- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT07314528
Evaluating the Impact of GLP-1 Receptor Agonists With Total Neoadjuvant Therapy in Rectal Cancer
A Phase II Multi-institutional Randomized Trial Evaluating the Impact of GLP-1 Receptor Agonists in Combination With Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer
The goal of this clinical trial is to see if adding a weight loss medication (GLP-1 receptor drug) to patients with an increased BMI receiving treatment for rectal cancer prior to surgery (total neoadjuvant chemoradiotherapy) improves cancer outcomes. The main questions it aims to answer is
- Does the drug increase weight loss in rectal cancer patients with a high BMI
- Does the drug improve response rates to chemotherapy and radiotherapy
- Does the drug improve survival outcomes and if cancer returns
Researchers will compare this drug in one group against a group of patients receiving preoperative total neoadjuvant chemoradiotherapy without the drug
Patients will be required to
1) take the GLP-1 receptor agonist drug during TNT or just having TNT alone as per standard hospital protocols
Body weight will be measured at three predefined time points:
- Baseline: Prior to initiation of semaglutide or TNT
- Pre-TNT: Start of TNT (for the intervention arm, this is 4 weeks after semaglutide initiation)
- Post-TNT: Within 7 days following completion of TNT and prior to definitive surgery
Patients will complete their treatment and go on to have surgery as per standard methods for treating rectal cancer
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
This Phase II multicentre, open-label randomized controlled trial aims to determine whether adding a GLP-1 receptor agonist (GLP-1RA) to standard Total Neoadjuvant Therapy (TNT) improves oncological outcomes in Locally Advanced Rectal Cancer (LARC). We will evaluate whether metabolic modulation through GLP-1RA increases pathological complete response (pCR) rates, accelerates the clearance of circulating tumour DNA (ctDNA), and reduces the risk of recurrence. Secondary outcomes include toxicity profiles, surgical parameters and outcomes, ctDNA dynamics, and 2-year disease-free (DFS) and overall survival (OS). By combining innovative metabolic therapy with biomarker-driven monitoring, this study pioneers a precision oncology approach in the management of LARC.
Immune metabolism refers to the bioenergetic and biosynthetic processes that support immune cell function. Obesity significantly alters this metabolic programming. Obesity has a significant impact on cancer development and progression, in part due to its effects on the tumour microenvironment (TME) and immune metabolism. Understanding this connection is key in cancer biology and can also inform therapeutic strategies. There are many consequences of obesity-induced TME alterations, including immune suppression, increased tumour progression, metastasis, and resistance to immunotherapy.
Obesity is linked to an increased risk of developing 13 different cancers, including CRC cancer. 1 The mechanisms are complex, but elevated systemic inflammation and dysregulated immunity are major factors. Emerging evidence is beginning to show the potential benefits of GLP-1 therapies in cancer treatment; since this class of medications improves obesity, they might also help improve cancer outcomes. In a large retrospective cohort study with a 15-year follow-up, GLP-1 medication use was associated with a significant risk reduction in 10 of the 13 obesity-related cancers. 1 Mechanistically, the reasons for this reduction are unknown, but decreased inflammation and immune dysregulation are likely key factors in lowering this risk.
Our research group has extensively documented the harmful effects of obesity on the immune system, including its impact on anti-cancer immunity. Additionally, we have provided clinical and experimental evidence that GLP-1 therapy reduces inflammation and can significantly enhance anti-tumor immune cell populations. In this study, we will precisely assess the effects of two specific interventions-either TNT combined with GLP-1 RA (intervention group) or TNT alone (control group)-on the systemic inflammatory profile and circulating/tumor immune phenotype in stage III rectal cancer.
GLP-1-based treatments originally developed for type 2 diabetes and obesity, are now gaining attention for their potential impact on immune metabolism and even cancer therapy. There has been direct links between GLP-1 treatment and immune metabolism, with GLP reducing inflammation and improving systemic metabolism enhancing immune fitness. Some studies have also shown that GLP treatment can also indirectly modulate the TME by lowering leptin and insulin levels, reducing tumour-promoting signalling and reducing immunosuppressive cells in the TME. It is important to note that different cancers may respond differently to GLP-1 modulation based on the complexity, composition and level of immune infiltration. In this current study, we will profile the metabolic profiles and inflammatory profiles in the complex TME across the two defined interventions (either TNT + GLP-1 RA (intervention group) or TNT alone (control group)) in stage III rectal cancer patents enrolled in the trial.
GLP-1 receptor agonists (GLP-1 RAs), such as semaglutide, have demonstrated strong effects on weight loss in individuals with obesity. In the STEP 1 trial, semaglutide led to an average weight loss of 14.9%, compared to 2.4% with placebo, over 68 weeks. Recent epidemiologic data also suggest a link between GLP-1 RA use and a reduced incidence of obesity-related cancers, including colorectal cancer. 3 Additionally, GLP-1 RAs may have anti-inflammatory and metabolic effects that could be beneficial in the context of cancer therapy.
Total neoadjuvant therapy (TNT) is increasingly utilized in managing locally advanced rectal cancer (LARC) to improve pathological complete response (pCR) rates, facilitate surgical downstaging, and support organ preservation. This trial aims to determine whether combining GLP-1 RAs with TNT leads to meaningful weight loss and better oncological outcomes compared to TNT alone in patients with BMI ≥30 and LARC.
Study Type
Enrollment (Estimated)
Phase
- Phase 2
Contacts and Locations
Study Contact
- Name: Michael Eamon Kelly, MB BAO BCH PhD FRCSI
- Phone Number: 00353876638956
- Email: kellym11@tcd.ie
Study Contact Backup
- Name: Ben Creavin, MB BAO BCH MD FRCSI
- Phone Number: 00353877830130
- Email: bencreavin@rcsi.com
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Written informed consent according to local guidelines obtained prior to any study-related activities.
- Histologically confirmed mismatch repair protein proficient adenocarcinoma of the rectum.
- BMI ≥25 kg/m²
- Radiological confirmed >T2, Node positive, Threatened Surgical Margin and/or EMVI+ by MRI
- Imaging available for radiomics analysis
- Absence of metastatic disease at registration.
- Adequate renal function is defined as calculated creatinine clearance (CrCl) >50ml/min.
- ANC > 1.5 cells/mm3, HGB > 8.0 gm/dl, PLT > 150,000/mm3, total bilirubin ≤ 1.5 x ULN (except in patients with Gilbert's Syndrome who must have total bilirubin ≤ 3.0 x ULN), AST≤ 3 x ULN, ALT ≤ 3 x ULN
- Able to tolerate medication.
- ECOG 0-2
Exclusion Criteria:
- Received prior chemotherapy or radiotherapy
- Previous or concurrent active malignancy ≤ 5 years prior to registration, with the exception of non-melanotic skin cancer or carcinoma in situ of any type, or other cancers that the treating investigator does not feel will impact the study objectives.
- Locally advanced disease T3N+ or T4 disease.
- Recurrent rectal cancer
- Metastatic disease at presentation
- Patients unable to undergo MRI
- Patients having already received weight-loss intervention (pharmacological or surgical)
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Treatment
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: Total Neoadjuvant Therapy and GLP-1 Receptor Agonist
This arm will have patients with increased BMI and locally advanced rectal cancer having total neoadjuvant chemoradiotherapy.
This arm will be given a GLP-1 receptor agonist
|
All patients will receive standard total neoadjuvant therapy for rectal cancer as per local standards.
One group will receive a GLP-1 rector agonist in addition to the standard treatment for rectal cancer
Total ne-adjuvant therapy is standard treatment for locally advanced rectal cancer
|
|
Active Comparator: Locally advanced rectal cancer and total neoadjuvant therapy alone
Patients with a high BMI and locally advanced rectal cancer undergoing total neoadjuvant therapy with not receiving a GLP-1 receptor agonist
|
Total ne-adjuvant therapy is standard treatment for locally advanced rectal cancer
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Weight Loss
Time Frame: 6 months
|
Change in weight loss (Kilograms) between groups at 2 time points
|
6 months
|
|
Metabolic Profile of the Tissue
Time Frame: From enrolment to operation within 1 year
|
Using a human ex vivo explant model (3D), we will assess in real time the metabolic profiles of the tissues from patents in the control and interventions groups.
Detailed metabolic profiling data using Seahorse technology.
These metabolic profile data will be correlated with detailed clinical, pathology and outcome data for each patient in the trial.
|
From enrolment to operation within 1 year
|
|
Inflammatory Mediators
Time Frame: From enrolment to surgical resection within 1 year
|
Using human ex vivo explant model (3D) system, we will profile the secretions of inflammatory mediators from the TME and how these cross talks to immune cells.
This data will be directly correlated with the detailed metabolic signatures.
|
From enrolment to surgical resection within 1 year
|
|
GLP-1 effects on mitochondrial fitness
Time Frame: From enrolment to surgical resection within 1 year
|
Determine of GLP-1 treatment alters mitochondrial fitness ex vivo in explants by assessing ATP levels (Relative Light Units), stress responses and adaptations to metabolic demands using tissues from both arms of the trial.
|
From enrolment to surgical resection within 1 year
|
|
Mapping systemic inflammatory profiles
Time Frame: From enrolment to surgical resection within 1 year
|
To definitively map the systemic inflammatory profile, we will investigate matched plasma samples (baseline and post-intervention) using a high dimensional approach (e.g Olink Target-96 Immunoncology panel or Olink Explore-396 inflammatory profile).
Samples will be taken at the time of diagnosis and the time of surgery
|
From enrolment to surgical resection within 1 year
|
|
Mapping circulating immune systems
Time Frame: From enrolment to surgical resection within 1 year
|
Map the circulating immune system using spectral flow cytometry to include cell frequencies (e.g.
T cells, Innate T cells, NK cells, Monocytes and DC subsets), activation/exhaustion phenotype (e.g.
CD69, PD-1, TIM-3 etc) and cytokine profiles (e.g.
interleukin (IL)-2, 4, 10 & 17, interferon gamma, tumour necrosis factor, granzymes etc).
Samples will be taken from pre treatment biopsies and from the tumour itself when removed at surgery.
|
From enrolment to surgical resection within 1 year
|
|
Mapping tumour resident immune system
Time Frame: From enrolment to surgical resection within 1 year
|
Map the tumour resident immune system using MACsima spatial imaging platform and their 61- parameter immuno-oncology antibody panel (which includes T cells, NK cells, Macrophages & DCs plus tumour specific markers).
Using this platform, in addition to deep immunopheotyping, we will allow perform neighbour analysis to determine cell-cell interactions.
Tissue will be taken from pre treatment biopsies and from the tumour itself when removed at surgery.
|
From enrolment to surgical resection within 1 year
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Oncological outcomes
Time Frame: 5 years
|
To compare pathological complete response (pCR) rates at the time of surgical resection. To assess overall survival (OS) at 3 and 5 years post-treatment. To assess disease-free survival (DFS) at 3 and 5 years post-treatment. To evaluate local recurrence rates at 1, 3 and 5 years |
5 years
|
|
Surgical Outcomes
Time Frame: Enrolment to surgical intervention and 30 days post discharge
|
To compare operative complexity (e.g., operative time, blood loss (millilitres), conversion rates).
|
Enrolment to surgical intervention and 30 days post discharge
|
|
Metabolic and Physiologic Outcomes:
Time Frame: From enrolment to surgical resection within 1 year
|
To measure changes in BMI, waist circumference, and visceral fat volume using imaging modalities.
(kg/m2)
|
From enrolment to surgical resection within 1 year
|
|
Treatment Tolerability and Safety:
Time Frame: 1 year
|
To compare the incidence and severity of adverse events (graded by CTCAE v5.0).
This will be assessed while on treatment and post surgery for 30-days To assess treatment compliance and any dose modifications or interruptions due to toxicity.
This will be measured continually during treatment To evaluate GLP-1 RA-related side effects, particularly gastrointestinal symptoms and hypoglycemia.
This will be assessed at the end of treatment
|
1 year
|
|
Patient-Reported Outcomes:
Time Frame: 2 years
|
To compare quality of life (QoL) scores using validated instruments (e.g., EORTC QLQ-C30).
This will happen at 3 monthly intervals from starting treatment To assess patient-reported functional status, fatigue, and appetite changes.
This will happen at 3 monthly intervals from starting treatment To evaluate psychological well-being (e.g., depression, anxiety scores) in the context of body weight changes and cancer therapy.
|
2 years
|
|
Translational Component: to investigate the molecular and cellular effects of GLP-1 RA therapy during TNT through analysis of tissue and blood biomarkers.
Time Frame: From enrolment to surgical resection within 1 year
|
To evaluate changes in tumor microenvironment, including immune cell infiltration (e.g., CD8+ T-cells, macrophages) via immunohistochemistry or multiplex immunofluorescence.
|
From enrolment to surgical resection within 1 year
|
|
Radiomics
Time Frame: From enrolment to surgical resection within 1 year
|
Standardize imaging and segmentation across sites with centralized protocols and ROI annotation for tumor and mesorectal fat. Extract baseline and post-TNT radiomic features and calculate delta-radiomics, alongside CT-based body composition measures. Develop predictive models combining radiomics with clinical and metabolic data to correlate with pCR, survival, and treatment toxicity. |
From enrolment to surgical resection within 1 year
|
|
Circulating Tumor DNA (ctDNA)
Time Frame: From enrolment to surgical resection within 1 year
|
Longitudinal sampling: Plasma will be collected at baseline, mid-TNT, preoperatively, and postoperatively at defined follow-up intervals. Analytical methods: ctDNA will be quantified and profiled using next-generation sequencing (NGS)-based assays to detect mutations, copy number variations, and methylation patterns relevant to rectal cancer. Endpoints: Dynamics of ctDNA clearance and re-emergence will be evaluated as biomarkers of treatment response, minimal residual disease, and early recurrence. Integration: ctDNA data will be correlated with radiomic signatures, metabolic changes, and pathological outcomes to explore composite biomarker models that predict pCR, DFS, and OS. |
From enrolment to surgical resection within 1 year
|
|
Surgical Outcomes
Time Frame: 30 days
|
To assess postoperative complications, including anastomotic leak, wound infection, and ileus (Clavien-Dindo classification).
|
30 days
|
|
Surgical Outcomes
Time Frame: 30 days
|
To evaluate length of hospital stay and 30-day readmission rates
|
30 days
|
|
Metabolic and Physiologic Outcomes:
Time Frame: From enrolment to 1 year
|
To assess changes in insulin sensitivity, lipid profile, and inflammatory markers (e.g., CRP, IL-6).
|
From enrolment to 1 year
|
|
Metabolic and Physiologic Outcomes:
Time Frame: Enrolment to 1 year
|
To evaluate resting metabolic rate (RMR) and body composition (e.g., lean mass vs. fat mass if DEXA or BIA is used).
|
Enrolment to 1 year
|
|
Translational Component: to investigate the molecular and cellular effects of GLP-1 RA therapy during TNT through analysis of tissue and blood biomarkers.
Time Frame: From enrolment to1 year
|
To assess systemic inflammatory and metabolic markers, such as IL-6, TNF-α, adiponectin, leptin, and CRP, at baseline and post-TNT.
|
From enrolment to1 year
|
|
Translational Component: to investigate the molecular and cellular effects of GLP-1 RA therapy during TNT through analysis of tissue and blood biomarkers.
Time Frame: Enrolment to 1 year
|
To perform gene expression profiling of tumor samples (pre- and post-TNT) to identify signatures associated with treatment response or resistance.
|
Enrolment to 1 year
|
|
Translational Component: to investigate the molecular and cellular effects of GLP-1 RA therapy during TNT through analysis of tissue and blood biomarkers.
Time Frame: Enrolment to 1 year
|
To explore gut microbiome composition in relation to treatment arm and metabolic outcomes, using fecal metagenomic sequencing.
|
Enrolment to 1 year
|
|
Translational Component: to investigate the molecular and cellular effects of GLP-1 RA therapy during TNT through analysis of tissue and blood biomarkers.
Time Frame: Enrolment to 1 year
|
To assess circulating tumor DNA (ctDNA) dynamics pre-, during, and post-TNT as a potential predictor of minimal residual disease and recurrence.
|
Enrolment to 1 year
|
Collaborators and Investigators
Sponsor
Investigators
- Principal Investigator: Michael Kelly, MB BAO BCH PHD FRCSI, St. James Hospital
Publications and helpful links
General Publications
- Wilding JPH, Batterham RL, Calanna S, Davies M, Van Gaal LF, Lingvay I, McGowan BM, Rosenstock J, Tran MTD, Wadden TA, Wharton S, Yokote K, Zeuthen N, Kushner RF; STEP 1 Study Group. Once-Weekly Semaglutide in Adults with Overweight or Obesity. N Engl J Med. 2021 Mar 18;384(11):989-1002. doi: 10.1056/NEJMoa2032183. Epub 2021 Feb 10.
- Kazi T, McKechnie T, Lee Y, Alsayari R, Talwar G, Doumouras A, Hong D, Eskicioglu C. The impact of obesity on postoperative outcomes following surgery for colorectal cancer: analysis of the National Inpatient Sample 2015-2019. ANZ J Surg. 2024 Jul-Aug;94(7-8):1305-1312. doi: 10.1111/ans.19135. Epub 2024 Jun 18.
- Martin-Carnicero A, Ramalle-Gomara E, Rubio-Mediavilla S, Alonso-Lago M, Zorrilla-Larraga M, Manrique-Abos I, de Las Heras-Duena ME, Larrayoz IM, Martinez A. Prognostic and Predictive Biomarkers in Patients with Locally Advanced Rectal Cancer (LARC) Treated with Preoperative Chemoradiotherapy. J Clin Med. 2022 Oct 16;11(20):6091. doi: 10.3390/jcm11206091.
- Dizdarevic E, Hansen TF, Jakobsen A. The Prognostic Importance of ctDNA in Rectal Cancer: A Critical Reappraisal. Cancers (Basel). 2022 Apr 30;14(9):2252. doi: 10.3390/cancers14092252.
- Chen C, Douglas MP, Ragavan MV, Phillips KA, Jansen JP. Clinical Validity and Utility of Circulating Tumor DNA (ctDNA) Testing in Advanced Non-small Cell Lung Cancer (aNSCLC): A Systematic Literature Review and Meta-analysis. Mol Diagn Ther. 2024 Sep;28(5):525-536. doi: 10.1007/s40291-024-00725-x. Epub 2024 Aug 2.
- Ryan EJ, Creavin B, Sheahan K. Delivery of Personalized Care for Locally Advanced Rectal Cancer: Incorporating Pathological, Molecular Genetic, and Immunological Biomarkers Into the Multimodal Paradigm. Front Oncol. 2020 Aug 14;10:1369. doi: 10.3389/fonc.2020.01369. eCollection 2020.
- Silverii GA, Marinelli C, Bettarini C, Del Vescovo GG, Monami M, Mannucci E. GLP-1 receptor agonists and the risk for cancer: A meta-analysis of randomized controlled trials. Diabetes Obes Metab. 2025 Aug;27(8):4454-4468. doi: 10.1111/dom.16489. Epub 2025 May 29.
- Ochiai K, Bhutiani N, Ikeda A, Uppal A, White MG, Peacock O, Messick CA, Bednarski BK, You YN, Skibber JM, Chang GJ, Konishi T. Total Neoadjuvant Therapy for Rectal Cancer: Which Regimens to Use? Cancers (Basel). 2024 May 31;16(11):2093. doi: 10.3390/cancers16112093.
- Johnson GGRJ, Park J, Helewa RM, Goldenberg BA, Nashed M, Hyun E. Total neoadjuvant therapy for rectal cancer: a guide for surgeons. Can J Surg. 2023 Apr 21;66(2):E196-E201. doi: 10.1503/cjs.005822. Print 2023 Mar-Apr.
- Lin A, Ding Y, Li Z, Jiang A, Liu Z, Wong HZH, Cheng Q, Zhang J, Luo P. Glucagon-like peptide 1 receptor agonists and cancer risk: advancing precision medicine through mechanistic understanding and clinical evidence. Biomark Res. 2025 Mar 27;13(1):50. doi: 10.1186/s40364-025-00765-3.
- Miousse IR. GLP-1 receptor agonists in the context of cancer: the road ahead. Am J Physiol Cell Physiol. 2025 Jun 1;328(6):C1822-C1828. doi: 10.1152/ajpcell.00245.2025. Epub 2025 Apr 26.
- Wang L, Xu R, Kaelber DC, Berger NA. Glucagon-Like Peptide 1 Receptor Agonists and 13 Obesity-Associated Cancers in Patients With Type 2 Diabetes. JAMA Netw Open. 2024 Jul 1;7(7):e2421305. doi: 10.1001/jamanetworkopen.2024.21305. Erratum In: JAMA Netw Open. 2025 Jun 2;8(6):e2519224. doi: 10.1001/jamanetworkopen.2025.19224.
Study record dates
Study Major Dates
Study Start (Estimated)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Estimated)
Study Record Updates
Last Update Posted (Estimated)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
- 435911714
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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