A novel urinary microRNA biomarker panel for detecting gastric cancer
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ABSTRACT:
PROVIDER: PRJNA528633 | ENA |
REPOSITORIES: ENA
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Project description:Purpose: Gastric cancer (GC) is one of the most common causes of cancer deaths worldwide; however, reliable and non-invasive screening methods for GC are not established. Therefore, we conducted this study to develop a biomarker for GC detection, consisting of urinary microRNAs (miRNAs). Experimental Design: We matched 306 participants by age and sex (153 pairs consisting of patients with GC and healthy controls [HCs]), then randomly divided them across three groups: (1) the discovery cohort (4 pairs); (2) the training cohort (95 pairs); (3) the validation cohort (54 pairs). Moreover, 64 participants (32 pairs) with serum samples were also enrolled in the serum cohort. Result: There were 22 urinary miRNAs with significantly aberrant expressions between the two groups in the discovery cohort. Upon multivariate analysis of the training cohort, urinary expression levels of miR-6807-5p and miR-6856-5p were significantly independent biomarkers for diagnosis of GC, in addition to Helicobacter pylori (H. pylori) status. A diagnostic panel that combined the aberrant miRNAs and H. pylori status distinguished between HC and GC samples with an area under the curve (AUC) = 0.736. In the validation cohort, urinary miR-6807-5p and miR-6856-5p showed significantly higher expression levels in the GC group, and the combination biomarker panel of miR-6807-5p, miR-6856-5p, and H. pylori status also showed excellent performance (AUC = 0.885). In addition, serum levels of miR-6807-5p and miR-6856-5p were significantly higher in the GC group. Conclusion: This novel biomarker panel enables early and non-invasive detection of GC.
2019-12-22 | GSE128720 | GEO
Project description:By comparing urinary microRNA expression in representative cases of pancreatic and gastric cancer with that in healthy individuals, we were able to extract candidate biomarkers.
2024-04-01 | GSE244347 | GEO
Project description:Development of a two-circular RNA panel as potential prognostic biomarker for gastric cancer
| PRJNA753325 | ENA
Project description:Exploring the usefulness of urinary microRNA as a biomarker in pancreatic cancer and gastric cancer patients.
| PRJNA1022445 | ENA
Project description:Although blood-based protein biomarkers have been described for diagnosis of some cancers, detection of tumor-derived peptides/proteins in urine provides an attractive and non-invasive alternative for diagnostic or screening purposes. For instance, bladder tumor antigen (BTA) assay is FDA approved urine-based biomarker assay to detect the bladder cancer. In this study, we decided to investigate the possibility of discovering proteins as biomarkers in urine from individuals diagnosed with gastric cancer. We carried out comprehensive quantitative profiling of urine samples using tandem mass tags (TMT)-based multiplexed mass spectrometry approach. Of the 1,504 total number of proteins identified, 246 proteins were differentially expressed in a gastric cancer cohort. Ephrin A1 (EFNA1), pepsinogen A3 (PGA3) and vitronectin (VTN) were among the upregulated proteins which are known to play crucial role in the progression of gastric cancer. Notably, our analysis also revealed other overexpressed proteins including shisa family member 5 (SHISA5), mucin like 1 (MUCL1) and leukocyte cell derived chemotaxin 2 (LECT2), which had not previously been linked to gastric cancer. We decided to deploy a recently developed targeted method, SureQuant, for validating a subset of potential proteins discovered in this study. We confirmed the overexpression of EFNA1, VTN and SORT1 in an independent set of urine samples. Our study demonstrates the potential of urinary proteomics to identify promising diagnostic biomarkers of cancers in a non-invasive fashion.
2024-08-10 | PXD040956 | Pride
Project description:Exercise could stimulate the release of exosomes into the circulation, transferring signals between the cells. Exosomes are also found in urine, which is an emerging biomarker of several diseases. However, the characteristics of urinary exosomes and their contents after exercise remain poorly understood. We used microarrays to identify the alteration of gene expression in urinary exosomes after exercise bout.
2022-01-09 | GSE193186 | GEO
Project description:This large-scale study focused on the discovery on urinary biomarker for ovarian cyst.
2017-04-01 | MSV000080874 | MassIVE
Project description:This large-scale study focused on the discovery on urinary biomarker for ovarian cyst.
2015-07-30 | PXD002549 | Pride
Project description:Background: Gastric cancer (GC) is often associated with a poor prognosis, due to its asymptomatic early stages. The current gold standard for diagnosing GC, upper endoscopy, is invasive and has limited sensitivity for detecting gastric preneoplasia such as dysplasia. Non-invasive biomarkers, such as circulating proteins in the blood, hold promise for the early detection of asymptomatic gastric lesions. Methods: During an exploratory study, plasma samples from 39 participants, including patients diagnosed with different gastric pathologies (gastritis, preneoplasia, GC) and healthy controls, were analyzed using mass spectrometry-based proteomics. Differentially abundant proteins were identified through pairwise comparisons and sparse Partial Least Squares Discriminant Analysis (sparse PLS-DA). Fifteen candidate proteins were selected and quantified by ELISA in plasma samples from the full cohort of 138 participants. Results: Proteomic profiling identified 691 proteins in plasma samples. Pairwise comparisons highlighted up to 213 candidate biomarkers distinguishing cancer patients from healthy controls, while distinguishing gastritis and preneoplasia proved challenging due to their similar proteomes. Sparse PLS-DA identified 85 proteins that distinguish all patient groups. Subsequent ELISA validation confirmed Leptin as a promising biomarker for detecting gastric preneoplasia, particularly in women. Nine additional proteins (ATAD3B, IGFALS, JUP, LBP, MAN2A1, ARG1, CA2, HPT, KRT14) showed differential plasma levels across patients groups, influenced by age and gender. Multi-biomarker prediction models that incorporated factors such as age, gender, and H. pylori status, outperformed single-protein models. Using 4-fold cross-validation repeated 10 times, the best-performing models achieved high predictive accuracy, with mean AUROC=85.3% for classifications cancer vs. non-cancer and 83.9% for cancer/preneoplasia vs. healthy/gastritis. On the full cohort, the best biomarker combinations reached AUROC values exceeding 94% for these classifications. Conclusions: This study introduces a novel, non-invasive approach for predicting GC based on plasma protein concentrations across a broad spectrum of gastric pathologies. Predictive models, validated through robust cross-validation, demonstrated high accuracy using a limited panel of biomarkers. By relying on simple blood sampling, this strategy holds promise for high-risk gastric mucosal lesions, including at asymptomatic stages. Such an approach could significantly improve early detection and clinical management of GC, offering direct benefit for patients outcomes.
2025-11-10 | PXD062318 | Pride
Project description:BackgroundWith the goal of discovering non-invasive biomarkers for early diagnosis of GC, we conducted a case-control study utilising urine samples from individuals with predominantly early GC vs. healthy control (HC).MethodsAmong urine samples from 372 patients, age- and sex-matched 282 patients were randomly divided into three groups: 18 patients in a discovery cohort; 176 patients in a training cohort and 88 patients in a validation cohort.ResultsAmong urinary proteins identified in the comprehensive quantitative proteomics analysis, urinary levels of TFF1 (uTFF1) and ADAM12 (uADAM12) were significantly independent diagnostic biomarkers for GC, in addition to Helicobacter pylori status. A urinary biomarker panel combining uTFF1, uADAM12 and H. pylori significantly distinguished between HC and GC patients in both training and validation cohorts. On the analysis for sex-specific biomarkers, this combination panel demonstrated a good AUC of 0.858 for male GC, whereas another combination panel of uTFF1, uBARD1 and H. pylori also provided a good AUC of 0.893 for female GC. Notably, each panel could distinguish even stage I GC patients from HC patients (AUC = 0.850 for males; AUC = 0.845 for females).ConclusionsNovel urinary protein biomarker panels represent promising non-invasive biomarkers for GC, including early-stage disease.
| S-EPMC7686371 | biostudies-literature