A Noninvasive and Screening miRNA Signature for Gastrointestinal Cancer
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 1,000
- 试验地点
- 1
- 主要终点
- Diagnostic Accuracy of miRNA Panel
研究概览
简要总结
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.
详细描述
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Adults aged 18 years or older at the time of blood sample collection.
- •Patients with a confirmed diagnosis of one of the following gastrointestinal cancers: Hepatocellular carcinoma (HCC), Cholangiocarcinoma (CCA), Pancreatic ductal adenocarcinoma (PDAC), Esophageal squamous cell carcinoma (ESCC), Gastric cancer (GC), Colorectal cancer (CRC), Non-cancer control participants, including healthy volunteers or patients with benign gastrointestinal conditions.
- •Availability of retrospective blood samples collected according to institutional protocols.
- •Willingness to allow use of de-identified clinical and demographic data for research purposes.
排除标准
- •other active malignancies; insufficient sample quality/volume; recent chemotherapy/radiotherapy/surgery; any condition preventing reliable participation.
研究组 & 干预措施
Hepatocellular Carcinoma cohort
Patients diagnosed with hepatocellular carcinoma (HCC) confirmed by clinical, imaging, and/or histopathological criteria. Blood samples collected retrospectively from multiple international centers.
Cholangiocarcinoma cohort
Patients diagnosed with cholangiocarcinoma (CCA), including intrahepatic and extrahepatic subtypes, confirmed clinically and/or histopathologically. Blood samples collected retrospectively from multiple international centers.
Pancreatic Ductal Adenocarcinoma cohort
Patients diagnosed with pancreatic ductal adenocarcinoma (PDAC), confirmed by standard diagnostic criteria. Samples collected from multiple international centers.
Esophageal Squamous Cell Carcinoma cohort
Patients diagnosed with esophageal squamous cell carcinoma (ESCC). Blood samples collected retrospectively from international collaborating centers.
Gastric Cancer cohort
Patients diagnosed with gastric cancer (GC), confirmed clinically and/or histopathologically. Samples collected from multiple international centers.
Colorectal Cancer cohort
Patients diagnosed with colorectal cancer (CRC), confirmed by standard diagnostic methods. Blood samples collected retrospectively from multiple international centers.
Non-cancer / Healthy control group
Non-cancer individuals, including healthy volunteers and patients with benign gastrointestinal conditions. Blood samples collected from international centers and matched for age and sex where possible.
结局指标
主要结局
Diagnostic Accuracy of miRNA Panel
时间窗: At baseline (pre-treatment blood sample).
Sensitivity, specificity, and area under the receiver operating characteristic curve (AUROC) for distinguishing GI cancer patients from non-cancer controls.
次要结局
未报告次要终点