Clinical trial · Observational
Exploring the Predictive Effect of Intestinal and Oral Microbiota on the Efficacy of Neoadjuvant Radiotherapy and Chemotherapy for Locally Advanced Rectal Cancer Based on Machine Learning
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
This study is a one-year, observational, prospective cohort study. For enrolled patients with newly diagnosed locally advanced rectal cancer, the treatment plan will be decided by the physician based on the 2022 NCCN Rectal Cancer Clinical Practice Guidelines in combination with the hospital's protocols. The researchers will review the patient's medical history and laboratory reports, along with imaging examinations, to determine the patient's eligibility based on the inclusion and exclusion criteria. Before data collection, patients must sign the most recent IRB/IEC-approved informed consent form (ICF). After being diagnosed with locally advanced MSS rectal cancer, patients will provide stool and saliva samples upon admission before receiving treatment. Metagenomic sequencing will be performed to determine the abundance of gut and oral microbiota. Using these data, a predictive model will be established using machine learning methods to predict the TRG (Tumor Regression Grade) after neoadjuvant chemoradiotherapy in the enrolled patients, with internal validation conducted.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Rectal Cancer | Malignant Rectal Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (2)
- label
- responder
- description
- good response to neoadjuvant chemoradiotherapy
- label
- non-responders
- description
- bad response to neoadjuvant chemoradiotherapy
Primary outcomes (1)
- measure
- Tumor Pathological Response Grading (TRG Grading)
- timeFrame
- an average of 3 months after neoadjuvant radiotherapy and chemotherapy
- description
- Tumor Pathological Response Grading (TRG Grading) of Patients after Neoadjuvant Radiotherapy and Chemotherapy
Secondary outcomes (2)
- measure
- Pathological Complete Response Rate (pCR)
- timeFrame
- an average of 3 months after neoadjuvant radiotherapy and chemotherapy
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
- Maximum age
- 75 Years
Show eligibility criteria text
Inclusion Criteria: 1. Voluntary signing of informed consent form 2. Age range: 18-75 years old 3. Diagnosed by histopathological examination and indicated by comprehensive evaluation for neoadjuvant radiotherapy and chemotherapy in locally advanced rectal cancer patients 4. Immunohistochemistry or genetic testing for MSS 5. Imaging shows no distant metastatic lesions 6. ECOG score 0-1 7. All patients are required to complete neoadjuvant concurrent chemoradiotherapy and intraoperative chemotherapy at our center, and return to the hospital on schedule for preoperative evaluation and tumor resection surgery 8. After inspection and evaluation, there is normal bone marrow hematopoiesis, liver and kidney function Exclusion Criteria: 1. Previously received anti-tumor treatment 2. History of other malignant tumors 3. Imaging confirms the presence of distant metastases 4. Patients with MSI-H or dMMR rectal cancer detected by immunohistochemistry or genetic testing 5. Used probiotics, antibiotics, prebiotics, immunosuppressants, and glucocorticoids within the 4 weeks 6. Pathological tissue specimens without assessable efficacy of neoadjuvant therapy 7. Change treatment plan due to disease progression or severe treatment side effects 8. According to the researcher's judgment, it is not suitable to participate in this study
References
Publications (1)
- Source
- PubMed (NLM)
- Dataset
- PubMed E-utilities
- Retrieved
- Sep 15, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
Yajing Wen, Ziqian Luo, Zhemin Li et al. · Funct Integr Genomics · Sep 3, 2026 · PMID 42690486 pubmed