Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA361074 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:CircRNA expression profiles for 6 human samples derived from patients with gastric cancer
| PRJNA350394 | ENA
Project description:LncRNA expression profiles for 6 human samples derived from patients with gastric cancer
| PRJNA208084 | ENA
Project description:The paper "Metabolomic Machine Learning Predictor for Diagnosis and Prognosis of Gastric Cancer" addresses the need for non-invasive diagnostic tools for gastric cancer (GC). Traditional methods like endoscopy are invasive and expensive. The authors conducted a targeted metabolomics analysis of 702 plasma samples to develop machine learning models for GC diagnosis and prognosis. The diagnostic model, using 10 metabolites, achieved a sensitivity of 0.905, outperforming conventional protein marker-based methods. The prognostic model effectively stratified patients into risk groups, surpassing traditional clinical models.
I have successfully reproduced the diagnosis model from the paper. This machine learning-based system differentiates GC patients from non-GC controls using metabolomics data from plasma samples analyzed by liquid chromatography-mass spectrometry (LC-MS). The model focuses on 10 metabolites, including succinate, uridine, lactate, and serotonin. Employing LASSO regression and a random forest classifier, the model achieved an AUROC of 0.967, with a sensitivity of 0.854 and specificity of 0.926. This model significantly outperforms traditional diagnostic methods and underscores the potential of integrating machine learning with metabolomics for early GC detection and treatment.
2024-07-23 | MODEL2407230001 | BioModels
Project description:To identify the circRNA expression profiles in HF patients’ plasma and to evaluate the potential application of circRNAs for HF diagnosis, circRNA microarrays were performed on plasma samples obtained from HF patients and healthy controls. The RNAs of the plasma from the HF and control groups were extracted for microarray analysis. The purified RNAs were hybridized to a microarray (Agilent human circRNA Array V2.0) containing 170,340 human circRNA probes. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to validate the results.
2019-07-20 | GSE134584 | GEO
Project description:circRNA expression profiles for 10 human samples derived from patients with hepatocellular carcinoma
| PRJNA370010 | ENA
Project description:Metabolic pathways-associated lncRNA expression profiles of 6 human samples derived from patients with gastric cancer
| PRJNA380115 | ENA
Project description:Background: suitable diagnostic markers for cancers are urgently required in clinical practice. Long noncoding RNAs, which have been reported in many cancer types, are a potential new class of biomarkers for tumor diagnosis. Method: LncRNA gene expression profiles were analyzed in two pairs of human gastric cancer and adjacent non-tumor tissues by microarray analysis. Nine gastric cancer-associated lncRNAs were selected and assessed by quantitative real-time polymerase chain reaction in gastric tissues, and 5 of them were further analyzed in gastric cancer patients’plasma. Results: Five lncRNAs, including AK001058, INHBA-AS1, MIR4435-2HG, UCA1 and CEBPA-AS1 were validated to be increased in gastric cancer tissues. Furthermore, we found that plasma level of these five lncRNAs were significantly higher in gastric cancer patients compared with normal controls. By receiver operating characteristic analysis, we found that the combination of plasma lncRNAs with the area under the curve up to 0.921, including AK001058, INHBA-AS1, MIR4435-2HG, and CEBPA-AS1, is a better indicator of gastric cancer than their individual levels or other lncRNA combinations. Simultaneously, we found that the expression levels of a series of MIR4435-2HG fragments are different in gastric cancer plasma samples, but most of them higher than that in healthy control plasma samples. Conclusion: Our results demonstrate that certain lncRNAs, such as AK001058, INHBA-AS1, MIR4435-2HG, and CEBPA-AS1, are enriched in human gastric cancer tissues and significantly elevated in the plasma of patients with gastric cancer. These findings indicate that the combination of these four lncRNAs might be used as diagnostic or prognostic markers for gastric cancer patients.
2017-01-12 | GSE93512 | GEO
Project description:Metastasis is a major problem of gastric cancer. In this study, small extracellular vesicle (sEV)-derived miRNAs were sequenced to screen biomarkers for GC’s organo-tropic metastasis. Plasma from 40 treatment-naïve gastric cancer patients including 10 no metastasis (M0) and 30 distant metastasis (M1) were assessed by sEV-miRNA-sequencing. sEV miRNAs with diverse expression profiles across different metastatic patterns were combined into sigantures to characterize and predict gastric cancer metastasis.
2024-06-16 | GSE178283 | GEO
Project description:This study compared the circRNA expression levels in plasma samples from patients with IH and control individuals. The circRNA expression profiles were determined using microarray in three pairs of plasma samples from patients with proliferative IH and healthy control individuals. Expression of the identified circRNAs was verified using quantitative reverse transcription polymerase chain reaction (RT-qPCR), and bioinformatic analysis was performed to predict the microRNAs targeted by the validated circRNAs. In the circRNA expression profiles in the plasma of patients with IHs, we found 128 differentially expressed circRNAs, of which 72 were upregulated and 56 were downregulated. The downregulated expression of three circRNAs (hsa_circRNA_101566, hsa_circRNA_103546, and hsa_circRNA_103573) was verified using RT-qPCR. Circular RNAs (circRNAs) are noncoding RNAs that play important roles in tumor progression. Few studies have examined the circRNAs involved in infantile hemangioma (IH) progression. This study compared the circRNA expression levels in plasma samples from patients with IH and control individuals. The circRNA expression profiles were determined using microarray in three pairs of plasma samples from patients with proliferative IH and healthy control individuals. Expression of the identified circRNAs was verified using quantitative reverse transcription polymerase chain reaction (RT-qPCR), and bioinformatic analysis was performed to predict the microRNAs targeted by the validated circRNAs. In the circRNA expression profiles in the plasma of patients with IHs, we found 128 differentially expressed circRNAs, of which 72 were upregulated and 56 were downregulated. The downregulated expression of three circRNAs (hsa_circRNA_101566, hsa_circRNA_103546, and hsa_circRNA_103573) was verified using RT-qPCR. Gene ontology term and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that all identified networks participated in angiogenesis and tumor formation and progression. We found that hsa_circRNA_101566, which can regulate the mammalian target of rapamycin signaling pathway, may be an important regulatory molecule in IH development and that targeting of hsa_miR_520c can indirectly regulate the vascular endothelial growth factor signaling pathway. Further studies are needed to clarify these effects and the underlying mechanisms.
2021-05-12 | GSE162905 | GEO
Project description:Arraystar Human circRNA Microarray is designed for the global profiling of human circRNAs. In this study, we applied a circRNA microarray to screen the potential biomarker for HCC. 20 samples extracted from plasma samples including HCC group before operation, and after operation, CH group and control group. Each group contained five samples.
2021-03-02 | E-MTAB-8799 | biostudies-arrayexpress