optimal patient treatment. This often includes genomic analyses. However, dynamic changes within an organism or tumor can be better reflected at the protein level. Therefore, proteomic technologies would seem to be the solution. To evaluate the application of different proteomic techniques to analyze body fluids and tissue samples with regards to implementation in diagnostics. All studies utilized mass spectrometry-based methods in order to achieve differentiation of anumber of different patient groups in various diseases. Whereas classical proteomic methods are particularly suitable for analyzing serum samples in order to diagnose bladder cancer or chronic hepatitisC, tissue analyses would require prior tissue lyses, thus erasing possible information to be obtained from histology. Imaging mass spectrometry offers a solution as it allows for the analysis of an intact tissue section. Possible applications and the added benefit of this method could be shown using various examples of tumors (prostate cancer, Hodgkin's lymphoma, cervical cancer, and different types of adenocarcinomas). Mass spectrometry-based technologies allow diagnostic confirmation with high sensitivity and specificity. In comparison to routine diagnostic approaches, results can be achieved faster, using less sample material, and with comparable accuracy.

Epigenetic drug target deconvolution by mass spectrometry-based technologies.

The identification of the full target spectrum of active molecules, known as target deconvolution, has become an indispensable step during the drug discovery process. It is now achievable thanks to mass spectrometry-based technologies. Here we discuss these approaches in the context of epigenetic drug discovery.

One-Step SH2 Superbinder-Based Approach for Sensitive Analysis of Tyrosine Phosphoproteome.

Tyrosine phosphorylation plays a major role in regulating cell signaling pathways governing diverse biological functions such as proliferation and differentiation. Systemically mapping phosphotyrosine (pTyr) sites is the key to understanding molecular mechanisms underlining pTyr-dependent signaling. Although mass spectrometry-based technologies have been widely used for pTyr site profiling and quantification, their applications are often hindered by the poor efficiency in current multistep enrichment procedures for inherently low abundance pTyr peptides, especially under physiological conditions. Taking advantage of the sequence-independent high affinity of SH2 superbinder toward pTyr residues, we have developed a simplified one-step pTyr peptide enrichment method that uses immobilized SH2 superbinder for unbiased and robust enrichment of endogenous pTyr peptides from biological samples. By eliminating the prerequisite global phosphopeptide enrichment step in our previously developed two-step method, we minimized sample loss and improved peptide capture efficiency. Applying this method to Jurkat cells at resting state, where the tyrosine phosphorylation level is low, both the number of identified pTyr peptides and sites are increased by three folds compared to the two-step method. Specifically, we were able to identify 511 nonredundant pTyr peptides, corresponding to 403 high confidence pTyr sites, from Jurkat cells with high level technical reproducibility (Pearson's correlation coefficient as high as 0.94). Further applying this method to two human breast cancer cell lines, BT474 and HCC1954, before and after EGF stimulation, we demonstrated that this approach could be a powerful tool for illustrating pTyr-dependent signaling network controlling cellular behaviors such as drug resistance.

The podocyte protease web: uncovering the gatekeepers of glomerular disease.

Proteases regulate glomerular physiology. The last decade has revealed a multitude of podocyte proteases that govern the glomerular response to numerous chemical, mechanical, and metabolic cues. These proteases form a protein signaling web that integrates stress stimuli and serves as a key controller of the glomerular microenvironment. Both the extracellular and intracellular proteolytic networks are perturbed in focal segmental glomerulosclerosis, as well as hypertensive and diabetic nephropathy. Accordingly, the highly intertwined podocyte protease web is an integrative part of the podocyte's damage response. Novel mass spectrometry-based technologies will help to untangle this proteolytic network: functional readouts acquired from deep podocyte proteomics, single glomerular proteomics, and degradomics have exposed unanticipated protease activity in podocytes. Future efforts should characterize the interdependency and upstream regulation of key proteases, along with their role in promoting tissue heterogeneity in glomerular diseases. These efforts will not only illuminate the machinery of podocyte proteostasis but also reveal avenues for therapeutic intervention in the podocyte protease web.

Impact of Mass Spectrometry-Based Technologies and Strategies on Chemoproteomics as a Tool for Drug Discovery.

Chemoproteomics is an invaluable tool to discover protein targets from phenotypic assays and to understand on- and off-target engagement of potential therapeutic compounds. Highlighted in this technology perspective is our view on how improvements in mass spectrometry (MS)-based proteomics technology have dramatically impacted chemoproteomics. Improvements in sample preparation, MS instrumentation, data acquisition, and quantification strategies have enabled medicinal chemists, chemical biologists, and mass spectrometrists to develop new chemoproteomic experiments and improve existing methods. As a result of improvements in MS, we will detail how bead-based affinity capture and activity-based proteome profiling methods have been reduced from multiple LC-MS runs for samples and controls down to a single LC-MS run each for sample and control. With improvements in scan duty cycle and sensitivity, sufficient depth of proteome coverage can be obtained for capture-free methods, which do not utilize an enrichment step.

Peptide Level Turnover Measurements Enable the Study of Proteoform Dynamics

The coordination of protein synthesis and degradation regulating protein abundance is a fundamental process in cellular homeostasis. Today, mass spectrometry-based technologies allow determination of endogenous protein turnover on a proteome-wide scale. However, standard dynamic SILAC (Stable Isotope Labeling in Cell Culture) approaches can suffer from missing data across pulse time-points limiting the accuracy of such analysis. This issue is of particular relevance when studying protein stability at the level of proteoforms because often only single peptides distinguish between different protein products of the same gene. To address this shortcoming, we evaluated the merits of combining dynamic SILAC and tandem mass tag (TMT)-labeling of ten pulse time-points in a single experiment. Although the comparison to the standard dynamic SILAC method showed a high concordance of protein turnover rates, the pulsed SILAC-TMT approach yielded more comprehensive data (6000 proteins on average) without missing values. Replicate analysis further established that the same reproducibility of turnover rate determination can be obtained for peptides and proteins facilitating proteoform resolved investigation of protein stability. We provide several examples of differentially turned over splice variants and show that post-translational modifications can affect cellular protein half-lives. For example, N-terminally processed peptides exhibited both faster and slower turnover behavior compared with other peptides of the same protein. In addition, the suspected proteolytic processing of the fusion protein FAU was substantiated by measuring vastly different stabilities of the cleavage products. Furthermore, differential peptide turnover suggested a previously unknown mechanism of activity regulation by post-translational destabilization of cathepsin D as well as the DNA helicase BLM. Finally, our comprehensive data set facilitated a detailed evaluation of the impact of protein properties and functions on protein stability in steady-state cells and uncovered that the high turnover of respiratory chain complex I proteins might be explained by oxidative stress.

A Comprehensive Analytical Strategy To Identify Malondialdehyde-Modified Proteins and Peptides.

Mass spectrometric-based proteomics is a powerful tool to analyze post-translationally modified proteins. Carbonylation modifications that result from oxidative lipid breakdown are a class of post-translational modifications that are poorly characterized with respect to protein targets and function. This is partly due to the lack of dedicated mass spectrometry-based technologies to facilitate the analysis of these modifications. Here, we present a comprehensive approach to identify malondialdehyde-modified proteins and peptides. Malondialdehyde is among the most abundant of the lipid peroxidation products; and malondialdehyde-derived adducts on proteins have been implicated in cardiovascular diseases, neurodegenerative disorders, and other clinical conditions. Our integrated approach targets three levels of the overall proteomic workflow: (i) sample preparation, by employing a targeted enrichment strategy; (ii) high-performance liquid chromatography, by using a gradient optimized for the separation of the modified peptides; and (iii) tandem mass spectrometry, by improving the spectral quality of very low-abundance peptides. By applying the optimized procedure to a whole cell lysate spiked with a low amount of malondialdehyde-modified proteins, we were able to identify up to 350 different modified peptides and localize the modification to a specific lysine residue. This methodology allows the comprehensive analysis of malondialdehyde-modified proteins.

Specific Metabolomics Adaptations Define a Differential Regional Vulnerability in the Adult Human Cerebral Cortex.

Brain neurons offer diverse responses to stresses and detrimental factors during development and aging, and as a result of both neurodegenerative and neuropsychiatric disorders. This multiplicity of responses can be ascribed to the great diversity among neuronal populations. Here we have determined the metabolomic profile of three healthy adult human brain regions—entorhinal cortex, hippocampus, and frontal cortex—using mass spectrometry-based technologies. Our results show the existence of a lessened energy demand, mitochondrial stress, and lower one-carbon metabolism (particularly restricted to the methionine cycle) specifically in frontal cortex. These findings, along with the better antioxidant capacity and lower mTOR signaling also seen in frontal cortex, suggest that this brain region is especially resistant to stress compared to the entorhinal cortex and hippocampus, which are more vulnerable regions. Globally, our results show the presence of specific metabolomics adaptations in three mature, healthy human brain regions, confirming the existence of cross-regional differences in cell vulnerability in the human cerebral cortex.

Biochemical and Mass Spectrometry-Based Approaches to Profile SUMOylation in Human Cells.

Posttranslational modification of proteins with the small ubiquitin-like modifier (SUMO) regulates protein function in the context of cell cycle and DNA repair. The occurrence of SUMOylation is less frequent as compared to protein modification with ubiquitin, and appears to be controlled by a smaller pool of conjugating and deconjugating enzymes. Mass spectrometry has been instrumental in defining specific as well as proteome-wide views of SUMO-dependent biological processes, and several methodological approaches have been developed in the recent past. Here, we provide an overview of the latest experimental approaches to the study of SUMOylation, and also describe hands-on protocols using a combination of biochemistry and mass spectrometry-based technologies to profile proteins that are SUMOylated in human cells.