Glycosaminoglycan Profile Research Articles

Discriminating Benign from Malignant Lung Diseases Using Plasma Glycosaminoglycans and Cell-Free DNA.

We aimed to investigate the use of free glycosaminoglycan profiles (GAGomes) and cfDNA in plasma to differentiate between lung cancer and benign lung disease, in a cohort of 113 patients initially suspected of lung cancer. GAGomes were analyzed in all samples using the MIRAM® Free Glycosaminoglycan Kit with ultra-high-performance liquid chromatography and electrospray ionization triple quadrupole mass spectrometry. In a subset of samples, cfDNA concentration and NGS-data was available. We detected two GAGome features, 0S chondroitin sulfate (CS), and 4S CS, with cancer-specific changes. Based on the observed GAGome changes, we devised a model to predict lung cancer. The model, named the GAGome score, could detect lung cancer with 41.2% sensitivity (95% CI: 9.2-54.2%) at 96.4% specificity (95% CI: 95.2-100.0%, n = 113). When we combined the GAGome score with a cfDNA-based model, the sensitivity increased from 42.6% (95% CI: 31.7-60.6%, cfDNA alone) to 70.5% (95% CI: 57.4-81.5%) at 95% specificity (95% CI: 75.1-100%, n = 74). Notably, the combined GAGome and cfDNA testing improved the sensitivity, compared to cfDNA alone, especially in ASCL stage I (55.6% vs 11.1%). Our findings show that plasma GAGome profiles can enhance cfDNA testing performance, highlighting the applicability of a multiomics approach in lung cancer diagnostics.

Urinary Free Glycosaminoglycans Identify Adults at High Risk of Developing Early-stage High-grade Bladder Cancer

Background and objectiveScreening for bladder cancer (BCa) could reduce mortality via early detection of early-stage high-grade (Ta/T1 N0 M0 grade 2–3) disease. Noninvasive biomarkers could aid in screening, but current markers lack the specificity required. The urinary free glycosaminoglycan profile (GAGome) is a promising biomarker for early detection of BCa metabolism. MethodsIn a prospective case-control development study, we included patients with BCa or no evidence of disease (NED) and measured the urinary GAGome. We then developed a score to predict the probability of BCa using GAGome features that correlated with BCa versus NED according to Bayesian regression. Next, in a retrospective, population-based, case-control study, we included adults from the Lifelines Cohort Study who were presumed healthy at baseline. All cases with BCa confirmed in the cancer registry by the 2-yr or 6-yr study visit were matched to randomly selected control subjects. We developed a reference logistic regression model using age and sex to predict BCa at 7 yr after baseline. We then added the GAGome score to the model and assessed model improvement using the likelihood ratio test. We dichotomized outputs for the reference model and saturated model (reference + GAGome score) into high-risk versus low-risk categories using a 99% specificity cutoff and estimated the sensitivity for association with BCa at 7 yr. Key findings and limitationsWe prospectively included 51 individuals with BCa and 38 with NED and observed alterations in three GAGome features compatible with BCa. We developed a score that discriminated BCa with an area under the receiver operating characteristic curve of 0.77 (95% confidence interval [CI] 0.67–0.87). We retrospectively selected a cohort of 1088 presumed healthy adults (median age 48 yr, 56% females), of whom 48 had developed BCa by 7 yr after baseline (median time to diagnosis 1.4 yr). The GAGome score was an independent predictor of BCa at 7 yr when added to the reference model (p < 0.001). The sensitivity for BCa at 7 yr for high-risk subjects was 31% (95% CI 20–43%) using the saturated model and 17% (95% CI 4.7–29%) using the reference model at 99% specificity (95% CI 98–99%). Conclusions and clinical implicationsThe urinary free GAGome is specifically altered in BCa and can be used for noninvasive identification of adults at high risk of developing BCa, independent of age and sex. This information could be useful for the design of risk-stratified targeted screening programs for BCa. Patient summaryWe tested whether measurement of a class of sugars called glycosaminoglycans (GAGs) in urine could be used for early detection of bladder cancer. Our results show that GAG levels in urine can distinguish people at high risk of developing bladder cancer within 7 years, even if they are healthy at the time of the urine sampling.

Abstract 6088: Predicting the risk of any-type cancer in asymptomatic adults using noninvasive glycosaminoglycan profiling

Abstract Background: Early detection of cancers through screening can reduce mortality. However, screening excludes individuals not considered at an increased risk of developing cancer, as determined by age, sex, or tobacco use. No molecular biomarker is routinely used to predict risk. Here, we investigated urine glycosaminoglycan profiles (GAGomes) as noninvasive biomarkers for any-cancer risk prediction. Methods: In this population-based case-control study, we included adults aged over 18 years from the Lifelines Cohort Study, Netherlands who were presumed healthy at baseline. All cases who self-reported any-type cancer or died by the 5-year study visit were confirmed in the Dutch Cancer Registry and matched 1:3 to randomly selected controls (1:1 for the interim analysis). We first developed a logistic regression reference model, including age, sex, and clinical variables to predict any-type cancer. Next, we added urine GAGomes (as a single aggregate score) to the model and assessed model improvement using the likelihood ratio test. We categorized the output of the saturated model (clinical variables plus urine GAGome score) into four groups based on bespoke specificity cut-offs: low-, moderate-, intermediate-, and high-risk. We estimated odds-ratios (ORs) for their association with any-type cancer compared to the moderate-risk group, as well as their sensitivity across subsets. Using the so-estimated OR in the high-risk group, we calculated the minimum pre-test 5-year absolute risk needed to reclassify an adult into a post-test 5-year absolute risk &amp;gt;3.00%. Results: In the interim analysis, we included 2054 adults (median age = 51 years, 57% females). Of them, 924 were diagnosed with any-type cancer over a 6 year-follow-up period (median time to diagnosis = 1.4 years). Urine GAGomes were found to be independent risk factors when added to the reference model, explaining 27% of the variance (Nagelkerke R2 = 0.26 vs. 0.21, p &amp;lt; 0.0001). The ORs in the low-, intermediate-, and high-risk groups were 0.05 (95% CI: 0.02-0.13 p &amp;lt; 0.0001), 5.31 (95% CI: 3.84-7.48, p &amp;lt; 0.0001) and 27.6 (95% CI: 14.3 - 51.6, p &amp;lt; 0.0001), respectively. The high-risk group detected +80% more cancers than the reference model at the same specificity (99.29%), particularly in situ and stage I (+204% and +64%) and among those aged 50-69 (+247%). Adults with a pre-test 5-year absolute risk &amp;gt; 0.25% returning a high-risk group would be reclassified to a post-test 5-year absolute risk &amp;gt; 3.00% for any-type cancer. Conclusion: Implementing urine GAGomes as a strategy for risk-stratified targeted screening could identify adults with increased risk of any-type cancer who are currently excluded from screening. Citation Format: Francesco Gatto. Predicting the risk of any-type cancer in asymptomatic adults using noninvasive glycosaminoglycan profiling [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6088.

Inter- and intratumoral proteomics and glycosaminoglycan characterization of ALK rearranged lung adenocarcinoma tissues: a pilot study

Lung cancer is one of the most common types of cancer with limited therapeutic options, therefore a detailed understanding of the underlying molecular changes is of utmost importance. In this pilot study, we investigated the proteomic and glycosaminoglycan (GAG) profile of ALK rearranged lung tumor tissue regions based on the morphological classification, mucin and stromal content. Principal component analysis and hierarchical clustering revealed that both the proteomic and GAG-omic profiles are highly dependent on mucin content and to a lesser extent on morphology. We found that differentially expressed proteins between morphologically different tumor types are primarily involved in the regulation of protein synthesis, whereas those between adjacent normal and different tumor regions take part in several other biological processes (e.g. extracellular matrix organization, oxidation–reduction processes, protein folding) as well. The total amount and the sulfation profile of heparan sulfate and chondroitin sulfate showed small differences based on morphology and larger differences based on mucin content of the tumor, while an increase was observed in both the total amount and the average rate of sulfation in tumors compared to adjacent normal regions.

Mucopolysaccharidoses Differential Diagnosis by Mass Spectrometry-Based Analysis of Urine Free Glycosaminoglycans-A Diagnostic Prediction Model.

Impaired glycosaminoglycans (GAGs) catabolism may lead to a cluster of rare metabolic and genetic disorders called mucopolysaccharidoses (MPSs). Each subtype is caused by the deficiency of one of the lysosomal hydrolases normally degrading GAGs. Affected tissues accumulate undegraded GAGs in cell lysosomes and in the extracellular matrix, thus leading to the MPS complex clinical phenotype. Although each MPS may present with recognizable signs and symptoms, these may often overlap between subtypes, rendering the diagnosis difficult and delayed. Here, we performed an exploratory analysis to develop a model that predicts MPS subtypes based on UHPLC-MS/MS measurement of a urine free GAG profile (or GAGome). We analyzed the GAGome of 78 subjects (38 MPS, 37 healthy and 3 with other MPS symptom-overlapping disorders) using a standardized kit in a central-blinded laboratory. We observed several MPS subtype-specific GAGome changes. We developed a multivariable penalized Lasso logistic regression model that attained 91.2% balanced accuracy to distinguish MPS type II vs. III vs. any other subtype vs. not MPS, with sensitivity and specificity ranging from 73.3% to 91.7% and from 98.4% to 100%, depending on the predicted subtype. In conclusion, the urine GAGome was revealed to be useful in accurately discriminating the different MPS subtypes with a single UHPLC-MS/MS run and could serve as a reliable diagnostic test for a more rapid MPS biochemical diagnosis.

Noninvasive detection of any-stage cancer using free glycosaminoglycans

Cancer mortality is exacerbated by late-stage diagnosis. Liquid biopsies based on genomic biomarkers can noninvasively diagnose cancers. However, validation studies have reported ~10% sensitivity to detect stage I cancer in a screening population and specific types, such as brain or genitourinary tumors, remain undetectable. We investigated urine and plasma free glycosaminoglycan profiles (GAGomes) as tumor metabolism biomarkers for multi-cancer early detection (MCED) of 14 cancer types using 2,064 samples from 1,260 cancer or healthy subjects. We observed widespread cancer-specific changes in biofluidic GAGomes recapitulated in an in vivo cancer progression model. We developed three machine learning models based on urine (Nurine = 220 cancer vs. 360 healthy) and plasma (Nplasma = 517 vs. 425) GAGomes that can detect any cancer with an area under the receiver operating characteristic curve of 0.83-0.93 with up to 62% sensitivity to stage I disease at 95% specificity. Undetected patients had a 39 to 50% lower risk of death. GAGomes predicted the putative cancer location with 89% accuracy. In a validation study on a screening-like population requiring ≥ 99% specificity, combined GAGomes predicted any cancer type with poor prognosis within 18 months with 43% sensitivity (21% in stage I; N = 121 and 49 cases). Overall, GAGomes appeared to be powerful MCED metabolic biomarkers, potentially doubling the number of stage I cancers detectable using genomic biomarkers.

Plasma and Urine Free Glycosaminoglycans as Monitoring Biomarkers in Nonmetastatic Renal Cell Carcinoma—A Prospective Cohort Study

BackgroundNo liquid biomarkers are approved in renal cell carcinoma (RCC), making early detection of recurrence in surgically treated nonmetastatic (M0) patients dependent on radiological imaging. Urine- and plasma free glycosaminoglycan profiles—or free GAGomes—are promising biomarkers reflective of RCC metabolism. ObjectiveTo explore whether free GAGomes could detect M0 RCC recurrence noninvasively. Design, setting, and participantsBetween June 2016 and February 2021, we enrolled a prospective consecutive series of patients elected for (1) partial or radical nephrectomy for clinical M0 RCC (cohort 1) or (2) first-line therapy following RCC metachronous metastatic recurrence (cohort 2) at Sahlgrenska University Hospital, Gothenburg, Sweden. The study population included M0 RCC patients with recurrent disease (RD) versus no evidence of disease (NED) in at least one follow-up visit. Plasma and urine free GAGomes—consisting of 40 chondroitin sulfate (CS), heparan sulfate, and hyaluronic acid (HA) features—were measured in a blinded central laboratory preoperatively and at each postoperative follow-up visit until recurrence or end of follow-up in cohort 1, or before treatment start in cohort 2. Outcome measurements and statistical analysisWe used Bayesian logistic regression to correlate GAGome features with RD versus NED and with various histopathological variables. We developed three recurrence scores (plasma, urine, and combined) proportional to the predicted probability of RD. We internally validated the area under the curve (AUC) using bootstrap resampling. We performed a decision curve analysis to select a cutoff and report the corresponding net benefit, sensitivity, and specificity of each score. We used univariable analyses to correlate each preoperative score with recurrence-free survival (RFS). Results and limitationsOf 127 enrolled patients in total, 62 M0 RCC patients were in the study population (median age: 63 year, 35% female, and 82% clear cell). The median follow-up time was 3 months, totaling 72 postoperative visits —17 RD and 55 NED cases. RD was compatible with alterations in 14 (52%) of the detectable GAGome features, mostly free CS. Eleven (79%) of these correlated with at least one histopathological variable. We developed a plasma, a urine, and a combined free CS RCC recurrence score to diagnose RD versus NED with AUCs 0.91, 0.93, and 0.94, respectively. At a cutoff equivalent to ≥30% predicted probability of RD, the sensitivity and specificity were, respectively, 69% and 84% in plasma, 81% and 80% in urine, and 80% and 82% when combined, and the net benefit was equivalent to finding an extra ten, 13, and 12 cases of RD per hundred patients without any unnecessary imaging for plasma, urine, and combined, respectively. The combined score was prognostic of RFS in univariable analysis (hazard ratio = 1.90, p = 0.02). Limitations include a lack of external validation. ConclusionsFree CS scores detected postsurgical recurrence noninvasively in M0 RCC with substantial net benefit. External validity is required before wider clinical implementation. Patient summaryIn this study, we examined a new noninvasive blood and urine test to detect whether renal cell carcinoma recurred after surgery.

Long-term intrathecal administration of morphine vs. baclofen: Differences in CSF glycoconjugate profiles using multiglycomics

Opioid use for treatment of persistent pain has increased dramatically over the past two decades, but it has not resulted in improved pain management outcomes. To understand the molecular mechanisms of opioids, molecular signatures that arise from opioid exposure are often sought after, using various analytical methods. In this study, we performed proteomics, and multiglycomics via sequential analysis of polysialic acids, glycosaminoglycans, N-glycans and O-glycans, using the same cerebral spinal fluid (CSF) sample from patients that had long-term (>2years), intrathecal morphine or baclofen administered via an indwelling pump. Proteomics and N-glycomics signatures between the two treatment groups were highly conserved, while significant differences were observed in polysialic acid, heparan sulfate glycosaminoglycan and O-glycan profiles between the two treatment groups. This represents the first study to investigate the potential relationships between diverse CSF conjugated glycans and long-term intrathecal drug exposure. The unique changes, observed by a sequential analytical workflow, reflect previously undescribed molecular effects of opioid administration and pain management.

Novel Insight Into Glycosaminoglycan Biosynthesis Based on Gene Expression Profiles.

Glycosaminoglycans (GAGs) including chondroitin sulfate, dermatan sulfate, heparan sulfate, and keratan sulfate, except for hyaluronan that is a free polysaccharide, are covalently attached to core proteins to form proteoglycans. More than 50 gene products are involved in the biosynthesis of GAGs. We recently developed a comprehensive glycosylation mapping tool, GlycoMaple, for visualization and estimation of glycan structures based on gene expression profiles. Using this tool, the expression levels of GAG biosynthetic genes were analyzed in various human tissues as well as tumor tissues. In brain and pancreatic tumors, the pathways for biosynthesis of chondroitin and dermatan sulfate were predicted to be upregulated. In breast cancerous tissues, the pathways for biosynthesis of chondroitin and dermatan sulfate were predicted to be up- and down-regulated, respectively, which are consistent with biochemical findings published in the literature. In addition, the expression levels of the chondroitin sulfate-proteoglycan versican and the dermatan sulfate-proteoglycan decorin were up- and down-regulated, respectively. These findings may provide new insight into GAG profiles in various human diseases including cancerous tumors as well as neurodegenerative disease using GlycoMaple analysis.

Detection of any-stage cancer using plasma and urine glycosaminoglycans.

3034 Background: Non-invasive liquid biopsies promise to enable early cancer detection and improve patient outcomes. However, virtually all liquid biopsies rely on genomic biomarkers, with limited sensitivity to early-stage tumors and poor detection of cancers shedding little cell-free DNA, like genitourinary or brain tumors. Here, we explored the use of plasma and urine glycosaminoglycan (GAGs) profiles, or GAGomes, as biomarkers reflective of tumor metabolism to serve as an alternative pan-cancer liquid biopsy. Methods: In this case-control study, we enrolled retrospective and prospective cohorts from Sweden and Italy. Included cases were treatment-naïve early-stage/low-grade cancers or metastatic/high-grade cancers across 14 histological types. Included controls were healthy 22-78 y/o adults with no history of cancer. We measured GAGomes – encompassing 17 chondroitin sulfate (CS), heparan sulfate (HS), and hyaluronate (HA) disaccharides - using a standardized UHPLC-MS/MS-based kit in a central blind laboratory. We tested the top GAGome features different in cancer using Bayesian estimation. These were used to design one plasma and one urine GAG score for the binary classification of cancer vs. control in a discovery set. We computed the area-under-the-curve (AUC), and sensitivity at 98% specificity of each GAG score in the validation set. A subset analysis was performed in early-stage/low-grade cancers only. In the subset of cases with survival records, we used multivariable Cox regression to estimate the hazard ratio (HR) for overall survival (OS) on each GAG score adjusted for cancer type, age, and gender. Results: GAGomes were measured in 753 plasma samples (460 cancers across 14 types, median age = 66 y/o, 51% female vs. 293 healthy adults, median age = 58 y/o, 57% female) and 559 urine samples (219 cancers across 5 types, median age = 69 y/o, 23% female vs. 340 healthy adults, median age = 56 y/o, 60% female). In the discovery set, the urine GAG score had an AUC = 0.80 (95% CI: 0.74-0.85, 124 cancers across 5 types vs. 184 controls) while the plasma GAG score had an AUC = 0.82 (95% CI: 0.78-0.86, 153 cancers across 14 types vs. 282 controls). In the validation set, the urine GAG score had an AUC = 0.78 (95% CI: 0.71-0.84, 95 cancers across 5 types vs. 156 controls) with 35% sensitivity at 98% specificity. The plasma GAG score had an AUC = 0.84 (95% CI: 0.79-0.88, 178 cancers across 14 types vs. 140 controls) with 41% sensitivity at 98% specificity. In the subset of early-stage/low-grade cancers, the AUC was 0.78 and 0.72 in plasma and urine, respectively. The plasma and urine GAG scores were independent predictors of OS regardless of cancer type (HR = 1.39, p = 0.005 in plasma [ N = 283, 11 types, 67 deaths, median follow-up 17 months] and HR = 1.53, p = 0.016 in urine [ N = 161, 4 types, 32 deaths, median follow-up 15 months]). Conclusions: GAGomes were sensitive non-invasive metabolic biomarkers for any-stage cancer, including genitourinary and brain tumors.

Plasma and urine free glycosaminoglycans as monitoring and predictive biomarkers in metastatic renal cell carcinoma: A prospective observational study.

e16540 Background: No liquid biomarkers are approved in renal cell carcinoma (RCC). In metastatic RCC (mRCC), there is a need to predict and monitor response noninvasively to guide the choice of treatment. Urine and plasma glycosaminoglycan (GAGs) profiles – or GAGomes - are promising biomarkers reflective of RCC metabolism. Here, we explored if GAGomes could predict and monitor response noninvasively. Methods: A single-center prospective consecutive series of mRCC patients elected for first-line therapy was enrolled between June 2016 - April 2019 at Sahlgrenska University Hospital, Gothenburg, Sweden. Response was assessed by the investigator as progressive disease (PD) versus non-PD. Plasma and urine GAGomes were measured at treatment start, after 6 weeks, and every 3rd month in a blinded central laboratory. We conducted Bayesian estimation to correlate GAGomes to response and to design GAG scores to classify PD. So-trained GAG scores were validated to predict PD vs. non-PD at treatment start or after 6 weeks. Results: Fifty patients with treatment-naïve mRCC were enrolled (median age: 68.5 years, 33% female). All received tyrosine-kinase inhibitors (37 sunitinib, 4 pazopanib, 9 cabozantinib). The median follow-up time was 3.5 months, totaling 65 response evaluation visits - 23 PD and 42 non-PD. PD was compatible with alterations in 40% of the detectable GAGome features. These were used to design a plasma, urine, and combined GAG progression score to classify PD vs. non-PD at response evaluation. The area-under-the-curve (AUC) was 0.91 in plasma, 0.98 in urine, and 0.99 when combined. In validation, the AUC to predict PD at treatment start was 0.64 in plasma, 0.63 in urine, and 0.71 when combined (N = 50); and, after 6 weeks, 0.75 in plasma, 0.66 in urine, and 0.80 when combined (N = 47). The combined GAG progression score had 62% sensitivity and 86% specificity to PD at treatment start and 67% and 87% after 6 weeks. Conclusions: GAGomes correlated with treatment response in mRCC. GAG scores were validated for the early prediction of response. Their clinical utility remains to be ascertained. Clinical trial information: NCT02732665.

Cardiac glycosaminoglycans and structural alterations during chronic stress-induced depression-like behavior in mice.

Major depressive disorder (MDD) is an independent risk factor for cardiovascular disease (CVD) and its complications; however, causal mechanisms remain unclear. In the present study, we investigate cardiac structural and functional alterations and associated changes in myocardial glycosaminoglycans (GAGs) disaccharide profile in mice that exhibit depression-like behavior. Mice were assigned to the chronic mild stress (CMS) group and nonstress control group (CT). The CMS group was exposed to a series of mild, unpredictable stressors for 7 wk. Mice in the CMS group show a significant decrease in protein expression of hippocampal brain-derived neurotrophic factor (BDNF) and exhibit depression-like behavioral changes, such as learned helplessness and decreased exploration behavior, as compared with the control group. Although cardiac function remained unchanged between the groups, echocardiography analysis showed slightly increased left ventricular wall thickness in the CMS group. Furthermore, the CMS group shows an increase in cardiomyocyte cross-sectional area and an associated decrease in BDNF protein expression and increase in IL-6 mRNA expression, when compared with control mice. GAG disaccharide analysis of the left ventricles of the CMS and CT mice revealed an elevation in heparan (HS) and chondroitin sulfate (CS) content in the CMS hearts (35.3% and 17.9%, respectively, vs. control group). Furthermore, we also observed that unsulfated or monosulfated disaccharides were the most abundant units; however, we did not find any significant difference in mole percent or sulfation pattern of HS/CS disaccharides between the groups. The current investigation highlights a need for further research to explore the relationship between cardiac GAGs biology and myocardial remodeling as a causal mechanism that underlie cardiovascular complications in patients with MDD.NEW & NOTEWORTHY Comorbidity between depression and CVD is well established, whereas its etiology, especially the role of nonfibrous components (proteoglycans/GAGs) of the extracellular matrix, is unexplored. To the best of our knowledge, this is the first study to characterize cardiac proteoglycan/glycosaminoglycan profile in response to depression-like behavioral changes in mice. We observed that chronic mild stress (CMS)-induced depression-like behavior and alterations in glycosaminoglycan profile were associated with structural changes in the heart.

The effect of electrospun scaffolds on the glycosaminoglycan profile of differentiating neural stem cells

The use of electrospun scaffolds for neural tissue engineering applications allows a closer mimicry of the native tissue extracellular matrix (ECM), important for the transplantation of cells in vivo. Moreover, the role of the electrospun fiber mat topography on neural stem cell (NSC) differentiation remains to be completely understood. In this work REN-VM cells (NSC model) were differentiated on polycaprolactone (PCL) nanofibers, obtained by wet/wet electrospinning, and on flat glass lamellas. The obtained differentiation profile of NSCs was evaluated using immunofluorescence and qPCR analysis. Glycosaminoglycan (GAG) analysis was successfully emplyed to evaluate changes in the GAG profile of differentiating cells through the use of the highly sensitive liquid chromatography-tandem mass/mass spectrometry (LC-MS/MS) method. Our results show that both culture platforms allow the differentiation of REN-VM cells into neural cells (neurons and astrocytes) similarly. Moreover, LC-MS/MS analysis shows changes in the production of GAGs present both in cell cultures and conditioned media samples. In the media, hyaluronic acid (HA) was detected and correlated with cellular activity and the production of a more plastic extracellular matrix. The cell samples evidence changes in chondroitin sulfate (CS4S, CS6S, CS4S6S) and heparan sulfate (HS6S, HS0S), similar to those previously described in vivo studies and possibly associated with the creation of complex structures, such as perineural networks. The GAG profile of differentiating REN-VM cells on electrospun scaffolds was analyzed for the first time. Our results highlight the advantage of using platforms obtain more reliable and robust neural tissue-engineered transplants.

MicroRNA-1252-5p Associated with Extracellular Vesicles Enhances Bortezomib Sensitivity in Multiple Myeloma Cells by Targeting Heparanase.

IntroductionMultiple myeloma (MM) remains an incurable disease, and patient survival requires a better understanding of this malignancy’s molecular aspects. Heparanase (HPSE) is highly expressed in aggressive MM cells and related to tumor growth, metastasis, and bortezomib (BTZ) resistance. Thus, targeting HPSE seems to be a promising approach for MM treatment, and because microRNAs (miRNAs) have emerged as potential regulators of HPSE expression, the use of extracellular vesicles (EVs) can allow the efficient delivery of therapeutic miRNAs.MethodsWe used prediction algorithms to identify potential miRNAs that regulate negatively HPSE expression. RT-qPCR was performed to assess miRNAs and HPSE expression in MM lines (U266 and RPMI-8226). Synthetic miRNA mimics were electroporated in MM cells to understand the miRNA contribution in HPSE expression, glycosaminoglycans (GAGs) profile, cell proliferation, and cell death induced by BTZ. EVs derived from HEK293T cells were engineered with miRNAs to evaluate their therapeutic potential combined with BTZ.ResultsIt revealed a direct association between BTZ sensitivity, HPSE, and miR-1252-5p expressions. Moreover, overexpression of miR-1252-5p significantly reduced HPSE expression and HPSE enzymatic activity in MM cells. The higher level of miR-1252-5p was correlated with a reduction of cell viability and higher sensitivity to BTZ. Further, EVs carrying miR-1252-5p increased MM cells' sensitivity to BTZ treatment.ConclusionThese results showed that miR-1252-5p could negatively regulate HPSE in MM, indicating the use of EVs carrying miR-1252-5p as a potential novel BTZ sensitization approach in MM cells.

Significant Remodeling Affects the Circulating Glycosaminoglycan Profile in Adult Patients with both Severe and Mild Forms of Acute Pancreatitis.

Acute pancreatitis (AP) manifests itself either as a mild, self-limiting inflammation or a severe, systemic inflammatory process that is associated with various complications and a high mortality rate. It is unknown whether these two forms of the disease can differ in the profile of circulating glycosaminoglycans, which are molecules with huge biological reactivity due to a high density of negative electric charge. Plasma glycosaminoglycans were characterized/quantified in 23 healthy controls, 32 patients with mild AP, and 15 individuals with severe disease using electrophoresis with enzymatic identification (chondroitin sulfate and heparan sulfate) or an ELISA-based test (hyaluronan). Moreover, the correlations between the glycosaminoglycan levels and clinical parameters were evaluated. Both forms of AP showed similar remodeling of the plasma profile of the sulfated glycosaminoglycans. In contrast, only in the patients with mild AP was the level of circulating hyaluronan significantly decreased as compared to the healthy controls. Both forms of AP are associated with systemic changes in the metabolism of glycosaminoglycans. However, the alterations in hyaluronan metabolism may contribute to the disease evolution. The circulating hyaluronan may have some clinical value to predict the severity of AP and to evaluate the clinical status of patients with severe AP.

Glycosaminoglycan remodeling during chondrogenic differentiation of human bone marrow-/synovial-derived mesenchymal stem/stromal cells under normoxia and hypoxia.

Glycosaminoglycans (GAGs) are major components of cartilage extracellular matrix (ECM), which play an important role in tissue homeostasis not only by providing mechanical load resistance, but also as signaling mediators of key cellular processes such as adhesion, migration, proliferation and differentiation. Specific GAG types as well as their disaccharide sulfation patterns can be predictive of the tissue maturation level but also of disease states such as osteoarthritis. In this work, we used a highly sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to perform a comparative study in terms of temporal changes in GAG and disaccharide composition between tissues generated from human bone marrow- and synovial-derived mesenchymal stem/stromal cells (hBMSC/hSMSC) after chondrogenic differentiation under normoxic (21% O2) and hypoxic (5% O2) micromass cultures. The chondrogenic differentiation of hBMSC/hSMSC cultured under different oxygen tensions was assessed through aggregate size measurement, chondrogenic gene expression analysis and histological/immunofluorescence staining in comparison to human chondrocytes. For all the studied conditions, the compositional analysis demonstrated a notable increase in the average relative percentage of chondroitin sulfate (CS), the main GAG in cartilage composition, throughout MSC chondrogenic differentiation. Additionally, hypoxic culture conditions resulted in significantly different average GAG and CS disaccharide percentage compositions compared to the normoxic ones. However, such effect was considerably more evident for hBMSC-derived chondrogenic aggregates. In summary, the GAG profiles described here may provide new insights for the prediction of cartilage tissue differentiation/disease states and to characterize the quality of MSC-generated chondrocytes obtained under different oxygen tension culture conditions.

Age-related functional changes of total thyroid hormones and glycosaminoglycans in growing calves.

Background and Aim:During the physiological growing, thyroid and proteoglycan glycosaminoglycan (GAG) changes dynamically occur, according to genetic and non-genetic factors. The purpose of this research was to compare the effects of early postnatal development (10 days) until 210 days of life on the triiodothyronine (T3), thyroxine (T4), the relative T4:T3 ratio, and GAGs profile, and to define the different reference intervals of the calf’s development through the various growing phases.Materials and Methods:The effect of growing on total thyroid hormones and GAG profiles was studied from 10 days to 210days of age in 64 clinically healthy Brown calves, 30males and 34females. Blood samples were collected at 10, 20, 30, 60, 90, 120, 150, 180, and 210days of age.Results:The results showed a significant effect of a calf’s growth on T3, T4, and GAG values (p<0.0001). Significant correlations between T3 and T4 were observed. Compared to the previous time point, T3 showed a significant decrease at 20days and at 60days (p<0.01), while a significant increase was observed at 90days and 210days (p<0.05); T4 showed a significant decrease at 20days (p<0.01), while significant increases were observed at both 180days and 210days (p<0.05); GAGs showed a significant increase at 120days and 210days (p<0.05). Positive and significant correlations between BW and GAGs in both males (p<0.0057) and females (p<0.0059) were observed.Conclusion:It can be concluded that the highest T3 and T4 concentrations have been associated with the early growing process (10days), with an increasing trend also at 210days, it is possible to hypothesize a probable metabolic effect of thyroid function in anabolic and/or catabolic directions during the calves’ development. Likewise, it can be reasonably inferred that the highest plasma GAGs at 210days may be due to their metabolic role during the development of growing calves. Taken together, these findings suggest the potential and relative contribution made by thyroid and GAGs effects on the dynamics of growing calves.

Multiplex testing for the screening of lysosomal storage disease in urine: Sulfatides and glycosaminoglycan profiles in 40 cases of sulfatiduria

PurposeTo describe an efficient and effective multiplex screening strategy for sulfatide degradation disorders and mucolipidosis type II/III (MLII/III) using 3 mL of urine. MethodsGlycosaminoglycans were analyzed by liquid chromatography-tandem mass spectrometry. Matrix assisted laser desorption/ionization-time of flight tandem mass spectrometry was used to identify free oligosaccharides and identify 22 ceramide trihexosides and 23 sulfatides, which are integrated by 670 calculated ratios. Collaborative Laboratory Integrated Reports (CLIR; https://clir.mayo.edu) was used for post-analytical interpretation of the complex metabolite profile and to aid in the differential diagnosis of abnormal results. ResultsMultiplex analysis was performed on 25 sulfatiduria case samples and compiled with retrospective data from an additional 15 cases revealing unique patterns of biomarkers for each disorder of sulfatide degradation (MLD, MSD, and Saposin B deficiency) and for MLII/III, thus allowing the formulation of a novel algorithm for the biochemical diagnosis of these disorders. ConclusionsComprehensive and integrated urine screening could be very effective in the initial workup of patients suspected of having a lysosomal disorder as it covers disorders of sulfatide degradation and narrows down the differential diagnosis in patients with elevated glycosaminoglycans.

Biochemical, machine learning and molecular approaches for the differential diagnosis of Mucopolysaccharidoses.

This study was aimed to construct classification and regression tree (CART) model of glycosaminoglycans (GAGs) for the differential diagnosis of Mucopolysaccharidoses (MPS). Two-dimensional electrophoresis and liquid chromatography-tandem mass spectrometry (LC-MS/MS) were used for the qualitative and quantitative analysis of GAGs. Specific enzyme assays and targeted gene sequencing were performed to confirm the diagnosis. Machine learning tools were used to develop CART model based on GAG profile. Qualitative and quantitative CART models showed 96.3% and 98.3% accuracy, respectively, in the differential diagnosis of MPS. The thresholds of different GAGs diagnostic of specific MPS types were established. In 60 MPS positive cases, 46 different mutations were identified in six specific genes. Among 31 different mutations identified in IDUA, nine were nonsense mutations and two were gross deletions while the remaining were missense mutations. In IDS gene, four missense, two frameshift, and one deletion were identified. In NAGLU gene, c.1693C > T and c.1914_1914insT were the most common mutations. Two ARSB, one case each of SGSH and GALNS mutations were observed. LC-MS/MS-based GAG pattern showed higher accuracy in the differential diagnosis of MPS. The mutation spectrum of MPS, specifically in IDUA and IDS genes, is highly heterogeneous among the cases studied.

The dual role of the glycosaminoglycan chondroitin-6-sulfate in the development, progression and metastasis of cancer.

The remarkable structural heterogeneity of chondroitin sulfate (CS) and dermatan sulfate (DS) generates biological information that can be unique to each of these glycosaminoglycans (GAGs), and changes in their composition are translated into alterations in the binding profiles of these molecules. CS/DS can bind to various cytokines and growth factors, cell surface receptors, adhesion molecules, enzymes and fibrillar glycoproteins of the extracellular matrix, thereby influencing both cell behavior and the biomechanical and biochemical properties of the matrix. In this review, we summarize the current knowledge concerning CS/DS metabolism in the human cancer stroma. The remodeling of the GAG profile in the tumor niche is manifested as a substantial increase in the CS content and a gradual decrease in the proportion between DS and CS. Furthermore, the composition of CS and DS is also affected, which results in a substantial increase in the 6‐O‐sulfated and/or unsulfated disaccharide content, which is concomitant with a decrease in the 4‐O‐sulfation level. Here, we discuss the possible impact of alterations in the CS/DS sulfation pattern on the binding capacity and specificity of these GAGs. Moreover, we propose potential consequences of the stromal accumulation of chondroitin‐6‐sulfate for the progression and metastasis of cancer.