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Tumor stemness is associated with the recurrence and incurability of colorectal cancer (CRC), which lacks effective therapeutic targets and drugs. Glycinamide ribonucleotide transformylase (GART) fulfills an important role in numerous types of malignancies. The present study aims to identify the underlying mechanism through which GART may promote CRC stemness, as to developing novel therapeutic methods. An elevated level of GART is associated with poor outcomes in CRC patients and promotes the proliferation and migration of CRC cells. CD133 + cells with increased GART expression possess higher tumorigenic and proliferative capabilities both in vitro and in vivo. GART is identified to have a novel methyltransferase function, whose enzymatic activity center is located at the E948 site. GART also enhances the stability of RuvB-like AAA ATPase 1 (RUVBL1) through methylating its K7 site, which consequently aberrantly activates the Wnt/β-catenin signaling pathway to induce tumor stemness. Pemetrexed (PEM), a compound targeting GART, combined with other chemotherapy drugs greatly suppresses tumor growth both in a PDX model and in CRC patients. The present study demonstrates a novel methyltransferase function of GART and the role of the GART/RUVBL1/β-catenin signaling axis in promoting CRC stemness. PEM may be a promising therapeutic agent for the treatment of CRC., (© 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Multiple myeloma (MM) is the second most common hematological malignancy, in which the dysfunction of the ubiquitin-proteasome pathway is associated with the pathogenesis. The valosin containing protein (VCP)/p97, a member of the AAA+ ATPase family, possesses multiple functions to regulate the protein quality control including ubiquitin-proteasome system and molecular chaperone. VCP is involved in the occurrence and development of various tumors while still elusive in MM. VCP inhibitors have gradually shown great potential for cancer treatment. This study aims to identify if VCP is a therapeutic target in MM and confirm the effect of a novel inhibitor of VCP (VCP20) on MM. We found that VCP was elevated in MM patients and correlated with shorter survival in clinical TT2 cohort. Silencing VCP using siRNA resulted in decreased MM cell proliferation via NF-κB signaling pathway. VCP20 evidently inhibited MM cell proliferation and osteoclast differentiation. Moreover, exosomes containing VCP derived from MM cells partially alleviated the inhibitory effect of VCP20 on cell proliferation and osteoclast differentiation. Mechanism study revealed that VCP20 inactivated the NF-κB signaling pathway by inhibiting ubiquitination degradation of IκBα. Furthermore, VCP20 suppressed MM cell proliferation, prolonged the survival of MM model mice and improved bone destruction in vivo . Collectively, our findings suggest that VCP is a novel target in MM progression. Targeting VCP with VCP20 suppresses malignancy progression of MM via inhibition of NF-κB signaling pathway.

Background: Glucose-6-phosphate dehydrogenase (G6PD) as the rate-limiting enzyme in the pentose phosphate pathway (PPP) is well-established as an aberrantly expressed protein in numerous clinical diseases; however, its role in cancer, specifically in multiple myeloma (MM) remains elusive., Methods: In this study, serum metabolites in 70 normal people and 70 newly diagnosed MM patients were analyzed using untargeted metabolomics and the results were verified using ELISA. The survival analysis of multiple clinical datasets was performed to identify a potential target gene in MM. The oncogenic role of G6PD was investigated using lentivirus-based overexpression or knockdown of G6PD using RNAi or an inhibitor in vitro, and in a xenograft mouse model in vivo. The mechanisms of induced Dexamethasone (Dexa)-resistance of G6PD were further explored using the above established MM cell lines in vitro., Results: Based on the screening of potential genes, PPP was shown to be involved in the occurrence of MM, which was evidenced by the differential expression of serum metabolites of G6P and Dehydroepiandrosterone sulfate (DHEAS, the more stable sulfate ester form of an endogenously uncompetitive G6PD inhibitor known as DHEA). Elevated G6PD promoted MM cell proliferation. Mechanistically, high G6PD expression enhanced enzymatic generation of the antioxidant NADPH via the PPP and decreased the production of reactive oxygen species (ROS), thus inducing the proliferation and Dexa resistance in MM cells. Furthermore, canonical Wnt/β-catenin signaling also participated in regulating G6PD-induced drug resistance and cellular redox levels of ROS. Intriguingly, DHEA treatment could enhance the sensitivity of MM cells to Dexa primarily through augmenting cellular oxidative stress., Conclusions: Our data demonstrate that G6PD enhances the generation of the enzymatic anti-oxidant NADPH and decreases ROS generation, thereby promoting resistance to Dexa-induced apoptosis via the enzymatic PPP and non-enzymatic Wnt/β-catenin signaling pathway in MM. Targeting G6PD to harness cellular redox may serve as a promising novel strategy for the management of MM., (© 2022. The Author(s).)

Crohn's disease (CD) is a subtype of inflammatory bowel disease (IBD) characterized by skip intestinal lesions that can occur in any part of the gastrointestinal tract. Currently, the diagnosis of CD is based on clinical history, physical examination and complementary diagnostic tests. It is challenging for physicians to make a definitive diagnosis. This study aimed to analyze the variation in metabolites in CD serum and identify potential predictive biomarkers of CD diagnosis. We collected serum samples from 316 subjects, including patients with CD and healthy controls (HCs). Serum metabolomics was conducted using liquid chromatography coupled to mass spectrometry. Potential biomarkers were screened and evaluated by univariate and multivariate analyses. A panel of two metabolites (deoxycholic acid and palmitic amide) was identified as a specific biomarker of CD. Receiver operating characteristic analysis (ROC) showed that the panel had a sensitivity of 80.25% with a specificity of 95.54% in discriminating CD patients from healthy controls. The biomarkers identified are increased in CD compared with healthy controls. Our approach successfully identified serum biomarkers associated with CD patients. The potential biomarkers indicated that CD metabolic disturbance might be associated with bile acid biosynthesis, fatty acids and energy metabolism., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Liu, Xu, He, Wei, Ke and Liu.)

Objectives: This study aimed to characterize the systemic lipid profile of patients with asymptomatic hyperuricemia (HUA) and gout using lipidomics, and to find potential underlying pathological mechanisms therefrom., Methods: Sera were collected from Affiliated Hospital of Nanjing University of Chinese Medicine as centre 1 (discovery and internal validation sets) and Suzhou Hospital of Traditional Chinese Medicine as centre 2 (external validation set), including 88 normal subjects, 157 HUA and 183 gout patients. Lipidomics was performed by ultra high performance liquid chromatography plus Q-Exactive mass spectrometry (UHPLC-Q Exactive MS). Differential metabolites were identifed by both variable importance in the projection ≥1 in orthogonal partial least-squares discriminant analysis mode and false discovery rate adjusted P ≤ 0.05. Biomarkers were found by logistic regression and receiver operating characteristic (ROC) analysis., Results: In the discovery set, a total of 245 and 150 metabolites, respectively, were found for normal subjects vs HUA and normal subjects vs gout. The disturbed metabolites included diacylglycerol, triacylglycerol (TAG), phosphatidylcholine, phosphatidylethanolamine, phosphatidylinositol, etc. We also found 116 differential metabolites for HUA vs gout. Among them, the biomarker panel of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 could differentiate well between HUA and gout. The area under the receiver operating characteristic ROC curve was 0.8288, the sensitivity was 82% and the specificity was 78%, at a 95% CI 0.747, 0.9106. In the internal validation set, the predictive accuracy of TAG 18:1-20:0-22:1 and TAG 14:0-16:0-16:1 panel for differentiation of HUA and gout reached 74.38%, while it was 84.03% in external validation set., Conclusion: We identified serum biomarkers panel that have the potential to predict and diagnose HUA and gout patients., (© The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In diabetes mellitus (DM), disorders of glucose and lipid metabolism are significant causes of the onset and progression of diabetic nephropathy (DN). However, the exact roles of specific lipid molecules in the pathogenesis of DN remain unclear. This study recruited 577 participants, including healthy controls (HCs), type-2 DM (2-DM) patients, and DN patients, from the clinic. Serum samples were collected under fasting conditions. Liquid chromatography-mass spectrometry-based lipidomics methods were used to explore the lipid changes in the serum and identify potential lipid biomarkers for the diagnosis of DN. Lipidomics revealed that the combination of lysophosphatidylethanolamine (LPE) (16:0) and triacylglycerol (TAG) 54:2-FA18:1 was a biomarker panel for predicting DN. The receiver operating characteristic analysis showed that the panel had a sensitivity of 89.1% and 73.4% with a specificity of 88.1% and 76.7% for discriminating patients with DN from HCs and 2-DM patients. Then, we divided the DN patients in the validation cohort into microalbuminuria (diabetic nephropathy at an early stage, DNE) and macroalbuminuria (diabetic nephropathy at an advanced stage, DNA) groups and found that LPE(16:0), phosphatidylethanolamine (PE) (16:0/20:2), and TAG54:2-FA18:1 were tightly associated with the stages of DN. The sensitivity of the biomarker panel to distinguish between patients with DNE and 2-DM, DNA, and DNE patients was 65.6% and 85.9%, and the specificity was 76.7% and 75.0%, respectively. Our experiment showed that the combination of LPE(16:0), PE(16:0/20:2), and TAG54:2-FA18:1 exhibits excellent performance in the diagnosis of DN., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Xu, Xu, Zhang, Zhang, Wei, Zhu, Yu, Xiao, Lin, Qian, Wang, Ke, An and Liu.)

Background: Diagnosing seronegative rheumatoid arthritis (RA) can be challenging due to complex diagnostic criteria. We sought to discover diagnostic biomarkers for seronegative RA cases by studying metabolomic and lipidomic changes in RA patient serum., Methods: We performed comprehensive metabolomic and lipidomic profiling in serum of 225 RA patients and 100 normal controls. These samples were divided into a discovery set (n = 243) and a validation set (n = 82). A machine-learning-based multivariate classification model was constructed using distinctive metabolites and lipids signals., Results: Twenty-six metabolites and lipids were identified from the discovery cohort to construct a RA diagnosis model. The model was subsequently tested on a validation set and achieved accuracy of 90.2%, with sensitivity of 89.7% and specificity of 90.6%. Both seropositive and seronegative patients were identified using this model. A co-occurrence network using serum omics profiles was built and parsed into six modules, showing significant association between the inflammation and immune activity markers and aberrant metabolism of energy metabolism, lipids metabolism and amino acid metabolism. Acyl carnitines (20:3), aspartyl-phenylalanine, pipecolic acid, phosphatidylethanolamine PE (18:1) and lysophosphatidylethanolamine LPE (20:3) were positively correlated with the RA disease activity, while histidine and phosphatidic acid PA (28:0) were negatively correlated with the RA disease activity., Conclusions: A panel of 26 serum markers were selected from omics profiles to build a machine-learning-based prediction model that could aid in diagnosing seronegative RA patients. Potential markers were also identified in stratifying RA cases based on disease activity., (© 2021. The Author(s).)

Multiple myeloma (MM) is a hematological malignancy worldwide in urgent need for novel therapeutic strategies. Since Velcade (bortezomib) was approved for the treatment of relapsed/refractory MM in 2003, we have seen considerable improvement in extending MM patient survival. However, most patients are fraught with high recurrence rate and incurability. Acupuncture is known for alleviating patient symptoms and improving the quality of life, but it is not well investigated in MM, especially in combination with bortezomib. In this study, we employed LC-MS and UHPLC-MS together with bioinformatics methods to test serum samples from 5TMM3VT MM murine model mice with four different treatments [control (C) group, bortezomib (V) treatment group, acupuncture (A) group, and combined (VA) group]. MM mice in group VA had longer survival time than mice in group A or group V. Joint pathway analysis indicated the underlying arginine and proline metabolism pathway among the 32 significantly decreased metabolites in group VA. CCK-8 assay and in vivo experiments validated that ornithine, the metabolite of arginine, promoted MM cell proliferation. In addition, gene expression omnibus (GEO) database analysis suggested that MM patients with higher ornithine decarboxylase 1 (ODC1) expression were evidently associated with poor overall survival. In summary, this study demonstrates the synergistic effects of acupuncture and bortezomib on extending the survival of MM model mice and provides potential therapeutic targets in the treatment of MM., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Ke, Qian, Hao, Li, Wu, Luo, Xu, Gu and Yang.)

Objectives: At present, the pathogenesis of Sjögren's syndrome (SS) remains unclear. This research aimed to identify differential metabolites that contribute to SS diagnosis and discover the disturbed metabolic pathways., Methods: Recent advances in mass spectrometry have allowed the identification of hundreds of unique metabolic signatures and the exploration of altered metabolite profiles in disease. In this study, 505 candidates including healthy controls (HCs) and SS patients were recruited and the serum samples were collected. A non-targeted gas chromatography-mass spectrometry (GC-MS) serum metabolomics method was used to explore the changes in serum metabolites., Results: We found SS patients and HCs can be distinguished by 21 significant metabolites. The levels of alanine, tryptophan, glycolic acid, pelargonic acid, cis-1-2-dihydro-1-2-naphthalenediol, diglycerol, capric acid, turanose, behenic acid, dehydroabietic acid, stearic acid, linoleic acid, heptadecanoic acid, valine, and lactic acid were increased in serum samples from SS patients, whereas levels of catechol, anabasine, 3-6-anhydro-D-galactose, beta-gentiobiose, 2-ketoisocaproic acid and ethanolamine were decreased. The significantly changed pathways included the following: Linoleic acid metabolism; unsaturated fatty acid biosynthesis; aminoacyl-tRNA biosynthesis; valine, leucine, and isoleucine biosynthesis; glycerolipid metabolism; selenocompound metabolism; galactose metabolism; alanine, aspartate and glutamate metabolism; glyoxylate and dicarboxylate metabolism; glycerophospholipid metabolism; and valine, leucine and isoleucine degradation., Conclusions: These findings enhance the informative capacity of biochemical analyses through the identification of serum biomarkers and the analysis of metabolic pathways and contribute to an improved understanding of the pathogenesis of SS.

Multiple myeloma (MM) is an incurable plasma cell malignancy in the bone marrow characterized by chromosome instability (CIN), which contributes to the acquisition of heterogeneity, along with MM progression, drug resistance, and relapse. In this study, we elucidated that the expression of BUB1B increased strikingly in MM patients and was closely correlated with poor outcomes. Overexpression of BUB1B facilitated cellular proliferation and induced drug resistance in vitro and in vivo, while genetic targeting BUB1B abrogated this effect. Mechanistic studies unveiled that enforced expression of BUB1B evoked CIN resulting in MM poor outcomes mainly through phosphorylating CEP170. Interestingly, we discovered the existence of circBUB1B_544aa containing the kinase catalytic center of BUB1B, which was translated by a circular RNA of BUB1B. The circBUB1B_544aa elevated in MM peripheral blood samples was closely associated with MM poor outcomes and played a synergistic effect with BUB1B on evoking CIN. In addition, MM cells could secrete circBUB1B_544aa and interfere the MM microenvironmental cells in the same manner as BUB1B full-length protein. Intriguingly, BUB1B siRNA, targeting the kinase catalytic center of both BUB1B and circBUB1B_544aa, significantly inhibited MM malignancy in vitro and in vivo. Collectively, BUB1B and circBUB1B_544aa are promising prognostic and therapeutic targets of MM., (© 2021. The Author(s).)

Objective: The relationship between serum lipid variations in SS and healthy controls was investigated to identify potential predictive lipid biomarkers., Methods: Serum samples from 230 SS patients and 240 healthy controls were collected. The samples were analysed by ultrahigh-performance liquid chromatography coupled with Q Exactive™ spectrometry. Potential lipid biomarkers were screened through orthogonal projection to latent structures discriminant analysis and further evaluated by receiver operating characteristic analysis., Results: A panel of three metabolites [phosphatidylcholine (18:0/22:5), triglyceride (16:0/18:0/18:1) and acylcarnitine (12:0)] was identified as a specific biomarker of SS. The receiver operating characteristic analysis showed that the panel had a sensitivity of 84.3% with a specificity of 74.8% in discriminating patients with SS from healthy controls., Conclusion: Our approach successfully identified serum biomarkers associated with SS patients. The potential lipid biomarkers indicated that SS metabolic disturbance might be associated with oxidized lipids, fatty acid oxidation and energy metabolism., (© The Author(s) 2020. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Rheumatoid arthritis (RA), afflicting over 1% of the population, is an inflammatory joint disease leading to cartilage damage and ultimately impaired joint function. Disease-modifying anti-rheumatic drugs are considered as the first-line treatment to inhibit the progression of RA, and the treatment depends on the disease status assessment. The disease activity score 28 as clinical gold standard is extensively used for RA assessment, but it has the limitations of delayed assessment and the need for specialized expertise. It is necessary to discover biomarkers that can precisely monitor disease activity, and provide optimized treatment for RA patients. A total of 1,244 participants from two independent centers were divided into five cohorts. Cohorts 1-4 constituted sera samples of moderate to high active RA, low active RA, RA in remission and healthy subjects. Cohort 5 consisted of sera of RA, osteoarthritis (OA), ankylosing spondylitis (AS), systemic lupus erythematosus (SLE), primary Sjogren's syndrome (pSS) and healthy subjects. Biomarkers were found from cohorts 1-2 (screening sets), cohort 3 (discovery and external validation sets), cohort 4 (drug intervention set) and cohort 5 (biomarker-specific evaluation set). We found 68 upregulated and 74 downregulated proteins by TMT-labeled proteomics in cohort 1, and fibrinogen-like protein 1 (FGL1) had the highest area under the receiver operating characteristic curve (AUC) values in cohort 2. In cohort 3, in cross-comparison among moderate/high active RA, low active RA, RA in remission and healthy subjects, FGL1 had AUC values of approximately 0.9000 and predictive values of 90%. Additionally, FGL1 had a predictive value of 91.46% for moderate/high active RA vs. remission/low active RA and 80.77% for RA in remission vs. low active RA in cohort 4. Importantly, FGL1 levels had no significant difference in OA and AS compared with healthy persons. The concentrations in SLE and pSS were improved, but approximately 3-fold lower than that in active RA in cohort 5. In summary, FGL1 is a novel and specific biomarker that could be clinically useful for predicting progression of RA., (Copyright © 2020 Liu, Guo, Lu, Lu, Ke, Xu, Lu, Chen, Wang, Kong, Shen, Zhu, Tan, Ji and Zhou.)