Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths globally, with increasing incidence rates. While predominantly affecting older adults, CRC cases among individuals under 50 (early-onset CRC, or EoCRC) are rising. This age group rarely undergoes routine screening, resulting in delayed diagnoses and more advanced disease at presentation. In the USA, EoCRC accounts for 10% of CRC cases and is the leading cause of cancer-related deaths in men under 50. Despite the increase in EoCRC incidence, the causes remain unclear. Only 25% of cases have a CRC family history, suggesting environmental factors. Diets low in fibre and rich in fat and red meat, obesity, alcohol consumption, sedentary lifestyle, stress, and chronic inflammation of the GI tract are estimated to account for 70-90% of CRC risk. According to the World Cancer Research Fund, 47% of all CRC cases could be prevented through lifestyle changes, particularly in diet and physical activity. These lifestyle factors are also strongly linked to changes in the gut microbiome, which differs markedly between CRC patients and healthy individuals. The microbiome may influence tumour development by producing metabolites that regulate immune responses or create anti-tumour environments. Thus, the gut microbiome is a promising target for early CRC detection and prevention. This study aims to develop a non-invasive, microbiome-based diagnostic tool for CRC, identifying biomarkers to improve early detection, personalise treatment, and reduce healthcare costs.
This study focuses on identifying faecal microbiome biomarkers for CRC across different stages, prognoses, and therapeutic responses, with a particular emphasis on EoCRC. Recruitment will include individuals recently diagnosed with CRC who have not undergone treatment. Faecal samples will be collected at three key time points: Baseline - At diagnosis and study entry. Post-Treatment - After completing each therapeutic regimen, such as neoadjuvant chemotherapy, surgery and/or adjuvant chemotherapy Follow-Up - Three years after diagnosis. The study will also monitor survival rates and disease progression over three years. Primary Objective: To identify and characterise changes in the gut microbiome at different CRC stages. Secondary Objectives: i. Identify faecal microbiome biomarkers associated with CRC overall and stratify findings by age and sex. ii. Compare microbiome profiles and associated clinical and lifestyle data between CRC patients and healthy controls, stratified by age and sex. iii. Identify lifestyle and dietary factors contributing to CRC risk, stratified by age and sex. iv. Validate biomarkers specific to EoCRC. v. Correlate microbiota composition with overall survival. vi. Correlate microbiota composition with disease-free survival. This is a longitudinal observational study targeting individuals aged 40-74 who have been newly diagnosed with CRC and are treatment-naïve Patients with all inclusion criteria and none of the exclusion criteria (detailed in the specific section of this website) will be considered for this study. Using a significance level of 5% and a power of 80%, the required sample size is 80 individuals per age group (40-49, 50-59, 60-64, 65-69, and 70-74 years). This results in a total of 400 participants. A control group of healthy individuals will be recruited from hospital patients undergoing routine screening colonoscopies. Biological and clinical data will be collected at multiple time points throughout the study. Faecal samples will be obtained at baseline, post-treatment, and during the three-year follow-up, accompanied by blood sample collection at each of these time points. Clinical data will include detailed tumour characteristics, such as location, symptoms, and staging, as well as treatment information, including surgery and chemotherapy. Outcomes related to survival and disease progression will also be recorded. Lifestyle and dietary data will be gathered through self-reported questionnaires capturing demographic factors such as age, smoking habits, physical activity, stress levels, and body mass index (BMI). Dietary habits and adherence to the Mediterranean diet will be assessed via telephone interviews. The gut microbiome will be profiled using shotgun metagenomic sequencing, enabling the characterisation of microbial species and functional pathways. This analysis will identify potential correlations between microbiome composition and clinical outcomes, including therapeutic responses and survival rates. For statistical testing, qualitative variables will be analysed using Chi-square or Fisher's exact tests, while quantitative variables will be assessed using Student's t-test or ANOVA. If the normality assumption is not met, Mann-Whitney or Kruskal-Wallis tests will be used. All statistical analyses will be two-sided, with a significance level set at 5%. Expected Outcomes: The study aims to identify biomarkers that enable early, non-invasive CRC detection. Findings will also provide insights into the interplay between lifestyle, diet, and microbiome changes in CRC progression. These insights could lead to personalised preventive strategies and improved therapeutic outcomes.
Study Type
OBSERVATIONAL
Enrollment
400
No intervention: observational study
Gulbenkian Institute for Molecular Medicine
Lisbon, Portugal
Microbiome biomarkers associated with CRC.
The faecal microbiome's composition and gene profiles will be analysed using shotgun metagenomic sequencing. Data will be integrated with lifestyle and dietary factors to identify biomarkers linked to CRC stages.
Time frame: Baseline and Follow-up up to 3 years
Microbiome biomarkers associated with EoCRC.
Similar analysis as Outcome number 1, focused specifically on early-onset CRC cases.
Time frame: Baseline and Follow-up up to 3 years
Correlation between microbiome biomarkers and overall survival and disease-free survival.
Biomarkers will be correlated with clinical follow-up data, including overall survival (survivors vs non-survivors) and disease-free progression (relapse vs no relapse).
Time frame: 3 years
Effect of diet on CRC risk and gut microbiota composition
Dietary intake will be assessed via telephone interviews using two 24-hour dietary recalls. These follow protocols validated by the European Food Safety Authority (EFSA) and the Portuguese National Food and Physical Activity Survey (IAN-AF).
Time frame: Baseline
Effect of the Mediterranean Diet (MD) on CRC risk and gut microbiota composition
Adherence to the MD will be assessed with the PREvención con DIeta MEDiterránea (PREDIMED) questionnaire, a validated 14-item tool. Scores (0-14) will categorise adherence as low (\<5), moderate (6-9), or high (\>10).
Time frame: Baseline
Effect of physical activity on CRC risk and gut microbiota composition
Physical activity will be assessed using the Nordic Physical Activity Questionnaire-Short (NAPQ-short) form, which evaluates adherence to WHO physical activity recommendations.
Time frame: Baseline
Effect of sleeping habits on CRC risk and gut microbiota composition
Sleeping habits will be assessed by the Pittsburgh Sleep Quality Index, a validated questionnaire that consists of 19 items which are distributed into seven "components": subjective sleep quality; sleep latency; sleep duration; habitual sleep efficiency; sleep disturbances; use of sleeping medication; day-time dysfunction. Each component is scored from 0 to 2, and the sum of the component scores yields a global PSQI score. A global PSQI score of ≥6 will indicate poor sleep quality.
Time frame: Baseline
Effect of stress levels on CRC risk and gut microbiota composition
Stress levels will be evaluated using the Perceived Stress Scale (PSS), a validated 10-item tool. Scores range from 0-40, categorised as low (0-13), moderate (14-26), or high (27-40).
Time frame: Baseline
Identify and quantity inflammation markers
Blood samples will be collected in K2EDTA tubes and processed for plasma separation. Inflammatory markers, including C-reactive protein and cytokines (e.g., IL-1β, IL-6, TNF-α), will be quantified using ELISA.
Time frame: Baseline and Follow-up up to 3 years
Differential gene expression in tumour samples
For participants undergoing surgery, tumour samples will be collected, preserved, and processed for transcriptomic analysis. RNA extraction will be performed to assess gene expression profiles, with a particular focus on microsatellite instability (MSI) and tumour microenvironment interactions.
Time frame: Baseline
This platform is for informational purposes only and does not constitute medical advice. Always consult a qualified healthcare professional.