An integrated computational and experimental study uncovers FUT9 as a metabolic driver of colorectal cancer

Intervening Non-Small-Cell Lung Cancer Progression by Cell Membrane Coated Platycodin D via Regulating Hsa-miR-1246/FUT9/GSK3β Pathway

Purpose

Metastatic non-small cell lung cancer (NSCLC) remains a global health threat, with patients facing inevitable disease progression despite standard-of-care therapy. Prior studies showed Platycodin D (PD)-induced cell cycle arrest and apoptosis in NSCLC via RNA regulatory network, yet elucidating PD's mechanisms in NSCLC progression is challenging in the real world.

Methods

Biological effects of PD on NSCLC cell lines A549 and PC-9 were assessed through in vitro assays, encompassing apoptosis, proliferation, colony formation, migration and invasion. MicroRNAs (miRNAs) expression was profiled, and their roles were investigated using miRNA mimics or inhibitors. Predicted miRNA targets were validated via dual-luciferase reporter assays and Western blotting following bioinformatic prediction. PD's metastatic inhibitory potential in NSCLC was evaluated in an in vivo lung cancer metastasis model. Furthermore, a homologous cell membrane-based PD delivery system was established to improve the biosafety and efficacy of PD in vivo.

Results

Hsa-miR-1246 was upregulated by PD treatment, and functional experiments demonstrated that the miR-1246-mimic enhanced PD's suppressive effects on NSCLC cell proliferation, colony formation, migration, and invasion, while the miR-1246-inhibitor abrogated these effects. Notably, dual-luciferase assays confirmed that hsa-miR-1246 directly targeted the 3' untranslated regions (3' UTRs) of Fucosyltransferase 9 (FUT9), modulating its expression. Moreover, the hsa-miR-1246/FUT9 axis regulated the phosphorylation level and expression of GSK3β protein. In vivo, PD encapsulated in homologous cell membranes mitigated tumor growth and migration in metastatic NSCLC mice with minimal side effects.

Conclusion

The application of PD prompted an increase in the expression levels of hsa-miR-1246 and a concurrent decrease in FUT9. Importantly, the therapeutic efficacy of PD in vivo was markedly enhanced through homologous cell delivery system. Collectively, this study revealed the potential utility of PD in the treatment of NSCLC progression.

Cell-specific genome-scale metabolic modeling of SARS-CoV-2-infected lung to identify antiviral enzymes

Computational systems biology plays a key role in the discovery of suitable antiviral targets. We designed a cell-specific, constraint-based modeling technique for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected lungs. We used the gene sequence of the alpha variant of SARS-CoV-2 to build a viral biomass reaction (VBR). We also used the mass proportion of lipids between the viral biomass and its host cell to estimate the stoichiometric coefficients of viral lipids in the reaction. We then integrated the VBR, the gene expression of the alpha variant of SARS-CoV-2, and the generic human metabolic network Recon3D to reconstruct a cell-specific genome-scale metabolic model. An antiviral target discovery (AVTD) platform was introduced using this model to identify therapeutic drug targets for combating COVID-19. The AVTD platform not only identified antiviral genes for eliminating viral replication but also predicted side effects of treatments. Our computational results revealed that knocking out dihydroorotate dehydrogenase (DHODH) might reduce the synthesis rate of cytidine-5'-triphosphate and uridine-5'-triphosphate, which terminate the viral building blocks of DNA and RNA for SARS-CoV-2 replication. Our results also indicated that DHODH is a promising antiviral target that causes minor side effects, which is consistent with the results of recent reports. Moreover, we discovered that the genes that participate in the de novo biosynthesis of glycerophospholipids and ceramides become unidentifiable if the VBR does not involve the stoichiometry of lipids.

Fucosyltransferase 9 promotes neuronal differentiation and functional recovery after spinal cord injury by suppressing the activation of Notch signaling

Individuals with spinal cord injury (SCI) suffer from permanent disabilities such as severe motor, sensory and autonomic dysfunction. Neural stem cell transplantation has proven to be a potential strategy to promote regeneration of the spinal cord, since NSCs can produce neurotrophic growth factors and differentiate into mature neurons to reconstruct the injured site. However, it is necessary to optimize the differentiation of NSCs before transplantation to achieve a better regenerative outcome. Inhibition of Notch signaling leads to a transition from NSCs to neurons, while the underlying mechanism remains inadequately understood. Our results demonstrate that overexpression of fucosyltransferase 9 (Fut9), which is upregulated by Wnt4, promotes neuronal differentiation by suppressing the activation of Notch signaling through disruption of furin-like enzyme activity during S1 cleavage. In an in vivo study, Fut9-modified NSCs efficiently differentiates into neurons to promote functional and histological recovery after SCI. Our research provides insight into the mechanisms of Notch signaling and a potential treatment strategy for SCI.

Folic Acid Supplementation Promotes Hypomethylation in Both the Inflamed Colonic Mucosa and Colitis-Associated Dysplasia

PURPOSE

The purpose of this study was to assess the effect of folic acid (FA) supplementation on colitis-associated colorectal cancer (CRC) using the azoxymethane/dextran sulfate sodium (AOM/DSS) model.

METHODS

Mice were fed a chow containing 2 mg/kg FA at baseline and randomized after the first DSS treatment to receive 0, 2, or 8 mg/kg FA chow for 16 weeks. Colon tissue was collected for histopathological evaluation, genome-wide methylation analyses (Digital Restriction Enzyme Assay of Methylation), and gene expression profiling (RNA-Seq).

RESULTS

A dose-dependent increase in the multiplicity of colonic dysplasias was observed, with the multiplicity of total and polypoid dysplasias higher (64% and 225%, respectively) in the 8 mg FA vs. the 0 mg FA group (p < 0.001). Polypoid dysplasias were hypomethylated, as compared to the non-neoplastic colonic mucosa (p < 0.05), irrespective of FA treatment. The colonic mucosa of the 8 mg FA group was markedly hypomethylated as compared to the 0 mg FA group. Differential methylation of genes involved in Wnt/β-catenin and MAPK signaling resulted in corresponding alterations in gene expression within the colonic mucosa.

CONCLUSIONS

High-dose FA created an altered epigenetic field effect within the non-neoplastic colonic mucosa. The observed decrease in site-specific DNA methylation altered oncogenic pathways and promoted colitis-associated CRC.

Cellular Genome-Scale Metabolic Modeling Identifies New Potential Drug Targets Against Hepatocellular Carcinoma

Genome-scale metabolic modeling (GEM) is one of the key approaches to unpack cancer metabolism and for discovery of new drug targets. In this study, we report the Transcriptional Regulated Flux Balance Analysis-CORE (TRFBA-), an algorithm for GEM using key growth-correlated reactions using hepatocellular carcinoma (HCC), an important global health burden, as a case study. We generated a HepG2 cell-specific GEM by integrating this cell line transcriptomic data with a generic human metabolic model to forecast potential drug targets for HCC. A total of 108 essential genes for growth were predicted by the TRFBA-CORE. These genes were enriched for metabolic pathways involved in cholesterol, sterol, and steroid biosynthesis. Furthermore, we silenced a predicted essential gene, 11-beta dehydrogenase hydroxysteroid type 2 (HSD11B2), in HepG2 cells resulting in a reduction in cell viability. To further identify novel potential drug targets in HCC, we examined the effect of nine drugs targeting the essential genes, and observed that most drugs inhibited the growth of HepG2 cells. Some of these drugs in this model performed better than Sorafenib, the first-line therapeutic against HCC. A HepG2 cell-specific GEM highlights sterol metabolism to be essential for cell growth. HSD11B2 downregulation results in lower cell growth. Most of the compounds, selected by drug repurposing approach, show a significant inhibitory effect on cell growth in a wide range of concentrations. These findings offer new molecular leads for drug discovery for hepatic cancer while also illustrating the importance of GEM and drug repurposing in cancer therapeutics innovation.

Intestinal Norovirus Binding Patterns in Nonsecretor Individuals

Human norovirus (HuNoV) infection is associated with an active FUT2 gene, which characterizes the secretor phenotype. However, nonsecretor individuals are also affected by HuNoV infection although in a lesser proportion. Here, we studied GII.3, GII.4, and GII.17 HuNoV interactions in nonsecretor individuals using virus-like particles (VLPs). Only GII.4 HuNoV specifically interacted with nonsecretor saliva. Competition experiments using histo-blood group antigen (HBGA)-specific monoclonal antibodies (MAbs) demonstrate that GII.4 VLPs recognized the Lewis a (Le^a) antigen. We also analyzed HuNoV VLP interactions on duodenum tissue blocks from healthy nonsecretor individuals. VLP binding was observed for the three HuNoV genotypes in 10 of the 13 individuals, and competition experiments demonstrated that VLP recognition was driven by an interaction with the Le^a antigen. In 3 individuals, binding was restricted to either GII.4 alone or GII.3 and GII.17. Finally, we performed a VLP binding assay on proximal and distal colon tissue blocks from a nonsecretor patient with Crohn's disease. VLP binding to inflammatory tissues was genotype specific since GII.4 and GII.17 VLPs were able to interact with regenerative mucosa, whereas GII.3 VLP was not. The binding of GII.4 and GII.17 HuNoV VLPs was linked to Le^a in regenerative mucosae from the proximal and distal colon. Overall, our data clearly showed that Le^a has a pivotal role in the recognition of HuNoV in nonsecretors. We also showed that Le^a is expressed in inflammatory/regenerative tissues and interacts with HuNoV in a nonsecretor individual. The physiological and immunological consequences of such interactions in nonsecretors have yet to be elucidated. IMPORTANCE Human norovirus (HuNoV) is the main etiological agent of viral gastroenteritis in all age classes. HuNoV infection affects mainly secretor individuals where ABO(H) and Lewis histo-blood group antigens (HBGAs) are present in the small intestine. Nonsecretor individuals, who only express Lewis (Le) antigens, are less susceptible to HuNoV infection. Here, we studied the interaction of common HuNoV genotypes (GII.3, GII.4, and GII.17) in nonsecretor individuals using synthetic viral particles. Saliva binding assays showed that only GII.4 interacted with nonsecretor saliva via the Lewis a (Le^a) antigen Surprisingly, the three genotypes interacted with nonsecretor enterocytes via the Le^a antigen on duodenal tissue blocks, which were more relevant for HuNoV/HBGA studies. The Le^a antigen also played a pivotal role in the recognition of GII.4 and GII.17 particles by inflammatory colon tissue from a nonsecretor Crohn's disease patient. The implications of HuNoV binding in nonsecretors remain to be elucidated in physiological and pathological conditions encountered in other intestinal diseases.

Bi-allelic hydroxymethylbilane synthase inactivation defines a homogenous clinico-molecular subtype of hepatocellular carcinoma

BACKGROUND & AIMS

Acute intermittent porphyria (AIP), caused by heterozygous germline mutations of the heme synthesis pathway enzyme HMBS (hydroxymethylbilane synthase), confers a high risk of hepatocellular carcinoma (HCC) development. Yet, the role of HMBS in liver tumorigenesis remains unclear.

METHODS

Herein, we explore HMBS alterations in a large series of 758 HCC cases, including 4 patients with AIP. We quantify the impact of HMBS mutations on heme biosynthesis pathway intermediates and we investigate the molecular and clinical features of HMBS-mutated tumors.

RESULTS

We identify recurrent bi-allelic HMBS inactivation, both in patients with AIP acquiring a second somatic HMBS mutation and in sporadic HCC with 2 somatic hits. HMBS alterations are enriched in truncating mutations, in particular in splice regions, leading to abnormal transcript structures. Bi-allelic HMBS inactivation results in a massive accumulation of its toxic substrate porphobilinogen and synergizes with CTNNB1-activating mutations, leading to the development of well-differentiated tumors with a transcriptomic signature of Wnt/β-catenin pathway activation and a DNA methylation signature related to ageing. HMBS-inactivated HCC mostly affects females, in the absence of fibrosis and classical HCC risk factors.

CONCLUSIONS

These data identify HMBS as a tumor suppressor gene whose bi-allelic inactivation defines a homogenous clinical and molecular HCC subtype.

LAY SUMMARY

Heme (the precursor to hemoglobin, which plays a key role in oxygen transport around the body) synthesis occurs in the liver and involves several enzymes including hydroxymethylbilane synthase (HMBS). HMBS mutations cause acute intermittent porphyria, a disease caused by the accumulation of toxic porphyrin precursors. Herein, we show that HMBS inactivation is also involved in the development of liver cancers with distinct clinical and molecular characteristics.

Detection of Glycosylated Markers From Cancer Stem Cells With ColoSTEM Dx Kit for Earlier Prediction of Colon Cancer Aggressiveness

Nowadays, colon cancer prognosis still difficult to predict, especially in the early stages. Recurrences remain elevated, even in the early stages after curative surgery. Carcidiag Biotechnologies has developed an immunohistochemistry (IHC) kit called ColoSTEM Dx, based on a MIX of biotinylated plant lectins that specifically detects colon cancer stem cells (CSCs) through glycan patterns that they specifically (over)express. A retrospective clinical study was carried out on tumor tissues from 208 non-chemotherapeutic-treated and 21 chemotherapeutic-treated patients with colon cancer, which were stained by IHC with the MIX. Clinical performances of the kit were determined, and prognostic and predictive values were evaluated. With 78.3% and 70.6% of diagnostic sensitivity and specificity respectively, our kit shows great clinical performances. Moreover, patient prognosis is significantly poorer when the MIX staining is “High” compared to “Low”, especially at 5-years of overall survival and for early stages. The ColoSTEM Dx kit allows an earlier and a more precise determination of patients’ outcome. Thus, it affords an innovating clinical tool for predicting tumor aggressiveness earlier and determining prognosis value regarding therapeutic response in colon cancer patients.

Morbid Obesity in Women Is Associated with an Altered Intestinal Expression of Genes Related to Cancer Risk and Immune, Defensive, and Antimicrobial Response

Background: Little is known about the relation between morbid obesity and duodenal transcriptomic changes. We aimed to identify intestinal genes that may be associated with the development of obesity regardless of the degree of insulin resistance (IR) of patients. Material and Methods: Duodenal samples were assessed by microarray in three groups of women: non-obese women and women with morbid obesity with low and high IR. Results: We identified differentially expressed genes (DEGs) associated with morbid obesity, regardless of IR degree, related to digestion and lipid metabolism, defense response and inflammatory processes, maintenance of the gastrointestinal epithelium, wound healing and homeostasis, and the development of gastrointestinal cancer. However, other DEGs depended on the IR degree. We mainly found an upregulation of genes involved in the response to external organisms, hypoxia, and wound healing functions in women with morbid obesity and low IR. Conclusions: Regardless of the degree of IR, morbid obesity is associated with an altered expression of genes related to intestinal defenses, antimicrobial and immune responses, and gastrointestinal cancer. Our data also suggest a deficient duodenal immune and antimicrobial response in women with high IR.

An NF-κB- and Therapy-Related Regulatory Network in Glioma: A Potential Mechanism of Action for Natural Antiglioma Agents

High-grade gliomas are among the most aggressive malignancies, with significantly low median survival. Recent experimental research in the field has highlighted the importance of natural substances as possible antiglioma agents, also known for their antioxidant and anti-inflammatory action. We have previously shown that natural substances target several surface cluster of differentiation (CD) markers in glioma cells, as part of their mechanism of action. We analyzed the genome-wide NF-κB binding sites residing in consensus regulatory elements, based on ENCODE data. We found that NF-κB binding sites reside adjacent to the promoter regions of genes encoding CD markers targeted by antiglioma agents (namely, CD15/FUT4, CD28, CD44, CD58, CD61/SELL, CD71/TFRC, and CD122/IL2RB). Network and pathway analysis revealed that the markers are associated with a core network of genes that, altogether, participate in processes that associate tumorigenesis with inflammation and immune evasion. Our results reveal a core regulatory network that can be targeted in glioblastoma, with apparent implications in individuals that suffer from this devastating malignancy.

Human/SARS-CoV-2 genome-scale metabolic modeling to discover potential antiviral targets for COVID-19

BACKGROUND

Coronavirus disease 2019 (COVID-19) has caused a substantial increase in mortality and economic and social disruption. The absence of US Food and Drug Administration-approved drugs for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) highlights the need for new therapeutic drugs to combat COVID-19.

METHODS

The present study proposed a fuzzy hierarchical optimization framework for identifying potential antiviral targets for COVID-19. The objectives in the decision-making problem were not only to evaluate the elimination of the virus growth, but also to minimize side effects causing treatment. The identified candidate targets could promote processes of drug discovery and development.

SIGNIFICANT FINDINGS

Our gene-centric method revealed that dihydroorotate dehydrogenase (DHODH) inhibition could reduce viral biomass growth and metabolic deviation by 99.4% and 65.6%, respectively, and increase cell viability by 70.4%. We also identified two-target combinations that could completely block viral biomass growth and more effectively prevent metabolic deviation. We also discovered that the inhibition of two antiviral metabolites, cytidine triphosphate (CTP) and uridine-5'-triphosphate (UTP), exhibits effects similar to those of molnupiravir, which is undergoing phase III clinical trials. Our predictions also indicate that CTP and UTP inhibition blocks viral RNA replication through a similar mechanism to that of molnupiravir.

Metabolic modeling of host-microbe interactions for therapeutics in colorectal cancer

The onset of colorectal cancer (CRC) is often attributed to gut bacterial dysbiosis, and thus gut microbiota are highly relevant in devising treatment strategies. Certain gut microbes, like Enterococcus spp., exhibit remarkable anti-neoplastic and probiotic properties, which can aid in silver nanoparticle (AgNPs) induced reactive oxygen species (ROS)-based CRC treatment. However, the effects of AgNPs on gut microbial metabolism have not been reported thus far. In this study, a detailed systems-level understanding of ROS metabolism in Enterococcus durans (E. durans), a representative gut microbe, was gained using constraint-based modeling, wherein, the critical association between ROS and folate metabolism was established. Experimental studies involving low AgNP concentration treatment of E. durans cultures confirmed these modeling predictions (an increased extracellular folate concentration by 52%, at the 9^th h of microbial growth, was observed). Besides, the computational studies established various metabolic pathways involving amino acids, energy metabolites, nucleotides, and SCFAs as the key players in elevating folate levels on ROS exposure. The anti-cancer potential of E. durans was also studied through MTT analysis of HCT 116 cells treated with microbial culture (AgNP treated) supernatant. A decrease in cell viability by 19% implicated the role of microbial metabolites (primarily folate) in causing cell death. The genome-scale modeling approach was then extended to extensively model CRC metabolism, as well as CRC-E. durans interactions in the context of CRC treatment, using tissue-specific metabolic models of CRC and healthy colon. These findings on further validation can facilitate the development of robust and effective cancer therapy.

Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets

Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism targeting as a promising antiviral strategy.

High-Throughput Sequencing Reveals the Differential MicroRNA Expression Profiles of Human Gastric Cancer SGC7901 Cell Xenograft Nude Mouse Models Treated with Traditional Chinese Medicine Si Jun Zi Tang Decoction

Objective. The present study aimed to investigate the potential mechanism underlying the antitumor effect of Si Jun Zi Tang (SJZT) decoction on gastric cancer. Methods. Twelve human gastric cancer SGC7901 cell xenograft nude mouse models were established. The mice were randomly divided into the Model group and SJZT group. SJZT exerted significant antitumor effects after 21 days of decoction administration. High-throughput sequencing was used to analyze the microRNA (miRNA) expression profiles of tumor tissues. Bioinformatics analysis was performed to provide further information regarding the differentially expressed miRNAs. Five representative differentially expressed miRNAs and four predicted target genes were further validated using quantitative real-time reverse transcription PCR (qRT-PCR). Results. We identified 33 miRNAs that were differentially expressed in the SJZT group compared with the Model group. Among them, 32 miRNAs were upregulated and 1 miRNA was downregulated. Bioinformatic analysis showed that most of miRNAs acted as tumor suppressors and their target genes participated in multiple signaling pathways, including the PI3K/Akt signaling pathway, microRNAs in cancer, and Wnt signaling pathway. The qRT-PCR result confirmed that miR-223-3p, miR-205-5p, miR-147b-3p, and miR-223-5p were overexpressed and their respective paired target genes FUT9, POU2F1, MUC4, and RAB14 mRNA were obviously downregulated in the SJZT group compared with those in the Model group. Network analysis revealed that miR-223-3p and miR-205-5p shared two targets POU2F1 (encoding POU class 2 homeobox 1) and FUT9 (encoding fucosyltransferase 9), suggesting they have a common role in certain pathways. Conclusion. This study provided novel insights into the anticancer mechanism of SJZT against gastric cancer, which might be partly related to the modulation of miRNA expression and their target pathways in tumors.

Genome-scale metabolic modeling reveals SARS-CoV-2-induced metabolic changes and antiviral targets

Tremendous progress has been made to control the COVID-19 pandemic caused by the SARS-CoV-2 virus. However, effective therapeutic options are still rare. Drug repurposing and combination represent practical strategies to address this urgent unmet medical need. Viruses, including coronaviruses, are known to hijack host metabolism to facilitate viral proliferation, making targeting host metabolism a promising antiviral approach. Here, we describe an integrated analysis of 12 published in vitro and human patient gene expression datasets on SARS-CoV-2 infection using genome-scale metabolic modeling (GEM), revealing complicated host metabolism reprogramming during SARS-CoV-2 infection. We next applied the GEM-based metabolic transformation algorithm to predict anti-SARS-CoV-2 targets that counteract the virus-induced metabolic changes. We successfully validated these targets using published drug and genetic screen data and by performing an siRNA assay in Caco-2 cells. Further generating and analyzing RNA-sequencing data of remdesivir-treated Vero E6 cell samples, we predicted metabolic targets acting in combination with remdesivir, an approved anti-SARS-CoV-2 drug. Our study provides clinical data-supported candidate anti-SARS-CoV-2 targets for future evaluation, demonstrating host metabolism-targeting as a promising antiviral strategy.

Genome-Scale Metabolic Modeling of the Human Microbiome in the Era of Personalized Medicine

The human microbiome plays an important role in human health and disease. Meta-omics analyses provide indispensable data for linking changes in microbiome composition and function to disease etiology. Yet, the lack of a mechanistic understanding of, e.g., microbiome-metabolome links hampers the translation of these findings into effective, novel therapeutics. Here, we propose metabolic modeling of microbial communities through constraint-based reconstruction and analysis (COBRA) as a complementary approach to meta-omics analyses. First, we highlight the importance of microbial metabolism in cardiometabolic diseases, inflammatory bowel disease, colorectal cancer, Alzheimer disease, and Parkinson disease. Next, we demonstrate that microbial community modeling can stratify patients and controls, mechanistically link microbes with fecal metabolites altered in disease, and identify host pathways affected by the microbiome. Finally, we outline our vision for COBRA modeling combined with meta-omics analyses and multivariate statistical analyses to inform and guide clinical trials, yield testable hypotheses, and ultimately propose novel dietary and therapeutic interventions. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Optimization of a modeling platform to predict oncogenes from genome-scale metabolic networks of non-small-cell lung cancers

Cancer cell dysregulations result in the abnormal regulation of cellular metabolic pathways. By simulating this metabolic reprogramming using constraint-based modeling approaches, oncogenes can be predicted, and this knowledge can be used in prognosis and treatment. We introduced a trilevel optimization problem describing metabolic reprogramming for inferring oncogenes. First, this study used RNA-Seq expression data of lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) samples and their healthy counterparts to reconstruct tissue-specific genome-scale metabolic models and subsequently build the flux distribution pattern that provided a measure for the oncogene inference optimization problem for determining tumorigenesis. The platform detected 45 genes for LUAD and 84 genes for LUSC that lead to tumorigenesis. A high level of differentially expressed genes was not an essential factor for determining tumorigenesis. The platform indicated that pyruvate kinase (PKM), a well-known oncogene with a low level of differential gene expression in LUAD and LUSC, had the highest fitness among the predicted oncogenes based on computation. By contrast, pyruvate kinase L/R (PKLR), an isozyme of PKM, had a high level of differential gene expression in both cancers. Phosphatidylserine synthase 1 (PTDSS1), an oncogene in LUAD, was inferred to have a low level of differential gene expression, and overexpression could significantly reduce survival probability. According to the factor analysis, PTDSS1 characteristics were close to those of the template, but they were unobvious in LUSC. Angiotensin-converting enzyme 2 (ACE2) has recently garnered widespread interest as the SARS-CoV-2 virus receptor. Moreover, we determined that ACE2 is an oncogene of LUSC but not of LUAD. The platform developed in this study can identify oncogenes with low levels of differential expression and be used to identify potential therapeutic targets for cancer treatment.

The Role of Glycosyltransferases in Colorectal Cancer

Colorectal cancer (CRC) is one of the main causes of cancer death in the world. Post-translational modifications (PTMs) have been extensively studied in malignancies due to its relevance in tumor pathogenesis and therapy. This review is focused on the dysregulation of glycosyltransferase expression in CRC and its impact in cell function and in several biological pathways associated with CRC pathogenesis, prognosis and therapeutic approaches. Glycan structures act as interface molecules between cells and their environment and in several cases facilitate molecule function. CRC tissue shows alterations in glycan structures decorating molecules, such as annexin-1, mucins, heat shock protein 90 (Hsp90), β1 integrin, carcinoembryonic antigen (CEA), epidermal growth factor receptor (EGFR), insulin-like growth factor-binding protein 3 (IGFBP3), transforming growth factor beta (TGF-β) receptors, Fas (CD95), PD-L1, decorin, sorbin and SH3 domain-containing protein 1 (SORBS1), CD147 and glycosphingolipids. All of these are described as key molecules in oncogenesis and metastasis. Therefore, glycosylation in CRC can affect cell migration, cell–cell adhesion, actin polymerization, mitosis, cell membrane repair, apoptosis, cell differentiation, stemness regulation, intestinal mucosal barrier integrity, immune system regulation, T cell polarization and gut microbiota composition; all such functions are associated with the prognosis and evolution of the disease. According to these findings, multiple strategies have been evaluated to alter oligosaccharide processing and to modify glycoconjugate structures in order to control CRC progression and prevent metastasis. Additionally, immunotherapy approaches have contemplated the use of neo-antigens, generated by altered glycosylation, as targets for tumor-specific T cells or engineered CAR (Chimeric antigen receptors) T cells.

Predictive modeling of complex ABO glycan phenotypes by lectin microarrays

Serological classification of individuals as A, B, O, or AB is a mainstay of blood banking. ABO blood groups or ABH antigens, in addition to other surface glycans, act as unique red blood cell (RBC) signatures and direct immune responses. ABO subgroups present as weakened, mixed field, or unexpected reactivity with serological reagents, but specific designations remain complex. Lectins detect glycan motifs with some recognizing ABH antigens. We evaluated a 45-probe lectin microarray to rapidly analyze ABO blood groups and associated unique glycan signatures within complex biological samples on RBC surface glycoproteins. RBC membrane glycoproteins were prepared from donor RBCs, n = 20 for each blood group. ABO blood group was distinguishable by lectin array, including variations in ABH antigen expression not observed with serology. Principal component analysis highlighted broad ABO blood group clusters with unexpected high and low antigen expression and variations were confirmed with ABH antibody immunoblotting. Using a subset of lectins provided an accurate method to predict an ABO serological phenotype. Lectin microarray highlighted the importance of ABO localization on glycoproteins and glycolipids and pointed to increased glycocalyx complexity associated with the expression of A and B antigens including high mannose and branched polylactosamine. Thus, lectins identified subtle surface ABO blood group glycoprotein density variations not detected by routine serological methods. Transfusion services observe alterations in ABH expression during malignancy, and ABO incompatible solid organ transplantation is not without risk of rejection. The presented methods may identify subtle but clinically significant ABO blood group differences for transfusion and transplantation.

Cysteine and Folate Metabolism Are Targetable Vulnerabilities of Metastatic Colorectal Cancer

Simple Summary

In this work, we studied the metabolic reprogramming of same-patient-derived cell lines with increasing metastatic potential to develop new therapeutic approaches against metastatic colorectal cancer. Using a novel systems biology approach to integrate multiple layers of omics data, we predicted and validated that cystine uptake and folate metabolism, two key pathways related to redox metabolism, are potential targets against metastatic colorectal cancer. Our findings indicate that metastatic cell lines are selectively dependent on redox homeostasis, paving the way for new targeted therapies.

Abstract

With most cancer-related deaths resulting from metastasis, the development of new therapeutic approaches against metastatic colorectal cancer (mCRC) is essential to increasing patient survival. The metabolic adaptations that support mCRC remain undefined and their elucidation is crucial to identify potential therapeutic targets. Here, we employed a strategy for the rational identification of targetable metabolic vulnerabilities. This strategy involved first a thorough metabolic characterisation of same-patient-derived cell lines from primary colon adenocarcinoma (SW480), its lymph node metastasis (SW620) and a liver metastatic derivative (SW620-LiM2), and second, using a novel multi-omics integration workflow, identification of metabolic vulnerabilities specific to the metastatic cell lines. We discovered that the metastatic cell lines are selectively vulnerable to the inhibition of cystine import and folate metabolism, two key pathways in redox homeostasis. Specifically, we identified the system xCT and MTHFD1 genes as potential therapeutic targets, both individually and combined, for combating mCRC.

Genome-scale metabolic modelling predicts biomarkers and therapeutic targets for neuropsychiatric disorders

Distinguishing neuropsychiatric disorders is challenging due to the overlap in symptoms and genetic risk factors. People suffering from these disorders face personal and professional challenges. Understanding the dysregulation of brain metabolism under disease condition can aid in effective diagnosis and in developing treatment strategies based on the metabolism. In this study, we reconstructed the metabolic network of three major neuropsychiatric disorders, schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) using transcriptomic data and constrained based modelling approach. We integrated brain transcriptomic data from six independent studies with a recent comprehensive genome-scale metabolic model Recon3D. The analysis of the reconstructed network revealed the flux-level alterations in the peroxisome-mitochondria-golgi axis in neuropsychiatric disorders. We also extracted reporter metabolites and pathways that distinguish these three neuropsychiatric disorders. We found differences with respect to fatty acid oxidation, aromatic and branched chain amino acid metabolism, bile acid synthesis, glycosaminoglycans synthesis and modifications, and phospholipid metabolism. Further, we predicted network perturbations that transform the disease metabolic state to a healthy metabolic state for each disorder. These analyses provide local and global views of the metabolic changes in SCZ, BD and MDD, which may have clinical implications.

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts.

van Vliet S. FUT9-Driven Programming of Colon Cancer Cells towards a Stem Cell-Like State

Cancer stem cells (CSCs) are located in dedicated niches, where they remain inert to chemotherapeutic drugs and drive metastasis. Although plasticity in the CSC pool is well appreciated, the molecular mechanisms implicated in the regulation of cancer stemness are still elusive. Here, we define a fucosylation-dependent reprogramming of colon cancer cells towards a stem cell-like phenotype and function. De novo transcriptional activation of Fut9 in the murine colon adenocarcinoma cell line, MC38, followed by RNA seq-based regulon analysis, revealed major gene regulatory networks related to stemness. Lewis^x, Sox2, ALDH and CD44 expression, tumorsphere formation, resistance to 5-FU treatment and in vivo tumor growth were increased in FUT9-expressing MC38 cells compared to the control cells. Likewise, human CRC cell lines highly expressing FUT9 displayed phenotypic features of CSCs, which were significantly impaired upon FUT9 knock-out. Finally, in primary CRC FUT9⁺ tumor cells pathways related to cancer stemness were enriched, providing a clinically meaningful annotation of the complicity of FUT9 in stemness regulation and may open new avenues for therapeutic intervention.

Transcriptome Based Profiling of the Immune Cell Gene Signature in Rat Experimental Colitis and Human IBD Tissue Samples

Chronic intestinal inflammation is characteristic of Inflammatory Bowel Disease (IBD) that is associated with the exaggerated infiltration of immune cells. A complex interplay of inflammatory mediators and different cell types in the colon are responsible for the maintenance of tissue homeostasis and affect pathological conditions. Gene expression alteration of colon biopsies from IBD patients and an in vivo rat model of colitis were examined by RNA-Seq and QPCR, while we used in silico methods, such as Ingenuity Pathway Analysis (IPA) application and the Immune Gene Signature (ImSig) package of R, to interpret whole transcriptome data and estimate immune cell composition of colon tissues. Transcriptome profiling of in vivo colitis model revealed the most significant activation of signaling pathways responsible for leukocyte recruitment and diapedesis. We observed significant alteration of genes related to glycosylation or sensing of danger signals and pro- and anti-inflammatory cytokines and chemokines, as well as adhesion molecules. We observed the elevated expression of genes that implies the accumulation of monocytes, macrophages, neutrophils and B cells in the inflamed colon tissue. In contrast, the rate of T-cells slightly decreased in the inflamed regions. Interestingly, natural killer and plasma cells do not show enrichment upon colon inflammation. In general, whole transcriptome analysis of the in vivo experimental model of colitis with subsequent bioinformatics analysis provided a better understanding of the dynamic changes in the colon tissue of IBD patients.

How glycosylation affects glycosylation: the role of N-glycans in glycosyltransferase activity

N-glycosylation is one of the most important posttranslational modifications of proteins. It plays important roles in the biogenesis and functions of proteins by influencing their folding, intracellular localization, stability and solubility. N-glycans are synthesized by glycosyltransferases, a complex group of ubiquitous enzymes that occur in most kingdoms of life. A growing body of evidence shows that N-glycans may influence processing and functions of glycosyltransferases, including their secretion, stability and substrate/acceptor affinity. Changes in these properties may have a profound impact on glycosyltransferase activity. Indeed, some glycosyltransferases have to be glycosylated themselves for full activity. N-glycans and glycosyltransferases play roles in the pathogenesis of many diseases (including cancers), so studies on glycosyltransferases may contribute to the development of new therapy methods and novel glycoengineered enzymes with improved properties. In this review, we focus on the role of N-glycosylation in the activity of glycosyltransferases and attempt to summarize all available data about this phenomenon.

Endothelial E-selectin inhibition improves acute myeloid leukaemia therapy by disrupting vascular niche-mediated chemoresistance

The endothelial cell adhesion molecule E-selectin is a key component of the bone marrow hematopoietic stem cell (HSC) vascular niche regulating balance between HSC self-renewal and commitment. We now report in contrast, E-selectin directly triggers signaling pathways that promote malignant cell survival and regeneration. Using acute myeloid leukemia (AML) mouse models, we show AML blasts release inflammatory mediators that upregulate endothelial niche E-selectin expression. Alterations in cell-surface glycosylation associated with oncogenesis enhances AML blast binding to E-selectin and enable promotion of pro-survival signaling through AKT/NF-κB pathways. In vivo AML blasts with highest E-selectin binding potential are 12-fold more likely to survive chemotherapy and main contributors to disease relapse. Absence (in Sele^−/− hosts) or therapeutic blockade of E-selectin using small molecule mimetic GMI-1271/Uproleselan effectively inhibits this niche-mediated pro-survival signaling, dampens AML blast regeneration, and strongly synergizes with chemotherapy, doubling the duration of mouse survival over chemotherapy alone, whilst protecting endogenous HSC.

The cell adhesion molecule E-selectin regulates haematopoietic stem cell self-renewal in the bone marrow vascular niche. Here, the authors show E-selectin adhesion directly induces survival signaling in acute myeloid leukaemia and therapeutic inhibition improves chemotherapy outcomes in mice.

Elucidating the Reprograming of Colorectal Cancer Metabolism Using Genome-Scale Metabolic Modeling

Colorectal cancer is the third most incidental cancer worldwide, and the response rate of current treatment for colorectal cancer is very low. Genome-scale metabolic models (GEMs) are systems biology platforms, and they had been used to assist researchers in understanding the metabolic alterations in different types of cancer. Here, we reconstructed a generic colorectal cancer GEM by merging 374 personalized GEMs from the Human Pathology Atlas and used it as a platform for systematic investigation of the difference between tumor and normal samples. The reconstructed model revealed the metabolic reprogramming in glutathione as well as the arginine and proline metabolism in response to tumor occurrence. In addition, six genes including ODC1, SMS, SRM, RRM2, SMOX, and SAT1 associated with arginine and proline metabolism were found to be key players in this metabolic alteration. We also investigated these genes in independent colorectal cancer patients and cell lines and found that many of these genes showed elevated level in colorectal cancer and exhibited adverse effect in patients. Therefore, these genes could be promising therapeutic targets for treatment of a specific colon cancer patient group.

Transcriptional activation of fucosyltransferase (FUT) genes using the CRISPR-dCas9-VPR technology reveals potent N-glycome alterations in colorectal cancer cells

Aberrant fucosylation in cancer cells is considered as a signature of malignant cell transformation and it is associated with tumor progression, metastasis and resistance to chemotherapy. Specifically, in colorectal cancer cells, increased levels of the fucosylated Lewis^x antigen are attributed to the deregulated expression of pertinent fucosyltransferases, like fucosyltransferase 4 (FUT4) and fucosyltransferase 9 (FUT9). However, the lack of experimental models closely mimicking cancer-specific regulation of fucosyltransferase gene expression has, so far, limited our knowledge regarding the substrate specificity of these enzymes and the impact of Lewis^x synthesis on the glycome of colorectal cancer cells. Therefore, we sought to transcriptionally activate the Fut4 and Fut9 genes in the well-known murine colorectal cancer cell line, MC38, which lacks expression of the FUT4 and FUT9 enzymes. For this purpose, we utilized a physiologically relevant, guide RNA-based model of de novo gene expression, namely the CRISPR-dCas9-VPR system. Induction of the Fut4 and Fut9 genes in MC38 cells using CRISPR-dCas9-VPR resulted in specific neo-expression of functional Lewis^x antigen on the cell surface. Interestingly, Lewis^x was mainly carried by N-linked glycans in both MC38-FUT4 and MC38-FUT9 cells, despite pronounced differences in the biosynthetic properties and the expression stability of the induced enzymes. Moreover, Lewis^x expression was found to influence core-fucosylation, sialylation, antennarity and the subtypes of N-glycans in the MC38-glycovariants. In conclusion, exploiting the CRISPR-dCas9-VPR system to augment glycosyltransferase expression is a promising method of transcriptional gene activation with broad application possibilities in glycobiology and oncology research.

Integrating -omics data into genome-scale metabolic network models: principles and challenges

At genome scale, it is not yet possible to devise detailed kinetic models for metabolism because data on the in vivo biochemistry are too sparse. Predictive large-scale models for metabolism most commonly use the constraint-based framework, in which network structures constrain possible metabolic phenotypes at steady state. However, these models commonly leave many possibilities open, making them less predictive than desired. With increasingly available -omics data, it is appealing to increase the predictive power of constraint-based models (CBMs) through data integration. Many corresponding methods have been developed, but data integration is still a challenge and existing methods perform less well than expected. Here, we review main approaches for the integration of different types of -omics data into CBMs focussing on the methods' assumptions and limitations. We argue that key assumptions - often derived from single-enzyme kinetics - do not generally apply in the context of networks, thereby explaining current limitations. Emerging methods bridging CBMs and biochemical kinetics may allow for -omics data integration in a common framework to provide more accurate predictions.

An integrated computational and experimental study uncovers FUT9 as a metabolic driver of colorectal cancer

Metabolic alterations play an important role in cancer and yet, few metabolic cancer driver genes are known. Here we perform a combined genomic and metabolic modeling analysis searching for metabolic drivers of colorectal cancer. Our analysis predicts FUT9, which catalyzes the biosynthesis of Ley glycolipids, as a driver of advanced-stage colon cancer. Experimental testing reveals FUT9's complex dual role; while its knockdown enhances proliferation and migration in monolayers, it suppresses colon cancer cells expansion in tumorspheres and inhibits tumor development in a mouse xenograft models. These results suggest that FUT9's inhibition may attenuate tumor-initiating cells (TICs) that are known to dominate tumorspheres and early tumor growth, but promote bulk tumor cells. In agreement, we find that FUT9 silencing decreases the expression of the colorectal cancer TIC marker CD44 and the level of the OCT4 transcription factor, which is known to support cancer stemness. Beyond its current application, this work presents a novel genomic and metabolic modeling computational approach that can facilitate the systematic discovery of metabolic driver genes in other types of cancer.