Identification and evaluation of biomarkers for screening and early diagnosis of colorectal neoplasms based on metabolomics
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Neoplasms
PROVIDER: 2701069 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Interventions: Gold Standard:Pathologic diagnosis;Index test:diagnostic model of intestinal microbiome progressive markers 
Primary outcome(s): Sensitivity;The area under the ROC curve
Study Design: Factorial
| 2701732 | ecrin-mdr-crc
Project description:BackgroundSeveral approaches have been suggested to be useful in the early detection of colorectal neoplasms. Since metabolites are closely related to the phenotype and are available from different human bio-fluids, metabolomics are candidates for non-invasive early detection of colorectal neoplasms.ObjectivesWe aimed to summarize current knowledge on performance characteristics of metabolomics biomarkers that are potentially applicable in a screening setting for the early detection of colorectal neoplasms.DesignWe conducted a systematic literature search in PubMed and Web of Science and searched for biomarkers for the early detection of colorectal neoplasms in easy-to-collect human bio-fluids. Information on study design and performance characteristics for diagnostic accuracy was extracted.ResultsFinally, we included 41 studies in our analysis investigating biomarkers in different bio-fluids (blood, urine, and feces). Although single metabolites mostly had limited ability to distinguish people with and without colorectal neoplasms, promising results were reported for metabolite panels, especially amino acid panels in blood samples, as well as nucleosides in urine samples in several studies. However, validation of the results is limited.ConclusionsPanels of metabolites consisting of amino acids in blood and nucleosides in urinary samples might be useful biomarkers for early detection of advanced colorectal neoplasms. However, to make metabolomic biomarkers clinically applicable, future research in larger studies and external validation of the results is required.
| S-EPMC6116151 | biostudies-literature
Project description:: Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which is crucial the discovery of effective diagnostic biomarkers. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into 3 experimental groups – healthy controls (Controls), Latent TB infection (LTBI) and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between Controls and TB patients. The AUC, specificity and sensitivity, determined by ROC statistical analysis of the model composed by four of these proteins considering both proteomic sets, were 0.96; 93% and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes, were submitted to ROC analysis. An AUC=1 was determined with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling 1 protein and 4 metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature has correctly assigned the 12 controls and 12 patients used only for prediction (AUC=1, specificity=100% and sensitivity=100%). This multi-omics approach has revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.
2023-03-11 | PXD037341 | Pride
Project description:Interventions: Gold Standard:Clinical outcome;Index test:Study on endogenous biomarkers by targeted metabonomics
Primary outcome(s): SEN, SPE, ACC, AUC of ROC, PPV, NPV
Study Design: Sequential
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Project description:Interventions: Gold Standard:Histology diagnosis;Index test:levels of vitamin D metabolites, bile acids and exosomes in serum; the compositions of the gut microbiome
Primary outcome(s): Vitamin D;Gut microbiome;Bile acid;Exosomes
Study Design: Diagnostic test: case-control
| 2681323 | ecrin-mdr-crc
Project description:Background: The present study was aimed to investigate the expression profile of long non-coding RNAs (lncRNAs) and its potential as biomarker for pancreaticobiliary maljunction (PBM). Methods: The differential expression of lncRNA and messenger RNA (mRNA) from 15 pediatric patients with PBM and 15 control subjects were analyzed with microArray and validated with quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Gene Ontology enrichment and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were used to investigate the biological functions of these genes. The area under curve (AUC) of receiver operating characteristic (ROC) curve was used to predict the biomarker of lncRNA in PBM. Results: There were 2915 mRNAs and 173 lncRNAs upregulated, 2121 mRNAs and 316 lncRNAs downregulated in PBM cases, respectively. The enriched GO associated with differentially expressed mRNA were extracellular matrix, extracellular region and kinetochore. The most enriched pathway of Protein digestion and absorption was associated with cancer and PI3K-Akt signaling. Cis- and Trans-target gene analysis indicated that mRNAs were predicted to be regulated by one lncRNA and one mRNA corresponded to several lncRNAs. The results showed that the expression trends of NR_110876, NR_132344, XR_946886 and XR_002956345 were consistent with the microarray results, and the difference was statistically significant NR_132344, XR_946886 and XR_002956345 (P < 0.05).The AUC of ROC curve was significant only for XR_946886 (0.837, P<0.001). Conclusion: The present study indicated that lncRNAs were involved the pathogenesis of common bile duct in PBM and XR_946886 would be biomarkers for PMB.
2021-09-02 | GSE183166 | GEO
Project description:Interventions: Gold Standard:Clinical outcome;Index test:multi-parameter combination model
Primary outcome(s): SEN, SPE, ACC, AUC of ROC
Study Design: Sequential
| 2689837 | ecrin-mdr-crc
Project description:Twenty metabolites across 6 studies, with 6 groups of experimental subjects
2008-06-21 | E-TABM-289 | biostudies-arrayexpress
Project description:Interventions: Gold Standard:Boston bowel preparation score;Index test:The diagnostic model was established by convolution neural network, and the sensitivity and specificity of the diagnosis model (modeling group) were evaluated. The accuracy of the model was comprehensively evaluated by ROC curve. The accuracy of the model was further evaluated by external validation of independent 
Primary outcome(s): rate of sufficient bowel preparation
Study Design: Sequential
| 2700500 | ecrin-mdr-crc
Project description:Background: Circular RNA (circRNA) has been reported to be involved in the pathogenesis of cardiovascular disease (CVD), however, it is unclear whether circRNA carried by exosomes (exos) can be used as biomarkers for chronic coronary syndrome (CCS). This study aimed to investigate the expression pattern of exosomal circRNAs in the plasma of CCS patients, and to screen exo-circRNAs that can act as biomarkers for the diagnosis of CCS. Methods: High-throughput sequencing technology was carried out in the plasma exosomal RNA of 15 CCS patients and 15 non-cardiac chest pain patients (NCCP, control group) (sequencing cohort) to screen for differentially expressed circRNAs. Selected differentially expressed exo-circRNAs were further verified by real time polymerase chain reaction (RT-PCR) in a small-sample cohort (derivation cohort) and a large-sample cohort (validation cohort). Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic value of exo-circRNAs for CCS patients. Results: By high-throughput sequencing of circRNAs in 15 CCS patients and 15 NCCP patients, 276 circRNAs differentially expressed in plasma exosomes of CCS patients were screened by using |log2(Fold change) |>1 and q-value<0.001, and 103 were up-regulated and 173 were down-regulated. Among the 103 up-regulated circRNAs, 5 circRNAs with high expression levels and significantly increased in plasma exosomes of CCS patients were selected for validation. Twice RT-PCR validation demonstrated that exo-hsa_circ_0075269 and exo-hsa_circ_0000284 were significantly up-regulated in patients with CCS (P<0.001). Circulating exo-hsa_circ_0075269 and exo-hsa_circ_0000284 yielded the area under the curve (AUC) values of 0.761 (P<0.001, 95%CI=0.669, 0.852) and 0.623 (P=0.015, 95%CI=0.522, 0.724) for CCS, respectively by ROC curve analysis. Moreover, AUC of hsa_circ_0075269 combined with hsa_circ_0000284 for diagnosing CCS was 0.741 (P<0.001, 95%CI=0.667, 0.850). Conclusion: The expression profile of circRNA in plasma exosomes of patients with CCS was significantly different from that of the control group. Plasma exo-hsa_circ_0075269 and exo-hsa_circ_0000284 have the potential to be new biomarkers for CCS diagnosis.
2023-11-09 | GSE237983 | GEO