ctDNA Trajectories Predict Survival in Trifluridine/Tipiracil-Treated Metastatic Colorectal Cancer Patients

Academic Background

Metastatic colorectal cancer (mCRC) is one of the leading causes of cancer-related deaths worldwide. Despite recent advancements in diagnosis and treatment, the prognosis for advanced-stage patients remains poor. Trifluridine/Tipiracil (FTD/TPI), an oral nucleoside analog, has been approved for the treatment of chemotherapy-refractory mCRC patients. However, not all patients benefit from this treatment, and some may experience severe side effects. Therefore, there is an urgent need to identify biomarkers that can predict treatment response and prognosis.

Circulating tumor DNA (ctDNA) is an emerging biomarker that can detect tumor gene mutations and tumor burden through blood samples. Due to its short half-life, ctDNA can more accurately reflect treatment response, showing great potential in monitoring mCRC treatment. However, the predictive and prognostic value of ctDNA in FTD/TPI treatment has not been fully explored. This study aims to investigate the changes in ctDNA trajectories before and after FTD/TPI treatment in mCRC patients and evaluate its relationship with patient survival.

Source of the Paper

This paper was co-authored by Matthias Unseld, Stefan Kühberger, Ricarda Graf, and others, affiliated with institutions such as the Medical University of Vienna and the Medical University of Graz in Austria. The paper was published in 2025 in the journal Molecular Oncology, with the DOI 10.¹⁰⁰²⁄₁₈₇₈-0261.13755.

Research Process and Results

Study Design

This study is a non-interventional translational biomarker phase II study involving 30 mCRC patients treated with FTD/TPI. The primary objective was to predict patient survival based on changes in ctDNA levels. The study utilized a 77-gene panel for ctDNA detection and assessed tumor burden through shallow whole-genome sequencing (SWGS) and the IchorCNA algorithm.

Sample Collection and ctDNA Extraction

Blood samples were collected from patients before treatment initiation (baseline, BL) and during follow-up (FU1, FU2, FU3). Blood samples were processed within 24 hours of collection to extract cell-free DNA (cfDNA) from plasma, which was then quantified using the Qubit dsDNA HS Assay Kit.

Molecular Analysis and ctDNA Level Assessment

Molecular analysis was performed using the Avenio ctDNA Expanded Kit (Roche) to sequence 77 genes. Tumor fraction (ITF) was assessed using the IchorCNA algorithm, and variant allele frequency (VAF) and mutant molecules per milliliter of plasma (MM) were calculated. SWGS was also performed on unenriched Avenio libraries to independently assess tumor fraction.

Statistical Analysis

The Kaplan-Meier method and log-rank test were used to evaluate the relationship between ctDNA levels and survival. Linear mixed models and joint models were applied to analyze the relationship between ctDNA trajectories and clinical outcomes. Univariate and multivariate Cox proportional hazards analyses were conducted to assess the impact of clinical factors on survival.

Key Findings

1. ctDNA Detection Rate and Tumor Burden: ctDNA was detected in 90% of patients, with high baseline ctDNA levels observed in 46.7% of patients (VAF ≥10%). ctDNA levels were significantly correlated with tumor burden, and high ctDNA levels (≥5%) were associated with poorer survival.

2. ctDNA Trajectories and Treatment Response: Patients with a good treatment response had significantly lower ctDNA levels compared to non-responders. Notably, at FU2 and FU3 time points, non-responders had significantly higher ctDNA levels than responders.

3. ctDNA Levels and Survival: Patients with baseline ctDNA levels ≥3% had significantly worse survival than those with ctDNA levels %. At the FU1 time point, patients with ctDNA levels ≥5% had significantly worse survival than those with ctDNA levels %.

4. ctDNA Trajectories Predict Survival: Joint model analysis revealed that increasing ctDNA trajectories were significantly associated with a higher risk of death. Patient-specific ctDNA trajectories could be used to predict the risk of death within six months.

Conclusion

This study demonstrates that ctDNA levels and their trajectories can effectively predict survival in mCRC patients treated with FTD/TPI. High ctDNA levels are associated with poor prognosis, while increasing ctDNA trajectories indicate a higher risk of death. These findings provide clinicians with critical decision-making tools to identify patients unlikely to benefit from treatment, thereby avoiding unnecessary therapies and side effects and improving patients’ quality of life.

Research Highlights

1. ctDNA as a Prognostic Marker: This study is the first to systematically evaluate the prognostic value of ctDNA in FTD/TPI treatment, confirming the significant correlation between ctDNA levels and patient survival.

2. Application of Joint Models: The study employed advanced joint models to analyze the relationship between ctDNA trajectories and clinical outcomes, offering new tools for personalized treatment.

3. Potential for Clinical Application: The proposed 5% ctDNA level threshold has broad potential for clinical application, aiding in treatment decision-making.

Research Value

This study not only provides a new biomarker for mCRC treatment but also offers critical evidence for the application of ctDNA in cancer treatment monitoring. By dynamically monitoring ctDNA levels, clinicians can earlier identify patients who are not responding to treatment, thereby optimizing therapeutic strategies and improving patient survival and quality of life.