ER-associated degradation ligase HRD1 links ER stress to DNA damage repair by modulating the activity of DNA-PKcs.

Proteostasis and genomic integrity are respectively regulated by the endoplasmic reticulum-associated protein degradation (ERAD) and DNA damage repair signaling pathways, with both pathways essential for carcinogenesis and drug resistance. How these signaling pathways coordinate with each other remains unexplored. We found that ER stress specifically induces the DNA-PKcs-regulated nonhomologous end joining (NHEJ) pathway to amend DNA damage and impede cell death. Intriguingly, sustained ER stress rapidly decreased the activity of DNA-PKcs and DNA damage accumulated, facilitating a switch from adaptation to cell death. This DNA-PKcs inactivation was caused by increased KU70/KU80 protein degradation. Unexpectedly, the ERAD ligase HRD1 was found to efficiently destabilize the classic nuclear protein HDAC1 in the cytoplasm, by catalyzing HDAC1's polyubiquitination at lysine 74, at a late stage of ER stress. By abolishing HDAC1-mediated KU70/KU80 deacetylation, HRD1 transmits ER signals to the nucleus. The resulting enhanced KU70/KU80 acetylation provides binding sites for the nuclear E3 ligase TRIM25, resulting in the promotion of polyubiquitination and the degradation of KU70/KU80 proteins. Both in vitro and in vivo cancer models showed that genetic or pharmacological inhibition of HADC1 or DNA-PKcs sensitizes colon cancer cells to ER stress inducers, including the Food and Drug Administration-approved drug celecoxib. The antitumor effects of the combined approach were also observed in patient-derived xenograft models. These findings identify a mechanistic link between ER stress (ERAD) in the cytoplasm and DNA damage (NHEJ) pathways in the nucleus, indicating that combined anticancer strategies may be developed that induce severe ER stress while simultaneously inhibiting KU70/KU80/DNA-PKcs-mediated NHEJ signaling.

Longitudinal integrative cell-free DNA analysis in gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) presents varied manifestations throughout pregnancy and poses a complex clinical challenge. High-depth cell-free DNA (cfDNA) sequencing analysis holds promise in advancing our understanding of GDM pathogenesis and prediction. In 299 women with GDM and 299 matched healthy pregnant women, distinct cfDNA fragment characteristics associated with GDM are identified throughout pregnancy. Integrating cfDNA profiles with lipidomic and single-cell transcriptomic data elucidates functional changes linked to altered lipid metabolism processes in GDM. Transcription start site (TSS) scores in 50 feature genes are used as the cfDNA signature to distinguish GDM cases from controls effectively. Notably, differential coverage of the islet acinar marker gene PRSS1 emerges as a valuable biomarker for GDM. A specialized neural network model is developed, predicting GDM occurrence and validated across two independent cohorts. This research underscores the high-depth cfDNA early prediction and characterization of GDM, offering insights into its molecular underpinnings and potential clinical applications.

Integration of metagenomics and metaproteomics in the intestinal lavage fluids benefits construction of discriminative model and discovery of biomarkers for HBV liver diseases.

Intestinal lavage fluid (IVF) containing the mucosa-associated microbiota instead of fecal samples was used to study the gut microbiota using different omics approaches. Focusing on the 63 IVF samples collected from healthy and hepatitis B virus-liver disease (HBV-LD), a question is prompted whether omics features could be extracted to distinguish these samples. The IVF-related microbiota derived from the omics data was classified into two enterotype sets, whereas the genomics-based enterotypes were poorly overlapped with the proteomics-based one in either distribution of microbiota or of IVFs. There is lack of molecular features in these enterotypes to specifically recognize healthy or HBV-LD. Running machine learning against the omics data sought the appropriate models to discriminate the healthy and HBV-LD IVFs based on selected genes or proteins. Although a single omics dataset is basically workable in such discrimination, integration of the two datasets enhances discrimination efficiency. The protein features with higher frequencies in the models are further compared between healthy and HBV-LD based on their abundance, bringing about three potential protein biomarkers. This study highlights that integration of metaomics data is beneficial for a molecular discriminator of healthy and HBV-LD, and reveals the IVF samples are valuable for microbiome in a small cohort.

Lipidomic studies revealing serological markers associated with the occurrence of retinopathy in type 2 diabetes.

PURPOSE: The duration of type 2 diabetes mellitus (T2DM) and blood glucose levels have a significant impact on the development of T2DM complications. However, currently known risk factors are not good predictors of the onset or progression of diabetic retinopathy (DR). Therefore, we aimed to investigate the differences in the serum lipid composition in patients with T2DM, without and with DR, and search for potential serological indicators associated with the development of DR. METHODS: A total of 622 patients with T2DM hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Xi'an JiaoTong University were selected as the discovery set. One-to-one case-control matching was performed according to the traditional risk factors for DR (i.e., age, duration of diabetes, HbA1c level, and hypertension). All cases with comorbid chronic kidney disease were excluded to eliminate confounding factors. A total of 42 pairs were successfully matched. T2DM patients with DR (DR group) were the case group, and T2DM patients without DR (NDR group) served as control subjects. Ultra-performance liquid chromatography-mass spectrometry (LC-MS/MS) was used for untargeted lipidomics analysis on serum, and a partial least squares discriminant analysis (PLS-DA) model was established to screen differential lipid molecules based on variable importance in the projection (VIP) > 1. An additional 531 T2DM patients were selected as the validation set. Next, 1:1 propensity score matching (PSM) was performed for the traditional risk factors for DR, and a combined 95 pairings in the NDR and DR groups were successfully matched. The screened differential lipid molecules were validated by multiple reaction monitoring (MRM) quantification based on mass spectrometry. RESULTS: The discovery set showed no differences in traditional risk factors associated with the development of DR (i.e., age, disease duration, HbA1c, blood pressure, and glomerular filtration rate). In the DR group compared with the NDR group, the levels of three ceramides (Cer) and seven sphingomyelins (SM) were significantly lower, and one phosphatidylcholine (PC), two lysophosphatidylcholines (LPC), and two SMs were significantly higher. Furthermore, evaluation of these 15 differential lipid molecules in the validation sample set showed that three Cer and SM(d18:1/24:1) molecules were substantially lower in the DR group. After excluding other confounding factors (e.g., sex, BMI, lipid-lowering drug therapy, and lipid levels), multifactorial logistic regression analysis revealed that a lower abundance of two ceramides, i.e., Cer(d18:0/22:0) and Cer(d18:0/24:0), was an independent risk factor for the occurrence of DR in T2DM patients. CONCLUSION: Disturbances in lipid metabolism are closely associated with the occurrence of DR in patients with T2DM, especially in ceramides. Our study revealed for the first time that Cer(d18:0/22:0) and Cer(d18:0/24:0) might be potential serological markers for the diagnosis of DR occurrence in T2DM patients, providing new ideas for the early diagnosis of DR.

Identification of pyruvic and maleic acid as potential markers for disease activity and prognosis in chronic urticaria.

BACKGROUND: Population-based studies have highlighted the link between chronic urticaria (CU) and metabolic syndrome, and metabolic alterations have been revealed in CU. However, to our knowledge, a comprehensive metabolomics study on a large cohort of patients with CU has not been reported. OBJECTIVE: We sought to explore the underlying metabolic subtypes and novel metabolite biomarkers for CU diagnosis and therapy. METHODS: Plasma samples from 80 patients with CU and 82 healthy controls were collected for metabolomics quantification and bioinformatics analysis. Another independent cohort consisting of 144 patients with CU was studied to validate the findings. Bone marrow-derived mast cells and mice with IgE-induced passive cutaneous anaphylaxis were used for in vitro and in vivo experiments, respectively. RESULTS: We observed clear metabolome differences between CU patients and healthy controls. Meanwhile, differential metabolites N6-acetyl-l-lysine, l-aspartate, maleic acid, and pyruvic acid were used to construct random forest classifiers and achieved area under receiver operating characteristic curve values greater than 0.85, suggesting their potential as diagnostic biomarkers of CU. More importantly, by exploring the underlying metabolic subtypes of CU, we found that the low abundance of pyruvic acid and maleic acid was significantly related to the activity of CU, poor efficacy of second-generation H1 antihistamines, and short relapse-free time. The results were validated in the independent cohort. Moreover, supplementation with pyruvate or maleate could significantly attenuate IgE-mediated mast cell activation in vitro and in vivo. CONCLUSIONS: Plasma pyruvic acid and maleic acid may be effective biomarkers for predicting disease activity, therapeutic efficacy, and prognosis for patients with CU.

A biomarker panel of secondary hypertension is simultaneously quantified by coupling of magnetic solid-phase extraction and liquid chromatography-tandem mass spectrometry.

RATIONALE: Secondary hypertension is often caused by activation of complex multi-organ endocrine systems, while renin activity indicated by angiotensins (Angs), aldosterone (ALD) and cortisol (COR) in such systems are generally accepted as its diagnostic markers. As antibody-based methods cannot offer comparable quantification for these biomarkers, a liquid chromatography (LC)-tandem mass spectrometry (MS/MS)-based approach was developed to quantify them simultaneously and accurately. METHODS: Five different beads for magnetic solid-phase extraction (MSPE) were evaluated towards their enrichment efficiency for these biomarkers. An LC system with optimized elution gradient and a triple-quadrupole MS with tuned parameters were coupled to quantitatively monitor the extracted analytes. The method performance was further examined such as linearity, precision, stability, recovery rate and matrix effect. Based on the developed method, the abundance of Ang II, ALD and COR in plasma was measured and the quantification was compared with that derived from commercial ELISA kits. RESULTS: As compared with other MSPEs, Angs, ALD and COR were highly enriched by the HLB magnetic beads with satisfactory recoveries. These analytes were simultaneously quantified by LC/MS/MS and all the method parameters for quantification were well matched with the requirements of clinical testing. Comparison of the quantitative results derived from ELISA and LC/MS/MS exhibited that the two methods offered basically comparable values with Pearson r values at 0.896, 0.895 and 0.835, respectively. The stability test for plasma Angs at room temperature indicated that the abundance of Ang II was relatively stable within 3 h, whereas that of Ang I and Ang 1-7 was time-dependently changed. CONCLUSIONS: Coupling of HLB beads and LC/MS/MS thus enables simultaneous quantification of a set of biomarkers related to secondary hypertension.

SMURF2 predisposes cancer cell toward ferroptosis in GPX4-independent manners by promoting GSTP1 degradation.

Ferroptosis is a non-apoptotic form of regulated cell death. Glutathione (GSH) peroxidase 4 (GPX4) and GSH-independent ferroptosis suppressor protein 1 (FSP1) have been identified as major defenses. Here, we uncover a protective mechanism mediated by GSH S-transferase P1 (GSTP1) by monitoring proteinomic dynamics during ferroptosis. Dramatic downregulation of GSTP1 is caused by SMURF2-mediated GSTP1 ubiquitination and degradation at early stages of ferroptosis. Intriguingly, GSTP1 acts in GPX4- and FSP1-independent manners by catalyzing GSH conjugation of 4-hydroxynonenal and detoxifying lipid hydroperoxides via selenium-independent GSH peroxidase activity. Genetic modulation of the SMURF2/GSTP1 axis or the pharmacological inhibition of GSTP1's catalytic activity sensitized tumor responses to Food and Drug Administration (FDA)-approved ferroptosis-inducing drugs both in vitro and in vivo. GSTP1 expression also confers resistance to immune checkpoint inhibitors by blunting ferroptosis. Collectively, these findings demonstrate a GPX4/FSP1-independent cellular defense mechanism against ferroptosis and suggest that targeting SMURF2/GSTP1 to sensitize cancer cells to ferroptosis has potential as an anticancer therapy.

LC-MS/MS-Based Absolute Quantitation of Hemoglobin Subunits from Dried Blood Spots Reveals Novel Biomarkers for α-Thalassemia Silent Carriers.

Identification of α-thalassemia silent carriers is challenging with conventional phenotype-based screening methods. A liquid chromatography tandem mass spectrometry (LC-MS/MS)-based approach may offer novel biomarkers to address this conundrum. In this study, we collected dried blood spot samples from individuals with three α-thalassemia subtypes for biomarker discovery and validation. We observed differential expression patterns of hemoglobin subunits among various α-thalassemia subtypes and normal controls through proteomic profiling of 51 samples in the discovery phase. Then, we developed and optimized a multiple reaction monitoring (MRM) assay to measure all detectable hemoglobin subunits. The validation phase was conducted in a cohort of 462 samples. Among the measured hemoglobin subunits, subunit µ was significantly upregulated in all the α-thalassemia groups with distinct fold changes. The hemoglobin subunit µ exhibits great potential as a novel biomarker for α-thalassemia, especially for silent α-thalassemia. We constructed predictive models based on the concentrations of hemoglobin subunits and their ratios to classify the various subtypes of α-thalassemia. In the binary classification problems of silent α-thalassemia vs normal, non-deletional α-thalassemia vs normal, and deletional α-thalassemia vs normal, the best performance of the models achieved average ROCAUCs of 0.9505, 0.9430, and 0.9976 in the cross-validation, respectively. In the multiclass model, the best performance achieved an average ROCAUC of 0.9290 in cross-validation. The performance of our MRM assay and models demonstrated that the hemoglobin subunit µ would play a vital role in screening silent α-thalassemia in clinical practice.

Long noncoding RNA HITT coordinates with RGS2 to inhibit PD-L1 translation in T cell immunity.

Programmed cell death ligand 1 (PD-L1) is an immune checkpoint protein frequently expressed in human cancers that contributes to immune evasion through its binding to PD-1 on activated T cells. Unveiling the mechanisms underlying PD-L1 expression is essential for understanding the impact of the immunosuppressive microenvironment and is also crucial for the purpose of reboosting antitumor immunity. However, how PD-L1 is regulated, particularly at translational levels, remains largely unknown. Here, we discovered that a long noncoding RNA (lncRNA), HIF-1α inhibitor at translation level (HITT), was transactivated by E2F transcription factor 1 (E2F1) under IFN-γ stimulation. It coordinated with regulator of G protein signaling 2 (RGS2) in binding to the 5' UTR of PD-L1, resulting in reduced PD-L1 translation. HITT expression enhanced T cell-mediated cytotoxicity both in vitro and in vivo in a PD-L1-dependent manner. The clinical correlation between HITT/PD-L1 and RGS2/PD-L1 expression was also detected in breast cancer tissues. Together, these findings demonstrate the role of HITT in antitumor T cell immunity, highlighting activation of HITT as a potential therapeutic strategy for enhancing cancer immunotherapy.

Maternal plasma diacylglycerols and triacylglycerols in the prediction of gestational diabetes mellitus.

OBJECTIVE: To define the lipidomic profile in plasma across pregnancy, and identify lipid biomarkers for gestational diabetes mellitus (GDM) prediction in early pregnancy. DESIGN: Case-control study. SETTING: Tertiary referral maternity unit. POPULATION OR SAMPLE: Plasma samples from 100 GDM and 100 normal glucose tolerance (NGT) women, divided into a training set (GDM first trimester = 50, GDM second trimester = 40, NGT first trimester = 50, NGT second trimester = 50) and a validation set (GDM first trimester = 45, GDM second trimester = 34, NGT first trimester = 44, NGT second trimester = 40). METHODS: Plasma samples were collected in the first (11+0 to 13+6 weeks), second (19+0 to 24+6 weeks), and third trimesters (30+0 to 34+6 weeks), and tested by ultra-high-performance liquid chromatography coupled with electrospray ionisation-quadrupole-time of flight-mass spectrometry; The GDM prediction model was established by the machine-learning method of random forest. MAIN OUTCOME MEASURES: Gestational diabetes mellitus. RESULTS: In both the GDM and NGT group, lyso-glycerophospholipids were down-regulated, whereas ceramides, sphingomyelins, cholesteryl ester, diacylglycerols (DGs) and triacylglycerols (TGs) and glucosylceramide were up-regulated across the three trimesters of pregnancy. In the training dataset, seven TGs and five DGs demonstrated good performance in the prediction of GDM in the first and second trimesters (area under the curve [AUC] = 0.96 with 95% confidence interval [CI] of 0.93-1 and AUC = 0.97 with 95% CI of 0.95-1, respectively), independent of maternal body mass index (BMI) and ethnicity. In the validation dataset, the predictive model achieved an AUC of 0.88 and 0.94 at the first and second trimesters, respectively. CONCLUSIONS: Our results have proposed new lipid biomarkers for the first trimester prediction of GDM, independent of ethnicity and BMI.

Lipidomic profiling reveals metabolic signatures in psoriatic skin lesions.

Psoriasis is a chronic immune-mediated inflammatory disease. Lipids play an important role in regulating the inflammatory response. However, the alteration of lipids involved in psoriasis particular in skin lesions remain unclear. Here, we performed the lipidomics to investigate lipid profiling in the skin lesions of the imiquimod-induced psoriasis-like dermatitis and psoriasis patients. The findings showed that ceramides phosphate (CerP) and ceramides were enriched in psoriatic lesions compared with controls from both psoriasis patients and psoriasis-like mouse model. Psoriasis patients were classified into two subtypes, the CC1 and CC2, by consensus clustering of these lipid signatures. The CC1 was characterized by the higher levels of CerP, uric acid, and more severe psoriasis, compared with CC2 subtype. Interestingly, ceramide-1-phosphate (C1P), dramatically enriched in CC1 subtype, facilitated imiquimod-induced psoriasis-like inflammatory responses. Mechanistically, C1P induced the expression of inflammatory factors and activated DNA replication and cell cycle signaling pathways in the primary keratinocytes. Inhibiting the production of C1P with ceramide kinase inhibitor effectively alleviated the imiquimod-induced psoriasis-like inflammation. Taken together, we described the landscape of lipids alteration and established lipids classification based on pattern of abundance of lipids in psoriatic skin lesions. Suppression of C1P pathway is a novel potential strategy for psoriasis treatment.

Integrative lipidomic features identify plasma lipid signatures in chronic urticaria.

Chronic urticaria (CU) is a chronic inflammatory skin disease mainly mediated by mast cells. Lipids exert essential functions in biological processes; however, the role of lipids in CU remains unclear. Nontargeted lipidomics was performed to investigate the differential lipid profiles between CU patients and healthy control (HC) subjects. Functional validation studies were performed in vitro and in vivo including ß-hexosaminidase release examination from mast cells and passive cutaneous anaphylaxis (PCA) mouse model. We detected dramatically altered glycerophospholipids in CU patients compared with HCs. Phosphatidylserine (PS), phosphatidylethanolamine (PE), and phosphatidylglycerol (PG) were increased, while phosphatidylcholine (PC) was reduced in CU patients. The reduction in PC was related to a high weekly urticaria activity score (UAS7), while PS was positively associated with the dermatology life quality index (DLQI). We also identified the differential lipid profiles between chronic spontaneous urticaria (CSU), symptomatic dermographism (SD), and CSU coexist with SD. CU patients were classified into two subtypes (subtype 1 and subtype 2) based on consensus clustering of lipid profiling. Compared with patients in subtype 2, patients in subtype 1 had elevated levels of PC (18:0e/18:2) and PE (38:2), and lower urticaria control test (UCT) scores indicated worse clinical efficiency of secondary generation H1 antihistamines treatment. Importantly, we found that supplementation with PC could attenuate IgE-induced immune responses in mast cells. In general, We described the landscape of plasma lipid alterations in CU patients and provided novel insights into the role of PC in mast cells.

IntroSpect: Motif-Guided Immunopeptidome Database Building Tool to Improve the Sensitivity of HLA I Binding Peptide Identification by Mass Spectrometry.

Although database search tools originally developed for shotgun proteome have been widely used in immunopeptidomic mass spectrometry identifications, they have been reported to achieve undesirably low sensitivities or high false positive rates as a result of the hugely inflated search space caused by the lack of specific enzymic digestions in immunopeptidome. To overcome such a problem, we developed a motif-guided immunopeptidome database building tool named IntroSpect, which is designed to first learn the peptide motifs from high confidence hits in the initial search, and then build a targeted database for refined search. Evaluated on 18 representative HLA class I datasets, IntroSpect can improve the sensitivity by an average of 76%, compared to conventional searches with unspecific digestions, while maintaining a very high level of accuracy (~96%), as confirmed by synthetic validation experiments. A distinct advantage of IntroSpect is that it does not depend on any external HLA data, so that it performs equally well on both well-studied and poorly-studied HLA types, unlike the previously developed method SpectMHC. We have also designed IntroSpect to keep a global FDR that can be conveniently controlled, similar to a conventional database search. Finally, we demonstrate the practical value of IntroSpect by discovering neoepitopes from MS data directly, an important application in cancer immunotherapies. IntroSpect is freely available to download and use.

iASPP suppresses Gp78-mediated TMCO1 degradation to maintain Ca2+ homeostasis and control tumor growth and drug resistance.

Ca2+ release from the endoplasmic reticulum (ER) is an essential event in the modulation of Ca2+ homeostasis, which is coordinated by multiple biological processes, ranging from cell proliferation to apoptosis. Deregulated Ca2+ homeostasis is linked with various cancer hallmarks; thus, uncovering the mechanisms underlying Ca2+ homeostasis dynamics may lead to new anticancer treatment strategies. Here, we demonstrate that a reported Ca2+-channel protein TMCO1 (transmembrane and coiled-coil domains 1) is overexpressed in colon cancer tissues at protein levels but not at messenger RNA levels in colon cancer. Further study revealed that TMCO1 is a substrate of ER-associated degradation E3 ligase Gp78. Intriguingly, Gp78-mediated TMCO1 degradation at K186 is under the control of the iASPP (inhibitor of apoptosis-stimulating protein of p53) oncogene. Mechanistically, iASPP robustly reduces ER Ca2+ stores, mainly by competitively binding with Gp78 and interfering with Gp78-mediated TMCO1 degradation. A positive correlation between iASPP and TMCO1 proteins is further validated in human colon tissues. Inhibition of iASPP-TMCO1 axis promotes cytosolic Ca2+ overload-induced apoptotic cell death, reducing tumor growth both in vitro and in vivo. Thus, iASPP-TMCO1 represents a promising anticancer treatment target by modulating Ca2+ homeostasis.

Profiling the Bisecting N-acetylglucosamine Modification in Amniotic Membrane via Mass Spectrometry.

Bisecting N-acetylglucosamine (GlcNAc), a GlcNAc linked to the core ß-mannose residue via a ß1,4 linkage, is a special type of N-glycosylation that has been reported to be involved in various biological processes, such as cell adhesion and fetal development. This N-glycan structure is abundant in human trophoblasts, which is postulated to be resistant to natural killer cell-mediated cytotoxicity, enabling a mother to nourish a fetus without rejection. In this study, we hypothesized that the human amniotic membrane, which serves as the last barrier for the fetus, may also express bisected-type glycans. To test this hypothesis, glycomic analysis of the human amniotic membrane was performed, and bisected N-glycans were detected. Furthermore, our proteomic data, which have been previously employed to explore human missing proteins, were analyzed and the presence of bisecting GlcNAc-modified peptides was confirmed. A total of 41 glycoproteins with 43 glycopeptides were found to possess a bisecting GlcNAc, and 25 of these glycoproteins were reported to exhibit this type of modification for the first time. These results provide insights into the potential roles of bisecting GlcNAc modification in the human amniotic membrane, and can be beneficial to functional studies on glycoproteins with bisecting GlcNAc modifications and functional studies on immune suppression in human placenta.

Multi-platform omics analysis reveals molecular signature for COVID-19 pathogenesis, prognosis and drug target discovery.

Disease progression prediction and therapeutic drug target discovery for Coronavirus disease 2019 (COVID-19) are particularly important, as there is still no effective strategy for severe COVID-19 patient treatment. Herein, we performed multi-platform omics analysis of serial plasma and urine samples collected from patients during the course of COVID-19. Integrative analyses of these omics data revealed several potential therapeutic targets, such as ANXA1 and CLEC3B. Molecular changes in plasma indicated dysregulation of macrophage and suppression of T cell functions in severe patients compared to those in non-severe patients. Further, we chose 25 important molecular signatures as potential biomarkers for the prediction of disease severity. The prediction power was validated using corresponding urine samples and plasma samples from new COVID-19 patient cohort, with AUC reached to 0.904 and 0.988, respectively. In conclusion, our omics data proposed not only potential therapeutic targets, but also biomarkers for understanding the pathogenesis of severe COVID-19.

Proteomic Profiling of Gastric Signet Ring Cell Carcinoma Tissues Reveals Characteristic Changes of the Complement Cascade Pathway.

Signet ring cell carcinoma (SRCC) is a histological subtype of gastric cancer with distinct features in multiple aspects compared with adenocarcinomas (ACs). The lack of a systematic molecular overview of this disease has led to slow progress in its clinical practice. In the present proteomics study, gastric tissues were collected from tumors and adjacent tissues, including 14 SRCCs and 34 ACs, and laser capture microdissection (LCM) was employed to eradicate the cellular heterogeneity of the tissues. The proteomes of tissues were profiled by data-independent acquisition (DIA) mass spectrometry (MS). Based on the over 6000 proteins quantified, univariate analysis and pathway enrichment revealed that some proteins and pathways demonstrated differences between SRCC and ACs. Importantly, the upregulation of a majority of complement-related proteins was notable for SRCC but not for ACs. A hypothesis, based on the proteomics evidence, was proposed that the complement cascade was evoked in the SRCC microenvironment upon infiltration, and the SRCC cells survived the complement cytotoxicity by secreting endogenous negative regulators. Moreover, an attempt was made to establish appropriate cell models for gastric SRCC through proteomic comparison of the 15 gastric cell lines and gastric tumors. The predictions of a supervised classifier suggested that none of these gastric cell lines qualified to mimic SRCC. This study discovered that the complement cascade is activated at a higher level in gastric SRCC than in ACs.

Metabolomic profiling reveals amino acid and carnitine alterations as metabolic signatures in psoriasis.

High-throughput metabolite profiling provides the opportunity to reveal metabolic mechanisms and identify biomarkers. Psoriasis is an immune-mediated chronic inflammatory disease. However, the role of metabolism in psoriasis pathogenesis remains unclear. Methods: Plasma samples of individuals (45 psoriasis and 45 sex-, age-, and BMI-matched healthy controls) were collected. Non-targeted metabolomics and amino acid- or carnitine-targeted metabolomics were conducted, then, plasma samples of mice induced by imiquimod (IMQ) were subjected to the amino acid- and carnitine-targeted metabolomic profiling. Flow cytometry was used to study the effect of L-carnitine (LC(C0)) on IMQ-induced psoriatic inflammation. Results: Through the non-targeted metabolomics approach, we detected significantly altered amino acids and carnitines in psoriasis patients. Amino acid-targeted metabolomic profiling identified 37 amino acids altered in psoriasis, of these 23 were markedly upregulated, including essential amino acids (EAAs), and branched-chain amino acids (BCAAs), whereas glutamine, cysteine, and asparagine were significantly down-regulated. Carnitine-targeted metabolomic profiling identified 40 significantly altered carnitines, 14 of which included palmitoylcarnitine (C16) and were markedly downregulated in psoriasis, whereas hexanoylcarnitine (C6) and 3-OH-octadecenoylcarnitine (C18:1-OH) were significantly upregulated. Interestingly, glutamine, asparagine, and C16 levels were negatively correlated with the PASI score. Moreover, a higher abundance of LC(C0) was associated with markedly reduced IMQ-induced epidermal thickening and infiltration of Th17 cells in skin lesions, indicating LC(C0) supplementation as a potential therapy for psoriasis treatment. Conclusion: Our results suggested the metabolism of amino acids and carnitines are significantly altered in psoriasis, especially the metabolism of EAAs, BCAAs, and LC(C0), which may play key roles in the pathogenesis of psoriasis.

Gut microbiome-related effects of berberine and probiotics on type 2 diabetes (the PREMOTE study).

Human gut microbiome is a promising target for managing type 2 diabetes (T2D). Measures altering gut microbiota like oral intake of probiotics or berberine (BBR), a bacteriostatic agent, merit metabolic homoeostasis. We hence conducted a randomized, double-blind, placebo-controlled trial with newly diagnosed T2D patients from 20 centres in China. Four-hundred-nine eligible participants were enroled, randomly assigned (1:1:1:1) and completed a 12-week treatment of either BBR-alone, probiotics+BBR, probiotics-alone, or placebo, after a one-week run-in of gentamycin pretreatment. The changes in glycated haemoglobin, as the primary outcome, in the probiotics+BBR (least-squares mean [95% CI], -1.04[-1.19, -0.89]%) and BBR-alone group (-0.99[-1.16, -0.83]%) were significantly greater than that in the placebo and probiotics-alone groups (-0.59[-0.75, -0.44]%, -0.53[-0.68, -0.37]%, P < 0.001). BBR treatment induced more gastrointestinal side effects. Further metagenomics and metabolomic studies found that the hypoglycaemic effect of BBR is mediated by the inhibition of DCA biotransformation by Ruminococcus bromii. Therefore, our study reports a human microbial related mechanism underlying the antidiabetic effect of BBR on T2D. (Clinicaltrial.gov Identifier: NCT02861261).