Recognition of early and late stages of bladder cancer using metabolites and machine learning

Kouznetsova, Valentina L.; Kim, Elliot; Romm, Eden; Zhu, Alan X.; Tsigelny, Igor F.

doi:10.1007/s11306-019-1555-9

Cited by 49 publications

(39 citation statements)

References 58 publications

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“…We also observed the enrichment of the starch and sucrose metabolism pathway in the control group compared with the CIN2/3-CC group. In line with our results, a recent study also demonstrated enrichment of the starch and sucrose metabolism pathway in healthy patients relative to those with prostate cancer 27 and bladder cancer 35 . The starch and sucrose metabolism pathway was associated with phosphotransferase enzymes, including sucrose-specific IIA, IIB, and IIC, as predicted using the PICRUSt pipeline (Table 4).…”

Section: Discussionsupporting

confidence: 92%

Taxonomic and Functional Differences in Cervical Microbiome Associated with Cervical Cancer Development

Tango

Seo

Kwon

et al. 2020

Sci Rep

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The cervical microbiome is associated with cervical cancer risk, but how microbial diversity and functional profiles change in cervical cancer remains unclear. Herein, we investigated microbialcompositional and functional differences between a control group and a high-grade cervical intraepithelial neoplasia and cervical cancer (CIN2/3-CC) group. After retrospective collection of 92 cervical swab samples, we carried out 16S rRNA amplicon sequencing on 50 and 42 samples from the control and CIN2/3-CC groups, respectively. The EzBioCloud pipeline was applied to identify the genomic features associated with the groups using 16S rRNA data. A linear discriminant analysis effect size (LEfSe) was performed to assess the enrichment in the assigned taxonomic and functional profiles. We found a lower richness in the control group relative to the CIN2/3-CC group; however, the β-diversity tended to be similar between the groups. The LEfSe analysis showed that a phylum Sacchaaribacteria_TM7, 11 genera, and 21 species were more abundant in the CIN2/3-CC group and that one uncharacterized Gardnerella species was more abundant only in the control group. Further characterization of the functional pathways using EzBioCloud showed that the 4 KEGG orthologs (Phosphotransferase system [PTS] sucrose-specific IIA, IIB, IIC components and PTS cellubiose-specific IIC component) were involved in the KEGG pathway of starch and sucrose metabolism. The two pathways of folate biosynthesis and oxidative phosphorylation were more abundant in the CIN2/3-CC group. Further confirmation of these results in larger samples can help to elucidate the potential association between the cervical microbiome and cervical cancer. Cervical intraepithelial neoplasia (CIN) is a precancerous lesion in cervical epithelial cells, and is histologically divided into different grades 1. Infection with HPV is the most important causative factor for CIN or cervical cancer. Although HPV is a major risk factor for cervical precancerous lesions or cancer, the potential role of the cervicovaginal microbiome in cervical cancer via the elevation of pH also has been reported 2. In fact, the role of the cervicovaginal microbiome in HPV infection has already been established, which fact suggests a possible role in cervical cancer through potentiation of HPV infection 3. Interestingly, the action of the microbiota is a complex process, the scientific data on which remains sparse 4,5. The impact of the microbiome and its functions on cervical pathophysiology differ among individuals 6. There is increasing evidence that the cervical microbiome plays important roles in the carcinogenesis process of the uterine cervix; thus, it is being considered as a target for development of innovative therapeutic approaches 7,8. The cervical microbiome's importance lies in its provision of the metabolic pathways and enzymatic machinery that help to process essential vitamins, remove toxic compounds, defend against pathogens, strengthen the female genital-tract epithelium, and stimulate as well a...

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Section: Discussionsupporting

confidence: 92%

Taxonomic and Functional Differences in Cervical Microbiome Associated with Cervical Cancer Development

Tango

Seo

Kwon

et al. 2020

Sci Rep

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“…In the case of patient 2852, his urinary metabolic pro le shows signi cant abnormal values for metabolites belonging to galactose metabolism/starch sucrose metabolism, caffeine metabolism, and lysine metabolism, all related to bladder cancer. In fact, a recent study, about recognition of different stages of BC using metabolites and machine learning, identi ed the rst two as the main dysregulated metabolisms in early stages, whereas lysine metabolism was found unbalanced in late stages 29 . The case of caffeine metabolism is very interesting, as this compound, together with one of its metabolites, 1,3-dimethylurate, are processed by CYP1A2, a cytochrome belonging to the P450 family, acting in the liver 30 .…”

Section: Discussionmentioning

confidence: 99%

Personalized metabolic profile by synergic use of NMR and HRMS

Petrella

Montesano

Lentini

et al. 2021

Preprint

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A new strategy that takes advantage of the synergism between NMR and LC-HRMS (SYNHMET), and that allows to obtain a unique list of the absolute concentrations of 164 metabolites in urine, is presented. Metabolite identification and quantification by this method in one of the most difficult biofluids to characterize, due to complexity and variability, is more accurate than what can be obtained using the two techniques separately. This result is achieved without the need for chemical reactions to cross-check the data between the two types of spectra, nor the use of analytical standards and calibration curves. The fact that the absolute rather than relative concentration is obtained allows the final dataset to be used to determine a patient's personalized profile. The number of quantifiable metabolites by the application of this method can be expanded in the future with further analysis. We will illustrate the use of SYNHMET in the study of urine samples from healthy subjects, patients with chronic cystitis and bladder cancer.

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“…Moreover, Ingenuity Pathway Analysis (IPA) software (QIAGEN Inc) is quantitative genomics, transcriptomics, proteomics and metabolomics analysis tool that provides the significance of the uploaded data and determines new biomarker candidates within a biological system. IPA is commonly used in the scientific research community for its analysis and interpretation of omics data (Kouznetsova et al, 2019). This study aimed to explore and evaluate the metabolic alterations and mechanism of the crude IL-GPE treatment on in vitro colon cancer HT29 cells by using multiple analytical approaches.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of metabolomics behavior of human colon cancer HT29 cell lines treated with ionic liquid graviola fruit pulp extract

Daddiouaissa

Amid

Sani

et al. 2021

Journal of Ethnopharmacology

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Medicinal plants have been used by indigenous people across the world for centuries to help individuals preserve their wellbeing and cure diseases. Annona muricata L. (Graviola) which is belonging to the Annonaceae family has been traditionally used due to its medicinal abilities including antimicrobial, anti-inflammatory, antioxidant and cancer cell growth inhibition. Graviola is claimed to be a potential antitumor due to its selective cytotoxicity against several cancer cell lines. However, the metabolic mechanism information underlying the anticancer activity remains limited. Aim of the study: This study aimed to investigate the effect of ionic liquid-Graviola fruit pulp extract (IL-GPE) on the metabolomics behavior of colon cancer (HT29) by using an untargeted GC-TOFMS-based metabolic profiling. Materials and methods: Multivariate data analysis was used to determine the metabolic profiling, and the ingenuity pathway analysis (IPA) was used to predict the altered canonical pathways after treating the HT29 cells with crude IL-GPE and Taxol (positive control). Results: The principal components analysis (PCA) identified 44 metabolites with the most reliable factor loading, and the cluster analysis (CA) separated three groups of metabolites: metabolites specific to the non-treated HT29 cells, metabolites specific to the treated HT29 cells with the crude IL-GPE and metabolites specific to Taxol treatment. Pathway analysis of metabolomic profiles revealed an alteration of many metabolic pathways, including amino acid metabolism, aerobic glycolysis, urea cycle and ketone bodies metabolism that contribute to energy metabolism and cancer cell proliferation. Conclusion:The crude IL-GPE can be one of the promising anticancer agents due to its selective inhibition of energy metabolism and cancer cell proliferation.

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Recognition of early and late stages of bladder cancer using metabolites and machine learning

Cited by 49 publications

References 58 publications

Taxonomic and Functional Differences in Cervical Microbiome Associated with Cervical Cancer Development

Taxonomic and Functional Differences in Cervical Microbiome Associated with Cervical Cancer Development

Personalized metabolic profile by synergic use of NMR and HRMS

Evaluation of metabolomics behavior of human colon cancer HT29 cell lines treated with ionic liquid graviola fruit pulp extract

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