Metabolomics Panel Associated with Cystic Fibrosis-Related Diabetes toward Biomarker Discovery.

The most prevalent comorbidity among cystic fibrosis (CF) patients is cystic fibrosis-related diabetes (CFRD). CFRD has been linked to one of the worse clinical outcomes and a higher mortality. Improved clinical results have been related to earlier diagnosis and treatment of CFRD. Therefore, the present study aimed to investigate the metabolome of human serum of patients with CFRD. This might aid in identifying novel biomarkers linked with the pathophysiology of CFRD and its diagnosis. The liquid chromatography-high-resolution mass spectrometry (LC-HRMS) metabolomics approach was utilized for serum samples from patients with CF (n = 36) and healthy controls (n = 36). Nine patients in the CF group had CFRD, and 27 were non-CFRD patients (nCFRD). A total of 2328 metabolites were significantly altered in CF compared with the healthy control. Among those, 799 significantly dysregulated metabolites were identified between CFRD and nCFRD. Arachidonic acid (AA), ascorbate, and aldarate metabolism were the most common metabolic pathways dysregulated in CF. l-Homocysteic acid (l-HCA) levels were significantly reduced in CF and CFRD compared to the control and nCFRD, respectively. In addition, gamma-glutamylglycine and l-5-hydroxytryptophan (5-HTP) had the highest discrimination between CFRD and nCFRD with AUC (0.716 and 0.683, respectively). These biomarkers might serve as diagnostic biomarkers and aid in understanding potential metabolic changes linked to CF and CFRD.

Plasma-based proteomic profiling identifies the distinct regulation of proteins in hyperplasia and endometrial cancer.

BACKGROUND: Among gynaecological malignancies, endometrial cancer (EC) is the most prevalent type of uterine cancer affecting women. This study explored the proteomic profiles of plasma samples obtained from EC patients, those with hyperplasia (Hy), and a control group (CO). A combination of techniques, such as 2D-DIGE, mass spectrometry, and bioinformatics, including pathway analysis, was used to identify proteins with modified expression levels, biomarkers and their associated metabolic pathways in these groups. METHODS: Thirty-four patients, categorized into three groups-10 with EC, 12 with Hy, and 12 CO-between the ages of 46 and 75 years old were included in the study. Untargeted proteomic analysis was carried out using two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). RESULTS: In all three groups, 114 proteins that were significantly (p ≤ 0.05 and fold change ≥ 1.5) altered were successfully identified using peptide mass fingerprints (PMFs). Compared with those in the control group (CO), the EC samples had 85 differentially expressed proteins (39 upregulated and 46 downregulated), and in the Hy group, 81 proteins were dysregulated (40 upregulated and 41 downregulated) compared to those in the CO group, while 33 proteins exhibited differential regulation (12 upregulated and 21 downregulated) in the EC plasma samples compared to those in the Hy group. Vitamin D binding protein and complement C3 distinguished Hy and EC from CO with the greatest changes in expression. Among the differentially expressed proteins identified, enzymes with catalytic activity represented the largest group (42.9%). In terms of biological processes, most of the proteins were involved in cellular processes (28.8%), followed by metabolic processes (16.7%). STRING analysis for protein interactions revealed that the significantly differentially abundant proteins in the three groups are involved in three main biological processes: signalling of complement and coagulation cascades, regulation of insulin-like growth factor (IGF) transport and uptake by insulin-like growth factor binding proteins (IGFBPs), and plasma lipoprotein assembly, remodelling, and clearance. CONCLUSION: The identified plasma protein markers have the potential to serve as biomarkers for differentiating between EC and Hy, as well as for early diagnosis and monitoring of cancer progression.

Plasma Proteomic Signature of Endometrial Cancer in Patients with Diabetes.

The incidence and mortality of endometrial cancer (EC) have increased in recent years. There is mounting evidence that diabetes may play a role in the greater incidence of EC. The molecular mechanisms of the interaction between type 2 diabetes and EC are not yet clearly understood yet. The present study was undertaken to investigate the plasma proteomics of EC patients with diabetes in comparison to those of EC patients without diabetes. Plasma samples were obtained from age-matched patients (EC diabetic and EC nondiabetic). Untargeted proteomic analysis was carried out using a two-dimensional differential gel electrophoresis coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. Of the 33 proteins identified, which significantly differed in the plasma abundance between groups, 17 were upregulated and 16 were downregulated. The majority of the altered proteins are involved in the acute phase reaction, cholesterol metabolism, scavenging of heme from plasma, and plasma lipoprotein assembly and mobilization. α-2-macroglobulin, Ras association domain-containing protein 3, apolipoprotein A-I, α-1B-glycoprotein, and zinc-α-2-glycoprotein were significantly upregulated. The significantly downregulated proteins included haptoglobin, apolipoprotein A-IV, hemopexin, and α-1-antichymotrypsin. The differential expression of proteins found in patients who had EC and diabetes indicated severe disease and a poor prognosis. The protein interaction analysis showed dysregulation of cholesterol metabolism and heme scavenging pathways in these patients.

Metabolomic Profiling of Blood Plasma in Females with Hyperplasia and Endometrial Cancer.

Uterine cancer is the most prevalent gynecologic malignancy in women worldwide. Endometrial cancer (EC) has an 81% five-year survival rate, depending on disease stage and time of diagnosis. While endometrial cancer is largely treatable when detected early, no established screening techniques are available in clinical practice. As a result, one of the most significant issues in the medical field is the development of novel ways for early cancer identification, which could boost treatment success rates. Liquid chromatography-high-resolution mass spectrometry (LC-HRMS)-based metabolomics was employed to explore the metabolomic markers and pathways unique to this cancer type and link them to the benign endometrial hyperplasia that may progress to cancer in 5% to 25% of patients. The study involved 59 postmenopausal participants, 20 with EC type 1, 20 with benign hyperplasia, and 19 healthy participants. Metabolite distribution changes were analyzed, and 338 of these features were dysregulated and significant. The first two main components, PC1 and PC2, were responsible for 11.5% and 12.2% of the total metabolites, respectively. Compared with the control group (CO), EC samples had 203 differentially expressed metabolites (180 upregulated and 23 downregulated); in hyperplasia (HP), 157 metabolites were dysregulated (127 upregulated and 30 downregulated) compared to the CO group while 21 metabolites exhibited differential regulation (16 upregulated and 5 downregulated) in EC plasma samples compared to the HP group. Hyperplasia samples exhibited similar metabolic changes to those reported in cancer, except for alterations in triglyceride levels, 7a,12 b-dihydroxy-5b-Cholan-24-oic acid, and Hept-2-enedioyl carnitine levels. The metabolites N-heptanoyl glycine and -(Methylthio)-2,3-isopentyl phosphate and formimino glutamic acid can be specific markers for hyperplasia conditions and dimethyl phosphatidyl ethanolamine and 8-isoprostaglandin E2 can be specific markers for EC conditions. Metabolic activities rely on mitochondrial oxidative phosphorylation for energy generation. The changes in metabolites identified in our study indicate that endometrial cancer cells adopt alternative strategies to increase energy production to meet the energy demand, thereby supporting proliferation.

Proteomics Investigation of the Impact of the Enterococcus faecalis Secretome on MCF-7 Tumor Cells.

Breast cancer is the most prevalent form of cancer among women. The microenvironment of a cancer tumor is surrounded by various cells, including the microbiota. An imbalance between microbes and their host may contribute to the development and spread of breast cancer. Therefore, the objective of this study is to investigate the influence of Enterococcus faecalis on a breast cancer cell line (MCF-7) to mimic the luminal A subtype of breast cancer, using an untargeted proteomics approach to analyze the proteomic profiles of breast cancer cells after their treatment with E. faecalis in order to understand the microbiome and its role in the development of cancer. The breast cancer cell line MCF-7 was cultured and then treated with a 10% bacterial supernatant at two time points (24 h and 48 h) at 37 °C in a humidified incubator with 5% CO2. Proteins were then extracted and separated using two-dimensional difference (2D-DIGE) gel electrophoresis, and the statistically significant proteins (p-value < 0.05, fold change > 1.5) were identified via matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS). The protein fingerprints showed a differential protein expression pattern in the cells treated with E. faecalis for 24 and 48 h compared with the control. We found 58 statistically significant proteins changes in the MCF-7 breast cancer cells affected by E. faecalis. Kilin and transgelin were upregulated after 24 h of treatment and could be used as diagnostic and prognostic markers for breast cancer. In addition, another protein involved in the inhibition of cell proliferation was coiled-coil domain-containing protein 154. The protein markers identified in this study may serve as possible biomarkers for breast cancer progression. This promotes their future uses as important therapeutic goals in the treatment and diagnosis of cancer and increases our understanding of the breast microbiome and its role in the development of cancer.

The metabolomics approach revealed a distinctive metabolomics pattern associated with hyperthyroidism treatment.

Background: Hyperthyroidism is characterized by increased thyroid hormone production, which impacts various processes, including metabolism and energy expenditure. Yet, the underlying mechanism and subsequent influence of these changes are unknown. Metabolomics is a broad analytical method that enables qualitative and quantitative examination of metabolite level changes in biological systems in response to various stimuli, pathologies, or treatments. Objectives: This study uses untargeted metabolomics to explore the potential pathways and metabolic patterns associated with hyperthyroidism treatment. Methods: The study consisted of 20 patients newly diagnosed with hyperthyroidism who were assessed at baseline and followed up after starting antithyroid treatment. Two blood samples were taken from each patient, pre (hyperthyroid state) and post-treatment (euthyroid state). Hyperthyroid and euthyroid states were identified based on thyroxine and thyroid-stimulating hormone levels. The metabolic alteration associated with antithyroid therapy was investigated using liquid chromatography- high-resolution mass spectrometry. The untargeted metabolomics data was analyzed using both univariate and multivariate analyses using MetaboAnalyst v5.0. The significant metabolic pattern was identified using the lab standard pipeline, which included molecular annotation in the Human Metabolome Database, LipidMap, LipidBlast, and METLIN. The identified metabolites were examined using pathway and network analyses and linked to cellular metabolism. Results: The results revealed a strong group separation between the pre- and post-hyperthyroidism treatment (Q2 = 0.573, R2 = 0.995), indicating significant differences in the plasma metabolome after treatment. Eighty-three mass ions were significantly dysregulated, of which 53 and 30 characteristics were up and down-regulated in the post-treatment compared to the pre-treatment group, respectively. The medium-chain acylcarnitines, octanoylcarnitine, and decanoylcarnitine, previously found to rise in hyperthyroid patients, were among the down-regulated metabolites, suggesting that their reduction could be a possible biomarker for monitoring euthyroid restoration. Kynurenine is a downregulated tryptophan metabolite, indicating that the enzyme kynurenine 3-hydroxylase, inhibited in hyperthyroidism, is back functioning. L-cystine, a cysteine dimer produced from cysteine oxidation, was among the down-regulated metabolites, and its accumulation is considered a sign of oxidative stress, which was reported to accompany hyperthyroidism; L-cystine levels dropped, this suggests that the plasma level of L-cystine can be used to monitor the progress of euthyroid state restoration. Conclusion: The plasma metabolome of patients with hyperthyroidism before and after treatments revealed differences in the abundance of several small metabolites. Our findings add to our understanding of hyperthyroidism's altered metabolome and associated metabolic processes and shed light on acylcarnitines as a new biomarker for treatment monitoring in conjunction with thyroxine and thyroid-stimulating hormone.

Lipids Alterations Associated with Metformin in Healthy Subjects: An Investigation Using Mass Spectrometry Shotgun Approach.

Metformin is an orally effective insulin-sensitizing drug widely prescribed for treating type 2 diabetes mellitus (T2DM). Metformin has been reported to alter lipid metabolism. However, the molecular mechanisms behind its impact on lipid metabolism remain partially explored and understood. In the current study, mass spectrometry-based lipid profiling was used to investigate the lipidomic changes in the serum of 26 healthy individuals after a single-dose intake of metformin. Samples were analyzed at five-time points: preadministration, before the maximum concentration of metformin (Cmax), Cmax, after Cmax, and 36 h post-administration. A total of 762 molecules were significantly altered between the five-time points. Based on a comparison between baseline level and Cmax, metformin significantly increased and decreased the level of 33 and 192 lipids, respectively (FDR ≤ 0.05 and fold change cutoff of 1.5). The altered lipids are mainly involved in arachidonic acid metabolism, steroid hormone biosynthesis, and glycerophospholipid metabolism. Furthermore, several lipids acted in an opposed or similar manner to metformin levels and included fatty acyls, sterol lipids, glycerolipids, and glycerophospholipids. The significantly altered lipid species pointed to fundamental lipid signaling pathways that could be linked to the pleiotropic effects of metformin in T2DM, insulin resistance, polycystic ovary syndrome, cancer, and cardiovascular diseases.

Proteomics Profiling of Osteoporosis and Osteopenia Patients and Associated Network Analysis.

Bone mass reduction due to an imbalance in osteogenesis and osteolysis is characterized by low bone mineral density (LBMD) and is clinically classified as osteopenia (ON) or osteoporosis (OP), which is more severe. Multiple biomarkers for diagnosing OP and its progression have been reported; however, most of these lack specificity. This cohort study aimed to investigate sensitive and specific LBMD-associated protein biomarkers in patients diagnosed with ON and OP. A label-free liquid chromatography-mass spectrometry (LC-MS) proteomics approach was used to analyze serum samples. Patients' proteomics profiles were filtered for potential confounding effects, such as age, sex, chronic diseases, and medication. A distinctive proteomics profile between the control, ON, and OP groups (Q2 = 0.7295, R2 = 0.9180) was identified, and significant dysregulation in a panel of proteins (n = 20) was common among the three groups. A comparison of these proteins showed that the levels of eight proteins were upregulated in ON, compared to those in the control and the OP groups, while the levels of eleven proteins were downregulated in the ON group compared to those in the control group. Interestingly, only one protein, myosin heavy chain 14 (MYH14), showed a linear increase from the control to the ON group, with the highest abundance in the OP group. A significant separation in the proteomics profile between the ON and OP groups (Q2 = 0.8760, R2 = 0.991) was also noted. Furthermore, a total of twenty-six proteins were found to be dysregulated between the ON and the OP groups, with fourteen upregulated and twelve downregulated proteins in the OP, compared to that in the ON group. Most of the identified dysregulated proteins were immunoglobulins, complement proteins, cytoskeletal proteins, coagulation factors, and various enzymes. Of these identified proteins, the highest area under the curve (AUC) in the receiver operating characteristic (ROC) analysis was related to three proteins (immunoglobulin Lambda constant 1 (IGLC1), RNA binding protein (MEX3B), and fibulin 1 (FBLN1)). Multiple reaction monitoring (MRM), LC-MS, was used to validate some of the identified proteins. A network pathway analysis of the differentially abundant proteins demonstrated dysregulation of inflammatory signaling pathways in the LBMD patients, including the tumor necrosis factor (TNF), toll-like receptor (TL4), and interferon-γ (IFNG) signaling pathways. These results reveal the existence of potentially sensitive protein biomarkers that could be used in further investigations of bone health and OP progression.

Proteomic profiling of thyroid tissue in patients with obesity and benign diffuse goiter.

Goiter is a term to describe the enlargement of the thyroid gland. The pathophysiology and molecular changes behind development of diffuse benign goiter remains unclear. The present study targeted to identify and describe the alterations in the thyroid tissue proteome from patients (obese euthyroid) with benign diffuse goiter (BDG) using proteomics approach. Thyroid tissue samples, from 7 age and sex matched, patients with BDG and 7 controls were obtained at the time of surgery. An untargeted proteomic analysis of the thyroid tissue was performed out utilizing two-dimensional difference (2D-DIGE) in gel electrophoresis followed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for identification of the proteins. Progenesis software was used to identify changes in expression of tissue proteins and found statistically significant differences in abundance in a total of 90 proteins, 46 up and 44 down (1.5-fold change, ANOVA, p ≤ 0.05) in BDG compared to the control group. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) identified dysregulation of signalling pathways linked to ERK1/2, Glutathione peroxidase and NADPH oxidase associated to organismal injury and abnormalities, endocrine system disorders and cancer. The thyroid tissue proteome in patients with BDG revealed a significant decrease in thyroglobulin along with dysregulation of glycolysis and an increase in prooxidant peroxidase enzymes. Dysregulation of metabolic pathways related to glycolysis, redox proteins, and the proteins associated with maintaining the cytoskeletal structure of the thyrocytes was also identified.

Genomic, Proteomic, and Phenotypic Spectrum of Novel O-Sialoglycoprotein Endopeptidase Variant in Four Affected Individuals With Galloway-Mowat Syndrome.

Galloway-Mowat syndrome is a rare autosomal recessive disease characterized by a unique combination of renal and neurological manifestations, including early-onset steroid-resistant nephrotic syndrome, microcephaly, psychomotor delay, and gyral abnormalities of the brain. Most patients die during early childhood. Here, we identified a novel homozygous O-sialoglycoprotein endopeptidase (OSGEP) variant, NM_017807.3:c.973C>G (p.Arg325Gly), in four affected individuals in an extended consanguineous family from Saudi Arabia. We have described the detailed clinical characterization, brain imaging results, and muscle biopsy findings. The described phenotype varied from embryonic lethality to early pregnancy loss or death at the age of 9. Renal disease is often the cause of death. Protein modeling of this OSGEP variant confirmed its pathogenicity. In addition, proteomic analysis of the affected patients proposed a link between the KEOPS complex function and human pathology and suggested potential pathogenic mechanisms.

Tissue-Based Proteomic Profiling in Patients with Hyperplasia and Endometrial Cancer.

Uterine cancers are among the most prevalent gynecological malignancies, and endometrial cancer (EC) is the most common in this group. This study used tissue-based proteomic profiling analysis in patients with endometrial cancer and hyperplasia, and control patients. Conventional 2D gel electrophoresis, followed by a mass spectrometry approach with bioinformatics, including a network pathway analysis pipeline, was used to identify differentially expressed proteins and associated metabolic pathways between the study groups. Thirty-six patients (twelve with endometrial cancer, twelve with hyperplasia, and twelve controls) were enrolled in this study. The mean age of the participants was 46-75 years. Eighty-seven proteins were significantly differentially expressed between the study groups, of which fifty-three were significantly differentially regulated (twenty-eight upregulated and twenty-five downregulated) in the tissue samples of EC patients compared to the control (Ctrl). Furthermore, 26 proteins were significantly dysregulated (8 upregulated and 18 downregulated) in tissue samples of hyperplasia (HY) patients compared to Ctrl. Thirty-two proteins (nineteen upregulated and thirteen downregulated) including desmin, peptidyl prolyl cis-trans isomerase A, and zinc finger protein 844 were downregulated in the EC group compared to the HY group. Additionally, fructose bisphosphate aldolase A, alpha enolase, and keratin type 1 cytoskeletal 10 were upregulated in the EC group compared to those in the HY group. The proteins identified in this study were known to regulate cellular processes (36%), followed by biological regulation (16%). Ingenuity pathway analysis found that proteins that are differentially expressed between EC and HY are linked to AKT, ACTA2, and other signaling pathways. The panels of protein markers identified in this study could be used as potential biomarkers for distinguishing between EC and HY and early diagnosis and progression of EC from hyperplasia and normal patients.

Plasma proteomics reveals an improved cardio-metabolic profile in patients with type 2 diabetes post-liraglutide treatment.

BACKGROUND: Diabetes mellitus is a chronic multisystem disease with a high global prevalence, including in Saudi Arabia. The Glucagon-like Peptide (GLP-1) receptor agonist liraglutide is known to lower glucose levels, reduce weight and improve cardiovascular outcome. However, mechanisms underlying the benefits of liraglutide treatment in patients with type 2 diabetes mellitus (T2DM) remain unclear. METHODS: In the present study, a 2D-DIGE MALDI-TOF mass spectrometric approach combined with bioinformatics and network pathway analysis explore the plasma proteomic profile. The study involved 20 patients with T2DM with mean age of 54.4 ± 9.5 years and Hemoglobin A1c (HbA1c) between 8% and 11% (inclusive). RESULTS: A statistically significant change (p < .006) was observed in HbA1c with no significant changes in body weight, renal function, or markers of dyslipidemia post-treatment with liraglutide. 2 D-DIGE gel analysis identified significant changes (⩾1.5-fold change, Analysis of variance (ANOVA), p ⩽ 0.05) in 72 proteins, (62 down and 10 up) in liraglutide pre-treatment compared to the post-treatment state. Proteins identified in our study were found to regulate metabolic processes including acute phase response proteins, enzymes, apolipoproteins with involvement of the inflammatory signaling pathways, NF-κB, AKT, and p38 MAPK. CONCLUSION: Liraglutide treatment decreased levels of acute phase response that to reduce the systemic chronic inflammatory state and oxidative stress, and eventually improve the cardio-metabolic profile in these patients.

Proteomic Analysis of Endometrial Cancer Tissues from Patients with Type 2 Diabetes Mellitus.

Endometrial cancer (EC) is the most common form of gynecological cancer. Type 2 diabetes mellitus is associated with an increased risk of EC. Currently, no proteomic studies have investigated the role of diabetes in endometrial cancers from clinical samples. The present study aims to elucidate the molecular link between diabetes and EC using a proteomic approach. Endometrial tissue samples were obtained from age-matched patients (EC Diabetic and EC Non-Diabetic) during surgery. Untargeted proteomic analysis of the endometrial tissues was carried out using a two-dimensional difference in gel electrophoresis (2D-DIGE) coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF). A total of 53 proteins were identified, with a significant difference in abundance (analysis of variance (ANOVA) test, p ≤ 0.05; fold-change ≥ 1.5) between the two groups, among which 30 were upregulated and 23 downregulated in the EC Diabetic group compared to EC Non-Diabetic. The significantly upregulated proteins included peroxiredoxin-1, vinculin, endoplasmin, annexin A5, calreticulin, and serotransferrin. The significantly downregulated proteins were myosin regulatory light polypeptide 9, Retinol dehydrogenase 12, protein WWC3, intraflagellar transport protein 88 homolog, superoxide dismutase [Cu-Zn], and retinal dehydrogenase 1. The network pathway was related to connective tissue disorder, developmental disorder, and hereditary disorder, with the identified proteins centered around dysregulation of ERK1/2 and F Actin signaling pathways. Cancer-associated protein alterations such as upregulation of peroxiredoxin-1, annexin 5, and iNOS, and downregulation of RDH12, retinaldehyde dehydrogenase 1, SOD1, and MYL 9, were found in the EC tissues of the diabetic group. Differential expression of proteins linked to cancer metastasis, such as the upregulation of vinculin and endoplasmin and downregulation of WWC3 and IFT88, was seen in the patients with diabetes. Calreticulin and alpha-enolase, which might have a role in the interplay between diabetes and EC, need further investigation.

Cervical Cancer and Human Papillomavirus Awareness among Women in Saudi Arabia.

Background and Objectives: Cervical cancer (CC) is the eighth most common cancer among Saudi women of all ages. With limited national data, we aimed to evaluate the public awareness of cervical cancer, CC risk factors, HPV infection, and HPV vaccines in different regions of Saudi Arabia. Materials and Methods: This was a survey-based cross-sectional study that encompassed 564 Saudi women over a period of a month. A self-administrated questionnaire was distributed through different social media platforms. Results: The collected data included sociodemographic variables and questions assessing awareness of CC, and the attitudes toward CC screening and human papillomavirus (HPV) vaccination. Most respondents were aware of CC (84.0%), although their primary source of information was the internet. However, only 45 females (8.0%) had a history of cervical screening. Furthermore, most females did not know that HPV was transmitted sexually (78.9%), or that it caused genital warts (81.7%) and CC (81.9%). Regarding the HPV vaccine, 100 females (17.7%) had heard about it, but only 11 (2.0%) took the vaccine, although more than half of the respondents (54.1%) were willing to take the vaccine after being informed about it. Conclusions: We noticed a remarkable lack of awareness among the respondents regarding HPV's clinical implications; and the HPV vaccine, and its importance and availability. The main source of information for most of the Saudi women in this study was the internet, which may be an unreliable source, or provide misleading information that may delay screening or discourage vaccination. Thus, organized campaigns by the Ministry of Health or other health-advocating agencies, in addition to screening and vaccination programs, are strongly encouraged.

Proteomic Profiling of Plasma-Derived Biomarkers in Patients with Bladder Cancer: A Step towards Clinical Translation.

BACKGROUND: Bladder cancer is a life-threatening disease and a major cause of cancer-associated complications. The main challenges confronted during the clinical management of bladder cancer are associated with recurrence and disease progression to the muscle-invasive phenotype. Improved early detection of the disease is of paramount importance to prevent disease progression and improve survival. Hence, novel clinically applicable biomarkers for early detection are warranted. METHODS: In the current study, a comparative proteomic approach was undertaken using plasma samples to identify protein biomarkers associated with the muscle-invasive phenotype of bladder carcinoma. Isolated plasma proteins were depleted, DIGE-labeled, then subjected to conventional 2D electrophoresis followed by mass spectrometry for identification of differentially expressed proteins. Western blot was used for data validation. RESULTS: Fourteen differentially expressed proteins with statistically significant changes in abundance between the cancer group and control group were identified. Three differentially expressed proteins were selected for validation, among which apolipoprotein A1 exhibited high specificity and sensitivity (AUC = 0.906). Ingenuity pathway analysis identified IFN-γ and TNF-α as the main signaling hub for the differentially regulated proteins. CONCLUSION: Our findings provide additional insight into understanding bladder cancer pathogenesis. Our data identified potential non-invasive plasma-derived biomarker proteins that merit additional investigation to validate its clinical usefulness to prevent bladder cancer progression.

Serum Proteomic Analysis of Cannabis Use Disorder in Male Patients.

Cannabis use has been growing recently and it is legally consumed in many countries. Cannabis has a variety of phytochemicals including cannabinoids, which might impair the peripheral systems responses affecting inflammatory and immunological pathways. However, the exact signaling pathways that induce these effects need further understanding. The objective of this study is to investigate the serum proteomic profiling in patients diagnosed with cannabis use disorder (CUD) as compared with healthy control subjects. The novelty of our study is to highlight the differentially changes proteins in the serum of CUD patients. Certain proteins can be targeted in the future to attenuate the toxicological effects of cannabis. Blood samples were collected from 20 male individuals: 10 healthy controls and 10 CUD patients. An untargeted proteomic technique employing two-dimensional difference in gel electrophoresis coupled with mass spectrometry was employed in this study to assess the differentially expressed proteins. The proteomic analysis identified a total of 121 proteins that showed significant changes in protein expression between CUD patients (experimental group) and healthy individuals (control group). For instance, the serum expression of inactive tyrosine protein kinase PEAK1 and tumor necrosis factor alpha-induced protein 3 were increased in CUD group. In contrast, the serum expression of transthyretin and serotransferrin were reduced in CUD group. Among these proteins, 55 proteins were significantly upregulated and 66 proteins significantly downregulated in CUD patients as compared with healthy control group. Ingenuity pathway analysis (IPA) found that these differentially expressed proteins are linked to p38MAPK, interleukin 12 complex, nuclear factor-κB, and other signaling pathways. Our work indicates that the differentially expressed serum proteins between CUD and control groups are correlated to liver X receptor/retinoid X receptor (RXR), farnesoid X receptor/RXR activation, and acute phase response signaling.

A Metabolic Pattern in Healthy Subjects Given a Single Dose of Metformin: A Metabolomics Approach.

Metformin is a widely prescribed medication for the treatment of type 2 diabetes mellitus (T2DM). It possesses effective roles in various disorders, including cancer, dyslipidemia, and obesity. However, the underlying mechanisms of metformin's multiple benefits are not fully understood. Herein, a mass spectrometry-based untargeted metabolomics approach was used to investigate the metabolic changes associated with the administration of a single dose of metformin in the plasma of 26 healthy subjects at five-time points; pre-dose, before the maximum concentration of metformin (Cmax), Cmax, after Cmax, and 36 h post-dose. A total of 111 metabolites involved in various biochemical processes were perturbed, with branched-chain amino acid (BCAA) being the most significantly altered pathway. Additionally, the Pearson similarity test revealed that 63 metabolites showed a change in their levels dependent on metformin level. Out of these 63, the level of 36 metabolites was significantly altered by metformin. Significantly altered metformin-dependent metabolites, including hydroxymethyl uracil, propionic acid, glycerophospholipids, and eicosanoids, pointed to fundamental biochemical processes such as lipid network signaling, energy homeostasis, DNA lesion repair mechanisms, and gut microbiota functions that could be linked to the multiple beneficial roles of metformin. Thus, the distinctive metabolic pattern linked to metformin administration can be used as a metabolic signature to predict the potential effect and mechanism of actions of new chemical entities during drug development.

Distinctive metabolic profiles between Cystic Fibrosis mutational subclasses and lung function.

INTRODUCTION: Cystic fibrosis (CF) is a lethal multisystemic disease of a monogenic origin with numerous mutations. Functional defects in the cystic fibrosis transmembrane conductance receptor (CFTR) protein based on these mutations are categorised into distinct classes having different clinical presentations and disease severity. OBJECTIVES: The present study aimed to create a comprehensive metabolomic profile of altered metabolites in patients with CF, among different classes and in relation to lung function. METHODS: A chemical isotope labeling liquid chromatography-mass spectrometry metabolomics was used to study the serum metabolic profiles of young and adult CF (n = 39) patients and healthy controls (n = 30). Comparisons were made at three levels, CF vs. controls, among mutational classes of CF, between CF class III and IV, and correlated the lung function findings. RESULTS: A distinctive metabolic profile was observed in the three analyses. 78, 20, and 13 significantly differentially dysregulated metabolites were identified in the patients with CF, among the different classes and between class III and IV, respectively. The significantly identified metabolites included amino acids, di-, and tri-peptides, glutathione, glutamine, glutamate, and arginine metabolism. The top significant metabolites include 1-Aminopropan-2-ol, ophthalmate, serotonin, cystathionine, and gamma-glutamylglutamic acid. Lung function represented by an above-average FEV1% level was associated with decreased glutamic acid and increased guanosine levels. CONCLUSION: Metabolomic profiling identified alterations in different amino acids and dipeptides, involved in regulating glutathione metabolism. Two metabolites, 3,4-dihydroxymandelate-3-O-sulfate and 5-Aminopentanoic acid, were identified in common between the three anlayses and may represent as highly sensitive biomarkers for CF.

A matrix-assisted laser desorption/ionization imaging mass spectrometric approach to study weight-related changes within thyroid tissue.

Obesity is associated with numerous comorbidities along with abnormalities of the endocrine system, more commonly manifesting as dysfunctions of the thyroid gland such as goiter. Changes in weight, especially an increase, could lead to an increase in the incidence of thyroid dysfunction; however, its pathophysiology remains to be elucidated. In the present study, we aimed to interrogate the changes in the protein distribution and abundance between the lean patients and patients with obesity thyroid tissue sections through utilizing this technique. The FFPE-fixed thyroid tissue blocks from the selected cases and controls were identified and targeted for matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) analysis. Patients in the 30 to 75 years age group and undergoing total thyroidectomy for benign thyroid disease were recruited. Patients with thyroid cancers, autoimmune disorders, and other inflammatory conditions were excluded from the study. The selected patients were divided into two groups according to their BMIs: lean (BMI < 25) and obese (BMI > 35). An initial trial set was used as a pilot study for the optimization of the MALDI IMS protocol that was next applied to the selected thyroid tissues. MALDI IMS data from all the samples were aligned and statistical analysis carried out by k-means and linear discriminant analysis (LDA) classification model using principle component analysis (PCA) results were evaluated between the two groups: controls (lean) and cases (obese). Receiver operator characteristic (ROC) curves were alternatively used to calculate the variability of the identified peptides. The discriminating peptides were also independently identified and related to their corresponding proteins by using liquid chromatography and tandem mass spectrometry (LC-MS/MS) analyses. Eight peptides mainly from thyroglobulin were found to be upregulated whereas 10 others were found to be downregulated in the lean compared to the obese group. Through this technique, we will be able to better understand the relationship between the disease entity and obesity.

Serum-Based Proteomics Profiling in Adult Patients with Cystic Fibrosis.

Cystic fibrosis (CF), the most common lethal autosomal recessive disorder among Caucasians, is caused by mutations in the CF transmembrane conductance regulator (CFTR) chloride channel gene. Despite significant advances in the management of CF patients, novel disease-related biomarkers and therapies must be identified. We performed serum proteomics profiling in CF patients (n = 28) and healthy subjects (n = 10) using the 2D-DIGE MALDI-TOF proteomic approach. Out of a total of 198 proteins identified, 134 showed a statistically significant difference in abundance and a 1.5-fold change (ANOVA, p < 0.05), including 80 proteins with increased abundance and 54 proteins with decreased abundance in CF patients. A multiple reaction monitoring-mass spectrometry analysis of six differentially expressed proteins identified by a proteomic approach (DIGE-MALD-MS) showed a significant increase in C3 and CP proteins and a decrease in APOA1, Complement C1, Hp, and RBP4proteins compared with healthy controls. Fifteen proteins were identified as potential biomarkers for CF diagnosis. An ingenuity pathway analysis of the differentially regulated proteins indicates that the central nodes dysregulated in CF subjects involve pro-inflammatory cytokines, ERK1/2, and P38 MAPK, which are primarily involved in catalytic activities and metabolic processes. The involved canonical pathways include those related to FXR/RXR, LXR/RXR, acute phase response, IL12, nitric oxide, and reactive oxygen species in macrophages. Our data support the current efforts toward augmenting protease inhibitors in patients with CF. Perturbations in lipid and vitamin metabolism frequently observed in CF patients may be partly due to abnormalities in their transport mechanism.