Metabolomic profiling reveals potential markers and bioprocesses altered in bladder cancer progression

Enzymatic depletion of circulating glutamine is immunosuppressive in cancers

Although glutamine addiction in cancer cells is extensively reported, there is controversy on the impact of glutamine metabolism on the immune cells within the tumor microenvironment (TME). To address the role of extracellular glutamine, we enzymatically depleted circulating glutamine using PEGylated Helicobacter pylori gamma-glutamyl transferase (PEG-GGT) in syngeneic mouse models of breast and colon cancers. PEG-GGT treatment inhibits growth of cancer cells in vitro, but in vivo it increases myeloid-derived suppressor cells (MDSCs) and has no significant impact on tumor growth. By deriving a glutamine depletion signature, we analyze diverse human cancers within the TCGA and illustrate that glutamine depletion is not associated with favorable clinical outcomes and correlates with accumulation of MDSC. Broadly, our results help clarify the integrated impact of glutamine depletion within the TME and advance PEG-GGT as an enzymatic tool for the systemic and selective depletion (no asparaginase activity) of circulating glutamine in live animals.

Inferring Bladder Cancer Evolution from Mucosal field Effects by Whole-Organ Spatial Mutational, Proteomic, and Metabolomic Mapping

Multi-platform mutational, proteomic, and metabolomic spatial mapping was used on the whole-organ scale to identify the molecular evolution of bladder cancer from mucosal field effects. We identified complex proteomic and metabolomic dysregulations in microscopically normal areas of bladder mucosa adjacent to dysplasia and carcinoma in situ. The mutational landscape developed in a background of complex defects of protein homeostasis which included dysregulated nucleocytoplasmic transport, splicesome, ribosome biogenesis, and peroxisome. These changes were combined with altered urothelial differentiation which involved lipid metabolism and protein degradations controlled by PPAR. The complex alterations of proteome were accompanied by dysregulation of gluco-lipid energy-related metabolism. The analysis of mutational landscape identified three types of mutations based on their geographic distribution and variant allele frequencies. The most common were low frequency α mutations restricted to individual mucosal samples. The two other groups of mutations were associated with clonal expansion. The first of this group referred to as β mutations occurred at low frequencies across the mucosa. The second of this group called γ mutations increased in frequency with disease progression. Modeling of the mutations revealed that carcinogenesis may span nearly 30 years and can be divided into dormant and progressive phases. The α mutations developed gradually in the dormant phase. The progressive phase lasted approximately five years and was signified by the advent of β mutations, but it was driven by γ mutations which developed during the last 2-3 years of disease progression to invasive cancer. Our study indicates that the understanding of complex alterations involving mucosal microenvironment initiating bladder carcinogenesis can be inferred from the multi-platform whole-organ mapping.

Metabolomics for the diagnosis of bladder cancer: A systematic review

Objective

Metabolomics has been extensively utilized in bladder cancer (BCa) research, employing mass spectrometry and nuclear magnetic resonance spectroscopy to compare various variables (tissues, serum, blood, and urine). This study aimed to identify potential biomarkers for early BCa diagnosis.

Methods

A search strategy was designed to identify clinical trials, descriptive and analytical observational studies from databases such as Medline, Embase, Cochrane Central Register of Controlled Trials, and Latin American and Caribbean Literature in Health Sciences. Inclusion criteria comprised studies involving BCa tissue, serum, blood, or urine profiling using widely adopted metabolomics techniques like mass spectrometry and nuclear magnetic resonance. Primary outcomes included description of metabolites and metabolomics profiling in BCa patients and the association of metabolites and metabolomics profiling with BCa diagnosis compared to control patients. The risk of bias was assessed using the Quality Assessment of Studies of Diagnostic Accuracy.

Results

The search strategy yielded 2832 studies, of which 30 case-control studies were included. Urine was predominantly used as the primary sample for metabolite identification. Risk of bias was often unclear inpatient selection, blinding of the index test, and reference standard assessment, but no applicability concerns were observed. Metabolites and metabolomics profiles associated with BCa diagnosis were identified in glucose, amino acids, nucleotides, lipids, and aldehydes metabolism.

Conclusion

The identified metabolites in urine included citric acid, valine, tryptophan, taurine, aspartic acid, uridine, ribose, phosphocholine, and carnitine. Tissue samples exhibited elevated levels of lactic acid, amino acids, and lipids. Consistent findings across tissue, urine, and serum samples revealed downregulation of citric acid and upregulation of lactic acid, valine, tryptophan, taurine, glutamine, aspartic acid, uridine, ribose, and phosphocholine.

A metabolomics study on carcinogenesis of ground-glass nodules

Objective

This study aimed to identify differential metabolites and key metabolic pathways between lung adenocarcinoma (LUAD) tissues and normal lung (NL) tissues using metabolomics techniques, to discover potential biomarkers for the early diagnosis of lung cancer.

Material and Methods

Forty-five patients with primary ground-glass nodules (GGN) identified on computed tomography imaging and who were willing to undergo surgery at Shanghai General Hospital from December 2021 to December 2022 were recruited to the study. All participants underwent video thoracoscopy surgery with segmental or wedge resection of the lung. Tissue samples for pathological examination were collected from the site of ground-glass nodules (GGN) lesion and 3 cm away from the lesion (NL). The pathology results were 35 lung adenocarcinoma (LUAD) cases (13 invasive adenocarcinoma, 14 minimally invasive adenocarcinoma, and eight adenocarcinoma in situ), 10 benign samples, and 45 NL tissues. For the untargeted metabolomics technique, 25 LUAD samples were assigned as the case group and 30 NL tissues as the control group. For the targeted metabolomics technique, ten LUAD samples were assigned as the case group and 15 NL tissues as the control group. Samples were analyzed by untargeted and targeted metabolomics, with liquid chromatography-tandem mass spectrometry detection used as part of the experimental procedure.

Results

Untargeted metabolomics revealed 164 differential metabolites between the case and control groups, comprising 110 up regulations and 54 down regulations. The main metabolic differences found by the untargeted method were organic acids and their derivatives. Targeted metabolomics revealed 77 differential metabolites between the case and control groups, comprising 69 up regulations and eight down regulations. The main metabolic changes found by the targeted method were fatty acids, amino acids, and organic acids. The levels of organic acids such as lactic acid, fumaric acid, and malic acid were significantly increased in LUAD tissue compared to NL. Specifically, an increased level of L-lactic acid was found by both untargeted (variable importance in projection [VIP] = 1.332, fold-change [FC] = 1.678, q = 0.000) and targeted metabolomics (VIP = 1.240, FC = 1.451, q = 0.043). Targeted metabolomics also revealed increased levels of fumaric acid (VIP = 1.481, FC = 1.764, q = 0.106) and L-malic acid (VIP = 1.376, FC = 1.562, q = 0.012). Most of the 20 differential fatty acids identified were downregulated, including dodecanoic acid (VIP = 1.416, FC = 0.378, q = 0.043) and tridecane acid (VIP = 0.880, FC = 0.780, q = 0.106). Furthermore, increased levels of differential amino acids were found in LUAD samples.

Conclusion

Lung cancer is a complex and heterogeneous disease with diverse genetic alterations. The study of metabolic profiles is a promising research field in this cancer type. Targeted and untargeted metabolomics revealed significant differences in metabolites between LUAD and NL tissues, including elevated levels of organic acids, decreased levels of fatty acids, and increased levels of amino acids. These metabolic features provide valuable insights into LUAD pathogenesis and can potentially serve as biomarkers for prognosis and therapy response.

Untargeted metabolomics of bladder tissue using liquid chromatography and quadrupole time-of-flight mass spectrometry for cancer biomarker detection

Bladder cancer (BC) ranks among the most common cancers globally, with an increasing occurrence, particularly in developed nations. Utilizing tissue metabolomics presents a promising strategy for identifying potential biomarkers for cancer detection. In this study, we utilized ultra-high-performance liquid chromatography coupled with ultra-high-resolution mass spectrometry (UHPLC-UHRMS), incorporating both C18-silica and HILIC columns, to comprehensively analyze both polar and non-polar metabolite profiles in tissue samples from 99 patients with bladder cancer. By utilizing an untargeted approach with external validation, we identified twenty-five tissue metabolites that hold promise as potential indicators of BC. Furthermore, twenty-five characteristic tissue metabolites that exhibit discriminatory potential across bladder cancer tumor grades, as well as thirty-nine metabolites that display correlations with tumor stages were presented. Receiver operating characteristics analysis demonstrated high predictive power for all types of metabolomics data, with area under the curve (AUC) values exceeding 0.966. Notably, this study represents the first report in which human bladder normal tissues adjacent to cancerous tissues were analyzed using UHPLC-UHRMS. These findings suggest that the metabolite markers identified in this investigation could serve as valuable tools for the detection and monitoring of bladder cancer stages and grades.

Metabolomic profiles in Jamaican children with and without autism spectrum disorder

Background

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition with a wide range of behavioral and cognitive impairments. While genetic and environmental factors are known to contribute to its etiology, the underlying metabolic perturbations associated with ASD which can potentially connect genetic and environmental factors, remain poorly understood. Therefore, we conducted a metabolomic case-control study and performed a comprehensive analysis to identify significant alterations in metabolite profiles between children with ASD and typically developing (TD) controls.

Objective

To elucidate potential metabolomic signatures associated with ASD in children and identify specific metabolites that may serve as biomarkers for the disorder.

Methods

We conducted metabolomic profiling on plasma samples from participants in the second phase of Epidemiological Research on Autism in Jamaica (ERAJ-2), which was a 1:1 age (±6 months)-and sex-matched cohort of 200 children with ASD and 200 TD controls (2-8 years old). Using high-throughput liquid chromatography-mass spectrometry techniques, we performed a targeted metabolite analysis, encompassing amino acids, lipids, carbohydrates, and other key metabolic compounds. After quality control and imputation of missing values, we performed univariable and multivariable analysis using normalized metabolites while adjusting for covariates, age, sex, socioeconomic status, and child's parish of birth.

Results

Our findings revealed unique metabolic patterns in children with ASD for four metabolites compared to TD controls. Notably, three of these metabolites were fatty acids, including myristoleic acid, eicosatetraenoic acid, and octadecenoic acid. Additionally, the amino acid sarcosine exhibited a significant association with ASD.

Conclusions

These findings highlight the role of metabolites in the etiology of ASD and suggest opportunities for the development of targeted interventions.

Quantitative transcriptomic and epigenomic data analysis: a primer

The advent of microarray and second generation sequencing technology has revolutionized the field of molecular biology, allowing researchers to quantitatively assess transcriptomic and epigenomic features in a comprehensive and cost-efficient manner. Moreover, technical advancements have pushed the resolution of these sequencing techniques to the single cell level. As a result, the bottleneck of molecular biology research has shifted from the bench to the subsequent omics data analysis. Even though most methodologies share the same general strategy, state-of-the-art literature typically focuses on data type specific approaches and already assumes expert knowledge. Here, however, we aim at providing conceptual insight in the principles of genome-wide quantitative transcriptomic and epigenomic (including open chromatin assay) data analysis by describing a generic workflow. By starting from a general framework and its assumptions, the need for alternative or additional data-analytical solutions when working with specific data types becomes clear, and are hence introduced. Thus, we aim to enable readers with basic omics expertise to deepen their conceptual and statistical understanding of general strategies and pitfalls in omics data analysis and to facilitate subsequent progression to more specialized literature.

Metabolomic profiling of human bladder tissue extracts

INTRODUCTION

Bladder cancer is a common malignancy affecting the urinary tract and effective biomarkers and for which monitoring therapeutic interventions have yet to be identified.

OBJECTIVES

Major aim of this work was to perform metabolomic profiling of human bladder cancer and adjacent normal tissue and to evaluate cancer biomarkers.

METHODS

This study utilized nuclear magnetic resonance (NMR) and high-resolution nanoparticle-based laser desorption/ionization mass spectrometry (LDI-MS) methods to investigate polar metabolite profiles in tissue samples from 99 bladder cancer patients.

RESULTS

Through NMR spectroscopy, six tissue metabolites were identified and quantified as potential indicators of bladder cancer, while LDI-MS allowed detection of 34 compounds which distinguished cancer tissue samples from adjacent normal tissue. Thirteen characteristic tissue metabolites were also found to differentiate bladder cancer tumor grades and thirteen metabolites were correlated with tumor stages. Receiver-operating characteristics analysis showed high predictive power for all three types of metabolomics data, with area under the curve (AUC) values greater than 0.853.

CONCLUSION

To date, this is the first study in which bladder human normal tissues adjacent to cancerous tissues are analyzed using both NMR and MS method. These findings suggest that the metabolite markers identified in this study may be useful for the detection and monitoring of bladder cancer stages and grades.

P2Y2 purinergic receptor gene deletion protects mice from bacterial endotoxin and sepsis-associated liver injury and mortality

The liver plays a significant role in regulating a wide range of metabolic, homeostatic, and host-defense functions. However, the impact of liver injury on the host's ability to control bacteremia and morbidity in sepsis is not well understood. Leukocyte recruitment and activation lead to cytokine and chemokine release, which, in turn, trigger hepatocellular injury and elevate nucleotide levels in the extracellular milieu. P2Y2 purinergic receptors, G protein-coupled and activated by extracellular ATP/UTP, are expressed at the cell surface of hepatocytes and nonparenchymal cells. We sought to determine whether P2Y2 purinergic receptor function is necessary for the maladaptive host response to bacterial infection and endotoxin-mediated inflammatory liver injury and mortality in mice. We report that P2Y2 purinergic receptor knockout mice (P2Y2-/-) had attenuated inflammation and liver injury, with improved survival in response to LPS/galactosamine (LPS/GalN; inflammatory liver injury) and cecal ligation and puncture (CLP; polymicrobial sepsis). P2Y2-/- livers had attenuated c-Jun NH2-terminal kinase activation, matrix metallopeptidase-9 expression, and hepatocyte apoptosis in response to LPS/GalN and attenuated inducible nitric oxide synthase and nucleotide-binding oligomerization domain, leucine-rich repeat and pyrin domain containing 3 protein expression in response to CLP. Implicating liver injury in the disruption of amino acid homeostasis, CLP led to lower serum arginine and higher bacterial load and morbidity in the WT mice, whereas serum arginine levels were comparable to sham-operated controls in P2Y2-/- mice, which had attenuated bacteremia and improved survival. Collectively, our studies highlight the pathophysiological relevance of P2Y2 purinergic receptor function in inflammatory liver injury and dysregulation of systemic amino acid homeostasis with implications for sepsis-associated immune dysfunction and morbidity in mice.NEW & NOTEWORTHY Our studies provide experimental evidence for P2Y2 purinergic receptor-mediated potentiation of inflammatory liver injury, morbidity, and mortality, in two well-established animal models of inflammatory liver injury. Our findings highlight the potential to target P2Y2 purinergic signaling to attenuate the induction of "cytokine storm" and prevent its deleterious consequences on liver function, systemic amino acid homeostasis, host response to bacterial infection, and sepsis-associated morbidity and mortality.

Analysis of the Inhibitory Effect of hsa-miR-145-5p and hsa-miR-203a-5p on Imatinib-Resistant K562 Cells by GC/MS Metabolomics Method

Imatinib (IM) resistance is considered to be a significant challenge in the management of chronic myeloid leukemia (CML). Previous studies have reported that hsa-miR-145-5p and hsa-miR-203a-5p can overcome IM resistance and hsa-miR-203a-5p can alter glutathione metabolism in IM-resistant cells. The purpose of this study was to examine whether hsa-miR-145-5p or hsa-miR-203a-5p counters IM resistance by targeting the overall metabolic profile of IM-resistant K562 cells. The metablic profiling of cell lysates obtained from IM-sensitive, IM-resistant, and miR-transfected IM-resistant K562 cells was carried out using the GC-MS technique. Overall, 75 major metabolites were detected, of which 32 were present in all samples. The pathway analysis of MetaboAnalyst 5.0 revealed that the majorly enriched pathways included glucose metabolism, fatty acid biosynthesis, lipogenesis, and nucleotide metabolism. Eleven of identified metabolites, l-glutamine, l-glutamic acid, l-lactic acid, phosphoric acid, 9,12-octadecadienoic acid, 9-octadecenoic acid, myristic acid, palmitic acid, cholesterol, and β-alanine, appeared in enriched pathways. IM-resistant cells had comparatively higher concentrations of all of these metabolites. Notably, the introduction of hsa-miR-145-5p or hsa-miR-203a-5p into resistant cells resulted in a decrease in levels of these metabolites. The efficacy of miR-203a-5p was particularly remarkable in comparison with miR-145-5p, as evidenced by partial least-squares-discriminant analysis (PLS-DA), which showed a high level of similarity in metabolic profile between IM-sensitive K562 cells and IM-resistant cells transfected with hsa-miR-203a-5p. The results indicate that GC-MS-based metabolic profiling has the potential to distinguish between drug-resistant and -sensitive cells. This approach can also be used to routinely monitor therapeutic response in drug-resistant patients, thus, enabling personalized therapy.

Sulforaphane and bladder cancer: a potential novel antitumor compound

Bladder cancer (BC) is a common form of urinary tract tumor, and its incidence is increasing annually. Unfortunately, an increasing number of newly diagnosed BC patients are found to have advanced or metastatic BC. Although current treatment options for BC are diverse and standardized, it is still challenging to achieve ideal curative results. However, Sulforaphane, an isothiocyanate present in cruciferous plants, has emerged as a promising anticancer agent that has shown significant efficacy against various cancers, including bladder cancer. Recent studies have demonstrated that Sulforaphane not only induces apoptosis and cell cycle arrest in BC cells, but also inhibits the growth, invasion, and metastasis of BC cells. Additionally, it can inhibit BC gluconeogenesis and demonstrate definite effects when combined with chemotherapeutic drugs/carcinogens. Sulforaphane has also been found to exert anticancer activity and inhibit bladder cancer stem cells by mediating multiple pathways in BC, including phosphatidylinositol-3-kinase (PI3K)/protein kinase B (Akt)/mammalian target of rapamycin (mTOR), mitogen-activated protein kinase (MAPK), nuclear factor kappa-B (NF-κB), nuclear factor (erythroid-derived 2)-like 2 (Nrf2), zonula occludens-1 (ZO-1)/beta-catenin (β-Catenin), miR-124/cytokines interleukin-6 receptor (IL-6R)/transcription 3 (STAT3). This article provides a comprehensive review of the current evidence and molecular mechanisms of Sulforaphane against BC. Furthermore, we explore the effects of Sulforaphane on potential risk factors for BC, such as bladder outlet obstruction, and investigate the possible targets of Sulforaphane against BC using network pharmacological analysis. This review is expected to provide a new theoretical basis for future research and the development of new drugs to treat BC.

Metabolic signature biomarkers for predicting the recurrence of urological cancers

A significant number of patients diagnosed with localized urological cancers experience relapse and disease progression after surgery. Hence, molecular markers for patient risk stratification are needed to improve the current management guidelines. This article critically reviews for the first time, to our knowledge, the promise of metabolomics-based approaches to identify metabolic signatures as candidate prognostic biomarkers to predict recurrences at the time of surgery in prostate cancer (PCa), bladder cancer (BCa), and renal cell carcinoma (RCC). Dysregulations in the levels of several tumoral, circulating, and excreted metabolites have been reported in PCa patients experiencing recurrence within 1.5 to 8 years of follow-up. The combination of these metabolic biomarkers with clinical parameters (e.g., pathological T stage, Gleason score) has shown great potential to improve the predictive ability of PCa recurrence. In contrast, predictive biomarkers of recurrence in BCa and RCC have been poorly explored. Overall, this review highlights the great potential of metabolomics in discovering prognostic biomarkers for a more accurate patient risk stratification in urological cancers.

Targeted quantitative metabolomics with a linear mixed-effect model for analysis of urinary nucleosides and deoxynucleosides from bladder cancer patients before and after tumor resection

In the present study, we developed and validated a fast, simple, and sensitive quantitative method for the simultaneous determination of eleven nucleosides and deoxynucleosides from urine samples. The analyses were performed with the use of liquid chromatography coupled with triple quadrupole mass spectrometry. The sample pretreatment procedure was limited to centrifugation, vortex mixing of urine samples with a methanol/water solution (1:1, v/v), evaporation and dissolution steps. The analysis lasted 20 min and was performed in dynamic multiple reaction monitoring mode (dMRM) in positive polarity. Process validation was conducted to determine the linearity, precision, accuracy, limit of quantification, stability, recovery and matrix effect. All validation procedures were carried out in accordance with current FDA and EMA regulations. The validated method was applied for the analysis of 133 urine samples derived from bladder cancer patients before tumor resection and 24 h, 2 weeks, and 3, 6, 9, and 12 months after the surgery. The obtained data sets were analyzed using a linear mixed-effect model. The analysis revealed that concentration level of 2-methylthioadenosine was decreased, while for inosine, it was increased 24 h after tumor resection in comparison to the preoperative state. The presented quantitative longitudinal study of urine nucleosides and deoxynucleosides before and up to 12 months after bladder tumor resection brings additional prospective insight into the metabolite excretion pattern in bladder cancer disease. Moreover, incurred sample reanalysis was performed proving the robustness and repeatability of the developed targeted method.

Liquid biopsy in urothelial carcinoma: Detection techniques and clinical applications

The types of urothelial carcinoma (UC) include urothelial bladder cancer and upper tract urothelial carcinoma. Current diagnostic techniques cannot meet the needs of patients. Liquid biopsy is an accurate method of determining the molecular profile of UC and is a cutting-edge and popular technique that is expected to complement existing detection techniques and benefit patients with UC. Circulating tumor cells, cell-free DNA, cell-free RNA, extracellular vesicles, proteins, and metabolites can be found in the blood, urine, or other bodily fluids and are examined during liquid biopsies. This article focuses on the components of liquid biopsies and their clinical applications in UC. Liquid biopsies have tremendous potential in multiple aspects of precision oncology, from early diagnosis and treatment monitoring to predicting prognoses. They may therefore play an important role in the management of UC and precision medicine.

Untargeted urinary metabolomics for bladder cancer biomarker screening with ultrahigh-resolution mass spectrometry

Bladder cancer (BC) is a common urological malignancy with a high probability of death and recurrence. Cystoscopy is used as a routine examination for diagnosis and following patient monitoring for recurrence. Repeated costly and intrusive treatments may discourage patients from having frequent follow-up screenings. Hence, exploring novel non-invasive ways to help identify recurrent and/or primary BC is critical. In this work, 200 human urine samples were profiled using ultra-high-performance liquid chromatography and ultra-high-resolution mass spectrometry (UHPLC-UHRMS) to uncover molecular markers differentiating BC from non-cancer controls (NCs). Univariate and multivariate statistical analyses with external validation identified metabolites that distinguish BC patients from NCs disease. More detailed divisions for the stage, grade, age, and gender are also discussed. Findings indicate that monitoring urine metabolites may provide a non-invasive and more straightforward diagnostic method for identifying BC and treating recurrent diseases.

Roles of non-coding RNAs in the metabolism and pathogenesis of bladder cancer

Bladder cancer (BC) is featured as the second most common malignancy of the urinary tract worldwide with few treatments leading to high incidence and mortality. It stayed a virtually intractable disease, and efforts to identify innovative and effective therapies are urgently needed. At present, more and more evidence shows the importance of non-coding RNA (ncRNA) for disease-related study, diagnosis, and treatment of diverse types of malignancies. Recent evidence suggests that dysregulated functions of ncRNAs are closely associated with the pathogenesis of numerous cancers including BC. The detailed mechanisms underlying the dysregulated role of ncRNAs in cancer progression are still not fully understood. This review mainly summarizes recent findings on regulatory mechanisms of the ncRNAs, long non-coding RNAs, microRNAs, and circular RNAs, in cancer progression or suppression and focuses on the predictive values of ncRNAs-related signatures in BC clinical outcomes. A deeper understanding of the ncRNA interactive network could be compelling framework for developing biomarker-guided clinical trials.

Mutations in the transcriptional regulator MeCP2 severely impact key cellular and molecular signatures of human astrocytes during maturation

Mutations in the MECP2 gene underlie a spectrum of neurodevelopmental disorders, most commonly Rett syndrome (RTT). We ask whether MECP2 mutations interfere with human astrocyte developmental maturation, thereby affecting their ability to support neurons. Using human-based models, we show that RTT-causing MECP2 mutations greatly impact the key role of astrocytes in regulating overall brain bioenergetics and that these metabolic aberrations are likely mediated by dysfunctional mitochondria. During post-natal maturation, astrocytes rely on neurons to induce their complex stellate morphology and transcriptional changes. While MECP2 mutations cause cell-intrinsic aberrations in the astrocyte transcriptional landscape, surprisingly, they do not affect the neuron-induced astrocyte gene expression. Notably, however, astrocytes are unable to develop complex mature morphology due to cell- and non-cell-autonomous aberrations caused by MECP2 mutations. Thus, MECP2 mutations critically impact key cellular and molecular features of human astrocytes and, hence, their ability to interact and support the structural and functional maturation of neurons.

Association of altered metabolic profiles and long non-coding RNAs expression with disease severity in breast cancer patients: analysis by 1H NMR spectroscopy and RT-q-PCR

INTRODUCTION

Globally, one of the major causes of cancer related deaths in women is breast cancer. Although metabolic pattern is altered in cancer patients, robust metabolic biomarkers with a potential to improve the screening and disease monitoring are lacking. A complete metabolome profiling of breast cancer patients may lead to the identification of diagnostic/prognostic markers and potential targets.

OBJECTIVES

The aim of this study was to analyze the metabolic profile in the serum from 43 breast cancer patients and 13 healthy individuals.

MATERIALS & METHODS

We used ¹H NMR spectroscopy for the identification and quantification of metabolites. q-RT-PCR was used to examine the relative expression of lncRNAs.

RESULTS

Metabolites such as amino acids, lipids, membrane metabolites, lipoproteins, and energy metabolites were observed in the serum from both patients and healthy individuals. Using unsupervised PCA, supervised PLS-DA, supervised OPLS-DA, and random forest classification, we observed that more than 25 metabolites were altered in the breast cancer patients. Metabolites with AUC value > 0.9 were selected for further analysis that revealed significant elevation of lactate, LPR and glycerol, while the level of glucose, succinate, and isobutyrate was reduced in breast cancer patients in comparison to healthy control. The level of these metabolites (except LPR) was altered in advanced-stage breast cancer patients in comparison to early-stage breast cancer patients. The altered metabolites were also associated with over 25 signaling pathways related to metabolism. Further, lncRNAs such as H19, MEG3 and GAS5 were dysregulated in the breast tumor tissue in comparison to normal adjacent tissue.

CONCLUSION

The study provides insights into metabolic alteration in breast cancer patients. It also provides an avenue to examine the association of lncRNAs with metabolic patterns in patients.

Obesity Is Associated with Altered Tumor Metabolism in Metastatic Melanoma

PURPOSE

Overweight/obese (OW/OB) patients with metastatic melanoma unexpectedly have improved outcomes with immune checkpoint inhibitors (ICI) and BRAF-targeted therapies. The mechanism(s) underlying this association remain unclear, thus we assessed the integrated molecular, metabolic, and immune profile of tumors, as well as gut microbiome features, for associations with patient body mass index (BMI).

EXPERIMENTAL DESIGN

Associations between BMI [normal (NL < 25) or OW/OB (BMI ≥ 25)] and tumor or microbiome characteristics were examined in specimens from 782 patients with metastatic melanoma across 7 cohorts. DNA associations were evaluated in The Cancer Genome Atlas cohort. RNA sequencing from 4 cohorts (n = 357) was batch corrected and gene set enrichment analysis (GSEA) by BMI category was performed. Metabolic profiling was conducted in a subset of patients (x = 36) by LC/MS, and in flow-sorted melanoma tumor cells (x = 37) and patient-derived melanoma cell lines (x = 17) using the Seahorse XF assay. Gut microbiome features were examined in an independent cohort (n = 371).

RESULTS

DNA mutations and copy number variations were not associated with BMI. GSEA demonstrated that tumors from OW/OB patients were metabolically quiescent, with downregulation of oxidative phosphorylation and multiple other metabolic pathways. Direct metabolite analysis and functional metabolic profiling confirmed decreased central carbon metabolism in OW/OB metastatic melanoma tumors and patient-derived cell lines. The overall structure, diversity, and taxonomy of the fecal microbiome did not differ by BMI.

CONCLUSIONS

These findings suggest that the host metabolic phenotype influences melanoma metabolism and provide insight into the improved outcomes observed in OW/OB patients with metastatic melanoma treated with ICIs and targeted therapies. See related commentary by Smalley, p. 5.

Impact of sex on outcomes after surgery for non-muscle-invasive and muscle-invasive bladder urothelial carcinoma: a systematic review and meta-analysis

PURPOSE

To assess the prognostic value of sex for non-muscle-invasive/muscle-invasive bladder urothelial carcinoma (NMIBC/MIBC) treated with radical surgery.

METHODS

The PubMed, Web of Science, and Scopus databases were searched in November 2021 according to the Preferred Reporting Items for Systematic Review and Meta-analysis statement. Studies were deemed eligible if they involved the comparison of the overall, cancer-specific, progression, and recurrence-free survival of patients with NMIBC/MIBC. Formal sex-stratified meta-analyses of these outcomes were performed.

RESULTS

Thirty-one studies, which included 32,525 patients with NMIBC, and 63 studies, which included 85,132 patients with MIBC, were eligible for review and meta-analysis. Female sex was associated with worse cancer-specific survival (pooled hazard ratio [HR], 1.21; 95% confidence interval [CI], 1.11-1.31) and overall survival (pooled HR, 1.02; 95% CI, 1.00-1.05) in patients with MIBC. In contrast, however, sex was not associated with cancer-specific survival (pooled HR, 1.01; 95% CI, 0.70-1.46), progression-free survival (pooled HR, 1.04; 95% CI, 0.88-1.24), and recurrence-free survival (pooled HR, 1.06; 95% CI, 0.98-1.16) in patients with NMIBC.

CONCLUSIONS

Sex is associated with an increased risk of worse survival outcomes in patients with MIBC but not in those with NMIBC. Given the genetic and social differences between sexes, sex may represent a key factor in the clinical decision-making process.

Integrative metabolomics and transcriptomics analysis reveals novel therapeutic vulnerabilities in lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) comprises the majority (~85%) of all lung tumors, with lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) being the most frequently diagnosed histological subtypes. Multi-modal omics profiling has been carried out in NSCLC, but no studies have yet reported a unique metabolite-related gene signature and altered metabolic pathways associated with LUAD and LUSC.

METHODS

We integrated transcriptomics and metabolomics to analyze 30 human lung tumors and adjacent noncancerous tissues. Differential co-expression was used to identify modules of metabolites that were altered between normal and tumor.

RESULTS

We identified unique metabolite-related gene signatures specific for LUAD and LUSC and key pathways aberrantly regulated at both transcriptional and metabolic levels. Differential co-expression analysis revealed that loss of coherence between metabolites in tumors is a major characteristic in both LUAD and LUSC. We identified one metabolic onco-module gained in LUAD, characterized by nine metabolites and 57 metabolic genes. Multi-omics integrative analysis revealed a 28 metabolic gene signature associated with poor survival in LUAD, with six metabolite-related genes as individual prognostic markers.

CONCLUSIONS

We demonstrated the clinical utility of this integrated metabolic gene signature in LUAD by using it to guide repurposing of AZD-6482, a PI3Kβ inhibitor which significantly inhibited three genes from the 28-gene signature. Overall, we have integrated metabolomics and transcriptomics analyses to show that LUAD and LUSC have distinct profiles, inferred gene signatures with prognostic value for patient survival, and identified therapeutic targets and repurposed drugs for potential use in NSCLC treatment.

Understanding uncontrolled severe allergic asthma by integration of omic and clinical data

BACKGROUND

Asthma is a complex, multifactorial disease often linked with sensitization to house dust mites (HDM). There is a subset of patients that does not respond to available treatments, who present a higher number of exacerbations and a worse quality of life. To understand the mechanisms of poor asthma control and disease severity, we aim to elucidate the metabolic and immunologic routes underlying this specific phenotype and the associated clinical features.

METHODS

Eighty-seven patients with a clinical history of asthma were recruited and stratified in 4 groups according to their response to treatment: corticosteroid-controlled (ICS), immunotherapy-controlled (IT), biologicals-controlled (BIO) or uncontrolled (UC). Serum samples were analysed by metabolomics and proteomics; and classifiers were built using machine-learning algorithms.

RESULTS

Metabolomic analysis showed that ICS and UC groups cluster separately from one another and display the highest number of significantly different metabolites among all comparisons. Metabolite identification and pathway enrichment analysis highlighted increased levels of lysophospholipids related to inflammatory pathways in the UC patients. Likewise, 8 proteins were either upregulated (CCL13, ARG1, IL15 and TNFRSF12A) or downregulated (sCD4, CCL19 and IFNγ) in UC patients compared to ICS, suggesting a significant activation of T cells in these patients. Finally, the machine-learning model built including metabolomic and clinical data was able to classify the patients with an 87.5% accuracy.

CONCLUSIONS

UC patients display a unique fingerprint characterized by inflammatory-related metabolites and proteins, suggesting a pro-inflammatory environment. Moreover, the integration of clinical and experimental data led to a deeper understanding of the mechanisms underlying UC phenotype.

Metabolomic Approaches for Detection and Identification of Biomarkers and Altered Pathways in Bladder Cancer

Metabolomic analysis has proven to be a useful tool in biomarker discovery and the molecular classification of cancers. In order to find new biomarkers, and to better understand its pathological behavior, bladder cancer also has been studied using a metabolomics approach. In this article, we review the literature on metabolomic studies of bladder cancer, focusing on the different available samples (urine, blood, tissue samples) used to perform the studies and their relative findings. Moreover, the multi-omic approach in bladder cancer research has found novel insights into its metabolic behavior, providing excellent start-points for new diagnostic and therapeutic strategies. Metabolomics data analysis can lead to the discovery of a “signature pathway” associated with the progression of bladder cancer; this aspect could be potentially valuable in predictions of clinical outcomes and the introduction of new treatments. However, further studies are needed to give stronger evidence and to make these tools feasible for use in clinical practice.

Prognostic impact of insulin‐like growth factor‐I and its binding proteins, insulin‐like growth factor‐I binding protein‐2 and ‐3, on adverse histopathological features and survival outcomes after radical cystectomy

Objectives

Insulin‐like growth factor‐I and its binding proteins are involved in cancer development, progression, and metastasis. In urothelial carcinoma, the impact of this pathway is still poorly investigated. The present large cohort study aimed to evaluate the association of preoperative circulating levels of insulin‐like growth factor‐I, insulin‐like growth factor‐I binding protein‐2 and ‐3 on outcomes after radical cystectomy.

Methods

A retrospective cohort study of the plasma specimens from 1036 consecutive urothelial carcinoma patients who were treated with radical cystectomy. The primary and secondary outcomes were adverse histopathological features and survival outcomes. Binominal logistic regression and multivariable Cox regression analyses were performed to assess the association of plasma levels of insulin‐like growth factor‐I, insulin‐like growth factor‐I binding protein‐2 and ‐3 with outcomes.

Results

On multivariable analysis adjusting for the effects of preoperative variables, lower insulin‐like growth factor‐I binding protein‐2 levels were associated with an increased risk of lymph node metastasis and (any non‐organ confined disease) any non‐organ confined disease. Insulin‐like growth factor‐I binding protein‐3 levels were also inversely independently associated with lymph node metastasis. Receiver operating characteristic curve analysis showed that the addition of insulin‐like growth factor‐I binding proteins biomarkers to a reference model significantly improved the discriminating ability for the prediction of lymph node metastasis (+10.0%, P < 0.001). On multivariable Cox regression models, lower levels of both insulin‐like growth factor‐I binding protein‐2 and ‐3 plasma levels were associated with recurrence‐free survival, cancer‐specific survival, and overall survival. insulin‐like growth factor‐I binding protein‐2 and ‐3 levels and improved the discrimination of a standard reference model for the prediction of recurrence‐free survival, cancer‐specific survival, and overall survival (+4.9%, 4.9%, 2.3%, respectively).

Conclusions

Preoperative insulin‐like growth factor‐I binding protein‐2 and ‐3 are significantly associated with features of biologically and clinically aggressive urothelial carcinoma. These biomarkers improved prognostic urothelial carcinoma models.

Diagnostic Value of 1H NMR-Based Metabolomics in Acute Lymphoblastic Leukemia, Acute Myeloid Leukemia, and Breast Cancer

Cancer refers to a massive number of diseases distinguished by the development of abnormal cells that divide uncontrollably and have the capability of infiltration and destroying the normal body tissue. It is critical to detect biomarkers that are early detectable and noninvasive to save millions of lives. The aim of the present work is to use NMR as a noninvasive diagnostic tool for cancer diseases. This study included 30 plasma and 21 urine samples of patients diagnosed with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), 25 plasma and 17 urine samples of patients diagnosed with breast cancer (BC), and 9 plasma and urine samples obtained from healthy individuals as controls. They were prepared for NMR measurements; then, the metabolites were identified and the data were analyzed using multivariate statistical procedures. The OPLS-DA score plots clearly discriminated ALL, AML, and BC from healthy controls. Plots of the PLS-DA loadings and S-line plots showed that all metabolites in plasma were greater in BC than in the healthy controls, whereas lactate, O-acetylcarnitine, pyruvate, trimethylamine-N-oxide (TMAO), and glucose were higher in healthy controls than in ALL and AML. On the other hand, urine samples showed lower amounts of lactate, melatonin, pyruvate, and succinate in all of the studied types of cancer when compared to those of healthy controls. ¹H NMR can be a successful and noninvasive tool for the diagnosis of different types of cancer.

Urinary metabolomics for discovering metabolic biomarkers of bladder cancer by UPLC-MS

Bladder cancer (BC) is one of the most frequent cancer in the world, and its incidence is rising worldwide, especially in developed countries. Urine metabolomics is a powerful approach to discover potential biomarkers for cancer diagnosis. In this study, we applied an ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) method to profile the metabolites in urine from 29 bladder cancer patients and 15 healthy controls. The differential metabolites were extracted and analyzed by univariate and multivariate analysis methods. Together, 19 metabolites were discovered as differently expressed biomarkers in the two groups, which mainly related to the pathways of phenylacetate metabolism, propanoate metabolism, fatty acid metabolism, pyruvate metabolism, arginine and proline metabolism, glycine and serine metabolism, and bile acid biosynthesis. In addition, a subset of 11 metabolites of those 19 ones were further filtered as potential biomarkers for BC diagnosis by using logistic regression model. The results revealed that the area under the curve (AUC) value, sensitivity and specificity of receiving operator characteristic (ROC) curve were 0.983, 95.3% and 100%, respectively, indicating an excellent discrimination power for BC patients from healthy controls. It was the first time to reveal the potential diagnostic markers of BC by metabolomics, and this will provide a new sight for exploring the biomarkers of the other disease in the future work.

A Prognostic Model of Bladder Cancer Based on Metabolism-Related Long Non-Coding RNAs

Background

Some studies have revealed a close relationship between metabolism-related genes and the prognosis of bladder cancer. However, the relationship between metabolism-related long non-coding RNAs (lncRNA) regulating the expression of genetic material and bladder cancer is still blank. From this, we developed and validated a prognostic model based on metabolism-associated lncRNA to analyze the prognosis of bladder cancer.

Methods

Gene expression, lncRNA sequencing data, and related clinical information were extracted from The Cancer Genome Atlas (TCGA). And we downloaded metabolism-related gene sets from the human metabolism database. Differential expression analysis is used to screen differentially expressed metabolism-related genes and lncRNAs between tumors and paracancer tissues. We then obtained metabolism-related lncRNAs associated with prognosis by correlational analyses, univariate Cox analysis, and logistic least absolute shrinkage and selection operator (LASSO) regression. A risk scoring model is constructed based on the regression coefficient corresponding to lncRNA calculated by multivariate Cox analysis. According to the median risk score, patients were divided into a high-risk group and a low-risk group. Then, we developed and evaluated a nomogram including risk scores and Clinical baseline data to predict the prognosis. Furthermore, we performed gene-set enrichment analysis (GSEA) to explore the role of these metabolism-related lncRNAs in the prognosis of bladder cancer.

Results

By analyzing the extracted data, our research screened out 12 metabolism-related lncRNAs. There are significant differences in survival between high and low-risk groups divided by the median risk scoring model, and the low-risk group has a more favorable prognosis than the high-risk group. Univariate and multivariate Cox regression analysis showed that the risk score was closely related to the prognosis of bladder cancer. Then we established a nomogram based on multivariate analysis. After evaluation, the modified model has good predictive efficiency and clinical application value. Furthermore, the GSEA showed that these lncRNAs affected bladder cancer prognosis through multiple links.

Conclusions

A predictive model was established and validated based on 12 metabolism-related lncRNAs and clinical information, and we found these lncRNA affected bladder cancer prognosis through multiple links.

Diagnostic and therapeutic biomarkers in colorectal cancer: a review

Colorectal cancer (CRC) is a public health concern and the second most common type of cancer among men and women causing a significant mortality. Biomarkers closely linked to the disease morbidity could holds potential as diagnostic and/or prognostic biomarker for the disease. This review provides an overview of recent advances in the search for colorectal cancer biomarkers through genomics and proteomics according to clinical function and application. Specifically, a number of biomarkers were identified and discussed. Emphasis was placed on their clinical applications relative to the diagnosis and prognosis of CRC. The discovery of more sensitive and specific markers for CRC is an urgent need, and the study of molecular targets is extremely important in this process, as they will allow for a better understanding of colorectal carcinogenesis, identification and validation of potential genetic signatures.

Comprehensive metabolomics expands precision medicine for triple-negative breast cancer

Metabolic reprogramming is a hallmark of cancer. However, systematic characterizations of metabolites in triple-negative breast cancer (TNBC) are still lacking. Our study profiled the polar metabolome and lipidome in 330 TNBC samples and 149 paired normal breast tissues to construct a large metabolomic atlas of TNBC. Combining with previously established transcriptomic and genomic data of the same cohort, we conducted a comprehensive analysis linking TNBC metabolome to genomics. Our study classified TNBCs into three distinct metabolomic subgroups: C1, characterized by the enrichment of ceramides and fatty acids; C2, featured with the upregulation of metabolites related to oxidation reaction and glycosyl transfer; and C3, having the lowest level of metabolic dysregulation. Based on this newly developed metabolomic dataset, we refined previous TNBC transcriptomic subtypes and identified some crucial subtype-specific metabolites as potential therapeutic targets. The transcriptomic luminal androgen receptor (LAR) subtype overlapped with metabolomic C1 subtype. Experiments on patient-derived organoid and xenograft models indicate that targeting sphingosine-1-phosphate (S1P), an intermediate of the ceramide pathway, is a promising therapy for LAR tumors. Moreover, the transcriptomic basal-like immune-suppressed (BLIS) subtype contained two prognostic metabolomic subgroups (C2 and C3), which could be distinguished through machine-learning methods. We show that N-acetyl-aspartyl-glutamate is a crucial tumor-promoting metabolite and potential therapeutic target for high-risk BLIS tumors. Together, our study reveals the clinical significance of TNBC metabolomics, which can not only optimize the transcriptomic subtyping system, but also suggest novel therapeutic targets. This metabolomic dataset can serve as a useful public resource to promote precision treatment of TNBC.

Identification of a novel metabolism-related gene signature associated with the survival of bladder cancer

Background

Bladder cancer (BC) is one of the most common malignancies and has a relatively poor outcome worldwide. In this study, we attempted to construct a novel metabolism-related gene (MRG) signature for predicting the survival probability of BC patients.

Methods

First, differentially expressed MRGs between BC and normal samples were identified and used to construct a protein-protein interaction (PPI) network and perform mutation analysis. Next, univariate Cox regression analysis was utilized to select prognostic genes, and multivariate Cox regression analysis was applied to establish an MRG signature for predicting the survival probability of BC patients. Moreover, Kaplan-Meier (KM) survival analysis and receiver operating characteristic (ROC) analysis were performed to evaluate the predictive capability of the MRG signature. Finally, a nomogram based on the MRG signature was established to better predict the survival of BC.

Results

In the present study, 27 differentially expressed MRGs were identified, most of which presented mutations in BC patients, and LRP1 showed the highest mutation rate. Next, an MRG signature, including MAOB, FASN and LRP1, was established by using univariate and multivariate Cox regression analysis. Furthermore, survival analysis indicated that BC patients in the high-risk group had a dramatically lower survival probability than those in the low-risk group. Finally, Cox regression analysis showed that the risk score was an independent prognostic factor, and a nomogram integrating age, pathological tumor stage and risk score was established and presented good predictive ability.

Conclusion

We successfully constructed a novel MRG signature to predict the prognosis of BC patients, which might contribute to the clinical treatment of BC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09006-w.

AKT1/HK2 Axis-mediated Glucose Metabolism: A Novel Therapeutic Target of Sulforaphane in Bladder Cancer

SCOPE

Metabolic disorder is a pivotal hallmark of cancer cells. Sulforaphane (SFN) is reported to improve lipid metabolism. However, the effect of SFN on glucose metabolism in bladder cancer remains unclear. Hence, the effect and underling mechanism is investigated.

METHODS AND RESULTS

Biological samples from bladder cancer patients are collected, and also investigated using N-butyl-N-(4-hydroxybutyl) nitrosamine-induced bladder cancer mice and bladder cancer cell lines. A novel glucose transport aberrant-independent aerobic glycolysis is found in bladder cancer patients, and the lower malignancy tissues have the more obvious abnormality. SFN strongly downregulates ATP production by inhibiting glycolysis and mitochondrial oxidative phosphorylation (OXPHOS). Both in vitro cell culture and in bladder tumor mice, SFN weaken the glycolytic flux by suppressing multiple metabolic enzymes, including hexokinase 2 (HK2) and pyruvate dehydrogenase (PDH). Moreover, SFN decreases the level of AKT1 and p-AKT ^ser473 , especially in low-invasive UMUC3 cells. The downregulation of ATP and HK2 by SFN is both reversed by AKT1 overexpression.

CONCLUSIONS

SFN downregulates the unique glucose transport aberrant-independent aerobic glycolysis existed in bladder cancer via blocking the AKT1/HK2 axis and PDH expression.

Urinary Metabolic Markers of Bladder Cancer: A Reflection of the Tumor or the Response of the Body?

This work will review the metabolic information that various studies have obtained in recent years on bladder cancer, with particular attention to discovering biomarkers in urine for the diagnosis and prognosis of this disease. In principle, they would be capable of complementing cystoscopy, an invasive but nowadays irreplaceable technique or, in the best case, of replacing it. We will evaluate the degree of reproducibility that the different experiments have shown in the indication of biomarkers, and a synthesis will be attempted to obtain a consensus list that is more likely to become a guideline for clinical practice. In further analysis, we will inquire into the origin of these dysregulated metabolites in patients with bladder cancer. For this purpose, it will be helpful to compare the imbalances measured in urine with those known inside tumor cells or tissues. Although the urine analysis is sometimes considered a liquid biopsy because of its direct contact with the tumor in the bladder wall, it contains metabolites from all organs and tissues of the body, and the tumor is separated from urine by the most impermeable barrier found in mammals. The distinction between the specific and systemic responses can help understand the disease and its consequences in more depth.

CHAF1A Blocks Neuronal Differentiation and Promotes Neuroblastoma Oncogenesis via Metabolic Reprogramming

Neuroblastoma (NB) arises from oncogenic disruption of neural crest (NC) differentiation. Treatment with retinoic acid (RA) to induce differentiation has improved survival in some NB patients, but not all patients respond, and most NBs eventually develop resistance to RA. Loss of the chromatin modifier chromatin assembly factor 1 subunit p150 (CHAF1A) promotes NB cell differentiation; however, the mechanism by which CHAF1A drives NB oncogenesis has remained unexplored. This study shows that CHAF1A gain-of-function supports cell malignancy, blocks neuronal differentiation in three models (zebrafish NC, human NC, and human NB), and promotes NB oncogenesis. Mechanistically, CHAF1A upregulates polyamine metabolism, which blocks neuronal differentiation and promotes cell cycle progression. Targeting polyamine synthesis promotes NB differentiation and enhances the anti-tumor activity of RA. The authors' results provide insight into the mechanisms that drive NB oncogenesis and suggest a rapidly translatable therapeutic approach (DFMO plus RA) to enhance the clinical efficacy of differentiation therapy in NB patients.

Preoperative plasma level of endoglin as a predictor for disease outcomes after radical cystectomy for nonmetastatic urothelial carcinoma of the bladder

Elevated preoperative plasma level of endoglin has been associated with worse oncologic outcomes in various malignancies. The present large-scale study aimed to determine the predictive and prognostic values of preoperative endoglin with regard to clinicopathologic and survival outcomes in patients treated with radical cystectomy (RC) for nonmetastatic urothelial carcinoma of the bladder (UCB). We prospectively collected preoperative blood samples from 1036 consecutive patients treated with RC for UCB. Logistic and Cox regression analyses were undertaken to assess the correlation of endoglin levels with pathologic and survival outcomes, respectively. The AUC and C-index were used to assess the discrimination. Patients with adverse pathologic features had significantly higher median preoperative endoglin plasma levels than their counterparts. Higher preoperative endoglin level was independently associated with an increased risk for lymph node metastasis, ≥pT3 disease, and nonorgan confined disease (NOCD; all p < 0.001). Plasma endoglin level was also independently associated with cancer-specific and overall survival in both pre- and postoperative models (all p < 0.05), as well as with recurrence-free survival (RFS) in the preoperative model (p < 0.001). The addition of endoglin to the preoperative standard model improved its discrimination for prediction of lymph node metastasis, ≥pT3 disease, NOCD, and RFS (differential increases in C-indices: 10%, 5%, 5.8%, and 4%, respectively). Preoperative plasma endoglin is associated with features of biologically and clinically aggressive UCB as well as survival outcomes. Therefore, it seems to hold the potential of identifying UCB patients who may benefit from intensified therapy in addition to RC such as extended lymphadenectomy or/and preoperative systemic therapy.

Integrative Transcriptomic, Lipidomic, and Metabolomic Analysis Reveals Potential Biomarkers of Basal and Luminal Muscle Invasive Bladder Cancer Subtypes

Muscle invasive bladder cancer (MIBC) is a heterogeneous disease with a high recurrence rate and poor clinical outcomes. Molecular subtype provides a new framework for the study of MIBC heterogeneity. Clinically, MIBC can be classified as basal and luminal subtypes; they display different clinical and pathological characteristics, but the molecular mechanism is still unclear. Lipidomic and metabolomic molecules have recently been considered to play an important role in the genesis and development of tumors, especially as potential biomarkers. Their different expression profiles in basal and luminal subtypes provide clues for the molecular mechanism of basal and luminal subtypes and the discovery of new biomarkers. Herein, we stratified MIBC patients into basal and luminal subtypes using a MIBC classifier based on transcriptome expression profiles. We qualitatively and quantitatively analyzed the lipids and metabolites of basal and luminal MIBC subtypes and identified their differential lipid and metabolite profiles. Our results suggest that free fatty acids (FFAs) and sulfatides (SLs), which are closely associated with immune and stromal cell types, can contribute to the diagnosis of basal and luminal subtypes of MIBC. Moreover, we showed that glycerophosphocholine (GCP)/imidazoles and nucleosides/imidazoles ratios can accurately distinguish the basal and luminal tumors. Overall, by integrating transcriptomic, lipidomic, and metabolomic data, our study reveals specific biomarkers to differentially diagnose basal and luminal MIBC subtypes and may provide a basis for precision therapy of MIBC.

Comprehensive polar metabolomics and lipidomics profiling discriminates the transformed from the non-transformed state in colon tissue and cell lines

Colorectal cancer (CRC) is the fourth most lethal disease worldwide. Despite an urgent need for therapeutic advance, selective target identification in a preclinical phase is hampered by molecular and metabolic variations between cellular models. To foster optimal model selection from a translational perspective, we performed untargeted ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry-based polar metabolomics and lipidomics to non-transformed (CCD841-CON and FHC) and transformed (HCT116, HT29, Caco2, SW480 and SW948) colon cell lines as well as tissue samples from ten colorectal cancer patients. This unveiled metabolic signatures discriminating the transformed from the non-transformed state. Metabolites involved in glutaminolysis, tryptophan catabolism, pyrimidine, lipid and carnitine synthesis were elevated in transformed cells and cancerous tissue, whereas those involved in the glycerol-3-phosphate shuttle, urea cycle and redox reactions were lowered. The degree of glutaminolysis and lipid synthesis was specific to the colon cancer cell line at hand. Thus, our study exposed pathways that are specifically associated with the transformation state and revealed differences between colon cancer cell lines that should be considered when targeting cancer-associated pathways.

Metabolic profiling analysis for clinical urine of colorectal cancer

AIM

To demonstrate the little-known metabolic changes and pathways in patients with colorectal cancer (CRC).

METHODS

We used gas chromatography time-of-flight mass spectrometry (GC-TOF/MS) to perform metabolic profiling of urine samples from 163 consecutive patients with CRC and 111 healthy controls without history of gastrointestinal tumors. The metabolic profiles were assayed using multivariate statistical analysis and one-way analysis of variance, and further analyzed to identify potential marker metabolites related to CRC. The GC-TOF/MS-derived models showed clear discriminations in metabolic profiles between the CRC group and healthy control group.

RESULTS

We demonstrated that 15 metabolites contributed to the differences. Among them, eleven metabolites were significantly upregulated, while other four metabolites were downregulated in the urine samples of CRC patients compared with healthy controls. Pathway analysis revealed changes in energy metabolism of patients with CRC, which are reflected in the upregulation of glycolysis and amino acid metabolism and the downregulation of lipid metabolism. Our study revealed the metabolic profile of urine from CRC patients and indicated that GC-TOF/MS-based methods can distinguish CRC from healthy controls.

CONCLUSION

GC-TOF/MS-based metabolomics has the potential to be developed into a novel, non-invasive, and painless clinical tool for CRC diagnosis, and may contribute to an improved understanding of disease mechanisms.

Epigenomic and Metabolomic Integration Reveals Dynamic Metabolic Regulation in Bladder Cancer

Bladder cancer (BC) represents a clinical, social, and economic challenge due to tumor-intrinsic characteristics, limitations of diagnostic techniques and a lack of personalized treatments. In the last decade, the use of liquid biopsy has grown as a non-invasive approach to characterize tumors. Moreover, the emergence of omics has increased our knowledge of cancer biology and identified critical BC biomarkers. The rewiring between epigenetics and metabolism has been closely linked to tumor phenotype. Chromatin remodelers interact with each other to control gene silencing in BC, but also with stress-inducible factors or oncogenic signaling cascades to regulate metabolic reprogramming towards glycolysis, the pentose phosphate pathway, and lipogenesis. Concurrently, one-carbon metabolism supplies methyl groups to histone and DNA methyltransferases, leading to the hypermethylation and silencing of suppressor genes in BC. Conversely, α-KG and acetyl-CoA enhance the activity of histone demethylases and acetyl transferases, increasing gene expression, while succinate and fumarate have an inhibitory role. This review is the first to analyze the interplay between epigenome, metabolome and cell signaling pathways in BC, and shows how their regulation contributes to tumor development and progression. Moreover, it summarizes non-invasive biomarkers that could be applied in clinical practice to improve diagnosis, monitoring, prognosis and the therapeutic options in BC.

The Epidemiology of Bladder Cancer

There are many risk factors for bladder cancer. During an initial assessment of a patient with bladder cancer, a careful discussion and history assessment is important. Particular focus should include social history with details regarding occupational background and discussion of any environmental exposure history.

Detection of Urothelial Bladder Cancer Based on Urine and Tissue Telomerase Activity Measured by Novel RT-TRAP-2PCR Method

Purpose: To assess the diagnostic performance of urine telomerase activity (TA) in detecting bladder cancer (BCa) using the modified Telomeric Repeat Amplification Protocol (TRAP) and the Real Time Telomeric Repeat Amplification Protocol with double Polymerase Chain Reaction (RT-TRAP-2PCR). Methods: In this case-control study, matching urine (in the pre- and post-surgical period) and tissue samples from 68 patients with BCa were assessed for TA. As a control, 45 urine samples were examined from non-BCa patients. TA levels were measured using TRAP and RT-TRAP-2 PCR methods. Results: Preoperative urinary TA was elevated in 64 (94.1%) of the 68 BCa patients. Urine TA was undetectable in 44 control patients, while TA was detected in one patient with histologically verified cystitis. Sensitivity for BCa detection of 94.1% and specificity of 97.8% were observed for urinary TA, while tissue TA had 100% sensitivity and 97.8% specificity. Both urine and tissue TA levels were not significantly higher in patients with muscle-invasive disease compared to those with non-muscle invasive BCa (p > 0.05). Urine and tissue TA levels were not associated with higher tumor grade, stage, and number of tumors (p > 0.05). However, the association was found between higher urinary and tissue TA levels with tumor size ≥ 3 cm (p = 0.02 and p = 0.01, respectively). During the first postoperative year, 17 BCa patients experienced disease recurrence, and urinary TA was present in 14 (82.4%) of these patients. The sensitivity and specificity of urinary TA levels for BCa recurrence in patients with non-muscle invasive bladder cancer (NMIBC) during follow-up were 82% and 94.4%, respectively. Conclusions: This pilot study demonstrates a high diagnostic performance of urinary and tissue TA levels measured by a new RT-TRAP-2PCR method for detecting and monitoring BCa. Additionally, the association was found between higher urinary and tissue TA levels with tumor size ≥ 3 cm; however, higher TA levels failed for significant correlation with advanced tumor stage and grade. Our study could serve as a benchmark for the evaluation of novel biomarkers using the RT-TRAP-2PCR method.

Urinary Metabolic Biomarkers in Cancer Patients: An Overview

The pathogenesis of cancer involves multiple molecular alterations at the level of genome, epigenome, and stromal environment, resulting in several deregulated signal transduction pathways. Metabolites are not only end products of gene and protein expression but also a consequence of the mutual relationship between the genome and the internal environment. Considering that metabolites serve as a comprehensive chemical fingerprint of cell metabolism, metabolomics is emerging as the method able to discover metabolite biomarkers that can be developed for early cancer detection, prognosis, and response to treatment. Urine represents a noninvasive source, available and rich in metabolites, useful for cancer diagnosis, prognosis, and treatment monitoring. In this chapter, we reported the main published evidences on urinary metabolic biomarkers in the studied cancers related to hepatopancreatic and urinary tract with the aim at discussing their promising role in clinical practice.

Isoform-specific Activities of Androgen Receptor and its Splice Variants in Prostate Cancer Cells

Androgen receptor (AR) signaling continues to drive castration-resistant prostate cancer (CRPC) in spite of androgen deprivation therapy (ADT). Constitutively active shorter variants of AR, lacking the ligand binding domain, are frequently expressed in CRPC and have emerged as a potential mechanism for prostate cancer to escape ADT. ARv7 and ARv567es are 2 of the most commonly detected variants of AR in clinical samples of advanced, metastatic prostate cancer. It is not clear if variants of AR merely act as weaker substitutes for AR or can mediate unique isoform-specific activities different from AR. In this study, we employed LNCaP prostate cancer cell lines with inducible expression of ARv7 or ARv567es to delineate similarities and differences in transcriptomics, metabolomics, and lipidomics resulting from the activation of AR, ARv7, or ARv567es. While the majority of target genes were similarly regulated by the action of all 3 isoforms, we found a clear difference in transcriptomic activities of AR versus the variants, and a few differences between ARv7 and ARv567es. Some of the target gene regulation by AR isoforms was similar in the VCaP background as well. Differences in downstream activities of AR isoforms were also evident from comparison of the metabolome and lipidome in an LNCaP model. Overall our study implies that shorter variants of AR are capable of mediating unique downstream activities different from AR and some of these are isoform specific.

Clinical, molecular, metabolic, and immune features associated with oxidative phosphorylation in melanoma brain metastases

Background

Recently, we showed that melanoma brain metastases (MBMs) are characterized by increased utilization of the oxidative phosphorylation (OXPHOS) metabolic pathway compared to melanoma extracranial metastases (ECMs). MBM growth was inhibited by a potent direct OXPHOS inhibitor, but observed toxicities support the need to identify alternative therapeutic strategies. Thus, we explored the features associated with OXPHOS to improve our understanding of the pathogenesis and potential therapeutic vulnerabilities of MBMs.

Methods

We applied an OXPHOS gene signature to our cohort of surgically resected MBMs that had undergone RNA-sequencing (RNA-seq) (n = 88). Clustering by curated gene sets identified MBMs with significant enrichment (High-OXPHOS; n = 21) and depletion (Low-OXPHOS; n = 25) of OXPHOS genes. Clinical data, RNA-seq analysis, and immunohistochemistry were utilized to identify significant clinical, molecular, metabolic, and immune associations with OXPHOS in MBMs. Preclinical models were used to further compare melanomas with High- and Low-OXPHOS and for functional validation.

Results

High-OXPHOS MBMs were associated with shorter survival from craniotomy compared to Low-OXPHOS MBMs. High-OXPHOS MBMs exhibited an increase in glutamine metabolism, and treatment with the glutaminase inhibitor CB839 improved survival in mice with MAPKi-resistant, High-OXPHOS intracranial xenografts. High-OXPHOS MBMs also exhibited a transcriptional signature of deficient immune activation, which was reversed in B16-F10 intracranial tumors with metformin treatment, an OXPHOS inhibitor.

Conclusions

OXPHOS is associated with distinct clinical, molecular, metabolic, and immune phenotypes in MBMs. These associations suggest rational therapeutic strategies for further testing to improve outcomes in MBM patients.

Metabolomic and lipidomic approaches to identify biomarkers for bladder cancer and interstitial cystitis (Review)

The discovery, introduction and clinical use of prognostic and diagnostic biomarkers has significantly improved outcomes for patients with various illnesses, including bladder cancer (BC) and other bladder-related diseases, such as benign bladder dysfunction and interstitial cystitis (IC). Several sensitive and noninvasive clinically relevant biomarkers for BC and IC have been identified. Metabolomic- and lipidomic-based biomarkers have notable clinical potential in improving treatment outcomes for patients with cancer; however, there are also some noted limitations. This review article provides a short and concise summary of the literature on metabolomic and lipidomic biomarkers for BC and IC, focusing on the possible clinical utility of profiling metabolic alterations in BC and IC.

Systemic lipid dysregulation is a risk factor for macular neurodegenerative disease

Macular Telangiectasia type 2 (MacTel) is an uncommon bilateral retinal disease, in which glial cell and photoreceptor degeneration leads to central vision loss. The causative disease mechanism is largely unknown, and no treatment is currently available. A previous study found variants in genes associated with glycine-serine metabolism (PSPH, PHGDH and CPS1) to be associated with MacTel, and showed low levels of glycine and serine in the serum of MacTel patients. Recently, a causative role of deoxysphingolipids in MacTel disease has been established. However, little is known about possible other metabolic dysregulation. Here we used a global metabolomics platform in a case-control study to comprehensively profile serum from 60 MacTel patients and 58 controls. Analysis of the data, using innovative computational approaches, revealed a detailed, disease-associated metabolic profile with broad changes in multiple metabolic pathways. This included alterations in the levels of several metabolites that are directly or indirectly linked to glycine-serine metabolism, further validating our previous genetic findings. We also found changes unrelated to PSPH, PHGDH and CPS1 activity. Most pronounced, levels of several lipid groups were altered, with increased phosphatidylethanolamines being the most affected lipid group. Assessing correlations between different metabolites across our samples revealed putative functional connections. Correlations between phosphatidylethanolamines and sphingomyelin, and glycine-serine and sphingomyelin, observed in controls, were reduced in MacTel patients, suggesting metabolic re-wiring of sphingomyelin metabolism in MacTel patients. Our findings provide novel insights into metabolic changes associated with MacTel and implicate altered lipid metabolism as a contributor to this retinal neurodegenerative disease.

Epigenetic Regulation of Differentially Expressed Drug-Metabolizing Enzymes in Cancer

Drug metabolism is a biotransformation process of drugs, catalyzed by drug-metabolizing enzymes (DMEs), including phase I DMEs and phase II DMEs. The aberrant expression of DMEs occurs in the different stages of cancer. It can contribute to the development of cancer and lead to individual variations in drug response by affecting the metabolic process of carcinogen and anticancer drugs. Apart from genetic polymorphisms, which we know the most about, current evidence indicates that epigenetic regulation is also central to the expression of DMEs. This review summarizes differentially expressed DMEs in cancer and related epigenetic changes, including DNA methylation, histone modification, and noncoding RNAs. Exploring the epigenetic regulation of differentially expressed DMEs can provide a basis for implementing individualized and rationalized medication. Meanwhile, it can promote the development of new biomarkers and targets for the diagnosis, treatment, and prognosis of cancer. SIGNIFICANCE STATEMENT: This review summarizes the aberrant expression of DMEs in cancer and the related epigenetic regulation of differentially expressed DMEs. Exploring the epigenetic regulatory mechanism of DMEs in cancer can help us to understand the role of DMEs in cancer progression and chemoresistance. Also, it provides a basis for developing new biomarkers and targets for the diagnosis, treatment, and prognosis of cancer.

Prognostic value of preoperative hematologic biomarkers in urothelial carcinoma of the bladder treated with radical cystectomy: a systematic review and meta-analysis

This systematic review and meta-analysis aimed to assess the prognostic value of preoperative hematologic biomarkers in patients with urothelial carcinoma of the bladder treated with radical cystectomy. PUBMED, Web of Science, Cochrane Library, and Scopus databases were searched in September 2019 according to the Preferred Reporting Items for Systematic Review and Meta-analysis statement. Studies were deemed eligible if they compared cancer-specific survival in patients with urothelial carcinoma of the bladder with and without pretreatment laboratoryabnormalities. Formal meta-analyses were performed for this outcome. The systematic review identified 36 studies with 23,632 patients, of these, 32 studies with 22,224 patients were eligible for the meta-analysis. Several preoperative hematologic biomarkers were significantly associated with cancer-specific survival as follows: neutrophil − lymphocyte ratio (pooled hazard ratio [HR]: 1.20, 95% confidence interval [CI]: 1.11–1.29), hemoglobin (pooled HR: 0.87, 95% CI 0.82–0.94), C-reactive protein (pooled HR: 1.44, 95% CI 1.26–1.66), De Ritis ratio (pooled HR: 2.18, 95% CI 1.37–3.48), white blood cell count (pooled HR: 1.05, 95% CI 1.02–1.07), and albumin-globulin ratio (pooled HR: 0.26, 95% CI 0.14–0.48). Several pretreatment laboratory abnormalities in patients with urothelial carcinoma of the bladder were associated with cancer-specific mortality. Therefore, it might be useful to incorporate such hematologic biomarkers into prognostic tools for urothelial carcinoma of the bladder. However, given the study limitations including heterogeneity and retrospective nature of the primary data, the conclusions should be interpreted with caution.

Cellular Metabolic Profiling of CrFK Cells Infected with Feline Infectious Peritonitis Virus Using Phenotype Microarrays

Feline infectious peritonitis (FIP) is a fatal feline immune-mediated disease caused by feline infectious peritonitis virus (FIPV). Little is known about the biological pathways associated in FIP pathogenesis. This is the first study aiming to determine the phenotypic characteristics on the cellular level in relation to specific metabolic pathways of importance to FIP pathogenesis.

METHODS

The internalization of type II FIPV WSU 79-1146 in Crandell-Rees Feline Kidney (CrFK) cells was visualized using a fluorescence microscope, and optimization prior to phenotype microarray (PM) study was performed. Then, four types of Biolog Phenotype MicroArray™ plates (PM-M1 to PM-M4) precoated with different carbon and nitrogen sources were used to determine the metabolic profiles in FIPV-infected cells.

RESULTS

The utilization of palatinose was significantly low in FIPV-infected cells; however, there were significant increases in utilizing melibionic acid, L-glutamine, L-glutamic acid and alanyl-glutamine (Ala-Gln) compared to non-infected cells.

CONCLUSION

This study has provided the first insights into the metabolic profiling of a feline coronavirus infection in vitro using PMs and deduced that glutamine metabolism is one of the essential metabolic pathways for FIPV infection and replication. Further studies are necessary to develop strategies to target the glutamine metabolic pathway in FIPV infection.

NMR-derived targeted serum metabolic biomarkers appraisal of bladder cancer: A pre- and post-operative evaluation

With high morbidity and mortality, urinary bladder cancer (BC) ranks fifth among common cancers globally. The inherent limitations of urine cytology and cystoscopy, and marginal enhancements in the rate of survival promt us to develop surrogate serum based metabolic biomarkers of screening, identification, and follow-up protocols of management for BC patients. Earlier, we exhibited that abnormal expression levels of dimethylamine (DMA), malonate, lactate, glutamine, histidine, and valine in serum may be used as signature metabolites to differentiate BC from healthy controls (HC) (J. Proteome Res. 2013; 12(12):5839-50). Here we further gauge and validate these observations by comparing pre-operative to post-operative follow-up BC patients. This study was conducted on 160 sera samples involving HC (n = 52), pre-operative (n = 55) and post-operative (n = 53) BC cases. ¹H nuclear magnetic resonance (NMR) spectroscopy was used to generate serum metabolic profiles and to gauge aberrantly expressed metabolites. The targeted metabolomic approach revealed that the expression levels of these signature metabolites were progressively and significantly decreased in post-operative follow-up at the interval of 30, 60, and 90 days compared to pre-operative BC sera samples and were maintained at HC levels. Serum metabolic biomarkers appear to be an inspiring and least-invasive tactic for detection and prognosticating BC patient follow-up.

Dnmt3a loss and Idh2 neomorphic mutations mutually potentiate malignant hematopoiesis

Mutations in the epigenetic regulators DNMT3A and IDH1/2 co-occur in patients with acute myeloid leukemia and lymphoma. In this study, these 2 epigenetic mutations cooperated to induce leukemia. Leukemia-initiating cells from Dnmt3a-/- mice that express an IDH2 neomorphic mutant have a megakaryocyte-erythroid progenitor-like immunophenotype, activate a stem-cell-like gene signature, and repress differentiated progenitor genes. We observed an epigenomic dysregulation with the gain of repressive H3K9 trimethylation and loss of H3K9 acetylation in diseased mouse bone marrow hematopoietic stem and progenitor cells (HSPCs). HDAC inhibitors rapidly reversed the H3K9 methylation/acetylation imbalance in diseased mouse HSPCs while reducing the leukemia burden. In addition, using targeted metabolomic profiling for the first time in mouse leukemia models, we also showed that prostaglandin E2 is overproduced in double-mutant HSPCs, rendering them sensitive to prostaglandin synthesis inhibition. These data revealed that Dnmt3a and Idh2 mutations are synergistic events in leukemogenesis and that HSPCs carrying both mutations are sensitive to induced differentiation by the inhibition of both prostaglandin synthesis and HDAC, which may reveal new therapeutic opportunities for patients carrying IDH1/2 mutations.