Metastatic Colorectal Cancer (CRC)
Conditions
Keywords
Metastatic Colorectal Cancer, Locally recurrent colorectal cancer
Brief summary
With high incidence and mortality rate, the effective therapeutic options of colorectal cancer remain limited. Up to 50% of patients with colorectal cancer will develop metastatic disease. Recurrent lesions can be diagnosed and characterized only when tumors have reached a certain volume by present radiologic imaging techniques such as CT and MRI. The exploration of differentiated clinical applications specifically for local recurrence versus distant metastasis remains an unmet need. The aim of this study is to explore methylation, fragmentomic, and cfRNA markers associated with local recurrence and distant metastasis of colorectal cancer by multi-omics approaches. By constructing a predictive model for the localization of post-treatment recurrence and metastasis, this study will compare the accuracy of different technical approaches in predicting the localization of recurrence and metastasis after colorectal cancer treatment.
Interventions
None listed
Sponsors
Study design
Eligibility
Inclusion criteria
* Age ≥ 18 years, male or female. * Patients with the following tumor types: primary colorectal cancer, locally recurrent colorectal cancer, colorectal cancer liver metastasis, colorectal cancer lung metastasis, colorectal cancer peritoneal metastasis, colorectal cancer bone metastasis, colorectal cancer multi-organ metastasis, primary liver cancer, primary lung cancer, primary peritoneal cancer, primary bone tumor. * No prior surgery or anti-tumor treatment at the time of enrollment assessment. * Subjects voluntarily participate in this study and sign the informed consent form.
Exclusion criteria
* Previous history of malignant tumors other than those within the inclusion criteria. * Pregnant or breastfeeding women.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Area Under the Receiver Operating Characteristic Curve (AUC) of the prediction models based on methylation, fragmentomics, and cfRNA data for local recurrence and distant metastasis localization in colorectal cancer | At baseline (at the time of study enrollment, prior to any surgical or anti-tumor treatment) | The AUC is calculated from the Receiver Operating Characteristic (ROC) curve to evaluate the discriminatory performance of the prediction model developed by use of methylation, fragmentomics, and cfRNA data. Model performance will be assessed on the validation cohort. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of the prediction models based on methylation, fragmentomics, and cfRNA data for colorectal cancer recurrence and metastasis localization | Baseline (at enrollment) | Accuracy is defined as the proportion of correctly predicted samples (true positives + true negatives) among the total number of samples in the validation cohort. |
| Sensitivity and specificity of individual omics technologies (methylation, fragmentomics, and cfRNA) | Baseline (at enrollment) | Comparison of predictive performance of three individual technical approaches for localization of recurrent and metastatic lesions. |