scholarly journals Carbon-ion Evokes Metabolic Reprogramming and Individualized Response in Prostate Cancer

2021 ◽  
Author(s):  
Yulei Pei ◽  
Renli Ning ◽  
Ping Li ◽  
Wei Hu ◽  
Yong Deng ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Treatment Response ◽  
High Throughput ◽  
Enrichment Analysis ◽  
Metabolic Reprogramming ◽  
Pathway Enrichment Analysis ◽  
Arginine Biosynthesis ◽  
Metabolic Pathway Analysis ◽  
Urine Metabolites ◽  
Carbon Ion

Abstract Background: Carbon ion radiotherapy (CIRT) is a novel and powerful tool for prostate cancer (PCa). However, the underlying mechanism for individualized treatment response after CIRT was not clear, and there was still no effective indicator to timely demonstrate the treatment response. Metabolic reprogramming is one of the main hallmarks of malignancy. Metabolic status might have a high relationship with the radiosensitivity and the individualized radiation response. The significant changes of metabolites profiles were detected after radiotherapy in the serum sample of different malignancies. But there was limited data regarding CIRT induced metabolic changes in prostate cancer. Our aim was to preliminary investigate the carbon-ion induced metabolic reprogramming in PCa patients and the individualized response of PCa patients to carbon ion. Methods: Urine samples collected from 15 pathology confirmed PCa patients before and after CIRT were enrolled into this analysis. High-throughput UPLC-MS/MS system was used for metabolites detection. XCMS online, MetDNA and MSDIAL were used for peak detection and identification of metabolites. Statistical analysis and metabolic pathway analysis were performed on Metaboanalyst.Results: A total of 1701 metabolites were monitored by high-throughput UPLC-MS/MS and 217 metabolites were identified. The PCA scores plot revealed clear discrimination of the patient’s urine metabolites profiles before (pre-CIRT) and after (pre-CIRT) CIRT treatment. 35 metabolites significantly altered after CIRT, and these metabolites mainly were amino acid. Pathway enrichment analysis further identified these metabolites could be enriched in 8 pathways (FDR<0.05, impact>2), while arginine biosynthesis and histidine metabolism pathways were the most significant. In addition, the HCA shows that after CIRT, the patients can be clustered into two groups according to the metabolites profiles. The discriminatory metabolites after CIRT in patients urine mainly enriched in the pathway of arginine biosynthesis and phenylalanine, tyrosine, and tryptophan biosynthesis. Conclusion: Metabolic reprogramming and metabolic inhibition seems one of the most important mechanisms of CIRT to cure PCa. Urine metabolites also showed their potentials to timely identify the individualized response of PCa patients to CIRT.

scholarly journals Carbon Ion Radiotherapy Evokes a Metabolic Reprogramming and Individualized Response in Prostate Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Renli Ning ◽  
Yulei Pei ◽  
Ping Li ◽  
Wei Hu ◽  
Yong Deng ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Principal Component ◽  
Metabolic Reprogramming ◽  
Carbon Ion Radiotherapy ◽  
Arginine Biosynthesis ◽  
Metabolic Pathway Analysis ◽  
Urine Metabolites ◽  
Carbon Ion ◽  
Metabolite Profiles ◽  
The Impact

Introduction: Carbon ion radiotherapy (CIRT) is a novel treatment for prostate cancer (PCa). However, the underlying mechanism for the individualized response to CIRT is still not clear. Metabolic reprogramming is essential for tumor growth and proliferation. Although changes in metabolite profiles have been detected in patients with cancer treated with photon radiotherapy, there is limited data regarding CIRT-induced metabolic changes in PCa. Therefore, the study aimed to investigate the impact of metabolic reprogramming on individualized response to CIRT in patients with PCa.Materials and Methods: Urine samples were collected from pathologically confirmed patients with PCa before and after CIRT. A UPLC-MS/MS system was used for metabolite detection. XCMS online, MetDNA, and MS-DIAL were used for peak detection and identification of metabolites. Statistical analysis and metabolic pathway analysis were performed on MetaboAnalyst.Results: A total of 1,701 metabolites were monitored in this research. Principal component analysis (PCA) revealed a change in the patient's urine metabolite profiles following CIRT. Thirty-five metabolites were significantly altered, with the majority of them being amino acids. The arginine biosynthesis and histidine metabolism pathways were the most significantly altered pathways. Hierarchical cluster analysis (HCA) showed that after CIRT, the patients could be clustered into two groups according to their metabolite profiles. The arginine biosynthesis and phenylalanine, tyrosine, and tryptophan biosynthesis pathways are the most significantly discriminated pathways.Conclusion: Our preliminary findings indicate that metabolic reprogramming and inhibition are important mechanisms involved in response to CIRT in patients with PCa. Therefore, changes in urine metabolites could be used to timely assess the individualized response to CIRT.

scholarly journals Comparative transcriptomic analysis of heterophylly of the aquatic plant Potamogeton octandrus (Potamogetonaceae)

2017 ◽  
Author(s):  
Dingxuan He ◽  
Pin Guo ◽  
Paul F Gugger ◽  
Youhao Guo ◽  
Xing Liu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
High Throughput ◽  
Leaf Development ◽  
Aquatic Plant ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Functional Studies ◽  
Floating Leaves

Many plant species exhibit heterophylly, displaying different leaves upon a single plant. The molecular mechanisms regulating this phenomenon, however, have remained elusive. In this study, the transcriptomes of submerged and floating leaves of an aquatic heterophyllous plant, Potamogeton octandrus Poir, were sequenced using a high-throughput sequencing technique (RNA-Seq), which aims to assist with the gene discovery and functional studies of genes involved in heterophyllous leaf development. A total of 81,103 unigenes were identified from the submerged and floating leaves, and a total of 6,822 differentially expressed genes (DEGs) were identified by comparing the samples from each developmental stage. KEGG pathway enrichment analysis categorized these unigenes into 128 pathways (p-value < 10-5). A total of 24,025 differentially expressed genes were involved in the carbon metabolic pathway, biosynthesis of amino acids, ribosomes, and plant-pathogen interaction. KEGG pathway enrichment analysis categorized a total of 70 DEGs into plant hormone signal transduction pathways. This study describes the initial results of the high-throughput transcriptome sequencing of heterophylly. Understanding the transcriptomes of floating and submerged leaves of the aquatic plant P. octandrus will assist with gene cloning and functional studies of genes involved in leaf development. This is especially the case with those involved in heterophyllous leaf development.

scholarly journals Comparative transcriptomic analysis of heterophylly of the aquatic plant Potamogeton octandrus (Potamogetonaceae)

2017 ◽  
Author(s):  
Dingxuan He ◽  
Pin Guo ◽  
Paul F Gugger ◽  
Youhao Guo ◽  
Xing Liu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
High Throughput ◽  
Leaf Development ◽  
Aquatic Plant ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Functional Studies ◽  
Floating Leaves

Many plant species exhibit heterophylly, displaying different leaves upon a single plant. The molecular mechanisms regulating this phenomenon, however, have remained elusive. In this study, the transcriptomes of submerged and floating leaves of an aquatic heterophyllous plant, Potamogeton octandrus Poir, were sequenced using a high-throughput sequencing technique (RNA-Seq), which aims to assist with the gene discovery and functional studies of genes involved in heterophyllous leaf development. A total of 81,103 unigenes were identified from the submerged and floating leaves, and a total of 6,822 differentially expressed genes (DEGs) were identified by comparing the samples from each developmental stage. KEGG pathway enrichment analysis categorized these unigenes into 128 pathways (p-value < 10-5). A total of 24,025 differentially expressed genes were involved in the carbon metabolic pathway, biosynthesis of amino acids, ribosomes, and plant-pathogen interaction. KEGG pathway enrichment analysis categorized a total of 70 DEGs into plant hormone signal transduction pathways. This study describes the initial results of the high-throughput transcriptome sequencing of heterophylly. Understanding the transcriptomes of floating and submerged leaves of the aquatic plant P. octandrus will assist with gene cloning and functional studies of genes involved in leaf development. This is especially the case with those involved in heterophyllous leaf development.

scholarly journals LIPEA: Lipid Pathway Enrichment Analysis

2018 ◽  
Author(s):  
Aldo Acevedo ◽  
Claudio Durán ◽  
Sara Ciucci ◽  
Mathias Gerl ◽  
Carlo Vittorio Cannistraci
Keyword(s):  
High Throughput ◽  
Metabolic Diseases ◽  
Enrichment Analysis ◽  
Absolute Quantification ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Web Tool ◽  
Gene Set Enrichment ◽  
Pathway Enrichment ◽  
Web Platform

AbstractMotivationAnalyzing associations among multiple omic variables to infer mechanisms that meaningfully link them is a crucial step in systems biology. Gene Set Enrichment Analysis (GSEA) was conceived to pursue this aim in computational genomics, unveiling significant pathways associated to certain gene signatures under investigation. Lipidomics is a rapidly growing omic field, and absolute quantification of lipid abundance by shotgun mass spectrometry is generating high-throughput datasets that depict lipid metabolism in a plethora of conditions and organisms. In addition, high-throughput lipidomics represents a new important ally to develop personalized medicine approaches, investigate the causes and predict effective biomarkers in metabolic diseases, and not only.ResultsHere, we present Lipid Pathway Enrichment Analysis (LIPEA), a web-tool for over-representation analysis of lipid signatures and detection of the biological pathways in which they are enriched. LIPEA is a new valid resource for biologists and physicians to mine pathways significantly associated to a set of lipids, helping them to discover whether common and collective mechanisms are hidden behind those lipids. LIPEA was extensively tested and we provide two examples where our system gave successfully results related with Major Depression Disease (MDD) and insulin re-sistance.AvailabilityThe tool is available as web platform at https://lipea.biotec.tu-dresden.de.

scholarly journals Identification of Potential Key Genes and Pathways in Enzalutamide-Resistant Prostate Cancer Cell Lines: A Bioinformatics Analysis with Data from the Gene Expression Omnibus (GEO) Database

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Long Zheng ◽  
Xiaojie Dou ◽  
Xiaodong Ma ◽  
Wei Qu ◽  
Xiaoshuang Tang
Keyword(s):  
Gene Expression ◽  
Prostate Cancer ◽  
Cell Lines ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Key Genes ◽  
Geo Database

Enzalutamide (ENZ) has been approved for the treatment of advanced prostate cancer (PCa), but some patients develop ENZ resistance initially or after long-term administration. Although a few key genes have been discovered by previous efforts, the complete mechanisms of ENZ resistance remain unsolved. To further identify more potential key genes and pathways in the development of ENZ resistance, we employed the GSE104935 dataset, including 5 ENZ-resistant (ENZ-R) and 5 ENZ-sensitive (ENZ-S) PCa cell lines, from the Gene Expression Omnibus (GEO) database. Integrated bioinformatics analyses were conducted, such as analysis of differentially expressed genes (DEGs), Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein-protein interaction (PPI) analysis, gene set enrichment analysis (GSEA), and survival analysis. From these, we identified 201 DEGs (93 upregulated and 108 downregulated) and 12 hub genes (AR, ACKR3, GPER1, CCR7, NMU, NDRG1, FKBP5, NKX3-1, GAL, LPAR3, F2RL1, and PTGFR) that are potentially associated with ENZ resistance. One upregulated pathway (hedgehog pathway) and seven downregulated pathways (pathways related to androgen response, p53, estrogen response, TNF-α, TGF-β, complement, and pancreas β cells) were identified as potential key pathways involved in the occurrence of ENZ resistance. Our findings may contribute to further understanding the molecular mechanisms of ENZ resistance and provide some clues for the prevention and treatment of ENZ resistance.

Investigation of Key Genes associated with Prostate Cancer using RNA-Seq Data

2014 ◽  
Vol 29 (1) ◽  
pp. e86-e92 ◽  
Author(s):  
Jitao Wu ◽  
Fan Feng ◽  
Diandong Yang ◽  
Shengqiang Yu ◽  
Jianqiu Liu ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Normal Sample ◽  
Pathway Enrichment Analysis ◽  
Rna Seq ◽  
Cancer Sample ◽  
Key Genes

We aimed to identify key genes associated with prostate cancer using RNA-sequencing (RNA-seq) data. RNA-seq data, including 1 cancer sample and 1 adjacent normal sample, were downloaded from the NCBI SRA database and the differentially expressed genes (DEGs) were identified with the software Cufflinks. Functional enrichment analysis was performed to uncover the biological functions of DEGs. Regulatory information was retrieved from the IPA database and a network was established. A total of 147 DEGs were obtained, including 96 downregulated and 51 upregulated DEGs. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis suggested that metabolism and signal transduction were the 2 major functions that were significantly influenced. Moreover, an interaction network was built. In conclusion, a number of DEGs was identified and their roles in the pathogenesis of cancer were supported by previous studies. More studies are necessary to further validate their usefulness in the diagnosis and treatment of prostate cancer.

scholarly journals Combination of 99mTc-labeled PSMA-SPECT/CT and Diffusion-Weighted MRI in the prediction of early response after carbon ion therapy in prostate cancer: a prospective study

2020 ◽  
Author(s):  
Ping Li ◽  
Chang Liu ◽  
Shuang Wu ◽  
Lin Deng ◽  
guangyuan Zhang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Treatment Response ◽  
Roc Curve ◽  
Poor Response ◽  
Localized Prostate Cancer ◽  
Roc Curve Analysis ◽  
Carbon Ion ◽  
Diffusion Weighted ◽  
And Diffusion

Abstract Background The purpose of this study was to assess the potential of 99mTc-labeled PSMA-SPECT/CT and Diffusion-Weighted Image (DWI) for predicting treatment response after carbon ion radiotherapy (CIRT) in prostate cancer. Methods We prospectively registered 26 patients with localized prostate cancer treated with CIRT. All patients underwent 99m Tc-labeled PSMA-SPECT/CT and multiparametric MRI before and after CIRT. The tumor/background ratio (TBR) and mean apparent diffusion coefficient (ADC mean ) were measured on the tumor and the percentage changes between 2 time points (ΔTBR and ΔADC mean ) were calculated. Patients were divided into two groups: good response and poor response according to clinical follow-up. Results The median follow up time was 38.3months. The TBR was significantly decreased ( p =0.001), while the ADC mean was significantly increased compared with the pretreatment value ( p <0.001). The ΔTBR and ΔADC mean were negatively correlated with each other ( p = 0.002). On ROC curve analysis for predicting treatment response, the area under the ROC curve (AUC) of ΔTBR (0.867) for predicting good response was higher than that of ΔADC mean (0.819). The AUC of combined with ΔTBR and ΔADC mean (0.895) was higher than that of either ΔADC mean or ΔTBR alone. The combined use of ΔTBR and ΔADC mean showed 91.4% sensitivity and 95.2% specificity. Conclusions Our preliminary data indicate that the changes of TBR and ADC mean maybe an early bio-marker for predicting prognosis after CIRT in localized prostate cancer patients. In addition, the ΔTBR was a more powerful prognostic factor than ΔADC mean in prostate cancer treated with CIRT.

scholarly journals Investigating the molecular basis for heterophylly in the aquatic plant Potamogeton octandrus (Potamogetonaceae) with comparative transcriptomics

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4448 ◽  
Author(s):  
Dingxuan He ◽  
Pin Guo ◽  
Paul F. Gugger ◽  
Youhao Guo ◽  
Xing Liu ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
High Throughput ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Pathway Enrichment ◽  
Floating Leaves

Many plant species exhibit different leaf morphologies within a single plant, or heterophylly. The molecular mechanisms regulating this phenomenon, however, have remained elusive. In this study, the transcriptomes of submerged and floating leaves of an aquatic heterophyllous plant, Potamogeton octandrus Poir, at different stages of development, were sequenced using high-throughput sequencing (RNA-Seq), in order to aid gene discovery and functional studies of genes involved in heterophylly. A total of 81,103 unigenes were identified in submerged and floating leaves and 6,822 differentially expressed genes (DEGs) were identified by comparing samples at differing time points of development. KEGG pathway enrichment analysis categorized these unigenes into 128 pathways. A total of 24,025 differentially expressed genes were involved in carbon metabolic pathways, biosynthesis of amino acids, ribosomal processes, and plant-pathogen interactions. In particular, KEGG pathway enrichment analysis categorized a total of 70 DEGs into plant hormone signal transduction pathways. The high-throughput transcriptomic results presented here highlight the potential for understanding the molecular mechanisms underlying heterophylly, which is still poorly understood. Further, these data provide a framework to better understand heterophyllous leaf development in P. octandrus via targeted studies utilizing gene cloning and functional analyses.

scholarly journals Metabolic Profiling Reveals Significant Perturbations of Intracellular Glucose Homeostasis in Enterovirus-Infected Cells

Metabolites ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 302
Author(s):  
Zijiao Zou ◽  
Jessica Oi-Ling Tsang ◽  
Bingpeng Yan ◽  
Kenn Ka-Heng Chik ◽  
Chris Chun-Yiu Chan ◽  
...  
Keyword(s):  
Neural Progenitor Cells ◽  
Viral Infections ◽  
Expression Profiles ◽  
Foot And Mouth Disease ◽  
Enrichment Analysis ◽  
Neurological Complications ◽  
Metabolic Reprogramming ◽  
Pathway Enrichment Analysis ◽  
Altered Expression

Enterovirus A71 (EV-A71) is a common cause of hand, foot, and mouth disease. Severe EV-A71 infections may be associated with life-threatening neurological complications. However, the pathogenic mechanisms underlying these severe clinical and pathological features remain incompletely understood. Metabolites are known to play critical roles in multiple stages of the replication cycles of viruses. The metabolic reprogramming induced by viral infections is essential for optimal virus replication and may be potential antiviral targets. In this study, we applied targeted metabolomics profiling to investigate the metabolic changes of induced pluripotent human stem cell (iPSC)-derived neural progenitor cells (NPCs) upon EV-A71 infection. A targeted quantitation of polar metabolites identified 14 candidates with altered expression profiles. A pathway enrichment analysis pinpointed glucose metabolic pathways as being highly perturbed upon EV-A71 infection. Gene silencing of one of the key enzymes of glycolysis, 6-phosphofructo-2-kinase (PFKFB3), significantly suppressed EV-A71 replication in vitro. Collectively, we demonstrated the feasibility to manipulate EV-A71-triggered host metabolic reprogramming as a potential anti-EV-A71 strategy.

Sign in / Sign up

Export Citation Format

Share Document