Development and Validation fo an Exosome-Based and Machine Learning Powered Liquid Biopsy for the Detection of Early-Onset Colorectal Cancer
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 400
- 试验地点
- 13
- 主要终点
- Sensitivity
研究概览
简要总结
Colorectal cancer (CRC) once predominantly affected older individuals, but in recent years has witnessed a progressive increase in incidence among young adults. Once rare, early-onset colorectal cancer (EOCRC, that is, a CRC diagnosed before the age of 50) now constitutes 10-15% of all newly diagnosed CRC cases and it stands as the first cause of cancer-related death in young men and the second for young women.
This study aims to detect EOCRC with a non-invasive test, using a blood-based molecular assay based on microRNA (ribonucleic acid)
详细描述
The rising incidence of early-onset colorectal cancer (EOCRC) is a pressing clinical issue unique to our times, and it is expected to grow with an anticipated further 90% increase in incidence by the decade's end. Challenges persist even after reducing the CRC screening age to 45: under-45s lack routine screening and compliance in the 45-50 age group remains low, partly due to invasiveness and discomfort of standard screening methods. Urgent action is warranted to develop affordable, sensitive, and feasible screening for timely detection and improved participation. A non-invasive, patient-friendly screening test, like a blood-based assay, could address these epidemiological concerns and also attract underserved populations.
This study involves the development and validation of a liquid biopsy, assessing circulating cell-free and exosomal microRNAs (cf-miRNA and exo-miRNA, respectively) for indirect sampling of tumor tissue in the bloodstream. The researchers intend to harness machine learning and bioinformatics to create an integrated panel (with both cf-miRNAs and exo-miRNAs) to enhance the inherently high sensitivity of cf-miRNAs with the distinctive specificity of exo-miRNAs. This combined approach will not only improve the performance of a diagnostic model but will also tap into the diverse tumor biology aspects of EOCRC.
The study's core goal is to develop cost-efficient, non-invasive, clinic-friendly biomarkers with high sensitivity and specificity, aiding EOCRC detection.
The researchers intend to do so in three phases:
- To perform comprehensive small RNA-Seq from matched cf-miRNA, exo-miRNA, cancer-derived miRNA, and mucosa-derived miRNA.
- To develop and train two miRNA detection panels (cf-miRNA and exo-miRNA, respectively) based on advanced machine-learning models and, then, combine these two using several machine-learning models to obtain a final detection biomarker.
- To validate the findings in an independent cohort of EOCRC and controls.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Retrospective
入排标准
- 年龄范围
- 18 Years 至 50 Years（Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- •Stage I, II, III, IV colorectal cancer (TNM classification, 8th edition) diagnosed before the age of 50 (EOCRC cases)
- •Received standard diagnostic and staging procedures as per local guidelines, and at least one sample was drawn before receiving any curative-intent treatment
- •Colonoscopy-proven cancer-free status at the time of study inclusion (Non-disease controls)
排除标准
- •Hereditary colorectal cancer syndromes (identified through genetic testing)
- •Inflammatory bowel diseases
- •Lack of written informed consent
研究组 & 干预措施
Non-disease controls (Training cohort)
Individuals free from colorectal cancer, younger than 50 years of age
干预措施: ENCODE (Diagnostic Test)
Early onset colorectal cancer (Validation cohort)
Colorectal cancer diagnosed before the age of 50
干预措施: ENCODE (Diagnostic Test)
Early onset colorectal cancer (Training cohort)
Colorectal cancer diagnosed before the age of 50
干预措施: ENCODE (Diagnostic Test)
Non-disease controls (Validation cohort)
Individuals free from colorectal cancer, younger than 50 years of age
干预措施: ENCODE (Diagnostic Test)
结局指标
主要结局
Sensitivity
时间窗: Through study completion, an average of 1 year
True Positive Rate: the probability of a positive test result, conditioned on the individual truly being positive
次要结局
- Specificity(Through study completion, an average of 1 year)
- Proportion of correct predictions (true positives and true negatives) among the total cases (i.e., accuracy)(Through study completion, an average of 1 year)