Pancreatic Cancer
Conditions
Brief summary
The purpose of this study is to enable non-invasive early detection of pancreatic cancer in high-risk populations through the establishment of a machine learning model using plasma cell-free DNA fragmentomics. Plasma cell-free DNA from early stage pancreatic cancer patients and healthy individuals will be subjected to whole-genome sequencing. Features, such as cell-free DNA fragmentation, copy number variations and the status of KRAS gene mutation, will be assessed to generate this model.
Detailed description
The incidence of pancreatic cancer is insidious. Most patients were in advanced stage when diagnosed and could not be cured by surgery. Early diagnosis of pancreatic cancer through screening is so important. Early screening detection projects derived from liquid biopsy technology are not only limited to circulating DNA methylation markers, but have developed into multi-dimensional indicators for joint evaluation. This large-scale early detection study will randomly enroll 260 stage I/II/III pancreatic patients, 80 patients with pancreatic benign diseases and 156 age- and sex-matched healthy individuals upon providing written informed consent. Plasma samples will be collected and extracted cell-free DNA will be subjected to whole genome sequencing. We aimed to incorporate genome-wide copy number variations, cell-free DNA fragmentomics, and status of KRAS gene mutation into the development of a multimodal biomarker-based prediction model.
Interventions
OTHERNo intervention
No intervention
Sponsors
Tianjin Medical University Cancer Institute and Hospital
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 75 Years
Healthy volunteers
Yes
Inclusion criteria
* Age minimum 18 years * Participants must have histologically and/or cytologically confirmed stage I/II/III pancreatic cancer * Full access to the patients' clinical and pathological records * Ability to understand and the willingness to sign a written informed consent document * Non-cancer controls are sex- and age-matched individuals without presence of any tumors or nodules or any other severe chronic diseases through systematic screening
Exclusion criteria
* Participants must not be pregnant or breastfeeding * Participants must not have prior cancer histories or a second non-pancreatic malignancy * Participants must not have had any form of cancer treatment before enrollment or plasma collection, including surgery, chemotherapy, radiotherapy, targeted therapy and immunotherapy * Participants must not present medical conditions of fever or have acute or immunological diseases that required treatment 14 days before plasma collection * Participants who underwent organ transplant or allogenic bone marrow or hematopoietic stem cell transplantation * Participants with clinically important abnormalities or conditions unsuitable for blood collection * Any uncontrolled intercurrent illness including, but not limited to, ongoing or active infection, symptomatic congestive heart failure, unstable angina pectoris, cardiac arrhythmia, myocardial infarction, major seizure disorder, unstable spinal cord compression, superior vena cava syndrome, or psychiatric illness/social situations that would limit compliance with study requirements or influence patient signing the written informed consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Area under curve of the model for detecting stage I/II/III pancreatic cancer | 2 years | The area under curve of the model for the ultrasensitive early detection of stage I/II/III pancreatic cancer would be evaluate |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Sensitivity of the early detection modell | 2 years | The sensitivity of the model for the ultrasensitive early detection of stage I/II/III pancreatic cancer would be evaluate |
| Specificity of the early detection model | 2 years | The specificity of the model for the ultrasensitive early detection of stage I/II/III pancreatic cancer would be evaluate |
Countries
China
Contacts
Primary ContactGao Chuntao, MD
Outcome results
None listed