ABSTRACT: Background and study aims
Colorectal cancer is the third most common cancer in men and the second in women, accounting for 10% of all cancers worldwide. It ranks second in terms of cancer-related deaths, just behind lung cancer. In certain European member states, a home-based screening test searching for occult blood in a stool sample has been in operation in recent years for people aged 50 years and over. Although this method is simple to perform, it only detects the already symptomatic stage of the disease. Therefore, although more invasive, colonoscopy remains the most reliable method of screening for colorectal cancer, as it enables polyps and other lesions to be visualized and removed using an endoscope with a camera. The risk of colorectal cancer following colonoscopy has been shown to be reduced by 70-90%. Early detection and removal of a pre-cancerous polyp prevents its progression to a tumor. In this way, colonoscopy saves many lives. Nevertheless, although colorectal cancer is now considered an easily preventable disease thanks to screening, long waiting and preparation times for colonoscopy prevent the implementation of large-scale screening for systematic surveillance and follow-up. Since the 1990s, there has been a gradual increase in the rate of colorectal cancer in adults under the age of 50. Although the reasons for this are still unknown, it has been suggested that environmental and behavioral changes influencing the microbiome (gut bacteria) are at the root of colorectal cancer in people under 50. The need to develop a large-scale, inexpensive, and non-invasive method of early detection of colorectal cancer is therefore urgent.
This study aims to develop a routine blood test accessible to all ages in order to identify people who would not otherwise be screened according to current European or national guidelines. The previous part of the DIOPTRA project would have identified in around 200 participants a protein group whose quantity varies during a precancerous stage of colon cancer. By quantifying this group of proteins, this blood test will be able to identify those citizens who absolutely should undergo further screening by colonoscopy. To validate this method, participants are invited to give a blood sample during their colonoscopy visit to the gastroenterology department. Once validated, this blood test has many advantages: it is almost non-invasive, inexpensive and could be well accepted by most of the population. As a result, DIOPTRA is positioning itself in the increasingly personalized medicine of the future, capable of adapting to the particularities of each individual.
Other aims:
1. In addition to an early detection method for colon cancer, numerous scientific studies have identified parameters called risk factors which could be associated with the development of colorectal cancer, and their importance is not negligible. Suggestions for daily habits can be generated from these risk factors and may be very useful in the prevention of colorectal cancer.
2. Another aim of the study is to validate some of the risk factors identified in the previous part of the project. The DIOPTRA application would be created to help collect information, offer up-to-date personalized suggestions and raise awareness of early detection of colorectal cancer.
3. The findings and the final DIOPTRA solution will be the subject of a study of healthcare performance indicators in view of widening screening eligibility thanks to an effective, minimally invasive and financially affordable method.
Who can participate?
Individuals between 18 and 80 years old who visit the clinical sites for a colonoscopy
What does the study involve?
According to each clinical site’s standards and pre-existing practice, enrolled individuals will undergo a screening colonoscopy, while blood will be collected via a minimally invasive method (before the colonoscopy) for the purposes of the study. All biological data will be used for protein-based analysis, allowing the construction of preliminary decision algorithms and AI analysis models.
