A Noninvasive and Screening miRNA Signature for Gastrointestinal Cancer

Phase

N/A

Condition

Esophageal Disorders

Liver Cancer

Squamous Cell Carcinoma

Treatment

N/A

Clinical Study ID

NCT07224750

23228/MiGIC

Ages > 18
All Genders
Accepts Healthy Volunteers

Study Summary

Gastrointestinal (GI) cancers remain a major global health burden, largely due to the lack of effective and accessible early screening strategies. Current diagnostic approaches-including endoscopy, computed tomography (CT), and magnetic resonance imaging (MRI)-are either invasive, resource-intensive, or insufficiently sensitive for detecting early-stage disease, and are therefore not suitable for population-wide screening or for simultaneously identifying multiple GI tumor types. As a result, many patients are diagnosed at advanced stages, when therapeutic options are limited and prognosis is poor.

Circulating microRNAs (miRNAs) offer a promising alternative, as they are stable in peripheral blood and reflect tumor-related molecular alterations. In this study, the investigators aim to develop and validate a robust, noninvasive miRNA-based signature capable of distinguishing GI cancers from non-malignant controls. By integrating multi-cohort datasets and applying machine learning-based feature selection and predictive modeling, the investigators will construct a screening panel optimized for reproducibility, scalability, and early-stage detection. This noninvasive miRNA signature has the potential to support accessible, cost-effective, and clinically practical population-level screening for GI cancers, ultimately facilitating earlier diagnosis and improving outcomes for participants.

Eligibility Criteria

Inclusion

Inclusion Criteria:

Adults aged 18 years or older at the time of blood sample collection.
Patients with a confirmed diagnosis of one of the following gastrointestinalcancers: Hepatocellular carcinoma (HCC), Cholangiocarcinoma (CCA), Pancreatic ductaladenocarcinoma (PDAC), Esophageal squamous cell carcinoma (ESCC), Gastric cancer (GC), Colorectal cancer (CRC), Non-cancer control participants, including healthyvolunteers or patients with benign gastrointestinal conditions.
Availability of retrospective blood samples collected according to institutionalprotocols.
Willingness to allow use of de-identified clinical and demographic data for researchpurposes.

Exclusion

Exclusion Criteria:

other active malignancies; insufficient sample quality/volume; recentchemotherapy/radiotherapy/surgery; any condition preventing reliable participation.

Study Design

June 21, 2024

June 18, 2026

Study Description

This study will establish a comprehensive, retrospective, international multi-center cohort consisting of peripheral blood samples from participants with major gastrointestinal cancers-including hepatocellular carcinoma (HCC), cholangiocarcinoma (CCA), pancreatic ductal adenocarcinoma (PDAC), esophageal squamous cell carcinoma (ESCC), gastric cancer (GC), and colorectal cancer (CRC)-as well as non-malignant controls. Small RNA sequencing will be performed to generate high-resolution circulating miRNA expression profiles.

During the discovery phase, the investigators will conduct rigorous preprocessing, normalization, batch effect correction, and differential expression analyses to identify circulating miRNAs associated with malignant transformation across GI cancer types. Machine learning-based feature selection (e.g., LASSO, mRMR, ensemble methods) and classifier development (e.g., SVM, Random Forest, XGBoost) will then be used to derive a minimal yet robust miRNA panel capable of optimally distinguishing cancer from non-cancer.

During the modeling and evaluation phase, the identified miRNA signature will undergo multi-center training and validation across international cohorts to ensure robustness across geographic regions, sequencing platforms, and clinical demographics. Beyond binary classification, the investigators will assess the panel's ability to discriminate among specific GI cancer subtypes, thereby supporting differential diagnosis and tumor-origin inference. Model performance will be evaluated using AUROC, sensitivity at clinically meaningful specificity thresholds, early-stage detection capability, and calibration in independent validation cohorts.

Through this sequential discovery → modeling → multi-center validation framework, the investigators aim to develop a noninvasive circulating miRNA panel that (1) accurately distinguishes cancer from non-cancer individuals and (2) differentiates among multiple gastrointestinal cancer types, thereby providing a clinically scalable solution for early cancer detection and population-level screening.

Connect with a study center

City of Hope Nat Medical Ctr
Duarte 5344147, California 5332921 91010
United States
Active - Recruiting

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