Metabolomics to Predict Treatment Response and Toxicities in Rectal Cancer

Background: Colorectal cancer is the leading cause of cancer-related deaths in Taiwan, with rectal cancer accounting for approximately 27% of all cases. Total neoadjuvant therapy (TNT), which consists of chemotherapy and radiation therapy delivered before surgery, has become the standard of care for locally advanced rectal cancer. However, there is currently no reliable method for predicting the response to TNT or the occurrence of radiation proctitis, a common side effect of treatment.

Objective: This study aims to evaluate the metabolomic profiles of individuals with locally advanced rectal cancer undergoing TNT and to identify a panel of metabolites that can predict treatment response and toxicities.

Methods: A prospective cohort study will be conducted to enrol patients with locally advanced rectal cancer who are scheduled to receive TNT. Blood, urine, tissue, and faecal samples will be collected at baseline, during, and after chemoradiotherapy. Metabolomic profiling of the samples will be performed using liquid-chromatography mass spectrometry (LC-MS). Treatment response will be assessed based on clinical downstaging (defined as a decrease in tumour size and/or T and N stage after TNT) and pathological response, such as pathological complete response (pCR). Radiation proctitis will be assessed using the Common Terminology Criteria for Adverse Events (CTCAE) v5.0. PCA and PLSDA will be used to identify metabolites that are associated with treatment response and radiation proctitis. Receiver operating characteristic (ROC) curves will be used to assess the predictive performance of the identified metabolites. Univariate and multivariate logistic regression will be used to build models to predict treatment response and radiation proctitis.

Hypothesis: Metabolomic profiling can be used to predict the response to total neoadjuvant therapy (TNT) and the incidence of radiotherapy-related diarrhoea in patients with locally advanced rectal cancer.

Rationale of the project: Metabolomics is a powerful tool for identifying biomarkers that are associated with disease and treatment response. It is more closely related to the biological phenotype than other omics approaches, such as genomics and transcriptomics, and it has the potential to be used for precision health applications.

In this project, the investigators aim to use metabolomics to predict the response to total neoadjuvant therapy (TNT) and the incidence of treatment-related toxicity in rectal cancer patients prior to treatment. This would allow us to select patients who are most likely to benefit from TNT and to minimize the risk of complications.

There is a growing body of evidence that suggests that metabolomics can be used to predict treatment response and toxicity in cancer patients. For example, one study found that plasma metabolites could be used to predict the overall survival and progression-free survival of patients with colorectal cancer. Another study found that the level of pretreatment faecal butyrate was directly related to gastrointestinal toxicity in prostate cancer patients. However, most studies on metabolomics and cancer have used long-course chemoradiotherapy. There is a limited amount of research on the use of metabolomics to predict treatment response and toxicity to TNT.

This project is the first to comprehensively evaluate the metabolomic profiles of patients with locally advanced rectal cancer undergoing TNT at multiple time points during and after treatment using liquid chromatography-mass spectrometry (LC-MS), and to assess the association of these profiles with treatment response and toxicities. The findings from this study have the potential to lead to the development of non-invasive biomarkers for predicting treatment response and toxicities, which could improve the clinical management of rectal cancer patients.

Eligibility Criteria:
Inclusion Criteria:

* Histologically confirmed adenocarcinoma of the rectum
* Scheduled to receive total neoadjuvant therapy

Exclusion Criteria:

* Previous pelvic radiation therapy
* Inflammatory bowel disease