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Stomach Cancer Exosome-based Detection

Early Detection of Stomach Cancer With a Liquid Biopsy Based on Exosomal Micro-RNA

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06342427
Acronym
DESTINEX
Enrollment
809
Registered
2024-04-02
Start date
2023-03-15
Completion date
2024-06-15
Last updated
2024-07-08

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Gastric Adenocarcinoma, Gastric Cancer, Gastric Cancer in Situ, Gastric Cancer Metastatic to Liver, Gastric Cancer Metastatic to Lung, Gastric Cancer Stage, Gastric Cancer, Stage 0, Gastric Cancer Stage I, Gastric Cancer Stage IA, Gastric Cancer Stage IB, Gastric Cancer Stage II, Gastric Cancer Stage III, Gastric Cancer Stage IIIA, Gastric Cancer Stage IIIB, Gastric Cancer Stage IV, Gastric Cancer TNM Staging, Gastric Cancer TNM Staging Primary Tumor (T) T2B, Gastric Lesion, Gastric Neoplasm

Brief summary

Gastric cancer continues to have a poor prognosis primarily due to the inability to detect it in its early stages. This study will develop and validate a blood assay to facilitate the non-invasive detection of gastric cancer.

Detailed description

Gastric cancer continues to have a poor prognosis primarily due to the inability to detect it in its early stages. Because conventional endoscopy is invasive and costly, gastric cancer is currently not considered to be screenable at a population level. However, if one could find less invasive and cheaper tools that accurately detect gastric cancer in its early stages, it could make a significant difference. Accurate biomarkers could help identify patients with gastric cancer before it becomes incurable. This study aims to develop a non-invasive test to detect gastric cancer early. It consists of four phases: 1. Discovering potential biomarkers with a comprehensive and genome-wide transcriptomic sequencing analysis that will involve gastric cancer tissue, normal tissue, and serum samples from patients with gastric cancer, as well as samples from people without the disease. 2. Using machine learning to develop a combination signature of cell-free (cf) and exosomal (exo)-miRNA in serum specimens from a training cohort. 3. A validation of this signature in an independent cohort to confirm its accuracy. 4. An evaluation of the temporal trend of this signature in paired samples collected pre-surgery and post-surgery to investigate their potential and specificity as indicators of minimal residual disease. In summary, this study aims to develop a highly accurate and cost-effective blood test for detecting gastric cancer early. Success could lead to significant improvements in clinical practice by catching cancer when it is most treatable. By combining different genetic markers (cell-free microRNA and exosomal microRNA) for accuracy, this study has the potential to reduce gastric cancer deaths and could lead to new screening methods in the future.

Interventions

DIAGNOSTIC_TESTDESTINEX

A panel of microRNA, whose expression level is tested in serum samples.

Sponsors

City of Hope Medical Center
Lead SponsorOTHER

Study design

Observational model
CASE_CONTROL
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
Yes

Inclusion criteria

* Histological diagnosis of stage I, II, III, IV gastric cancer (TNM classification, 8th edition) (cases). * Received standard diagnostic and staging procedures as per local guidelines, and at least one sample was drawn before receiving any curative-intent treatment. * Confirmed cancer-free status at the time of study inclusion (Non-disease controls).

Exclusion criteria

* Lack of written informed consent. * Systemic therapy before sampling. * Synchronous gastric and non-gastric cancer diagnosed at or before surgery.

Design outcomes

Primary

MeasureTime frameDescription
SensitivityThrough study completion, an average of 1 yearTrue positive rate: the probability of a positive test result, conditioned on the individual truly being positive

Secondary

MeasureTime frameDescription
SpecificityThrough study completion, an average of 1 yearTrue negative rate: the probability of a negative test result, conditioned on the individual truly being negative
Proportion of correct predictions (true positives and true negatives) among the total cases (i.e., accuracy)Through study completion, an average of 1 yearA measure of trueness: proportion of correct predictions (both true positives and true negatives) among the total number of cases examined

Countries

Japan, United States

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026