Predicting treatment response in advanced rectal cancer using multi-omics data

A Study of the Clinical Value of Dynamic Multi-omics Integration Model to Predict Neoadjuvant Therapy Response in Locally Advanced Rectal Cancer (T3-4NxM0)

This study is testing a new way to predict how well treatment will work for people with advanced rectal cancer by using different types of data from their scans and blood tests.

Quick facts

• Study type: Observational
• Enrollment: 106 (estimated)
• Ages: 18 Years to 80 Years
• Sex: All
• Sponsor: Sixth Affiliated Hospital, Sun Yat-sen University (other)
• Drugs / interventions: chemotherapy, immunotherapy, prednisone
• Locations: 1 site (Guangzhou, Guangdong)
• Trial ID: NCT06364371 on ClinicalTrials.gov

What this trial studies

This observational study aims to develop a dynamic multi-omics integration model to predict pathological complete response (pCR) in patients with locally advanced rectal cancer undergoing neoadjuvant therapy. By collecting and analyzing data from various sources, including MRI scans, histopathology slides, and molecular biomarkers like ctDNA and CEA, the study seeks to validate the predictive accuracy of this model. The goal is to determine if this multi-omics approach can outperform traditional single-modality prediction methods. Eligible patients will be prospectively enrolled, and their clinical features will be annotated throughout the treatment process.

Who should consider this trial

Good fit: Ideal candidates are individuals with histologically confirmed locally advanced rectal adenocarcinoma (T3-4NxM0) who have not undergone prior treatments.

Not a fit: Patients with a history of previous colorectal surgery, chemotherapy, radiotherapy, or biological therapy may not benefit from this study.

Why it matters

Potential benefit: If successful, this model could help identify patients who are likely to achieve a complete response to treatment, potentially allowing for a more tailored and effective management strategy.

How similar studies have performed: While the approach of integrating multi-omics data is gaining traction, this specific model's predictive capabilities in rectal cancer are novel and have not been extensively tested in prior studies.

Eligibility criteria

Inclusion Criteria:

1. Histologically confirmed rectal adenocarcinoma;
2. Clinical stage T3-4NxM0, with or without positive Mesorectum Fascia(MRF), and with or without positive Extra-Mural Venous Invasion(EMVI);
3. Preoperative staging method: All patients undergo preoperative staging with enhanced CT. Criteria for mesorectal lymph node metastasis: Short axis ≥ 10mm lymph nodes or lymph node morphology and CT characteristics consistent with typical lymph node metastasis. Preoperative chest, abdominal CT, and pelvic MRI exclude distant metastases;
4. Absence of signs of intestinal obstruction; or relief of obstruction after proximal colon diversion surgery;
5. No history of previous colorectal surgery;
6. No history of previous chemotherapy or radiotherapy;
7. No history of previous biological therapy (such as monoclonal antibodies), immunotherapy \[such as anti-programmed cell death protein 1(PD-1) antibodies, anti-PD-L1 antibodies, anti-PD-L2 antibodies, or anti-Cytotoxic T Lymphocyte-Associated Antigen-4(CTLA-4)\], or other investigational drug therapy;
8. No history of previous hormonal therapy: no restrictions;
9. Signed informed consent form.

Exclusion Criteria:

1. Patients requiring antiarrhythmic therapy (excluding β-blockers or digoxin), symptomatic coronary artery disease, recent myocardial infarction within the past 6 months, or congestive heart failure exceeding New York Heart Association(NYHA) class II;
2. Poorly controlled severe hypertension;
3. History of HIV infection or active chronic hepatitis B or C (high viral DNA load);
4. Active pulmonary tuberculosis (TB) or receiving anti-TB treatment, or having received anti-TB treatment within the past year;
5. Other active clinically severe infections ;
6. Evidence of distant metastases outside the pelvis preoperatively;
7. Cachexia, organ decompensation;
8. History of pelvic or abdominal radiotherapy;
9. Multifocal colorectal cancer;
10. Patients requiring management for epileptic seizures (e.g., with steroids or antiepileptic therapy);
11. History of other malignant tumors within the past 5 years, excluding cured carcinoma in situ of the cervix or basal cell carcinoma of the skin;
12. Substance abuse or medical, psychological, or social conditions that may interfere with patient participation in the study or assessment of study results;
13. Presence of any active autoimmune disease or history of autoimmune disease (including but not limited to: interstitial pneumonia, uveitis, enteritis, hepatitis, pituitary inflammation, nephritis, hyperthyroidism, hypothyroidism; patients with vitiligo or childhood asthma that has completely resolved and does not require any intervention in adulthood may be included; patients with asthma requiring bronchodilators for medical intervention cannot be included);
14. Vaccination with any anti-infective vaccine (e.g., influenza vaccine, varicella vaccine, etc.) within 4 weeks before enrollment;
15. Complications requiring long-term use of immunosuppressive drugs or systemic or local administration of corticosteroids with immunosuppressive effects (dose \> 10mg/day of prednisone or equivalent corticosteroids);
16. Known or suspected allergy to the investigational drug or any medication administered related to this trial;
17. Any unstable condition or situation that may jeopardize patient safety and compliance;
18. Pregnancy or lactation in women of childbearing potential who have not taken adequate contraceptive measures;
19. Refusal to sign the informed consent form.

Where this trial is running

Guangzhou, Guangdong

• The Sixth Affiliated Hospital, Sun Yatsen University — Guangzhou, Guangdong, China (RECRUITING)

Study contacts

• Principal investigator: Jun Huang — Sun Yat-sen University
• Study coordinator: Jun Huang

Conditions: Predictive Cancer Model, Pathologic Complete Response, Magnetic resonance imaging, ctDNA, Histopathology slide, CEA